Datasets:

afg1

/

litscan-epmc-subset

like 0

PMC10002930

Elena E. Fedorova

Rapid Changes to Endomembrane System of Infected Root Nodule Cells to Adapt to Unusual Lifestyle

28-02-2023

symbiosis,root nodule,cell membranes,membrane transporters,intracellular bacteria accommodation

Symbiosis between leguminous plants and soil bacteria rhizobia is a refined type of plant–microbial interaction that has a great importance to the global balance of nitrogen. The reduction of atmospheric nitrogen takes place in infected cells of a root nodule that serves as a temporary shelter for thousands of living bacteria, which, per se, is an unusual state of a eukaryotic cell. One of the most striking features of an infected cell is the drastic changes in the endomembrane system that occur after the entrance of bacteria to the host cell symplast. Mechanisms for maintaining intracellular bacterial colony represent an important part of symbiosis that have still not been sufficiently clarified. This review focuses on the changes that occur in an endomembrane system of infected cells and on the putative mechanisms of infected cell adaptation to its unusual lifestyle.

Rapid Changes to Endomembrane System of Infected Root Nodule Cells to Adapt to Unusual Lifestyle Symbiosis between leguminous plants and soil bacteria rhizobia is a refined type of plant–microbial interaction that has a great importance to the global balance of nitrogen. The reduction of atmospheric nitrogen takes place in infected cells of a root nodule that serves as a temporary shelter for thousands of living bacteria, which, per se, is an unusual state of a eukaryotic cell. One of the most striking features of an infected cell is the drastic changes in the endomembrane system that occur after the entrance of bacteria to the host cell symplast. Mechanisms for maintaining intracellular bacterial colony represent an important part of symbiosis that have still not been sufficiently clarified. This review focuses on the changes that occur in an endomembrane system of infected cells and on the putative mechanisms of infected cell adaptation to its unusual lifestyle. Symbiosis between leguminous plants and soil bacteria rhizobia is initiated by a signal exchange between the host plant and bacteria. In response to flavonoids secreted by legume roots, rhizobia synthesize lipochito-oligosaccharids, which are nodulation factors (Nod factors) that initiate the expression of genes of the so-called Nod factor signaling pathway, thereby inducing nodule organogenesis. The Nod factor signaling pathway has been extensively studied and reviewed, and detailed information concerning this early stage of symbiosis can be found in several excellent reviews [1,2,3,4]. However, the functional role of the root nodule is associated with later stages of symbiosis when the colony of bacteria accommodated in a living plant cell become capable of reducing atmospheric nitrogen. The aim of this paper was to review the data concerning the changes in a host cell endomembrane system that occur during the short but quite important co-existence of symbiotic partners and to specify possible directions for new research. Nitrogen-fixing root nodules are transitory organs formed on plant roots upon inoculation by symbiotic microorganisms. Legume root nodule development starts with the initiation of a new meristem from the dedifferentiated root cortical cell followed by root nodule organogenesis [5,6,7,8]. The spatial pattern of meristem initiation determines the anatomical pattern and the growth of root nodules [5]. In a nodule with a meristem situated at the nodule apex, newly produced postmeristematic cells are shifted downward with a basipetal gradient of cell differentiation. Such a nodule develops as an elongated cylindrical structure and is termed the indeterminate type of growth nodule, examples of which are nodules of Medicago truncatula and Pisum sativum. The activity of the apical meristem in these nodules persists for 5–6 weeks [1,5,9,10,11]. Nodules with apical and lateral meristematic loci develop in globoid form with a centripetal developmental gradient, examples of which are nodules of Phaseolus vulgaris, Lotus japonicum, and Glycine max. The oldest cells are situated in the center of the nodule and are covered by layers of younger cells [6,12]. This type of nodule is termed the determinate type of growth nodule because its growth mostly depends on cell enlargement [6]. The lupinoid nodules of Lupinus albus and Lupinus luteus are globoid in form but contain lobes with an indeterminate type of growth as well as the infected cells, which are able to divide [13]. Several excellent reviews dedicated to nodule organogenesis have addressed the details [5,6,14,15,16]. At the initial stages of nodule formation, rhizobia enter the intercellular space of nodule primordia that is initiated on the young root. Bacteria are unable to enter the symplast of mature cells, probably due to the developed cell wall and a high turgor pressure; however, infected threads carrying rhizobia enter the symplast of young, postmeristematic cells [5,10]. Inside the host cell, the microsymbionts are situated in specific asymmetric protrusions of the plasma membrane. In legume root nodules, such protrusions are tubular structures called infection threads, the extensions of infection threads with reduced cell walls are termed infection droplets, and released bacteria surrounded by a host cell-derived membrane are called symbiosomes (Figure 1) [17,18,19]. Root nodule development is accompanied by a massive transcriptional reprogramming that causes changes in the anatomy, physiology, transcriptome, and metabolome of host cells [4,19,20]. Infected cells maintain thousands of living rhizobia for a prolonged period of up to 6–7 weeks; hence, they are permissive for intracellular accommodation of bacteria and must be considered as special biological units—symbiotic cells. These cells are protected from the default answers for infection such as programmed cell death (PCD) by a set of genes that causes the suppression of innate immunity responses [20,21,22,23,24,25]. However, this suppression is not universal, and some antimicrobial peptides (NCRs) that are synthesized in legumes from the inverted repeat-lacking clade (IRLC) including M. truncatula cause the terminal differentiation of intracellular bacteria or the termination of incompatible symbiosis [26,27]. The specific environment that is maintained in infected cells helps (or forces) intracellular rhizobia at a certain stage of development to start the reduction of nitrogen from the air via the bacterial enzyme nitrogenase. Mature symbiotic cells are partly hypoxic, which allows the functional activity of oxygen-sensitive nitrogenase [28]. The rhizobia that have entered the symplast of the host cell are kept separate from the host cytoplasm by the membrane, the source of which initially is the plasma membrane of the host cell [17,18]. The symbiosome has some structural analogy with pathogenic vacuoles that house microbes in mammals [29]. The bacterial pathogens Salmonella, Mycobacteria, Legionella, Chlamydia, and Brucella temporarily reside in membrane compartments—bacteria-containing vacuoles. The modification of endocytic, exocytic, and/or ER-to-Golgi vesicle trafficking of invaded cells helps to maintain the bacterial population [29,30]. The pathogenic vacuoles mostly are destined to fuse with lysosomes of the host cell with a consequent lytic clearance of bacteria. In infected cells of root nodules, however, most symbiosomes persist as individual units for 3–4 weeks and do not fuse with the host cell vacuoles [31,32]. Some putative mechanisms that inhibit fusion with the host vacuole in infected cells have been described for M. truncatula root nodules [32,33]; these include a gradual change in the identity of the symbiosome membrane as well as changes in the functionality of the vacuole of the infected cell. At the same time, lysis of bacteria and termination of symbiosis is induced in many cases that include incompatible interactions and environmental stresses [27,34,35]. The comprehensive model of the processes that prevent lytic clearance of bacteria has not yet been developed. All membrane-bound organelles of eukaryotic cells have their own identity that defines the compartment-depending membrane features [36]. The identity of cell organelles is determined by specific membrane-bound proteins that are mostly involved in the process of membrane fusion. These are the regulatory GTPases of the Rab family and the Rab-interacting integral proteins of the soluble NSF attachment protein receptor (SNARE) families [36,37]. During the fusion of vesicles with the membrane, matching types of SNAREs form a highly stable protein association called the SNARE complex [37,38]. Studies in plants have shown that most SNAREs are associated with specific intracellular compartments [39,40]. Some animal intracellular pathogens utilize the strategy of host cell mimicry; for example, Salmonella-containing vacuoles acquire Rab proteins and hence accept an identity similar to early/late endosomes [28,29]. Symbiosomes in root nodules of M. truncatula acquire a specific set of membrane identity proteins, which is similar to other cell organelles. This event determines membrane traffic as well as the dynamic changes in symbiosome membrane features (Figure 1). Rhizobia cells that have entered the host cell have a fragment of the plasma membrane as an integral part of the symbiosome membrane, and symbiosomes of M. truncatula and soybean contain plasma-membrane Syntaxin 134 and vesicular v-SNARE VAMP72, the markers of plasma-membrane-targeted exocytosis [31,32]. However, the “classical” markers of endocytosis (small GTPase Rab5 and trans-Golgi network identity marker SYP4) do not show an association with freshly released rhizobia, therefore the “endocytotic” entrance of rhizobia into the host cell has some pronounced deviations [31]. The molecular marker of endocytosis—small GTPase Rab7—is temporarily present on the membrane of endosomes and on tonoplast; this marker appears on the symbiosome membrane at later stages of development [12,31,32]. Mature symbiosomes also recruit tonoplast-resident vacuolar SNAREs from the so-called vacuolar SNAREpin complex [31,32,41]. Evidently, mature symbiosomes have a mosaic identity and combine different markers of the plasma membrane and the endosome/vacuole on their membranes (Figure 1). It can be assumed that anterograde, retrograde, and endocytic trafficking pathways may be operational in transport toward the symbiotic membrane. The acceptance of host cell molecular markers may facilitate retargeting of membrane transporters (for example, aquaporins) toward the membrane, thereby ensuring the growth and development of the symbiosome [42,43]. The host cell membrane transporters that have been identified on the symbiosome membrane include the iron transporter [44,45], the iron-activated citrate transporter [46], the molybdenum transporter [47], Zinc-Iron Permease6 [48], the SST1 sulfate transporter [49], copper transporter1 [50], peptide transporter Soybean Yellow Stripe-like 7 [51], and several putative candidates for malate transporters [52]. The recently presented work by Luo et al. [53] described a quantitative proteomics analysis of soybean root nodule symbiosome membranes and provided a framework of putative research in transport toward the symbiosome membrane and the regulatory mechanisms of this transport. During nodule development, the complete maturation of symbiosomes of M. truncatula requires 5–7 cell layers, with the most rapid growth in 1–2 cell layers proximal to the zone of nitrogen fixation in interzone 2–3 [11]. The infected cells grow concomitantly with the increasing symbiosome population. As a result, the infected cell’s volume increases several times in comparison with that of a non-infected cell [33]. This speedy expansion brings under consideration the putative membrane resources provided by the host cell for this process as well as the causes that force the host to maintain such explosive growth. The most obvious membrane resource is an exocytotic pathway with post-Golgi vesicles [12,17,31,54] and endoplasmic reticulum (ER), which has long been considered to be one of the sources of the membrane for symbiosomes [17]. The ER is always abundant in young infected cells, and the contacts of ER vesicles with symbiosome membranes have been displayed by using electron microscopy [12,17,31,54,55]. The rapid growth of infected cells and the propagation of intracellular bacteria raises a question regarding the causes of the synthesis of membranes by the host cell at such an unprecedented scale. The plasma membrane is known to be inelastic and unable to stretch more than 3% [56], hence the growth of new membrane interfaces as the plasma membrane or the membrane enveloping an infection thread, unwalled droplet, or symbiosome depend on the host cell resources. The growth of symbiotic structures in infected cells is mainly isodiametric for unwalled droplets and symbiosomes (apart from a tip growth of infection threads). Hence, the membrane resources have to be targeted to support the expansion indiscriminately of the growth type. The pronounced changes in membrane interphase in an infected cell include ER–plasma membrane remodeling and changes in membrane curvature, similar to a recent report by Rosado and Bayer [57]. At the same time, the idea that the ER is just a source of membrane for expanding symbiosomes is a very simplified view of a very complicated matter. Apart from the available membrane, the ER is a source of a plethora of different molecules. It is difficult to estimate the number of proteins that may be excreted in this manner into the symbiosome space at different time points of this communication. The inner space of organelles of symbiotic origin (mitochondria and plastids), according to Bellucci et al. [58], can be defined as an “external space” that is similar to the apoplast. It is quite plausible that the symbiosome also can be defined as “the extracellular space”. The recent data reported by Luo et al. [53] provided some support for this speculation. According to the data obtained via label-free quantitative proteomic technology for the soybean symbiosome membrane (SM), peribacteroid space (PBS), and root microsomal fraction (RMF), material exchange and signal communication indicate the likely extracellular nature of the symbiosome [53]. Several coatomer proteins of the COPI complex were detected in the SM proteome; the COPI and COPII complexes are known to be involved in retrograde and anterograde trafficking between the ER and Golgi apparatus [53]. Secretory proteins released into the ER lumen can be retained in this compartment, move along the secretory pathway, be transported to vacuoles in plants (bypassing the Golgi apparatus), or be excreted to the external (extracellular) space [58]. We can guess that in infected cells, the transport via ER (which is yet unexplored), is an important method of communication between symbiotic partners. The retargeting toward the symbiotic interface of membrane resources that were pre-directed to the plasma membrane, endosomes, and tonoplast favors the propagation of the intracellular microsymbiont colony [12,18,59]. Concerning the change in the destination of these membrane resources, it was proposed that the membrane tension created by the expanding microsymbiont provides the vector for targeted endomembrane traffic toward the new forming membranes in infected cells of M. truncatula [59]. Protein trafficking via the endomembrane system is tightly regulated in response to environment stimuli [60,61], but the response of the cells to mechanical stress involves quick indiscriminative retargeting of all membrane resources available in place to prevent a possible rupture of the membrane [62]. Hence, the unprecedented increase in membrane formation in the infected cell may be a repair mechanism induced as a response to the membrane stretching caused by the propagation of the microsymbiont in an infected cell. How specific in this case will protein traffic to interface with symbiotic membranes be? Currently, the mechanisms of a specific sorting of proteins toward the symbiotic interphase (if they exist) have not been elucidated. The mechanisms that adapt the host cell architecture to accommodate intracellular bacteria are not yet clear; however, the host cell cytoskeleton seems to reorganize after bacteria enter the host cell. Actin microfilament rearrangement, which is linked to the positioning of organelles and influences cell shape, provides a roadway for the transport of membrane vesicles [63]. During symbiosome growth in root nodules of M. truncatula, the actin microfilament network plays an indispensable role in membrane traffic and the reformation of cytoplasm architecture for symbiosome accommodation [64,65,66,67]. Actin configuration in infected nodule cells changes markedly during infected cell development. Zhang et al. [67] defined five zones in the infected zone of M. truncatula root nodules with specific rearrangements of actin. The cytoskeletal patterns are mediated by diverse actin-binding proteins such as actin depolymerization factors (ADFs) [68], formin [64,65,66], Phospholipase Dβ [69] and the ARP2/3 complex [70], which nucleates new actin filaments and forms branched actin networks. The manipulation of host cell actin via the ARP2/3 actin nucleating complex is also used as common strategy for the establishment of an intracellular lifestyle by enteropathogenic bacteria in animal cells [71]. In Arabidopsis thaliana, ARP2/3 is strongly associated with cell membranes of the microsomal fraction from several organelles that include the endoplasmic reticulum (ER), tonoplast, plasma membrane, and the early endosome [72,73]. The microtubule cytoskeleton pattern also undergoes changes during symbiosis development [13] starting from reorganization of microtubules on initial stages of root hair responses to rhizobia [74]. In nodule cells, bacteroid positioning correlates with characteristic microtubule rearrangements [75], wherein the pattern in root nodules was found to be host-plant specific [75]. The nodulation-specific kinesin-like calmodulin-binding protein (nKCBP), which crosslinks microtubules with the actin cytoskeleton, controls central vacuole morphogenesis in symbiotic cells in M. truncatula [76]. Apart from non-dividing infected cells of M. truncatula, the rearrangement of the cytoskeleton in infected cells of Lupinus albus is rather unusual. The infected cells of L. albus root nodules are able to divide while already infected. The pattern of the cytoskeleton during infected cell mitosis is comparable to that of the other dividing cells. The clustered symbiosomes move to the cell poles during spindle elongation in a manner similar to other host cell organelles. This implies the existence of functional mechanisms of microtubule and microfilament attachment on symbiosome membranes and the presence of suitable identity markers as well as the physical anchoring mechanism [13]. Throughout their development, plants balance cell surface area and volume with water and ion transport and turgor. This balance lies at the core of cellular homeostatic networks and is central to a plant cell’s capacity to withstand abiotic as well as biotic stress [77]. During the symbiosis development, the volume and surfaces of the host cell and microsymbiont change quite dramatically: the host cell volume increases 5 times, and the volume of intracellular bacteria increases 10 times [33]. How is the space for the microsymbiont created in the infected cell? When symbiosomes of M. truncatula nodules begin to fix nitrogen, a developmental switch occurs and concomitant changes in vacuoles features are induced. In infected cells, the expression of VPS11 and VPS39, which are genes of the HOPS complex that are essential to the specific tethering and fusion of vesicles to vacuoles [78], become suppressed. Vacuoles lose their acidic pH, which coincides with the rapid expansion of symbiosomes in the cell layer proximal to interzone 2/3 and the contraction of vacuoles [33] (Figure 2). The tonoplast aquaporin TIP1g is retargeted to the symbiosome membrane, which provides the microsymbiont with an advantage in water transport from the host cell to the bacteroid. As a result of these changes, the total vacuole volume in mature infected cells remains only 30% of total cell volume, whereas for plant cells it is normally from 70 to 90%. At the same time, the volume of symbiosomes increases to occupy 65% of the cell volume [33]. Taking into account the fact that the vacuole is a vital organelle of the plant cell [79], the suppression of the HOPS complex and the loss in vacuole lytic properties in living cells may be ruinous to the host cell’s wellbeing. This situation may be one of the reasons for the extremely short lifespan of symbiotic cells. On the other hand, the vacuole defunctionalization most likely contributes to the maintenance of symbiosomes as individual units, thereby preventing fusion with the lytic compartment [33,80]. As a result, symbiosomes with a “fake” identity of “late endosomes/young vacuoles” due to the presence of endocytotic identical markers on the membrane are able to survive and fix atmospheric nitrogen for several days (the time to fulfill the task for the infected cell). However, the mechanisms that regulate vacuole defunctionalization, the putative translational regulation of involved proteins [81], and the formation of an osmotic upshift of the symbiosome to ensure the vector of water transport have not yet been clarified. Methods to estimate the cost of nitrogen fixation have been proposed and are usually based on the amount of energy in terms of carbohydrates per the unit of fixed nitrogen [82]. However, the cost of co-existence of symbionts in terms of host cell fitness and life span has ever been considered. Generally, symbiosis is described as mutually beneficial to both partners [83], but the short life span and the inevitable scenario of infected cell death after 4–5 weeks of existence has been well described and accepted as the norm [84,85]. It is a reasonable assumption that the maintenance of an intracellular bacterial colony may have a detrimental effect on the host cell’s wellbeing. To identify the putative negative effects caused by an intracellular bacterial colony, the well-known fact of the high sensitivity of root nodule to ionic stresses such as salinity was used. Such a low tolerance suggested some pre-existing irregularities in the uptake or distribution of some ions in the nodule tissue [86,87]. As it turned out, the mature nitrogen-fixing cells during the 2–3 weeks of their existence were rapidly losing potassium ions (K+) [86,87]. It is understandable that the pool of K+ in infected cells is shared between two partners—the host plant cell and several thousand bacteria that propagate and reside inside host cells. This situation significantly increases the demand for potassium (K+). However, the deficiency is also caused by the insufficient of K+ inward transport. Analysis of the distributions of ion transporter proteins in infected cells versus non-infected ones showed that in mature infected cells, the K+ channel MtAKT1 (Figure 3A) and Na+/K+ exchanger MtNHX7 (Figure 3B) were mistargeted, rapidly shed from their destination membranes, and expelled to young vacuolar compartments. In uninfected cells located nearby, however, the potassium level and the distribution of transporter proteins on the target membranes did not undergo such drastic changes. The application of salt stress revealed the accumulation of 5–6 times more Na+ per infected cell versus a non-infected one. Thus, the presence of a bacterial colony in the cell caused the deterioration in the ion exchange and a failure in the distribution of proteins responsible for ion transport [86,87]. It is plausible that the hypoxic conditions of infected cells that promote the nitrogenase activity as well as the alteration in endomembrane traffic in infected cells may be causal in such a situation. Hence, the high sensitivity toward salt stress seems to be a consequence of the infected cell’s environment; i.e., it is a consequence of the presence on bacteria in cell’s symplast. Therefore, this is a default situation for infected cells. It is understandable that membrane protein biogenesis and proper targeting can fail at any of the various steps: translation, targeting, insertion, folding, or assembly [88]. Currently, we cannot diagnose all mechanisms for dislocation and retargeting of proteins in infected cells, but we can be sure that this situation is widespread and on a much larger scale than mere changes in the distribution of several ion transporters [12,31,32,33,86,87]. This must be taken into consideration in research aimed at improving the stress tolerance of root nodules. Putative gene modification to obtain the overexpression of selected genes as such may be useless if the proteins are not on their correct destination membranes. The real distribution of proteins (including transporters of necessary elements in infected cells) must be verified. Currently, membrane protein targeting, insertion into the transmembrane domains, translocation, additional folding steps in the membrane, and assembly with interaction partners have not yet been sufficiently studied in an infected cell environment. Taking into account the data described above, the aim to improve the health of infected cells may represent one of the possible ways to extend the period of active nitrogen fixation and reduce the cost of symbiosis for the host plant. The lifespan of symbiosomes is terminated in the so-called senescent zone [64,84,85]. The typical cytological events during an infected cell’s senescence/symbiosis termination have been well studied and described [84,85]. Symbiosomes in the zone of senescence fuse together, which is followed by the formation of lytic vacuole-like structures [89] as well as the expression of lytical enzymes [90,91] and induction of reactive oxygen species (ROS) [35,92]. Recently, with the aim of clarifying the mechanisms of nodule senescence, Sauviac et al. [93] performed a dual plant–bacteria RNA sequencing approach on M. truncatula–Sinorhizobium meliloti nodules that created a comprehensive resource of hundreds of host plant and bacterial genes that are differentially regulated during this stage of symbiosis. Some changes in gene expression in the zone of natural nodule senescence may also be a consequence of intracellular bacterial colony presence in the host cell. It can be assumed that the conditions in an infected cell become suboptimal during its lifespan. Currently, the reasons why an infected cell dies after a maximum of 5 weeks of existence while a genetically identical uninfected cell can live for years have not been explained. The changes in endomembranes of infected cells occur at each stage of symbiosis development, beginning with the architecture of the root hair after the contact with rhizobia up to the formation of lytic compartments in the zone of symbiosis termination. The entrance of microsymbionts triggers the formation of specific asymmetric protrusions of the plasma membrane. The growth of symbiotic structures in infected cells is mainly isodiametric for unwalled droplets and symbiosomes (apart from a tip growth of infection threads). The special ecological niche for living nitrogen-fixing bacteria is based on the specific membrane interface. Due to the presence of endocytotic identical markers on the membrane, symbiosomes are able to survive and fix atmospheric nitrogen for several days (the time to fulfill the task for the infected cell). The spectrum of proteins that appear on this and other membranes of an infected cell may not be identical to the spectrum and state of the homologous membrane in uninfected cells from nodules or other tissues. The functionality of proteins and their residence time on membranes in infected cells may have specific differences that distinguish them from proteins in uninfected cells. In this regard, the study of endoplasmic reticulum proteins and their transport into symbiosomes is quite important and timely. The maintenance of the bacteria colony in the host cell has its price that is expressed in the shortening of the life span, which may be an integral result of the infected cell’s conditions. The features of an infected cell’s endomembrane system must be taken into consideration in works aimed to improve certain aspects of the symbiotic relationship via creation of genetically modified mutants with an altered level of expression of certain genes. During the last 20 years, the study of symbiotic relations in plants has made a great progress. We can point to the tremendous advances in research on signaling between partners in the early stages of symbiosis and the excellent transcriptomics research that has made it possible to understand changes in gene expression during symbiosis development. However, a great number of the processes that relate to the regulation of membrane transport, protein targeting, changes in the cytoskeleton, and the regulation of osmotic processes in infected cells are still waiting to be explored.

PMC10002933

Satu Pekkala

Fecal Metagenomics and Metabolomics Identifying Microbial Signatures in Non-Alcoholic Fatty Liver Disease

02-03-2023

gut microbiota,metabolomics,metagenomics,liver fat,NAFLD,diet,metabolic pathways

The frequency of non-alcoholic fatty liver disease (NAFLD) has intensified, creating diagnostic challenges and increasing the need for reliable non-invasive diagnostic tools. Due to the importance of the gut–liver axis in the progression of NAFLD, studies attempt to reveal microbial signatures in NAFLD, evaluate them as diagnostic biomarkers, and to predict disease progression. The gut microbiome affects human physiology by processing the ingested food into bioactive metabolites. These molecules can penetrate the portal vein and the liver to promote or prevent hepatic fat accumulation. Here, the findings of human fecal metagenomic and metabolomic studies relating to NAFLD are reviewed. The studies present mostly distinct, and even contradictory, findings regarding microbial metabolites and functional genes in NAFLD. The most abundantly reproducing microbial biomarkers include increased lipopolysaccharides and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of branched chain amino acids, as well as altered lipid and carbohydrate metabolism. Among other causes, the discrepancies between the studies may be related to the obesity status of the patients and the severity of NAFLD. In none of the studies, except for one, was diet considered, although it is an important factor driving gut microbiota metabolism. Future studies should consider diet in these analyses.

Fecal Metagenomics and Metabolomics Identifying Microbial Signatures in Non-Alcoholic Fatty Liver Disease The frequency of non-alcoholic fatty liver disease (NAFLD) has intensified, creating diagnostic challenges and increasing the need for reliable non-invasive diagnostic tools. Due to the importance of the gut–liver axis in the progression of NAFLD, studies attempt to reveal microbial signatures in NAFLD, evaluate them as diagnostic biomarkers, and to predict disease progression. The gut microbiome affects human physiology by processing the ingested food into bioactive metabolites. These molecules can penetrate the portal vein and the liver to promote or prevent hepatic fat accumulation. Here, the findings of human fecal metagenomic and metabolomic studies relating to NAFLD are reviewed. The studies present mostly distinct, and even contradictory, findings regarding microbial metabolites and functional genes in NAFLD. The most abundantly reproducing microbial biomarkers include increased lipopolysaccharides and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of branched chain amino acids, as well as altered lipid and carbohydrate metabolism. Among other causes, the discrepancies between the studies may be related to the obesity status of the patients and the severity of NAFLD. In none of the studies, except for one, was diet considered, although it is an important factor driving gut microbiota metabolism. Future studies should consider diet in these analyses. WHO estimates that over 1.9 billion adults worldwide are overweight, and consequently, the frequency of metabolic disorders, including non-alcoholic fatty liver disease (NAFLD) has exacerbated. Metabolic disorders include a cluster of physiological conditions, including increased blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol or triglyceride levels, which often occur together. Alarmingly, these diseases now also extend to children, in addition to the young and middle-aged population [1]. In Western countries, up to 90% of the obese population is estimated to suffer from NAFLD [2]. In Nordic countries, NAFLD is the second-most increasing indication for liver transplantation, and thus, it is a great burden to the healthcare system. Therefore, new diagnostic tools allowing early detection of the disease would be of great importance. NAFLD is defined as excessive fat accumulation (over 5% fat in hepatocytes) in the liver, without secondary causes of fat accumulation, such as the excessive drinking of alcohol and treatment with steatogenic drugs (e.g., methotrexate). Histopathologically, NAFLD can be categorized into simple steatosis (non-alcoholic fatty liver, NAFL), which is diagnosed as a presence of hepatic fat accumulation without any histological or biochemical injuries, and non-alcoholic steatohepatitis (NASH), which is characterized by steatosis, inflammation, and hepatocyte damage, i.e., ballooning, and can be accompanied by cirrhosis or not [3,4]. It is estimated that 3 to 5% of NAFLD patients can develop NASH [5]. The high prevalence of NAFLD creates diagnostic challenges, and there is a growing need for reliable non-invasive diagnostic tools. Due to the importance of the gut–liver axis in the onset and progression of NAFLD [6], several recent studies have attempted to reveal the microbial signatures in NAFLD, to evaluate their suitability as diagnostic biomarkers of NAFLD, and to predict the progression of the disease. This article reviews the evidence of microbial signatures in NAFLD that have been analyzed using fecal metagenomics and metabolomics. Metagenomics refers to the analysis of gut microbiota composition and functional genes using shotgun sequencing. Metabolomics refers to quantification of the fecal metabolites using either nuclear magnetic resonance (1H-NMR) or ultra-high performance liquid chromatography (LC)/mass spectrophotometry (MS). Ultimately, the pitfalls and caveats of such approaches will be summarized, as well as the avenues for future directions. The literature searches for this review article were made between September and December 2022. The search words “fecal AND metabolomics AND (liver fat OR NAFLD OR NASH)” and “fecal AND metagenomics AND (liver fat OR NAFLD OR NASH)” were used in both PubMed and Ovid Medline. Animal studies were omitted from the search results. Due to the fact that liver biopsies are highly invasive, the development of new cost-effective diagnostic tools for NAFLD is important. What makes the early diagnosis difficult is that before the onset of severe fibrosis or cirrhosis, the NAFLD patients may remain asymptomatic. Therefore, the diagnosis is often made coincidentally due to abnormal findings in routine blood samples. Values above the upper limit of normal serum alanine aminotransferase (ALT, ~40 IU/L in men and ~30 IU/L in women), as well as abnormally high serum triglycerides and LDL cholesterol, can be an indication of NAFLD [7]. However, according to some studies, the liver enzymes may be completely normal in most patients [8]. At present, there are several available non-invasive methods to diagnose NAFLD; however, these do not enable the distinguishing of steatosis from steatohepatitis, nor do they evaluate the severity of hepatic fibrosis. In this context, several panel markers, indexes, and scores have been developed for diagnostics. For instance, the liver fat score includes as measured variables, including the presence of metabolic syndrome and type 2 diabetes (T2D), fasting serum insulin, serum aspartate aminotransferase (AST), and the AST/ALT ratio [9]. The fatty liver index (FLI) considers body mass index (BMI), waist circumference, serum triglyceride levels, and gamma-glutamyltransferase (GGT) in the general population, with low prevalence of T2D [10]. To distinguish NASH from NAFL, the HAIR score, which includes the determination of the presence of hypertension, elevated ALT, and insulin resistance, has been employed [11]. An advanced fibrosis scoring system, developed and validated by McPherson et al., is generated by determining age, hyperglycemia, BMI, platelet count, serum albumin, and the AST/ALT ratio [12]. However, measuring variables of blood and body composition is insufficient for the ultimate diagnosis, and thus, imaging techniques and other analyses are needed. While ultrasonography is the most cost-effective and suitable method in clinical practice, it may fail to detect mild steatosis. One study showed that ultrasound was unable to detect steatosis present in less than 10% of hepatocytes [13]. In addition, the visual assessment of NAFLD by ultrasonography exhibits significant substantial inter-observer variability, which limits the reproducibility of the results [14]. It is now well accepted that the pathogenesis of NAFLD involves multiple simultaneous “hits” associated with environmental, host genetic, and physiologic factors [15], as opposed to the initially proposed “two-hit theory” [16]. The multiple hit hypothesis implies that simple hepatic steatosis may be a benign process, and NASH might be a separate disease with a different pathogenesis. The pathogenic hits include: (1) inflammatory mediators derived from various tissues [17,18]; (2) increased lipid storage, lipogenesis, and (adipo)cytokines that activate endoplasmic reticulum stress [19,20,21]; (3) mitochondrial dysfunction [21] and reactive oxygen species due to lipotoxicity [22,23]; (4) nutrient sensing [24]; and (5) genetic factors [25,26,27,28]. Importantly, all these events may occur together rather than consecutively. Recent studies have also highlighted the importance of connective tissue dysfunction and insulin resistance in the onset of NAFLD [29,30,31]. However, if these above-described factors were used for diagnostic purposes, they would all require invasive sampling; thus, non-invasive alternatives are of interest. Nearly a decade ago, we [32] and Mouzaki et al. [33] were pioneers in showing that gut microbiota composition associates with hepatic fat content in humans. There are recent excellent reviews on the topic [34]; therefore, this review will concentrate on the advances in fecal metabolomics and metagenomics related to NAFLD. It is increasingly accepted that the abundance and functions of many members of the gut microbiota affect human physiology by processing the ingested food into certain bioactive metabolites [35]. These molecules can act as inter-tissue signaling messengers by penetrating the portal vein and subsequently, the liver, to promote or prevent hepatic fat accumulation (Figure 1). Collecting fecal samples for gut microbiota composition and microbial metabolite analyses would be an excellent non-invasive method for NAFLD diagnostics, which will be reviewed in the upcoming sections. While this review concentrates on the human gut microbiota metabolism (fecal metabolomics and metagenomics) and not animal studies, one important host molecular mechanism that connects the gut microbiota and its metabolism to NAFLD is briefly introduced below as an example of animal models. One mechanistic animal study showed that gut microbiota-dependent hepatic lipogenesis was mediated by hepatic stearoyl CoA desaturase 1 (SCD1) [36]. The authors used germ-free and conventional Toll-like receptor 5 (TLR5) deficient (T5KO) mice, which are prone to develop microbiota-dependent metabolic syndrome, to first show that the T5KO mice displayed elevated hepatic neutral lipid content, depending on the presence of gut microbiota. TLR5 recognizes flagellin, which is the structural protein of the locomotive organelle of bacteria [37]. After the initial observations, Singh et al. found that colonic short-chain fatty acids (SCFA) receptors, as well as hepatic lipogenic enzymes, including SCD1, were upregulated in T5KO mice, and that gut-derived SCFA were increasingly incorporated into palmitate in the liver. Dietary SCFA further aggravated hepatic steatosis and metabolic syndrome, which were impeded by the hepatic deletion of SCD1. All the above-mentioned effects were ablated in the germ-free mice, but when the germ-free mice were transplanted with the cecal microbiota of T5KO mice, their hepatic palmitate content doubled. The authors concluded that while several beneficial properties have been recognized for SCFA, their excess in conditions combined with innate immune deficiency and dysbiotic, overgrown microbiota due to T5KO may increase susceptibility to metabolic diseases [36]. The biological system effects of gut microbial metabolism are excellently reviewed elsewhere [35], and therefore, in this review the emphasis will be on NAFLD. It is likely that the severity of NAFLD affects the functions of the gut microbiota differently, and vice versa. Therefore, the reviewed studies are divided below into subsections by the disease severity (steatotic, without diagnosed NAFLD, NAFL, NASH, fibrosis, cirrhosis, or hepatocellular carcinoma). Ultimately, studies in children with NAFLD are also reviewed. The reviewed studies are listed in Table 1, which is primarily divided according to the sections below, and by the order of appearance of the references in the text. By far, the largest metagenomic study conducted in fatty liver disease included a sample of 6269 Finnish participants, most of which were overweight, but according to the BMI, there were normal weight individuals included as well [38]. It should be noted that the functional metagenomic profiling was qualitative and not quantitative because the sequencing depth did not allow for the assembling of contigs. In addition, instead of measuring liver fat content with imaging, the authors used FLI to categorize the participants into liver fat content groups. Nevertheless, FLI is a rather widely used and accepted index for NAFLD and its stratification [39]. Ethanol and the SCFA acetate production pathways were found to be positively associate with FLI [38]. Previously, it has been shown, for instance, that high-alcohol-producing strains of Klebsiella pneumoniae exist in humans with NAFLD [40]. Thus, it seems that endogenously produced alcohol may play a role in hepatic fat accumulation, at least in some populations. Generally, SCFA are considered to exert beneficial functions in the host, such as modulating immune functions [41] and gastrointestinal permeability [42]. However, they may also negatively impact the inflammatory status of the host [36]. Fecal metagenomic signatures have been described in non-diabetic morbidly obese women with hepatic steatosis [43]. By mapping the microbial genes into the Kyoto Encyclopedia of Genes and Genomes (KEGG) modules, it was found that steatosis associated positively with carbohydrate, lipid, and amino acid metabolism, as well as lipopolysaccharide (LPS) and peptidoglycan biosynthesis. LPS are recognized by Toll-like receptor 4 (TLR4), which expression has been shown to be increased in the livers of obese patients with NASH [44]. Peptidoglycan, in turn, is recognized by multiple pattern-recognition receptors, including nucleotide-binding oligomerization domain-containing proteins (NODs), domain-containing 3 (NLRP3), and Toll-like receptor 2 (TLR2) [45]. In addition to the above-mentioned pathways, Hoyles et al. also observed that hepatic steatosis was associated with an increased number of genes related to the biosynthesis of branched-chain amino acids (BCAA) and aromatic amino acids [43]. The metagenomic findings of feces were further supported by the elevated concentrations of these particular amino acids in plasma. To mechanistically show that the microbiome contributes to hepatic steatosis, the authors transplanted feces from steatotic human donors into mice. Indeed, the fecal transplants caused rapid hepatic fat accumulation in mice, which involved elevated circulating BCAA [43]. These observations are interesting, as numerous studies have linked BCAA to obesity and NAFLD (for review, see [46]). We recently compared fecal and plasma metabolomes of humans with low (<5% of fat in liver) and high (>5% of fat in liver) liver fat content, without diagnosed NAFLD [47]. The study groups did not differ from each other in BMI. We found that the fecal histidine metabolism product, N-omega-acetylhistamine, was markedly increased in individuals with fatty liver disease. In addition, another product of histidine degradation, anserine, positively associated with liver fat content [47]. Previously, plasma levels of histidine have been shown to associate with the grade of hepatic steatosis [48]. In agreement with a previous metagenome study [49], we found that the levels of lysine degradation product, saccharopine, were higher in the feces of individuals with high liver fat content [47]. As an indication of decreased steroid metabolism, the fecal levels of 6-hydroxybetatestosterone were reduced in the steatotic individuals. In contrast, a previous study reported that low serum testosterone levels were associated with hepatic steatosis in obese males [50]. In summary, the two metagenomic studies in individuals with hepatic steatosis show different microbial signatures, which may be due to the differences in obesity status between the study populations. Neither of the metagenomic studies determined dietary factors between the groups or used them as confounding factors [38,43]. In our metabolomic study, there were no major dietary differences between the high and low liver fat content groups, except that higher vitamin E and sucrose intake was observed in individuals with fatty livers [47]. Interestingly, sucrose is known to contribute to the onset of NAFLD [51], while vitamin E is considered as a possible treatment for NAFLD [52]. The main findings of the three reviewed studies in this section are presented in Figure 2. Ge et al. studied fecal metabolomics in patients with NAFLD and healthy controls using UHPLC/MS/MS [53]. All participants were overweight and/or had visceral obesity. Combining the metabolite identification with KEGG pathway analysis, the authors found that the metabolism of nicotinate, nicotinamide, and pyrimidine, as well as signaling pathways of calcium and oxytocin and pancreatic secretion were altered in NAFLD patients compared to healthy controls. Interestingly, nicotinamide adenine dinucleotide (NAD+) is being studied in clinical trials as a potential target to treat NAFLD [54]. However, Ge et al. failed to show differences in the fecal levels of nicotinate between the healthy and NAFLD groups [53]. Altered pyrimidine metabolism was reflected in lower fecal levels of uracil in the NAFLD patients. In addition, the catabolic byproduct of purine metabolism, xanthine, was also lower, likely due to the lower enzymatic activity of xanthine oxidase. The authors concluded that xanthine, along with the abundance of specific microbial taxa, might contribute to the diagnostics of NAFLD [53]. Intriguingly, it has been shown that the inhibition of xanthine oxidase can ameliorate hepatic steatosis in mice [55]. This might be related to the decreased production of reactive oxygen species (ROS) [56]. Based on the literature, it seems that microbial functional genes can differentiate less advanced NAFLD from NASH and NAFLD according to the presence of significant fibrosis [57] and the stage of fibrosis [58]. However, the authors of one paper did not perform shotgun metagenome sequencing but predicted the functional potential of the gut microbiota from 16S rRNA gene data using PICRUSt [57]. The name is an abbreviation for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States. PICRUSt is a bioinformatics software package designed to predict metagenome functional content from marker gene (e.g., 16S rRNA gene) surveys and full genomes using an algorithm developed by Languille et al. [59]. However, the enriched functional categories in NASH were mostly related to carbohydrate and lipid metabolism [57], which is similar to what has been found by others in simple steatosis [43] and in NASH [60]. Interestingly, patients with fibrosis could be distinguished from the patients without fibrosis by their microbial functional genes. Fibrosis was associated with enriched functional categories related to carbohydrate and lipid metabolism [57]. A study that combined real microbial metagenomics and the analysis of plasma metabolites in obese NAFLD patients [58] did not find similar microbial signatures in fibrosis, as did PICRUSt [57]. Of the set of 89 metabolites that are produced by both the host and the microbiota, 11 metabolites could differentiate between mild/moderate NAFLD and advanced fibrosis. These enriched genes/metabolites were mainly related to carbon metabolism in fibrosis grade 2, as well as to nucleotide and steroid degradation in fibrosis grade 1. In addition, higher SCFA butyrate was annotated in grade 1, while the SCFA butyrate and propionate were higher in grade 2. Many findings from plasma metabolites and fecal metagenomic pathways supported each other [58]. Contrary to these findings, using fecal metabolomics, we have found that testosterone metabolism in the gut is lower in obese individuals with fatty liver disease [47]. In addition to the stage of hepatic fibrosis, the obesity status of the patients appears to be linked to the distinct gut microbial features in NAFLD [61]. Lee et al. reported that while not seen in obese individuals with NAFLD, the levels of SCFA acetate and propionate increased along with the stage of fibrosis in non-obese individuals [61]. This again indicates that the SCFA are not necessarily always beneficial for the host’s health. Lee et al. further found that the fecal levels of several conjugated and unconjugated bile acids were higher in non-obese individuals with fibrosis, while in obese individuals, the levels of total conjugated bile acids were inversely associated with the severity of fibrosis [61]. Supporting the findings of fecal metabolomics, the expression levels of microbial genes encoding for bile salt hydrolase and 7α-hydroxy-3-oxochol-4-en-24-oyl-CoA dehydrogenase were lower in the non-obese patients with fibrosis. The contribution of the bile acids to the pathophysiology of NAFLD via the gut–liver axis is rather well established, yet the bile acids have been mostly analyzed in plasma and not in feces in NAFLD studies [62]. However, contrary to the findings of Lee et al. [61] reviewed above, Smirnova et al. reported that the fecal concentrations of several secondary bile acids were lower in obese NASH patients with advanced fibrosis [63]. Yet, there is a difference between the two studies in the obesity status of the patients. In the study by Smirnova et al., taurine conjugated bile acids in particular increased along with the stage of fibrosis [63]. Interestingly, when the authors looked at the NAFLD activity scores (NAS), the findings were the opposite. Compared to the healthy controls, the NAFLD patients had higher fecal levels of secondary bile acids and expression of microbial genes involved in the biotransformation of bile acids. Further, NASH patients had higher levels of conjugated bile acids than patients with NAFL [63]. This, in turn, is contrary to another study by Sui et al., which showed higher levels of primary bile acids, chenodeoxycholic acid, and cholic acid in the feces of non-diabetic individuals with NASH compared to healthy controls [64]. Nevertheless, these patients were of normal weight, and therefore, the obesity status may be related to the different results between the reviewed studies. Of the other fecal metabolites, increased kynurenine and decreased L-tryptophan levels were good predictors of hepatic steatosis [64]. The latter finding is interesting as a previous study had shown that tryptophan-derived metabolite kynurenine causes hepatic steatosis in mice by activating aryl hydrocarbon receptor signaling [65]. In summary, while fecal bile acids seem to play an important role in NAFLD and fibrosis, the reviewed studies present different findings, which may, at least partly, depend on the obesity status of the study populations. None of the studies reported whether there were differences in dietary intakes between the study groups, although one study [64] collected food consumption data. The main findings of the microbial metagenomes and fecal metabolomics of the studies reviewed in this section are presented in Figure 3. With the global rise in the incidence of obesity and type 2 diabetes, NAFLD-related hepatocellular carcinoma (HCC) and NAFLD-cirrhosis are also becoming common liver diseases [66]. By using metagenomics, Behary et al. showed that the gut microbiome of the NAFLD-HCC patients was characterized by a higher number of SCFA synthesizing genes [67], which is in line with what was found related to an earlier stage of the disease, namely higher FLI [38]. Compared to the NAFLD-cirrhosis patients and healthy controls, genes related to acetate (phosphate acetyltransferase, pta), butyrate (phosphate butyryltransferase, ptb), and propionate (fumarate reductase, frd, and succinate-CoA synthetase, scs) synthesis were over-expressed in the feces of the NAFLD-HCC patients [67]. The gene expression findings were further confirmed using targeted LC/MS/MS and 1H-NMR quantification of the fecal metabolites. The levels of acetate and butyrate, as well as oxaloacetate and acetylphosphate, which are intermediates of the SCFA metabolism, were higher in the feces of the NAFLD-HCC patients, while the propionate concentration did not differ between the study groups [67]. In the future, it would be interesting to investigate which other metabolites characterize the NAFLD-HCC patients using a non-targeted metabolomic profiling. In NAFLD-cirrhosis, the gut microbial signatures have been studied by Oh et al. [68]. Interestingly, similar to what has been shown in steatosis without diagnosed NAFLD [43], BCAA and aromatic amino acids were predictors of cirrhosis, as shown by both metagenomic and metabolomic analyses [68]. In the fecal samples of NAFLD-cirrhotic patients, the levels of L-tryptophan were increased due to its decreased metabolism. This is contrary to another study showing that decreased L-tryptophan levels were good predictors of hepatic steatosis [64]. To summarize the literature reviewed above, in NAFLD-associated cirrhosis and HCC, some metabolic signatures similar to those in hepatic steatosis without diagnosed NAFLD can be found, namely higher fecal levels of SCFA, BCAA, and aromatic amino acids. Thus, in the future it would be important to further explore their role and to consider whether these fecal metabolites would be suitable early biomarkers of advanced liver diseases before its onset. It should be noted, however, that as in the other studies reviewed above, none of the studies in this section considered dietary differences as confounding factors between the study groups. A multi-omics study by Michail et al. combined metagenomic, metabolomic, and proteomic approaches to study the gut microbiome of obese children, with and without NAFLD [49]. In contrast to one targeted metabolomics study showing higher fecal acetate and propionate levels in NAFLD patients [69], the 1H-NMR quantification of the fecal metabolites revealed that acetate levels were lower in pediatric NAFLD patients, while propionate was unaffected [49]. As reviewed above, again supporting the role of endogenously produced ethanol in NAFLD, the fecal levels of ethanol were ~2-fold higher in obese children with NAFLD than in the healthy children and obese children without NAFLD. Based on the microbial metagenomic analysis, the lysine degradation pathway was exclusively identified in children with NAFLD and not in healthy individuals [49]. This agrees with our metabolomic findings from adults, showing higher degradation products of lysine in the feces of individuals with high liver fat content [47]. The metagenome shotgun sequencing of Michail et al. suggested that the microbial energy metabolism, including fatty acid and carbohydrate biosynthesis, is much more enhanced in NAFLD pediatric patients compared to healthy children [49]. However, this might be solely due to the different obesity status of the patients in the studies, as it has been shown that an obese microbiome more efficiently harvests energy from the diet [70]. Testerman et al. studied the fecal metagenomes of children with and without NAFLD [71]. They observed that multiple pathways for lysine synthesis were increased, and histidine degradation was decreased in NAFLD patients. This is contrary to our recent metabolomics findings in adults with fatty liver, showing higher fecal levels of lysine and histidine degradation products [47]. However, in the NAFLD patient’s metagenomes, microbial metabolic pathways for BCAA, aromatic amino acids, and peptidoglycan synthesis were also enriched [71]. Interestingly, similar findings have been reported in morbidly obese adults with hepatic steatosis [43]. Thus, it could be that these metabolic pathways might help in the detection of the disease at an early age and/or stage of the disease. Another metagenomic study compared healthy children, obese children, and obese children with NAFLD [72]. Compared to healthy children, the obese pediatric patients with and without NAFLD had a lower abundance of microbial genes related to the pathways of replication and reparation, folding, sorting, and metabolism of amino acids. The presence of NAFLD differentiated the obese groups, showing the enrichment of pathways related to the digestive system, immune system, and glycan biosynthesis [72]. Thus, in this case, there were microbial signatures in NAFLD that were likely not dependent on the obesity status of the patients. In agreement with the findings of Hoyles et al. in adults [43], Kordy et al. report that compared to the healthy BMI-matched individuals, the microbiome of the pediatric patients with NASH was characterized by increased carbohydrate, lipid, and amino acid metabolism, as well as LPS biosynthesis [60]. While the panels of plasma metabolites could accurately predict NASH, this was not seen for the fecal metabolites analyzed from rectal swabs. The author of this current review suggests that the rectal swabs, even if stored at correct temperatures, may not be a reliable way to preserve the fecal metabolites for subsequent analyses. A combination of fecal metagenomics and targeted UPLC-MS/MS identified alterations in bile acid metabolism in children with NAFLD [73]. The number of genes related to the biosynthesis of secondary bile acids was more abundant in NAFLD patients, which agrees with one study in adults [63]. However, the comparison between the metagenomic and metabolomic results is a bit confusing, as the fecal levels of many secondary bile acids (a-hyodeoxycholic acid, 7-ketolithocholic acid, 23-nordeoxycholic acid, 7,12-diketolithocholic acid, 3-epideoxycholic acid, and dehydrocholic acid) were reduced in NAFLD, while only chenodeoxycholic acid-3-b-D-glucuronide was increased [73]. Unfortunately, the authors did not discuss these discrepant results in their publication. One study in children with NAFL and NASH used metagenomic shotgun sequencing to reveal microbial signatures related to the disease [74]. Compared to the BMI-matched healthy controls, microbial LPS biosynthesis was significantly enriched in children with NAFL and NASH. This finding agrees with what has been found in non-diabetic obese women with hepatic steatosis [43]. Several genes related to flagellar assembly were also enriched in children with NASH and in those with moderate-to-severe fibrosis [74]. We have previously shown in a mouse model that gut microbial flagellin causes hepatic fat accumulation, which is mediated by vascular adhesion protein-1 [75]. Altogether, these results suggest that flagellin may promote NAFLD, while other studies have suggested that a knockout of flagellin-recognizing TLR5 protects mice from NAFLD [36]. However, it should be noted that flagellin can also act via cytosolic nucleotide oligomerization domain (NOD)-like receptors to affect the inflammatory status [76]. Thus, the effects of flagellin and its receptors in relation to the onset of NAFLD should be further explored in the future. In summary, studies in children with NAFLD have reported microbial signatures, some of which are similar (increased LPS biosynthesis and amino acid metabolism) and some of which are distinct from each other. However, a few of the reviewed findings are similar to those seen in adults, such as higher fecal levels of ethanol in individuals with hepatic steatosis and increased LPS biosynthesis in NAFLD. None of the reviewed studies in children analyzed whether there were dietary differences between the study groups. The main microbial metagenomic and fecal metabolomic findings from children with NAFLD are summarized in Figure 4. Due to the increasing incidence of NAFLD, there is a growing need for non-invasive diagnostic tools. Because of the importance of the gut–liver axis in the pathophysiology of NAFLD, there is the hope that signatures of microbial metabolism could be used for diagnostic purposes. However, studies on the microbial metagenomics and fecal metabolomics in humans with NAFLD are surprisingly scarce. The existing studies reviewed here present mostly distinct, and even contradictory, findings on the microbial metabolites and functional genes in NAFLD. The most abundant reproducing markers reviewed here are increased LPS and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of BCAA, as well as altered lipid and carbohydrate metabolism. Among many other causes, the discrepancies between the studies may be related to the obesity status of the patients, their ethnicity, and the severity of the disease. Hence, to reliably identify microbial metabolites as potential diagnostic biomarkers in NAFLD, studies should be conducted repeatedly in cohorts with the same characteristics and with a larger number of patients. One of the most important factors driving the metabolism of the gut microbes is the diet. Besides the influence of long-term dietary intakes, diet can also very rapidly change the microbiome [77]. It is also well known that hypercaloric diets promote the onset of NAFLD [78]. Therefore, it is surprising that besides our study [47], none of the other studies reviewed here compared dietary intakes between the study groups. Thus, it cannot be known whether the reported metabolic differences in the gut microbiota between the study groups are solely or partly due to dietary differences. In the future, diet should definitely be considered in studies presenting results from fecal metagenomics and metabolomics so that the microbiome could be included in the possible future diagnostics of NAFLD. Interestingly, it seems that in undernourished NAFLD patients, altered bile acid signatures are consistently reported [79]. Bauer et al. effectively proposed that collaborative, multi-omics approaches could improve hepatic health in an undernourished population. Henceforth, similar approaches should also be considered for over nourished Western populations suffering from NAFLD.

PMC10002945

Yanlei Xiong,Yueming Wang,Yanlian Xiong,Lianghong Teng

4‐PBA inhibits hypoxia‐induced lipolysis in rat adipose tissue and lipid accumulation in the liver through regulating ER stress

09-02-2023

endoplasmic reticulum stress,hypoxia,lipolysis,liver dysfunction,white adipose tissue

Abstract High‐altitude hypoxia may disturb the metabolic modulation and function of both adipose tissue and liver. The endoplasmic reticulum (ER) is a crucial organelle in lipid metabolism and ER stress is closely correlated with lipid metabolism dysfunction. The aim of this study is to elucidate whether the inhibition of ER stress could alleviate hypoxia‐induced white adipose tissue (WAT) lipolysis and liver lipid accumulation‐mediated hepatic injury. A rat model of high‐altitude hypoxia (5500 m) was established using hypobaric chamber. The response of ER stress and lipolysis‐related pathways were analyzed in WAT under hypoxia exposure with or without 4‐phenylbutyric acid (PBA) treatment. Liver lipid accumulation, liver injury, and apoptosis were evaluated. Hypoxia evoked significant ER stress in WAT, evidenced by increased GRP78, CHOP, and phosphorylation of IRE1α, PERK. Moreover, Lipolysis in perirenal WAT significantly increased under hypoxia, accompanied with increased phosphorylation of hormone‐sensitive lipase (HSL) and perilipin. Treatment with 4‐PBA, inhibitor of ER stress, effectively attenuated hypoxia‐induced lipolysis via cAMP‐PKA‐HSL/perilipin pathway. In addition, 4‐PBA treatment significantly inhibited the increase in fatty acid transporters (CD36, FABP1, FABP4) and ameliorated liver FFA accumulation. 4‐PBA treatment significantly attenuated liver injury and apoptosis, which is likely resulting from decreased liver lipid accumulation. Our results highlight the importance of ER stress in hypoxia‐induced WAT lipolysis and liver lipid accumulation.

4‐PBA inhibits hypoxia‐induced lipolysis in rat adipose tissue and lipid accumulation in the liver through regulating ER stress High‐altitude hypoxia may disturb the metabolic modulation and function of both adipose tissue and liver. The endoplasmic reticulum (ER) is a crucial organelle in lipid metabolism and ER stress is closely correlated with lipid metabolism dysfunction. The aim of this study is to elucidate whether the inhibition of ER stress could alleviate hypoxia‐induced white adipose tissue (WAT) lipolysis and liver lipid accumulation‐mediated hepatic injury. A rat model of high‐altitude hypoxia (5500 m) was established using hypobaric chamber. The response of ER stress and lipolysis‐related pathways were analyzed in WAT under hypoxia exposure with or without 4‐phenylbutyric acid (PBA) treatment. Liver lipid accumulation, liver injury, and apoptosis were evaluated. Hypoxia evoked significant ER stress in WAT, evidenced by increased GRP78, CHOP, and phosphorylation of IRE1α, PERK. Moreover, Lipolysis in perirenal WAT significantly increased under hypoxia, accompanied with increased phosphorylation of hormone‐sensitive lipase (HSL) and perilipin. Treatment with 4‐PBA, inhibitor of ER stress, effectively attenuated hypoxia‐induced lipolysis via cAMP‐PKA‐HSL/perilipin pathway. In addition, 4‐PBA treatment significantly inhibited the increase in fatty acid transporters (CD36, FABP1, FABP4) and ameliorated liver FFA accumulation. 4‐PBA treatment significantly attenuated liver injury and apoptosis, which is likely resulting from decreased liver lipid accumulation. Our results highlight the importance of ER stress in hypoxia‐induced WAT lipolysis and liver lipid accumulation. Abbreviations CD36 cluster of differentiation CHOP CCAAT/enhancer‐binding protein homologous protein ER endoplasmic reticulum FABP1 fatty acid binding protein 1 FABP4 fatty acid binding protein 4 FFA Free fatty acids GRP78 glucose‐regulated protein 78 HSL Hormone‐sensitive lipase IRE1α inositol‐requiring enzyme 1α PERK protein kinase RNA (PKR) ‐like ER kinase PKA cAMP‐dependent protein kinase A TG Triacylglycerol UPR unfolded protein response WAT White adipose tissue Ascent to high altitude is associated with multi physiological and metabolic responses to counter with the stress of hypobaric hypoxia. White adipose tissue (WAT) is the largest reservoir of energy reserves, which stores energy in the form of triglyceride in lipid droplets. WAT plays an essential role in maintaining the whole‐body lipid metabolism homeostasis and accumulated evidence has demonstrated the functional association between adipose tissue and liver (Natarajan et al., 2017; Sun et al., 2012). In our previous work, hypobaric hypoxia was proved to accelerate lipolysis and suppress lipogenesis of WAT (Xiong et al., 2014). Under normal conditions, the lipid metabolism is a dynamic equilibrium process between different organs. However, under hypoxia environment, the activation of lipolysis promotes excessive free fatty acids (FFA) release, which is taken up by the liver, contributing to ectopic lipid accumulation and pathogenesis of liver (Lefere et al., 2016). Adipose tissue dysfunction could lead to increased delivery of FFA and glycerol to the liver which drives hepatic gluconeogenesis and facilitates the accumulation of lipids and insulin signaling inhibiting lipid intermediates (Bosy‐Westphal et al., 2019). Herein, hypoxia caused lipid metabolism disorder of WAT may further influence liver function, leading to the maladaptation to high‐altitude environment and increasing the incidence of acute mountain sickness (AMS). The endoplasmic reticulum (ER) is an organelle that functions to synthesize, fold, and transport proteins. It is also the site of triglyceride synthesis and nascent lipid droplet formation (Nettebrock & Bohnert, 2019). The sensing, metabolizing, and signaling mechanisms for lipid metabolism exist within or on the ER membrane domain (Balla et al., 2020). Dysregulation of ER homeostasis led to accumulation of misfolded proteins in the ER lumen and evoke ER stress (Henne, 2019). To reduce ER stress, the unfolded protein response (UPR) signal pathways are activated. Recently, accumulated evidence suggested that ER homeostasis and UPR activation play an important homeostatic role in lipid metabolism (Basseri & Austin, 2012; Mohan et al., 2019). As reported by Deng et al., ER stress could induce lipolysis by activating cAMP/PKA and ERK1/2 pathways (Deng et al., 2012). Previous study also found that burned patients displayed significant ER stress within adipose tissue and ER stress could augment lipolysis in cultured human adipocytes (Bogdanovic et al., 2015). The disulfide bond formation during protein synthesis is independent of oxygen, however, the post‐translational protein folding and isomerization process is oxygen‐dependent (Koritzinsky et al., 2013). Herein, hypoxia exposure could induce extensive protein modification in the ER and result in the accumulation of misfolded/unfolded proteins, which activate UPR and evoke ER stress (Chipurupalli et al., 2019; Maekawa & Inagi, 2017). We decided to test the hypothesis that ER stress may modulate hypoxia‐induced WAT metabolic derangement and liver dysfunction based on the following evidence: (1) ER is one of the major sites of lipid metabolism. (2) lipid metabolism and function are sensitive to oxygen concentration. (3) Hypoxia could induce ER stress due to the accumulation of misfolded proteins (Xu et al., 2015; Yang et al., 2014). (4) ER stress is closely correlated with lipid metabolism dysfunction (Mohan et al., 2019). (5) lipid metabolism in WAT plays a critical role in the progression of liver dysfunction (Dong et al., 2020). To address this issue, we investigated the effects of ER stress in hypoxia‐induced lipolysis using chemical chaperone 4‐PBA, antagonist of ER stress. The main objective of this study was to clarify the role of ER stress which regulates WAT lipolysis and liver lipid accumulation under continuous high‐altitude hypoxia exposure. An understanding of the interplay between tissues and these proposed mechanisms may provide novel therapeutic strategies for the treatment of the whole‐body metabolism dysfunction at high altitude. Adult male Sprague–Dawley rats (280–330 g) were purchased from Weitong Lihua Laboratory Animal Limited Company. The rats were housed at room temperature (22°C–25°C) and in a 12–12 h light–dark cycle with free access to food and water and adapted to the condition above for 1 week before experiment. All experiments were conducted in strict accordance with the laboratory animal care guidelines published by the US National Institutes of Health (NIH publication no. 85–23, revised 1996). All protocols concerning animal use were approved by the Institutional Animal Care and Use Committee of Institute of Basic Medical Sciences, Peking Union Medical College and Capital Medical University. Hypoxia group rats were placed in a hypobaric chamber (Guizhou Fenglei Air Ordnance Co., Ltd.) and subjected to hypoxia mimicking an altitude of 5500 m for 10 days. The chamber was opened daily for 30 min to clean and replenish food and water and room temperature was kept at 20°C–22°C. We monitored the body weights of rats every day. 4‐PBA (P21005) was commercially purchased (Sigma‐Aldrich). Rats were randomly divided into four groups: (1) Control group, (2) Hypoxia group, (3) Control + 4‐PBA (30 mg/kg /day), and (4) Hypoxia + 4‐PBA (30 mg/kg/day). The dose of 4‐PBA was set based on previous reports (Luo et al., 2015; You et al., 2019; Zeng et al., 2017). All the rats were sacrificed by decapitation and serum was obtained by centrifugation and stored at −80°C. The perirenal fat pads were collected and weighed immediately, frozen in liquid nitrogen, and stored at −80°C. WAT and liver tissue were fixed in 4% paraformaldehyde overnight, followed by embedment in paraffin and longitudinal slicing, with 4‐μm‐thick sections obtained for hematoxylin‐eosin (HE) staining. The stained slides were examined by microscopy for histomorphological analyses. A commercial terminal deoxynucleotidyl transferase‐mediated dUTP nick‐end labeling (TUNEL) kit (Roche) was employed to assess the degree of hepatic cell apoptosis. Histological alterations were assessed in randomly selected histological fields at ×400 magnification and apoptosis index (AI) was calculated. Homogenized rat WAT was lysed in 200 μl RIPA lysis buffer (Beyotime, P0013B) with 1% phenylmethyl sulfurylfluoride and 4% complete protease inhibitor cocktail mix (Roche). Extracts were centrifuged at 14,000 g for 15 min at 4°C. Eighty micrograms of total protein was used for sodium dodecyl sulfate‐polyacrylamide gel electrophoresis, followed by transferring blotting to nitrocellulose membrane (Millipore Corp., Billerica). Membranes were then blocked with 5% non‐fat‐dried milk in PBS for 1 h with gentle shaking. Membranes were incubated first with primary antibodies (dilution: 1:1000) overnight at 4°C, in 1% BSA in PBS overnight at 4°C with shaking. The following primary antibodies were purchased from Cell Signaling Technology: anti‐p‐HSL (#4139), anti‐HSL (#18381), anti‐pPKA, anti‐perilipin, anti‐Phospho‐PKA Substrate (RRXS*/T*) (#9624), anti‐GRP78 (#3183 S), anti‐CHOP (#2895P), anti‐protein kinase‐like eIF2α kinase (PERK) (#3192 S), and their phosphorylated species. anti‐ATGL antibody (ab109251), anti‐CGI58 antibody (ab111984), and anti‐β‐actin antibody (ab6276) were purchased from Abcam. Then, membranes were washed and incubated with secondary antibodies for 2 h at room temperature. Finally, the samples were visualized by enhanced chemiluminescence using Tanon‐410 automatic gel imaging system (Shanghai Tianneng Corporation). After scanning, band density was analyzed using Image J 1.33 software (National Institutes of Health). Total RNA was prepared from frozen liver tissues with TRIZOL (Invitrogen) reagent and the cDNA was synthesized using TransScript TM First‐Strand cDNA Synthesis Super‐Mix (TransGen Biotech, AT301). The program was run on a S1000 Thermal Cycler. Quantitative real‐time PCR was performed using the SYBR®Pre‐mix Ex TaqTMkit (Takara, RR420A) and analyzed in a step‐one plus RT‐PCR system (life science, Applied Biosystems). The primer sequences are listed in Table 1. Serum levels of non‐esterified fatty acid (NEFA) and glycerol were measured using NEFA kit (A042, Jiancheng Biotechnology) and Glycerol Assay kit (F005‐1, Jiancheng Biotechnology), respectively. These assays were performed according to manufacturer's instructions. Serum levels of triglyceride (TG), total cholesterol (TC), high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C) were measured by an automatic biochemical analyzer (Chemray 240, Rayto Life and Analytical Sciences). Serum alanine (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) microplate test kits were obtained from Nanjing Jiancheng Bioengineering Institute. These assays were performed as previously described (Wang et al., 2020). Briefly, ALT, AST, and ALP activities were evaluated at 37°C for 15 min by assessing for a decrease in absorbance at a wavelength of 510 nm, with Chemi Lab ALT, AST, and ALP assay kits, respectively. The data are presented as mean ± standard error (SE). For Western blot, protein levels were normalized to β‐actin. Statistical significance is determined by one‐way Analysis of variance (ANOVA) or nonparametric for more than three groups. p‐Value < .05 was considered statistically significant (SPSS 18.0 software). To investigate the role of ER stress in WAT under hypoxia treatment, we first examined the expression of ER stress markers, namely GRP78 and CHOP (Figure 1a). Under ER stress conditions, increased GRP78 is dissociated from unfolded proteins and activates ER stress receptors triggering the UPR. As shown in Figure 1b,c, hypoxia exposure significantly increased levels of GRP78 and CHOP. Continuous hypoxia treatment also activated ER stress‐related pathways in rat adipose tissue, evidenced by enhanced p‐PERK/PERK ratio (Figure 1d) and p‐IRE1α/IRE1α ratio (Figure 1e). 4‐PBA treatment significantly attenuated hypoxia‐induced ER stress, evidenced by decreased GRP78, CHOP, p‐PERK/PERK ratio, and p‐IRE1α/IRE1α ratio in 4‐PBA + hypoxia group as compared with hypoxia group. Compared with control group, exposure to hypoxia equivalent to an altitude of 5500 m for 10 days significantly reduced the body weight of rat and wet weight of perirenal fat (Figure 2a,b). Both serum levels of glycerol and FFA significantly increased in hypoxia group rats, indicating enhanced lipolysis under hypoxia exposure (Figure 2c,d). In support of these findings, histological analysis of WAT showed that continuous hypoxia significantly reduced the volume of adipocytes compared with that in control group rats (Figure 2e,f). Hypoxia exposure led to increased serum levels of triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), while the levels of total cholesterol (TC) level and high‐density lipoprotein cholesterol (HDL‐C) did not change significantly (Figure 2g–j). To investigate the effect of inhibition of ER stress on WAT lipolysis under hypoxia, we first evaluated the body weight and wet weight of perirenal fat in hypoxia rats with or without 4‐PBA treatment. 4‐PBA significantly attenuated the reduction of body weight and wet weight of perirenal fat after 10 days exposure to hypoxia (Figure 2a,b). In addition, inhibition of ER stress via 4‐PBA was associated with a significant reduction of lipolysis, evidenced by a significant reduction in serum glycerol and FFA levels (Figure 2c,d). Moreover, 4‐PBA treatment significantly attenuated hypoxia caused reduction of adipocyte volume (Figure 2f). 4‐PBA treatment effectively attenuated hypoxia‐induced increased levels of TG (Figure 2j). Endoplasmic reticulum stress has been suggested to trigger lipolysis in adipocytes. The lipolysis process is closely correlated with the production of cAMP and activation of cAMP‐dependent protein kinase A (PKA). In our study, hypoxia challenge significantly increased pPKA production (Figure 3a,b), which phosphorylates HSL and perilipin (Miyoshi et al., 2006; Sztalryd et al., 2003). The p‐HSL/HSL ratio (Figure 3c) and p‐Perilipin/Perilipin (Figure 3d) significantly increased in the hypoxic group, which were attenuated by 4‐PBA treatment. Although the abundance of ATGL remained unchanged in the WAT of the hypoxia rats, the level of CGI‐58 significantly increased in the hypoxia rats compared with the control rats (Figure 3e,f). Taken together, these data indicated that the inhibition of ER stress was shown to alleviate hypoxia‐induced lipolysis mainly by blocking the activation of cAMP‐PKA‐pHSL/Perilipin pathway. Under continuous hypoxia exposure, increased delivery of free fatty acids (FFA) caused by enhanced lipolysis in WAT may contribute to the lipid accumulation in the liver. As shown in Figure 4a, levels of FFA content significantly increased in hypoxia group rat liver, which was attenuated by 4‐PBA treatment. Lipid uptake in the liver was regulated by many transporters, including cluster of differentiation (CD36), fatty acid binding protein 1(FABP1), and FABP4. mRNA levels of CD36, FABP1, and FABP4 that regulate the entry of fatty acids into hepatocyte, are generally upregulated to cope with increased circulation FFAs (Figure 4b–d). Hypoxia‐induced liver lipid accumulation may further trigger the pathogenesis of liver injury, serum levels of liver enzyme were tested to confirm our speculation. As shown in Figure 5a–c, the hypoxia group rat exhibited a marked increase in the levels of AST, ALT, and ALP (p<.05), indicating potential liver injury. However, the hypoxia + 4‐PBA group significantly decreased the levels of AST and ALT (p<.05) when compared with hypoxia group, indicating that 4‐PBA inhibits hypoxia‐induced hepatocellular injury. The apoptosis status of rat liver exposed to hypoxia was evaluated with a TUNEL assay. As shown in Figure 5d,e, the percentage of apoptotic cells was significantly increased in hypoxia group as compared with control group, which was effectively attenuated by 4‐PBA treatment. Lipid metabolism in white adipose tissue played an essential role in maintaining energy homeostasis at high‐altitude area. In this study, WAT ER stress‐mediated lipolysis is enhanced in a rat model of high‐altitude hypoxia. Moreover, we found that increased FFA release results in liver lipid accumulation and liver dysfunction, which was attenuated by the inhibition of ER stress using 4‐PBA. As ER membrane are located with a variety of lipid metabolism‐related enzymes and ER is the major site of lipid metabolism, ER is involved in the control of metabolic homeostasis via regulating lipid metabolism. Under normal conditions, ER in the adipocyte functions to meet the demands of protein synthesis and secretion, triglyceride synthesis, nascent lipid droplet formation, and nutrient sensing. However, ER function is overwhelmed and the UPR is activated under stressful conditions (Menikdiwela et al., 2019; Sikkeland et al., 2019). Therefore, perturbations in ER homeostasis exerts a vital pathogenic mechanism in multi metabolic disorders of adipose tissue (Khan & Wang, 2014; Suzuki et al., 2017). Adverse stimuli like hypoxia may pose challenges to adipocyte and induce ER stress. In the present study, continuous hypoxia exposure evoked ER stress in adipose tissue, evidenced by increased GRP78, CHOP, p‐PERK, and p‐IRE1α expression in rat WAT. Our finding is in accordance with previous studies showing that hypoxia exposure induce ER stress in 3 T3‐F442A and 3 T3‐L1 adipocytes (Mihai & Schroder, 2015). UPR pathways were activated to ameliorate the overload of unfolded proteins under ER stress, which in turn influence lipid metabolism (Song et al., 2016). The activation of ER stress in adipose tissue may further induce lipolysis and elevated circulating FFAs (Song et al., 2017). To confirm the potential role of the ER stress and UPR in the modulation of the lipolysis, we treated rat with 4‐PBA, an ER stress inhibitor. 4‐PBA treatment led to significant reduction in lipolysis, which blocked the phosphorylation of HSL and perilipin. As the results from upstream regulation, 4‐PBA treatment then effectively reduced glycerol and FFA release from adipose tissue, suggesting that ER stress‐mediated lipolysis mainly by regulating cAMP‐PKA/HSL under hypoxia. Similar to our study, enhanced lipolysis and ER stress occurred in the visceral WAT and inhibition of ER stress alleviated lipolysis in a rat model of chronic kidney disease(Zhu et al., 2014). In addition, curcumin was reported to suppress the ER stress‐mediated lipolysis via cAMP/PKA/HSL pathway (Wang et al., 2016). Deng et al., also reported that ER stress involved lipolysis through up‐regulation of GRP78 and activation of phosphorylation status of PERK and eIF2α in rat adipocytes (Deng et al., 2012). Since the liver is the largest metabolic organ and regulates various physiological and metabolic processes, it also performs a key role in high‐altitude adaptation (Xu et al., 2019). Adipose dysfunction is closely associated with metabolism‐related liver diseases, an understanding of the interplay between tissues and these proposed mechanisms is still necessary (Da Silva Rosa et al., 2020). Accumulating data are pointing out the pathophysiological role of ectopic fat accumulation in different organs, including the liver (Bosy‐Westphal et al., 2019). In this study, the increased uptake of circulating lipids induced by WAT lipolysis significantly stimulated hepatic expression of lipid uptake and transport proteins CD36 and FABP4, which resulted in excess fatty acid uptake and lipid over accumulation in the liver. As a result, hypoxia‐treated rats displayed increased liver enzymes and hepatic apoptosis. As shown in Figure 6, 4‐PBA effectively attenuated hypoxia‐induced lipolysis via cAMP‐PKA‐HSL/perilipin pathway. The protective effect of 4‐PBA on liver injury and apoptosis, is likely resulting from decreased liver lipid accumulation via inhibiting FFA transport. Lines of evidence proved that excess FFA may modify the biology and function of hepatocyte and play an essential role in the pathogenesis liver dysfunction (Pereira et al., 2021). A high serum level of saturated FFAs is associated with hepatocyte lipo‐apoptosis (Takahara et al., 2017). In line with our fundings, Hubel, E., et al. found that repetitive Amiodarone treatment led to ER stress and aggravated lipolysis in adipose tissue while inducing a lipotoxic hepatic lipid environment and hepatic injury (Hubel et al., 2021). In conclusion, enhanced ER stress‐mediated WAT lipolysis was observed in a rat model of high‐altitude hypoxia, which contributes to hepatic dysfunction and apoptosis through excess release of FFA. Our findings highlight the vital role of 4‐PBA in WAT lipolysis and liver dysfunction via regulating ER stress, which may provide novel insights into systemic metabolic disturbances in high‐altitude area. The authors declare no conflict of interests.

PMC10002948

Hyeon Ji Kim,Sung Joon Mo,Jisoo Kim,Bora Nam,Soo‐Dong Park,Jae‐Jung Sim,Jaehun Sim,Jung‐Lyoul Lee

Organic vegetable juice supplement alleviates hyperlipidemia in diet‐induced obese mice and modulates microbial community in continuous colon simulation system

13-01-2023

colon simulation system,hyperlipidemia,lipid profiles,organic vegetable juice

Abstract In this study, we investigated the effects of organic vegetable juice (OVJ) supplementation on modulating the microbial community, and how its consumption ameliorated blood‐lipid profiles in diet‐induced obese mice. Here, we studied the alleviating effect of hyperlipidemia via animal experiments using diet‐induced obese mice and analyzed the effect of OVJ on the microbial community in continuous colon simulation system. OVJ consumption did not have a significant effect on weight loss but helped reduce the weight of the epididymis fat tissue and adipocytes. Additionally, blood‐lipid profiles, such as triglyceride, high‐density lipoprotein, and glucose, were improved in the OVJ‐fed group. Expression levels of genes related to lipid synthesis, including SREBP‐1, PPARγ, C/EBPα, and FAS, were significantly decreased. In addition, OVJ treatment significantly reduced inflammatory cytokines and oxidative stress. OVJ supplement influenced intestinal bacterial composition from phylum to genus level, including decreased Proteobacteria in the ascending colon in the phylum. At the family level, Akkermansia, which are associated with obesity, were significantly augmented in the transverse colon and descending colon compared to the control juice group. In addition, treatment with OVJ affected predicted lipid‐metabolism‐function genes related to lipid synthesis. These results suggest that OVJ supplementation may modulate gut microbial community and reduce the potential symptom of hyperlipidemia in diet‐obese mice.

Organic vegetable juice supplement alleviates hyperlipidemia in diet‐induced obese mice and modulates microbial community in continuous colon simulation system In this study, we investigated the effects of organic vegetable juice (OVJ) supplementation on modulating the microbial community, and how its consumption ameliorated blood‐lipid profiles in diet‐induced obese mice. Here, we studied the alleviating effect of hyperlipidemia via animal experiments using diet‐induced obese mice and analyzed the effect of OVJ on the microbial community in continuous colon simulation system. OVJ consumption did not have a significant effect on weight loss but helped reduce the weight of the epididymis fat tissue and adipocytes. Additionally, blood‐lipid profiles, such as triglyceride, high‐density lipoprotein, and glucose, were improved in the OVJ‐fed group. Expression levels of genes related to lipid synthesis, including SREBP‐1, PPARγ, C/EBPα, and FAS, were significantly decreased. In addition, OVJ treatment significantly reduced inflammatory cytokines and oxidative stress. OVJ supplement influenced intestinal bacterial composition from phylum to genus level, including decreased Proteobacteria in the ascending colon in the phylum. At the family level, Akkermansia, which are associated with obesity, were significantly augmented in the transverse colon and descending colon compared to the control juice group. In addition, treatment with OVJ affected predicted lipid‐metabolism‐function genes related to lipid synthesis. These results suggest that OVJ supplementation may modulate gut microbial community and reduce the potential symptom of hyperlipidemia in diet‐obese mice. Vegetables are a major source of phytochemicals with potential beneficial health properties (Nuutila et al., 2003; Singh et al., 2009). Among the major phytochemicals of vegetables are polyphenols and carotenoids. Polyphenols have been studied for their antioxidant properties of preventing the damage caused by reactive oxygen species (ROS), such as hydroxyl radicals, hydrogen peroxide (H2O2), and superoxide (Williams et al., 2013). Carotenoid compounds have been studied for their anti‐obesity and anti‐inflammatory effects (González‐Castejón & Rodriguez‐Casado, 2011). Intake of vegetables prevented damage by oxidative stress and improved hyperlipidemia according to previous studies. The relationship between lipid levels in the blood and the level of antioxidants from vegetables has been recently suggested (Kim et al., 2008; Yang et al., 2008). Obesity occurs because of many factors, such as energy imbalance, neurosecretion factors, and environmental factors. Recently, the number of obese patients has sharply increased due to westernized diet, stress, and lack of exercise, and obesity has been a major health problem worldwide (Jeung et al., 2019). Obesity causes various diseases, such as metabolic syndrome, cholelithiasis, cardiovascular disease, hypertension, diabetes, and hyperlipidemia (Bray, 2000). Hyperlipidemia refers to a condition that causes inflammation due to the presence of more fatty substances than necessary in the blood (Williams et al., 2013). Although hyperlipidemia does not have any specific symptoms, it is a risk factor for high blood pressure, arteriosclerosis, and stroke, and significantly increases the mortality rate in cardiovascular diseases (Klop et al., 2013; Nelson, 2013). The human gut microbiota is composed of more than 1 million bacteria and a complex community of over 100 trillion diverse bacteria (Doré & Blottière, 2015; Graf et al., 2015). The gastrointestinal tract (GIT) includes a diverse and complex microorganism community, which are major contributors to human health (Mangal et al., 2017). The human digestive system has no digestive enzymes for plant‐derived complex carbohydrates, but the human gut microbiota can decompose and utilize them (Graf et al., 2015). In addition, gut microbiota plays a role in producing organic acid and short‐chain fatty acids (SCFAs) including propionate, butyrate, and acetate in the human GIT. These SCFAs are known to affect and regulate the microbial composition of the human intestinal microbiota (Den Besten et al., 2013). For these reasons, studies of human intestinal microbiome using genomic and metagenomic analyses on various topics have been actively conducted in recent years. The in vivo analysis of human or animal gut is an ideal method to investigate intestinal microbiota, but these methods have technical and ethical difficulties, including expensive experimental cost, long time consumption, and difficulty in standardization due to limitations in controlling individual diets (Cha et al., 2018). In addition, in vivo studies are limited to fecal samples, which do not provide information about dynamic microbial changes in the fermentation site of the gut (Sousa et al., 2008). Furthermore, the gut microbiome of in vivo is often impaired due to inter‐individual differences associated with numerous factors such as age, gender, diet, geography, genetic background, and antibiotic use (Williams et al., 2015). To resolve these problems, an in vitro gut fermentation model has been developed and characterized by applying simple batch culture conditions and using a more complex apparatus for human fecal samples to control pH, temperature, and anaerobic conditions. A simple culture system, such as the TNO in vitro model, replicates the proximal colon in a single‐segment fermenter, whereas the three‐stage continuous system replicates the whole large intestine (Cinquin et al., 2006; Feria‐Gervasio et al., 2014). Batch colon simulation models are generally closed systems, and these models are used with sealed vessels containing suspensions of fecal samples and culture system medium under anaerobic conditions. Batch culture systems have the advantage of being easy to set up and useful for fermentation, but these systems create a short time frame for fermentation research and are unable to control microorganisms. In contrast, continuous culture systems are open systems, where the fresh medium is injected and waste is released periodically. These systems simulate the major parts of the large intestine, including the ascending colon (AC), transverse colon (TC), and descending colon (DC). Continuous colon simulation systems are well‐controlled environmental parameters, which enable the detection of changes in metabolites and microbial composition in each part of the large intestine (Adamberg et al., 2014; Costabile et al., 2015; Maccaferri et al., 2012). Therefore, continuous colon simulation systems are more similar to the human GIT compared to the batch model. This study investigated whether organic vegetable juice (OVJ) can modulate large intestinal microbiota and affect the predicted lipid metabolism function genes using continuous colon simulation systems. Based on the results of continuous simulation systems, we studied the effects of OVJ on the blood‐lipid levels, liver gene expression, and adipocytes in the epididymal fat of diet‐induced obese mice. In addition, we investigated the effects of OVJ on the antioxidant levels of diet‐induced obese mice. Figure 1a shows the design of the in vivo experiments performed in this study. Six‐week‐old male C57BL/6 was purchased from Laonbio. All mice were fed at constant humidity (55 ± 10%) and temperature (22 ± 1°C) with a 12 h light/dark cycle. After 7 days of acclimatization, mice were fed a normal diet group (n = 10; AIN‐93G), high‐fat diet (HFD) group (n = 10; Rodent diet with 60 Kcal% fat), and high‐fat with organic vegetable juice (HFD‐OVJ) (n = 10, group) for 9 weeks. The composition of the ND was formulated based on the AIN‐93G purified rodent diet. In this study, the recommended daily intake of OVJ obtained from hy Co., Ltd. was applied for mice to examine the health effects of OVJ. Table S1 shows the configuration of the OVJ. The OVJ was freeze‐dried, evenly mixed with a HFD in powder form, and then supplied to mice in the HFD‐OVJ group. Body weight and food intake were measured weekly. The food efficiency ratio (FER) was calculated by applying the equation: Blood samples were taken from the inferior vena cava and immediately placed at room temperature (20–23°C) and then centrifuged at 3000 g at 4°C for 10 min. The serum was separated from the blood sample. The harvested serum was stored at −80°C until analysis. The liver and epididymis fat tissues were collected, rinsed with sterilized PBS, and weighed. The partial liver tissue was stored in a deep freezer at −80°C immediately after collection for gene expression analysis using real‐time PCR. The animal experimental plan was approved by the Ethics Committee at the R&D Center, hy Co., Ltd. (AEC‐2020‐00003‐Y). Serum samples were collected at T&P Bio for blood analysis. The serum total cholesterol (T‐CHOL), triglyceride (TG), high‐density lipoprotein cholesterol (HDL), low‐density lipoprotein cholesterol (LDL), glucose (GLU), aspartate transaminase (AST), and alanine transaminase (ALT) levels were determined using Beckman Coulter AU480 analyzer (Beckman Coulter Inc.). Serum samples remaining after the blood biochemistry tests were used to measure the following antioxidant biomarkers: (a) 8‐hydroxy‐2‐deoxyguanosine (8‐OHdG) ELISA Kit (Abcam) was used. (b) malondialdehyde (MDA) concentration in serum samples was measured using a lipid peroxidation Assay Kit (Abcam). (c) H2O2 level was measured using a Catalase Assay Kit (Colorimetric/Fluorometer) (Abcam). The liver and epididymis fat tissues were washed with sterilized PBS and fixed in 10% formalin. Tissue samples were obtained from T&P Bio for histological analysis. Fixed tissues were implanted in paraffin for hematoxylin and eosin staining. The liver and epididymis fat tissues were observed under a fluorescence microscope (Axiovert 200M, Carl Zeiss) at a magnification of ×20 and ×10, respectively. Total tissue RNA was extracted from liver tissues using the easy spin Total RNA Extraction Kit (iNtRON) via bead‐beating. The liver tissues were mixed with 1 ml lysis buffer and transferred into lysing matrix tubes, containing specialized beads (MP Biomedicals), and pulverized through Fastprep24. After bead‐beating, the remaining procedure of easy spin Total RNA Extraction Kit was followed. Consequently, total RNA was eluted with 50 μl elution buffer. Total RNA samples were quantified using Nanodrop and stored at 20°C until gene expression analysis. The extracted total RNA was reverse‐transcribed into cDNA using an Omniscript RT Kit (Qiagen). Reverse transcription PCR conditions were set at 37°C for 60 min. The cDNA was amplified using a QuantStudio 6 Flex‐Real Time Instrument with a gene expression master mix. Real‐time PCR was performed using mouse‐specific TaqMan Gene Expression Assays and normalized by the expression of GAPDH (Applied Biosystems). Table S2 shows the catalog numbers of the genes and names. Figure 1b shows the workflow of the continuous colon simulation system performed in this study. Fecal samples were collected from three healthy adults who had not taken antibiotics for 3 months. Fecal samples were diluted with phosphate‐buffered saline (PBS) at a 1:10 (v/v) ratio in an anaerobic chamber. The fecal slurry sample was separated into each vessel at a final concentration of 2%. The continuous colon simulation system medium contained 1 g/L peptone, 4 g/L mucin, 0.5 g/L l‐cystein‐HCl, 1 g/L xylan, 0.5 g/L inulin, 0.4 g/L bile salt, 0.0025 g/L resazurin, 3 g/L yeast extract, 0.4 g/L d‐glucose, 2 g/L pectin, 1 g/L arabinogalactan, and 3 g/L starch. To simulate the environment of the large intestine, conditions were created for the three major parts of the large intestine; AC, TC, and DC. The volume and pH were as follows: 300 ml, pH 5.5 for AC; 400 ml, pH 6.2 for TC; 325 ml, pH 6.8 for DC (Cha et al., 2018). To maintain the anaerobic conditions in the simulation system, nitrogen gas (N2) was constantly injected at a flow rate of 10 ml/min. The temperature of each vessel was maintained at 37°C and the pH was automatically adjusted with 1 N HCl and 1 N NaOH. In addition, the pump on/off time interval was controlled to 12.5 ml/h to maintain a continuous flow. The colon system was pre‐run to achieve chemical and microbial stabilization for 2 weeks. After the stable step, the sample was treated in the AC and the washout step proceeded for 2 weeks. Organic vegetable juice was obtained from the hy Co., Ltd. Control juice was diluted with water and mixed carbohydrates (glucose 4.44 g/200 ml, fructose 4.52 g/200 ml, and sucrose 7.84 g/200 ml). The amount of these monosaccharides and disaccharides was the same as the OVJ. Two hundred microliters OVJ and control juice were injected into the AC of the continuous colon simulation system per day for 2 weeks. The same amount of sample of fecal slurry from the colon simulation system was carried out at a constant time point at the same amount in each vessel. Sampling was performed a total of 8 times, once a day from 2 days before the end of the stable period, 4 days before the end of the juice treatment period, and 2 days before the end of the washout period. These fecal slurries were used to analyze microbial community. The bioinformatics analysis of fecal DNA samples from the colon simulation system was carried out at Chunlab. Total fecal DNA samples were extracted using the QIAamp DNA Stool Mini Kit (Qiagen). PCR amplification of 16S rRNA sequences was conducted to prepare DNA sequencing templates. The V3–V4 region of the 16S rRNA sequence was amplified using the 341‐forward (341F)/805‐reverse (805R) primer set (341F: 5′‐TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG‐3′; 805R: 5′‐GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC‐3′). PCR conditions for the 341F/805R primer set were as follows: initial denaturation at 95°C for 3 min; 25 cycles of denaturation at 95°C for 30 s; annealing at 55°C for 30 s; extension at 72°C for 30 s; final elongation at 72°C for 5 min. After amplification of the 16S rRNA gene, the 16S rRNA amplicon library was used as a template DNA for next‐generation sequencing (NGS). Illumina MiSeq sequencing platform (Illumina) was used for NGS. The microbiome taxonomic profiling was analyzed using the EzBioCloud database provided by Chunlab. The raw data were analyzed using the QIIME 1.9.1 package program. The sequencing data were filtered for low‐quality reads and mismatched indexes using “Trim sequence” during quality control. High‐quality sequences of 300 bp were extracted using open reference clustering, one of several operational taxonomic unit clustering (OTU clustering) methods. After OTU clustering, Chimera checking was performed using ChimerSlayer. β‐diversity analysis was performed using unweighted UniFrac distances and visualized based on unweighted PCoAs. Linear discriminant analysis effect size (LEfSe) analysis (Segata et al., 2011) and PICRUSt platform were used for metagenome prediction (Langille et al., 2013). The data were analyzed using R version 3.6.2 (https://www.r‐project.org). All datasets have been deposited in NCBI Gene Expression Omnibus with the accession code PRJNA720297 and GSE171609. All data were expressed as mean ± standard error (SE). All data in this study were presented as the mean ± SE. For blood analysis, gene expression data analysis, and metabolic analysis, differences between groups (Normal vs. HFD, HFD vs. HFD‐OVJ) were evaluated using unpaired Student's t‐tests. p < .05 was considered statistically significant. Body weight of the HFD group was significantly increased after only 1 week of the HFD. Final body weight was 30% higher in the HFD group than in the normal group (p < .05). Body weight of the HFD‐OVJ group was slightly lower than that of the HFD group, but the difference was not significant (Figure 2a). After 9 weeks, the weight gain in the HFD group was significantly increased compared to the normal group (p < .001). Weight gain of mice in the HFD‐OVJ group was significantly lower than that of the HFD group (p < .05) (Figure 2b). The food efficiency ratio of the HFD group was significantly higher than that of the normal group (p < .001), but was significantly decreased when the HFD was supplemented with OVJ (p < .05) (Figure 2c). The HFD group showed increased liver mass compared to normal group (p < .001). The liver mass of the HFD‐OVJ group was slightly lower than that of the HFD group, but there was no significant difference (Figure 2d). The epididymal fat mass of the HFD group was also increased by 78.5% compared to that in the normal group (p < .001). The weight of epididymal fat in the HFD‐OVJ group was significantly lower than that in the HFD group (p < .01) (Figure 2e). The adipocyte size in the liver and epididymal fat was measured using histological tissue analysis. The epididymal fat adipocyte was markedly enlarged in HFD group compared with the normal group. However, adipose tissue was reduced in the HFD‐OVJ group (Figure 3a). The degree of hepatic steatosis in the HFD group developed compared with the Normal group, but mice fed OVJ showed reduced steatosis compared to the HFD group (Figure 3b). The adipocyte area of epididymal fat showed significant reductions in the HFD‐OVJ group compared to the HFD group (p < .01) (Figure 3c). Intake of OVJ decreased epididymal fat mass and adipocyte formation in diet‐induced obese mice. The levels of liver toxicity biomarkers AST and ALT were increased in the HFD group compared with the normal group, but only statistically significant for ALT (p < .01). AST and ALT levels were significantly reduced in the HFD‐OVJ group (p < .05) (Figure 3d). GLU levels were increased in the HFD group compared to the normal group (p < .01) and significantly decreased in the HFD‐OVJ group compared to the HFD group (p < .05). T‐CHOL and LDL were both increased in high‐fat diet‐induced obese mice (p < .05 and p < .01, respectively). The levels of T‐CHOL and LDL in the HFD‐OVJ group were similar to those in the HFD mice. A high‐fat diet increased TG levels in the serum to 211.83 ± 13.88 mg/dl compared with 145.43 ± 15.54 mg/dl in the normal group (p < .01). The level of TG in the HFD‐OVJ group (204.50 ± 4.19 mg/dl) was slightly lower than that in the HFD group, but the difference was not significant. The levels of HDL in the HFD and HFD‐OVJ groups were both higher than those in the normal group; especially, the HDL level of HFD‐OVJ fed mice was significantly increased compared to that of the HFD group (p < .01) (Figure 3e). We examined gene expression related to lipid synthesis in liver tissues. The HFD group showed increased expression of genes involved in the regulation of sterol regulatory element‐binding protein 1 (SREBP‐1), peroxisome proliferator‐activated receptor (PPARγ), CCAAT/enhancer‐binding protein α (C/EBPα) and fatty acid synthesis (FAS) (Figure 4a). The expression of SREBP‐1 and FAS was significantly increased in HFD‐fed mice (p < .001 and p < .05, respectively). Lipid synthesis‐related gene expression, including FAS, SREBP1, PPARγ, and C/EBPα was significantly lower in the HFD‐OVJ group than in the HFD group (FAS and SREBP‐1, p < .001; PPARγ and C/EBPα, p < .05). We measured the mRNA levels of genes related to inflammation (Figure 4b). IL‐6 expression was significantly higher in the HFD group compared to that in the normal group (p < .05). In addition, HFD‐OVJ intake decreased the expression of SREBP‐1, PPARγ, and C/EBPα, and IL‐6 compared to HFD group. 8‐OHdG causes oxidative DNA damage via ROS. Therefore, 8‐OHdG is an established biomarker of oxidative stress. A high‐fat diet significantly increased 8‐OHdG in the serum compared with the normal group (p < .05). The level of 8‐OHdG in the HFD‐OVJ group was significantly lower than that in the HFD group (p < .05). In addition, the intake of OVJ in diet‐induced obese mice reduced 8‐OHdG activity to the level of the normal group (Figure 5a). MDA was used as a marker of lipid peroxidation by oxidative degradation of lipids. MDA concentration in the HFD group was significantly higher than that in the normal group (p < .01), while the MDA level in the HFD‐OVJ group was significantly lower than that in the HFD group (p < .01) (Figure 5b). H2O2 level was significantly elevated in the HFD group compared to the normal group (p < .05), but slightly reduced in the HFD‐OVJ group; there was no significant difference (Figure 5c). The microbial composition of the continuous colon simulation was analyzed using the Illumina MiSeq platform, targeting the variable region from V3 to V4 of the bacterial 16S rRNA gene with the 341F/805R primer set. After low‐quality sequence filtering, chimera checking, and OTU clustering, we confirmed an average of 190 OTUs with 97% sequence identity. We obtained an average of 35,512 high‐quality sequences per sample and classified reads were obtained. Alpha diversity, such as the Shannon diversity index, was used to measure the biodiversity and richness of all groups. Table 1 shows the alpha diversity of AC, TC, and DC for each control juice group and OVJ group. When control juice and organic juice treatment were processed, the average alpha‐diversity was identified as 2.66 and 2.79, respectively. These results indicated that the microbial community after OVJ treatment was slightly more diverse compared to that after control juice treatment. The Shannon index was significantly increased in the TC and DC after organic juice treatment (p < .01 and p < .05, respectively). After treatment with control juice, the Shannon diversity was also significantly increased in the TC, but there was no significant difference in the DC compared to the AC. The beta‐diversity showed by principal coordinates analysis, including classified OTUs, confirmed a difference in the microbial composition as a result of colon simulation parts after organic juice and control juice treatment (Figure 6a). When control juice and organic juice were added, the composition of the intestinal flora was changed according to different parts of the colon and sample type. The AC showed a similar beta‐diversity in the control juice and organic juice groups. Beta‐diversity of the transverse and descending parts showed alterations in the microbial community caused by control juice and organic juice treatment. The microbiota of the OVJ and control juice‐treated groups was analyzed at the phylum level (Figure S1A, Table S3). We analyzed four major phyla; Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Bacteroidetes and Firmicutes occupied most of the microbial composition in each group (Figure 6b). Bacteroidetes were significantly increased in the TC and DC of OVJ group compared with the control juice group (p < .001 and p < .05, respectively). Firmicutes abundance was significantly lower in the TC and DC of the OVJ group than in those of the control juice treatment but significantly increased in the AC compared with the control juice treatment (p < .05). Proteobacteria abundance was reduced significantly in the AC of the OVJ‐treated group compared to the control juice group (p < .01). At the family level, the top 30 species obtained from the colon simulation system were analyzed (Figure S1B). The abundance of Bacteroidaceae was significantly higher in TC and DC of OVJ group than in those of the control juice group (p < .001 and p < .01, respectively). Bacteroidaceae belongs to Bacteroidetes, and the abundance of these species was decreased in the intestines of obese people (Figure 6c). The abundance of this species was higher in the TC and DC of OVJ group than in those of the control juice group. In particular, there was a significant difference in DC (p < .05) (Figure 6d). We compared changes in the relative abundance of the top 40 at the genus level (Figure S1C). The abundance of Holdemania was significantly higher in TC and DC of control juice group than in those of the OVJ‐treated group (p < .05) (Figure 6e). Butyricimonas occupied a very small percentage of the OVJ‐treated group, but this species did not exist in the control juice group. There was a significant difference in DC (p < .05) (Figure 6f). Lachnospira abundance was significantly increased in the AC of the OVJ group compared to the control juice group (p < .05) and was higher in the TC and DC of the control juice‐treated group (Figure 6g). The LDA score was used to confirm the significant difference in the microbial composition in the colon section. There was a significant difference in microbial taxa level with a log LDA score above 3.0 for each colon section. In the AC of the OVJ treatment group, Lactobacillus abundance was significantly higher than in that of the other groups. Bacteroidales, Frisingicoccus, Lachnospira, and Alistipes abundance was significantly higher in the TC of the OVJ group than in that of the control group. Clostridium_g24, Clostridium_g35, Ruminococcus_g4, and Agathobaculum abundance were significantly increased in the DC of the OVJ group. Escherichia abundance was significantly higher in the AC of the control juice treatment group than in that of the OVJ group. Fusicatenibacter, Faecalicatena, and Anaerostipes abundance were significantly increased in the TC of the control juice group. In DC of control group, Eubacterium, Hungatella, Elsenbergiella, and Blautia abundance were significantly higher than in the other groups (Figure 7a). At the family level, 28 bacterial genera showed differences among different groups. The abundance of Akkermansiaceae was increased in the TC and DC of the OVJ group compared to the control juice group (Figure 7b). We predicted the metagenome function of each taxonomy group using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We investigated the predicted lipid metabolism function genes of the microbiome in OVJ and control juice groups with PICRUSt (Figure 7c). OVJ significantly changed the microbial functions, such as primary and secondary bile acid biosynthesis (LDA score: 4.13, 4.22, respectively). However, in the control juice group fatty acid biosynthesis (LDA score: 4.02), fatty acid metabolism (LDA score: 5.18), and lipid metabolism (LDA score: 4.83) were significantly shifted (Figure S2). Obesity causes hyperlipidemia, which increases mortality by causing cardiovascular disease when the degree is severe. Therefore, it is necessary to lower the risk of cardiovascular disease by regulating blood lipids (Klop et al., 2013; Nelson, 2013). The human gut microbiota has been a major research topic in human health. A growing number of studies have suggested that the gastrointestinal microbiome is not only important for gut health but also for diseases such as obesity, diabetes, and atopy (Larsen et al., 2010; Penders et al., 2007; Zhao, 2013). Vegetables are a functional source that reduces the risk of diseases, such as cancer, cardiovascular disease, as well as aging (Liu, 2003). Major phytochemicals in the OVJ used in this study were β‐carotene and lycopene (β‐carotene; 113.1 ± 7.6, lycopene; 30.8 ± 0.9). β‐carotene and lycopene are carotenoids that have anti‐obesity properties (González‐Castejón & Rodriguez‐Casado, 2011). Here, we aimed to study the alleviating effect of hyperlipidemia effect of OVJ through in vivo experiment. Furthermore, we analyzed the gut microbiome using a continuous colon simulation system and investigated the correlation between the community and the metabolic pathways related to lipid synthesis predicted gene functions through OVJ consumption. A HFD with OVJ slightly reduced body and liver weight gain and significantly decreased epididymal fat gain. Adipocytes of epididymal fat were also decreased, indicating that OVJ supplement can reduce adipocyte size in the epididymal fat of obese mice (Duwaerts et al., 2017). Serum lipid and cholesterol levels of diet‐induced obese mice tended to increase, which are correlated with hyperlipidemia (Neyrinck et al., 2013; Zhang et al., 2007). OVJ decreased GLU and TG levels and increased blood HDL. When GLU concentration increases, insulin ratio increases, and the excess glucose is stored in the subcutaneous fat, causing hyperlipidemia (Koopmans et al., 2001). According to previous studies, fruit and vegetable juice may contribute to improving blood lipid profiles and further prevent cardiovascular diseases, including hyperlipidemia (Chang & Liu, 2009; Zheng et al., 2017). In other words, the results of this study suggested that the juice used in the study might also improve blood lipids. Lipid synthesis‐related gene expression was significantly decreased in the liver tissue of HFD‐OVJ mice, including SREBP‐1, PPARγ, C/EBPα, and FAS, which suggested lower lipid levels and lower fatty acid synthesis in OVJ‐treated mice (Hu et al., 2010; Park et al., 2013). FAS is a key factor in determining the maximum capacity to synthesize fatty acids via the de novo pathway (Clarke, 1993). PPARγ is a transcription factor that is mainly expressed in the adipose tissue and regulates the accumulation of fat in adipocytes by being involved in the production of insulin‐sensitive adipokines, such as adiponectin. It is also involved in the synthesis of TG (Medina‐Gomez et al., 2007; Park et al., 2019). SREBP‐1 is a transcription factor that plays an important role in the synthesis of TG in adipose and liver tissues. The expression of SREBP‐1 is dominant in liver tissues, and it regulates the expression of enzymes related to TG synthesis in hepatocytes (Shimano et al., 1999; Yuan et al., 2009). Hyperlipidemia is accompanied by an increase in free fatty acids in the blood. Increased blood‐free fatty acids are directly toxic to hepatocytes (Feingold & Grunfeld, 1992). The increase in free fatty acids in the liver increases the activity of enzymes that generate free radicals, lipid peroxidation, and the production of inflammatory cytokines such as IL‐6. Oxidative stress is associated with obesity‐related complications, such as hyperlipidemia. Production of 8‐OHdG is caused by oxidative DNA damage, which increases in overweight and obese people. The level of 8‐OHdG in obese women is significantly higher than that in lean women (Devries et al., 2008). MDA is the main product of lipid peroxidation, which is a free radical‐generating process by oxidants (Garcia‐Sanchez et al., 2020). The concentration of MDA was significantly reduced in patients with healthy BMI compared to that in obese individuals (BMI above 40 kg/m2) (Olusi, 2002). In this study, treatment with OVJ significantly decreased the lipid synthesis‐related genes and oxidative stress. It could be the effect of β‐carotene and lycopene. The anti‐obesity effect of β‐carotene is related to the provitamin A effect. This effect is associated with reduced expression of PPARγ in the adipose tissue through the involvement of retinol X receptor signaling (Mounien et al., 2019). Lycopene blocks lipid accumulation in the adipose tissue by decreasing the expression of lipogenesis‐related genes, which is also related to the reduction of inflammatory cytokines (Fenni et al., 2017; Wang et al., 2019). Given this, it is possible to predict vegetables influenced improvement of blood lipids and antioxidant activity in animal experiments. We examined the positive alterations of the microbiome and metagenomic functions in each section of the continuous colon simulation system. OVJ treatment significantly improved the richness of microorganisms in TC and DC and caused distinct alterations in the composition of the gut microbiome. The relative abundance of the family Erysipelotrichaceae and the genus Holdemania was significantly reduced in the DC of OVJ‐treated group compared to the control group. Previous studies have reported that Erysipelotrichaceae exhibits high abundance in obese individuals (Zhang et al., 2009), and that there is a correlation between Erysipelotrichaceae levels and host cholesterol metabolites (Martínez et al., 2013). In addition, it has been reported that supplementation of flavonol quercetin inhibits the growth of Erysipelotrichaceae (Etxeberria et al., 2015). The genus Holdemania has been reported to correlate with clinical markers of impaired lipid and glucose metabolism (Lippert et al., 2017). Our study shows that supplementation of OVJ can inhibit the growth of taxa associated with obesity and lipid metabolism, such as Erysipelotrichaceae and Holdemania. The three taxa whose relative abundance were increased significantly in the OVJ‐treated group compared to the control group were the family Bacteroidaceae in TC and DC, the genus Butyricimonas in DC and the genus Lachnospira in AC. Bacteroidaceae family is known to be significantly decreased in obesity, and the genus Bacteroides spp. has been reported to indicate a negative correlation between energy intake and obesity (Chávez‐Carbajal et al., 2019). Butyricimonas is known as butyrate‐producing bacteria with anti‐inflammatory effects (Den Besten et al., 2013). Lachnospira also belongs to butyrate‐producing bacteria and is known for the fermentation of polysaccharides of SCFAs (Ferrario et al., 2014). Butyrate has very beneficial effects on energy metabolism, intestinal homeostasis, and regulation of immune response, and has the potential to alleviate obesity and related comorbidities by regulating liver and intestinal lipid metabolism (Coppola et al., 2021). In addition, OVJ consumption increases the relative abundance of Lactobacillus and Akkermansia, known as beneficial bacteria. According to Wiese et al. lycopene‐rich food and flavonol consumption increase the relative abundance of Lactobacillus and change liver metabolism and vascular functions (Wiese et al., 2019). Previous research supports the link between the gut and vascular systems, which also links risk factor‐mediated cardiovascular diseases (Li et al., 2017). According to Chang et al., Akkermansia, belonging to the Akkermansiaceae family, is related to reduced weight gain and maintenance of metabolic homeostasis (Baldwin et al., 2016) and is enriched in healthy people rather than people with metabolic syndrome (Lim et al., 2017). We also observed that the OVJ‐treated group and control juice‐treated group showed a shift in metagenome function, related to the lipid metabolism. KEGG pathway analysis showed a lower number of genes related to lipid metabolism in OVJ‐induced vessels. This suggested that the administration of OVJ improved the microbiome environment and potentially reduced lipid metabolism‐related gene expression. In our results, treatment with OVJ increased the abundance of butyrate‐producing bacteria and therefore OVJ treatment could increase endogenous butyrate production and could be a useful strategy for the prevention of obesity and related metabolic diseases. In this study, we showed that the microbial community and lipid metabolism were altered in the culture system upon treatment with OVJ, and that blood lipid profiles and antioxidant ability were alleviated in diet‐induced obese mice. These results suggest that OVJ may represent a natural way of alleviating hyperlipidemia. In future studies, it may be necessary to determine whether OVJ influences lipid metabolism‐related genes directly or whether its effects are predominantly mediated by changes in the microbiome. In addition, it may be necessary to investigate the effects of the ingredients on the lipid metabolic gene pathways of microbiome to improve blood lipid profiles and hyperlipidemia in future studies. This research received no external funding. The authors declare no conflict of interest. Click here for additional data file.

PMC10002949

Matthias Eckhardt

Fatty Acid 2-Hydroxylase and 2-Hydroxylated Sphingolipids: Metabolism and Function in Health and Diseases

03-03-2023

cancer,fatty acid hydroxylase-associated neurodegeneration,fatty acid 2-hydroxylase,leukodystrophy,hereditary spastic paraplegia,myelin,neurodegeneration with brain iron accumulation,neurodegeneration,sphingolipids,skin

Sphingolipids containing acyl residues that are hydroxylated at C-2 are found in most, if not all, eukaryotes and certain bacteria. 2-hydroxylated sphingolipids are present in many organs and cell types, though they are especially abundant in myelin and skin. The enzyme fatty acid 2-hydroxylase (FA2H) is involved in the synthesis of many but not all 2-hydroxylated sphingolipids. Deficiency in FA2H causes a neurodegenerative disease known as hereditary spastic paraplegia 35 (HSP35/SPG35) or fatty acid hydroxylase-associated neurodegeneration (FAHN). FA2H likely also plays a role in other diseases. A low expression level of FA2H correlates with a poor prognosis in many cancers. This review presents an updated overview of the metabolism and function of 2-hydroxylated sphingolipids and the FA2H enzyme under physiological conditions and in diseases.

Fatty Acid 2-Hydroxylase and 2-Hydroxylated Sphingolipids: Metabolism and Function in Health and Diseases Sphingolipids containing acyl residues that are hydroxylated at C-2 are found in most, if not all, eukaryotes and certain bacteria. 2-hydroxylated sphingolipids are present in many organs and cell types, though they are especially abundant in myelin and skin. The enzyme fatty acid 2-hydroxylase (FA2H) is involved in the synthesis of many but not all 2-hydroxylated sphingolipids. Deficiency in FA2H causes a neurodegenerative disease known as hereditary spastic paraplegia 35 (HSP35/SPG35) or fatty acid hydroxylase-associated neurodegeneration (FAHN). FA2H likely also plays a role in other diseases. A low expression level of FA2H correlates with a poor prognosis in many cancers. This review presents an updated overview of the metabolism and function of 2-hydroxylated sphingolipids and the FA2H enzyme under physiological conditions and in diseases. Sphingolipids are important components of biological membranes that play multiple important roles in signal transduction, intracellular trafficking, apoptosis, cell differentiation and other processes [1]. These various functions are reflected in the structural diversity of sphingolipids. The different chain length of the acyl residue or the sphingoid base, the degree of saturation, diversities in the polar head group (particularly within the complex glycosphingolipids), hydroxylations of the sphingoid base and the acyl residue add structural diversity that appears to be important for the physiological function of sphingolipids. Hydroxylation can occur at C-4 of the sphingoid base and at C-2, C-3 and ω-C of the acyl residue [2]. This review only deals with the biosynthesis and function of sphingolipids with a 2-hydroxyl group in the acyl residue. The interest in these 2-hydroxylated fatty acids (2hFA) containing sphingolipids (2hFA-SL) has steadily increased over the last 15 years. This interest was stimulated by the characterization of the fatty acid 2-hydroxylase (FA2H) in mammals and other higher eukaryotes in 2004, which was later followed by the identification of a human disease (FAHN/SPG35) caused by mutations in the FA2H gene in 2008 (Figure 1A). The observation that FA2H expression level affects tumor progression in different cancer types further strengthened interest in the FA2H gene and 2hFA-SL. 2hFA and 2hFA-SL are found in all kingdoms of eukaryotes (Animalia, Plantae, Fungi and Protista) and in eubacteria. Though this review primarily discusses the role of 2hFA-SL in mammals and human diseases, several aspects of the synthesis and function of 2hFA-SL in invertebrates, plants, fungi and bacteria will not be ignored, as these may also provide some additional hints as to the functional role and synthesis of 2hFA-SL in mammals, which are currently not well understood. 2hFA-SL are especially abundant in some tissues, e.g., the brain, specifically in myelin, and skin. With the development of sensitive methods, however, 2hFA were identified in many tissues [3]. A comprehensive overview of the occurrence of 2hFA-SL in mammalian tissues can be found in the review by Hama [4]. Different tissues and cell types differ significantly with respect to the relative amount of 2hFA-SL, chain lengths of 2hFA and sphingolipid species that are 2-hydroxylated [4]. Currently, the only known enzyme that hydroxylates straight fatty acids at position 2 in eukaryotes is the FA2H enzyme in mammals or its orthologs in other classes. Two stereoisomers can be formed by the hydroxylation of acyl residues. In mammals (likely in all vertebrates and possibly in all eukaryotes), the (R)-enantiomer is synthesized [5]. It is assumed that the presence of the (S)-enantiomer in milk and brain samples from animals and also vegetable oils is derived originally from bacterial sources [6]. 2hFA-SL are present in several bacteria, e.g., Flavobacterium and Sphingomonas species, and the relative abundance of 2hFA-SL differes significantly under different growth conditions [7,8]. Many bacteria synthesize the (S)-enantiomer [8,9]. Fatty acid 2-hydroxylases have been cloned from Sphingomonas species [10] and are not homologues of the eukaryotic FA2H but are cytochrome P450 (CYP450) hydroxylases acting in a H2O2-dependent manner [11,12]. In addition to these, there are several myxobacteria species that have functional fatty acid 2-hydroxylases with significant similarities to the eukaryotic FA2H enzyme, including conserved histidine motifs that form the active center of the enzyme [13]. Notably, the stereochemical specificity of these prokaryotic FA2H orthologs differs between species: while some add the hydroxyl group in the (S)-configuration, such as other bacteria using CYP450 enzymes, others synthesize (R)-2-hydroxy fatty acids, such as the eukaryotic FA2H enzyme [13]. Analytical methods for the detection and quantification of 2hFA-SL (as well as technical challenges) are, in general, the same as for their non-hydroxylated counterparts. There is no specific extraction method to obtain only 2-hydroxylated sphingolipids because the extraction behavior is much more influenced by the (polar or anionic) head group of the lipid. Thus, non-hydroxylated and the corresponding 2-hydroxylated sphingolipids are analyzed together, and their molar ratio often provides valuable information. In most studies, lipids are extracted using one of the liquid–liquid biphasic systems composed of water and organic solvents (such as the Bligh Dyer [14] or Folch [15] method using methanol and chloroform, or chloroform-free methods using methyl-tert-butyl ether [16] or 1-butanol [17], or modifications of these [18]; see [19,20] for comprehensive reviews). Anionic sphingolipids (e.g., sphingosine-1-phosphate or sulfatide (see Section 5.2)) and complex glycosphingolipids require modifications or different extraction methods to ensure an efficient recovery of the lipids [19,20]. The current standard method for the structural analysis and quantification of 2hFA-SL (as well as non-2hFA-SL) in lipidomic studies, as well as in the analysis of individual lipids or lipid classes, is liquid chromatography–tandem mass spectrometry (LC-MS/MS). An overview of the workflow in mass spectrometry lipidomics is presented in the review by Köfeler et al. [21]. Although direct infusion mass spectrometry is possible, chromatography (reversed phase-HPLC or hydrophilic interaction liquid chromatography [22]) is usually applied because it provides additional information about the lipid structure and reduces the complexity of the sample. A comprehensive review of the specific requirements for the mass spectrometry of glycosphingolipids can be found in [23]. The C-2 position of the hydroxyl group in 2hFA-SL can usually be confirmed by a characteristic fragmentation pattern in the MS² spectrum [24]. The 2-hydroxyl group in hydroxylated-SL can cause problems of isobaric and isomeric interference because of the very similar mass of the hydroxylated lipid with the 13C2 isotope to a related lipid with a +1 chain length. This may be difficult to resolve by mass spectrometry and may require specific chromatography steps to separate the isobaric species [25]. Isomeric interference may be due to the identical mass of stereoisomers of sugars in glycosphingolipids (2-hydroxylated or not). The stereospecific discrimination between glucosylceramide and galactosylceramide was made possible by using a new hydrophilic interaction liquid chromatography–MS/MS protocol [26]. A very promising new approach in the area of spatial metabolomics is mass spectrometry imaging (MSI), which is also being progressively applied in (sphingo) lipid analysis [27,28,29,30]. Several studies performed MSI to detect 3’-sulfo-galactosylceramide (sulfatide) and 2hFA-sulfatide (which are abundant in myelin; see Section 5.2) and other sphingolipids in tissue sections using matrix-assisted laser desorption/ionization (MALDI)-MSI [31,32,33,34], time-of-flight secondary ion mass spectrometry (TOF-SIMS)-MSI [35,36,37] or desorption electrospray ionization (DESI)-MSI [38]. By combining the high spatial resolution of SIMS with the high mass resolution of the Orbitrap mass spectrometer in a method called 3D OrbiSIMS, Passarelli et al. [39] could map the distribution of 2hFA-sulfatide in mouse brains at a cellular to subcellular resolution. Using MALDI-MSI, it was possible to demonstrate the differential distribution of non-hydroxylated sulfatide and 2hFA-sulfatide in a human neocortex [34]. With TOF-SIMS-MSI, Hirahara et al. [40] demonstrated a sequential change from C18-2hFA-sulfatide in oligodendrocyte progenitor cells (OPC) to C20-2hFA-sulfatide in differentiating oligodendrocytes and C24-2hFA-sulfatide in mature oligodendrocytes. Nakashima et al. [41] demonstrated a differential localization of C22:0/C24:0-2hFA-sulfatide with phytosphingosine as a long chain base in intercalated mouse renal cells in combination with the mislocalization of vesicular H+-ATPase, suggesting a role of these 2hFA-sulfatide species in NH4+ and H3O+ excretion. It is obvious that the analysis of lipids in tissue samples by MSI with cellular and possibly subcellular resolution has outstanding potential for the analysis of functional roles of lipids, including 2hFA-SL. The fatty acid 2-hydroxylase enzyme, which is encoded by the FA2H gene in humans, has orthologs in apparently all eukaryotes. The FA2H gene has been characterized in mammals [42,43], yeast (SCS7) [44,45], plants (FAH1, FAH2) [46] and protists [47]. The FA2H enzyme belongs to the fatty acid hydroxylase/desaturase gene family and is an NAD(P)H-dependent monooxygenase that localizes to the endoplasmic reticulum [43]. The catalytic center is composed of four conserved histidine motifs that form an essential di-metal ion center in the catalytic center of the enzyme [48] (Figure 2). The enzyme adds the hydroxyl group in a stereospecific manner and forms only the (R)-enantiomer [49]. While in most eukaryotic genomes only one FA2H gene is present, Arabidopsis thaliana and other plants express two related FA2H genes, FAH1 and FAH2 [50], which differ with respect to their substrate specificity. The FAH1 enzyme mainly uses mainly very long chain fatty acids (VLCFAs) as substrates, whereas FAH2 prefers long chain fatty acids (LCFAs) [51]. In animals, fungi and protists, the FA2H enzyme contains an N-terminal cytochrome b5-like domain that is responsible for electron transfer from NAD(P)H. In contrast, the plant enzymes lack this domain but interact with one of the separate cytochrome b5 proteins within the ER membrane [52]. Whether cytochrome b5 can partially functionally replace the cytochrome b5-like domain, e.g., in cases of FAHN (see Section 6), with mutations in this domain is not known. The X-ray crystal structure of the baker’s yeast FA2H enzyme (SCS7p) has been resolved, though without the N-terminal cytochrome b5-like domain [48]. This study confirmed the previously predicted four-transmembrane domain structure [42,43] of the enzyme, with N-terminal cytochrome b5 domain and C-terminus facing the cytosol. Although FA2H is regarded as a di-iron enzyme, the yeast ortholog contains two zinc ions in the di-metal ion binding site [48]. Based on structural differences between SCS7p and the functionally and structurally related stearoyl-CoA desaturase-1 (SCD1), it was concluded that acyl-CoAs are most likely not substrates for FA2H/Scs7p, whereas a ceramide fits well into the catalytic center of the enzyme. On the other hand, the only established in vitro enzymatic FA2H assay used free fatty acids as an efficient substrate [53]. It is an open question whether or to what extent free fatty acids may serve as substrates in vivo. Heme is synthesized in mitochondria and thus must be transferred to the ER-localized FA2H protein when its cytochrome b5-like domain is folded into its native conformation. A screen for FA2H interaction partners identified progesterone receptor membrane component 1 (PGRMC1) as a binding partner of FA2H [54]. PGRMC1 binds heme and is a putative heme chaperon [55]. Its yeast homologue (Dap1) is known to be required for the activation of several CYP450 enzymes [56]. A PGRMC1 antagonist reduced FA2H activity [54], and PGRMC1 may be involved in the delivery of heme to the cytochrome b5 domain of FA2H. FA2H is the most studied enzyme involved in the synthesis of 2hFA in eukaryotes. However, the FA2H enzyme is not the only enzyme capable of synthesizing 2hFA or 2hFA-ceramides. It is clear that mice lacking a functional Fa2h gene seem to be devoid of 2hFA-SL in the nervous system [57,58] yet still contain 2hFA-SL in various organs, such as the skin [59]. In addition, levels of 2hFA-sphingomyelin in lymphocytes and erythrocytes from FAHN/SPG35 patients with a mutation causing exon 5/6 skipping (which is expected to fully abolish FA2H activity) were not reduced [60]. One alternative source for 2hFA is an α-oxidation pathway in the ER [61]. Through this pathway, 2-hydroxylated palmitic acid can be formed from phytosphingosine (Figure 3). However, this pathway mainly generates C16-2hFA (and C18-2hFA from C20-phytosphingosine base). Longer phytosphingosine bases that could potentially enable the synthesis of VLCFA 2hFA (>C20) are rare. As FA2H knockout mice and FAHN patients still contain substantial amounts of VLCFA 2hFA-SL [59,60], it is very likely that additional enzymes, which have not yet been characterized, exist that are capable of synthesizing 2hFA/2hFA-SL, at least in mammals. The only other known mammalian fatty acid 2-hydroxylase, peroxisomal phytanoyl-CoA hydroxylase, appears to be unable to hydroxylate straight fatty acids. As CYP450 enzymes synthesize 2hFA in certain bacteria (see above), they are possible candidates for these currently unknown enzymes. The degradation of 2hFA-SL occurs mainly in lysosomes (Figure 3). This is achieved by the same acid hydrolases that degrade their non-hydroxylated counterparts. The sphingolipid activator protein (saposin) D, one essential cofactor of acid ceramidase, seems to be mainly involved in extracting the 2hFA-ceramide from the membrane to enable its hydrolysis [62]. Alternatively, the amide bond of 2hFA-ceramide may be hydrolyzed by alkaline or neutral ceramidase outside the lysosome; however, to what extent this happens with the 2hFA-ceramide is unclear. The released 2hFA can likely be recycled through a salvage pathway (Figure 3). All six mammalian ceramide synthases (CerS1-6) accept 2hFA-CoA as substrate [63]. Alternatively, 2hFA can be degraded through peroxisomal α-oxidation. In addition to branched chain fatty acids, peroxisomal 2-hydroxyphytanoyl-CoA lyase is able to cleave 2-hydroxylated straight chain fatty acids [64]. Whether free 2hFA have a physiological function is currently not known. However, exogenously added 2hFA can dramatically affect cell physiology (see Section 6). What is the functional role of 2hFA-SL in biological membranes? Knockout and knock-down experiments as well as biophysical studies in artificial membranes have been performed to address this question. The results suggest that 2hFA-SL has a significant influence on the structure and stability of membrane microdomains and affects the trafficking of membranes/membrane proteins. Support for a functional role of 2hFA-SL in membrane trafficking comes from studies in Drosophila melanogaster, which demonstrated that FA2H overexpression can interfere (depending on the genetic background) with the apical membrane trafficking of newly synthesized Rhodopsin via Rab11-positive vesicles (recycling endosomes) to the rhabdomeres [65]. Along this line, monitoring the localization of 2hFA-SL in Caenorhabditis elegans (using 2-hydroxy palmitic acid alkyne and click chemistry labeling with azide-Cy3) revealed its accumulation in the apical membrane of polarized cells in the intestinal tract [66]. The loss of the C. elegans FA2H gene fath-1 strongly affected distribution of late and recycling endosomes, which then accumulated in the apical region of intestinal cells [66]. The inactivation of fath-1 strongly reduced the level of C17:1Δ10 (heptadecenoic acid) that can be generated through the α-oxidation of 2hFA-C18:1. This indicates the possibility that the effects of FA2H effects are not necessarily mediated by 2hFA or 2hFA-SL but may also depend on downstream reaction products. An important role of 2hFA-SL in apical membrane sorting was also suggested by the observation that the polarization of MDCK cells is associated with a strong increase in the percentage of hydroxylated sphingolipids [67], though this study did not discriminate between different hydroxylations. Hydroxyl groups of the sphingoid base are essential for lipid–lipid interactions in the membrane through the formation of inter- and intramolecular hydrogen bonds [68]. Likewise, the 2-hydroxyl group of the fatty acid residue plays a comparable role in stabilizing lipid–lipid interactions. The 2-hydroxyl group appears to stabilize membrane microdomains, possibly through the additional intermolecular hydrogen bonds between the 2-hydroxyl group, the amino group of the sphingosine and the sugar head group [69,70,71]. Glycosyl inositol phosphorylceramides (GIPCs) are abundant sphingolipids in the tobacco (Nicotiana tabacum) cell plasma membrane (comprising up to 80% of the lipid molecules in the outer leaflet). It was shown that GIPCs containing 2hFA are specifically enriched in detergent-insoluble membranes that form small membrane domains and interact with phytosterols within membranes via hydrogen bonds [72,73]. In line with this, plant cells lacking FAH1 and FAH2 have reduced levels of membrane microdomains [74]. In artificial membranes, the size of the membrane domains containing 2hFA-galactosylceramides was smaller, but they covered twice the membrane when compared to membranes containing non-hydroxylated galactosylceramide [75]. The reduced expression of FA2H in adipocytes increased the mobility of raft-associated lipids and thereby reduced the plasma membrane levels of insulin receptors and GLUT4 glucose transporters [49,76]. This effect was abolished specifically by the addition of ®-2-hydroxy palmitic acid (but not the (S)-stereoisomer), which was incorporated into hexosylceramides. Such a stereo-specific effect was also observed for the antiproliferative activity of synthetic 2hFA-ceramides in which the (R)-enantiomers had a much stronger activity [69]. Such enantiomer-specific effects should result from stereospecific interactions, which could occur through a specific protein (this possibility has, however, not been reported yet) or a stereo-specific interaction with another lipid or a functional group within the same sphingolipid molecule (e.g., with the glucose or galactose residue). For example, while 2hFA-sphingomyelin stabilizes, 2hFA-phytosphingomyelin (containing an additional hydroxyl group at C-4 of the sphingoid base; see Figure 3) destabilizes the gel phase of a membrane [77]. FA2H expression is detectable in most tissues, though its level varies strongly between different organs/tissues and cell types (Figure 4). In humans, FA2H mRNA is only undetectable in the ovaries and skeletal muscle. In addition to the brain and peripheral nervous system (PNS), where myelinating cells (oligodendrocytes and Schwann cells, respectively) express FA2H, it is particularly abundant in the intestinal tract. Looking at individual cell types, strong FA2H expression is particularly present in glandular epithelial cells (Figure 4, right panel). Accordingly, FA2H expression in skin is mainly found in sebaceous glands [78]. A high-level expression in glandular epithelial cells was also observed in murine tissues [59,79]. With the exception of sebocytes (see Section 5.3), there is currently no knowledge about the role of FA2H or 2hFA-SL in glandular epithelial cells. Unfortunately, there are almost no reliable data on the FA2H protein level in different tissues because of a lack of specific and sensitive antibodies. In the mammalian nervous system (and in many non-mammalian vertebrates), the majority of 2hFA-SL are 2hFA-galactosylceramide and 2hFA-sulfatide, which are abundant components of the myelin sheath [82] (Figure 5). It is, however, worth mentioning that some vertebrates do not have 2hFA-SL in their myelin [83]. FA2H is highly expressed in the myelinating cells (oligodendrocytes in brain and Schwann cells in PNS) [42,43]. An analysis of two independent FA2H-deficient mouse lines, generated by gene targeting, confirmed the assumption that the synthesis of these 2hFA-SL in the brain and PNS fully depends on FA2H activity [57,58]. Nonetheless, myelin was normally formed in these mice. However, adult mice developed a late-onset demyelination and axonal degeneration with motor behavioral deficits that are reminiscent of human FAHN/SPG35 disease (see Section 6.1). Thus, 2hFA-SL are not essential structural components of myelin that are necessary to build up compact myelin sheaths to enable saltatory nerve conduction, but they are required for long-term myelin maintenance and axonal support. Galactosylceramides and sulfatides have important functions in the differentiation of oligodendrocytes and the establishment of stable paranodal junctions at the node of Ranvier [82,84,85,86]. These are, however, apparently normal in FA2H-deficient mice. Thus, sulfatides and galactosylceramides do not have to be 2-hydroxylated to fulfill these functions. Skin contains large amounts of 2-hydroxylated and ω-hydroxylated ceramides and glucosylceramides [2,87]. While the essential role of the ω-hydroxylation for the formation of the permeability barrier is well known, the specific role of the 2-hydroxylation is not clear. FA2H expression is upregulated during in the vitro differentiation of human keratinocytes, and 2hFA-ceramides/glucosylceramides appear to be required for the formation of epidermal lamellar membranes that are essential to build up the epidermal permeability barrier [88]. In FA2H-deficient mice, however, the 2hFA-ceramide level in skin was unaltered and only a fraction of the 2hFA-glucosylceramide level (acyl chain length C20 to C24) was reduced [59]. Moreover, the permeability barrier was apparently unaffected, in line with undetectable FA2H expression in keratinocytes. The possibility that FA2H plays different roles in human and mouse keratinocytes remains to be determined. Skin is also the only organ where the role of FA2H in glandular epithelial cells has been examined to some extent. FA2H is strongly expressed in sebocytes, and FA2H-deficient mice have enlarged sebaceous glands and develop a cyclic alopecia [59]; the latter is possibly a consequence of altered sebum composition with a strongly reduced wax diester level that causes a significant increase in the melting temperature of the sebum above body temperature [59,79]. A chemically induced FA2H mouse mutant (‘sparse’) exhibited a comparable phenotype [89]. Wax diester synthesis requires 2hFA [90]. However, because 2hFA may also be formed by FA2H independently (see Section 3.2), it is unclear whether FA2H is directly involved in this reaction. Interestingly, mice deficient in the ceramide synthase CerS4 (the major ceramide synthase in sebaceous glands) and alkaline ceramidase 1 (ACER1)-deficient mice exhibit a very similar skin/sebaceous gland phenotype [91,92]. This may suggest a critical role of 2hFA-ceramide/2hFA-SL turnover in sebocytes. A significant role of FA2H in mammalian skin physiology is further supported by an FA2H mutation causing ichthyosis congenita in a Chianina cattle [93]. Deficiency in FA2H causes a human disease known as fatty acid hydroxylase-associated neurodegeneration (FAHN) or hereditary spastic paraplegia (HSP) type 35/spastic paraplegia 35 (HSP35 or SPG35) [94,95]. The disease is an autosomal recessive disorder belonging to the complex HSP type. It is a rare form among all hereditary spastic paraplegias known today [96,97]. Characteristic clinical signs in FAHN are spasticity of the lower limbs, ataxia, cognitive problems, and leukodystrophy [98]. FAHN is part of a group of diseases designated as neurodegeneration with brain iron accumulation (NBIA) [99]. Iron deposits in the basal ganglia that cause lesions in the globus pallidus (“eye-of-the-tiger sign”) are a typical finding in these diseases. Currently, more than 60 different mutations in the human FA2H gene that cause FAHN/SPG35 have been described in the literature [94,95,99,100,101,102,103,104,105,106,107,108,109,110,111,112]. Detailed description of the clinical signs and mutations identified will not be reviewed here, and the interested reader is referred to previous reviews/overviews on the disease [98,110]. Transgenic mouse lines with total or conditional FA2H knockout have been established and serve as animal models of FAHN [58,59]. Analysis of these mice showed that the synthesis of 2hFA-SL in myelinating cells is important for the maintenance of the myelin sheath, though not for myelin formation per se [58,59]. Phenotypes of both the total and the oligodendrocyte conditional FA2H knockout were similar and reminiscent of the symptoms of the human disease [58,59], indicating that most symptoms are caused by a deficiency of FA2H in the myelinating glia. Notably, however, the oligodendrocyte-specific FA2H knockout was not associated with learning and memory deficits, which were observed in the total knockout [59]. This suggests a (low) expression of FA2H in other cell types within the brain as well. It may thus be possible that cognitive impairment in FAHN could be a result of loss of FA2H activity in neurons. Nevertheless, most FAHN-related symptoms in the mouse models depend on FA2H loss in oligodendrocytes, leading to the question of how changes in the lipid composition of the myelin sheath cause axonal degeneration. A proteome analysis of myelin purified from FA2H-deficient mice found a relative specific accumulation of a major myelin protein called Opalin in compact myelin [113]. As the compact myelin corresponds to the apical membrane in polarized cells, this finding further supports the proposed role of 2hFA-SL in apical membrane sorting, as discussed previously. Altered trafficking or accumulation of myelin membrane proteins could be a possible link between altered myelin lipids and axonal pathology. As mentioned above, FAHN belongs to a group of diseases known as neurodegeneration with brain iron accumulation (NBIA) that demonstrate a characteristic accumulation of iron in the basal ganglia [114], which has been observed in most FAHN patients [110]. However, how FA2H deficiency leads to brain iron accumulation is not understood. Fibroblasts from FAHN and other NBIA cases cultured in the presence of high iron exhibited a stronger intracellular iron increase compared to control fibroblasts. This possibly results from reduced lysosomal degradation and increased recycling of the transferrin receptor [115]. Mitochondrial dysregulation occurs in several types of NBIA [116]. Changes in mitochondrial fission and fusion altered the mitochondrial network in a Drosophila FAHN model [117]. This was accompanied by increased levels of the autophagy marker LC3 and its activated, lipidated form LC3-II, which was also observed in FAHN patient fibroblasts [117]. Although a hallmark of FAHN is the degeneration of upper motor neuron axons in the CNS, peripheral neuropathy has been observed in several FAHN patients [100,110,118]. A related, late-onset peripheral neuropathy was observed in older FA2H-deficient mice [58]. A proteome analysis of peripheral myelin identified elevated levels of a membrane complex containing the adhesion molecule CADM4, which is localized in Schmidt–Lanterman incisures [119]. This suggests that 2hFA-galactosylceramide or 2hFA-sulfatide may play a role in the trafficking or turnover of CADM4, though further studies are required to prove this. Sphingolipids play important roles in many neurodegenerative diseases, such as Alzheimer’s (AD) or Parkinson’s disease (PD) [120]. Until now, however, there was no evidence that the 2-hydroxylation of sphingolipids or the expression of the FA2H gene had a significant influence in these or other neurodegenerative diseases. A strongly reduced brain sulfatide concentration was identified as an early event in AD [121,122], but there was no alteration of the 2hFA-sulfatide to total sulfatide ratio [34]. A genetic interaction of PARK2 (mutated in early-onset PD) and FA2H mutations was reported by Benger et al. [108]. However, to the knowledge of the author of this review, there is currently no evidence for altered FA2H expression or 2hFA-SL levels in PD. In a mouse model of Sjögren–Larsson syndrome, which is caused by mutations in the fatty aldehyde dehydrogenase gene ALDH3A2 (see Figure 3), the brain concentration of 2hFA-galactosylceramide was significantly reduced. This may play a functional role in the disease [123]. Previously, it was shown that reduced 2hFA-galactosylceramide levels in transgenic mice destabilize the CNS myelin [124]. Notably, ALDH3A2 strongly increased the activity of co-expressed FA2H (in CHO cells), suggesting that the ALDH3A2 substrate trans-2-hexadecenal (formed by degradation of sphingosine) may inhibit the FA2H enzyme (a reaction of the fatty aldehyde with a histidine residue in the catalytic center of the enzyme was proposed) [123]. The close proximity of the two enzymes ALDH3A2 and FA2H was suggested by the identification of ALDH3A2 as an interaction partner of FA2H [55], which would enable the efficient protection of FA2H by ALDH3A2. FA2H may be a factor involved in obesity-induced insulin resistance as FA2H downregulation through the micro-RNA miR-3075 led to enhanced insulin signaling [125]. In early-onset obesity, miR-3075 is released via exosomes from hepatocytes and mediates enhanced insulin sensitivity. However, Guo et al. [49,76] found a downregulation of the insulin receptor upon FA2H knockdown. Thus, further studies are needed to clarify the role of FA2H in insulin signaling and resistance. In many FAHN patients, bristly hairs with plaques attached to the hair shaft were observed [110]. This is, to some extent, reminiscent to the phenotype of FA2H-deficient mice [59]. As human sebum lacks wax diesters, this strongly suggests that, in addition to its possible role in sebum (wax diester) synthesis, FA2H or its reaction products have other important roles in sebocytes and/or keratinocytes. It is thus possible that FA2H may play a role in dermatological diseases. It is well known that sphingolipids have important functions in cancer cell signaling, cancer therapy and various aspects of tumor biology [126,127]. Therefore, it may not come as a surprise that changes in the abundance of 2hFA-SL in tumor cells have been observed in tumors of different origins [128,129,130]. High 2hFA-SL levels in carcinoma cells correlated with drug resistance [131,132]. In cases of cholangiocarcinoma, a lower survival rate of patients correlated with a higher relative abundance of 2-hydroxylated lactosylceramide (d18:1-h23:0/23:0) [133]. A strong association between high levels of 2hFA-hexosylceramides (most likely galactosylceramide) and high FA2H gene expression were found in low- and high-grade lung adenocarcinoma but not other lung cancers [134]. The latter study is a rare exception as it examined the 2hFA-SL levels together with FA2H expression. A different picture emerged in more recent studies, which examined FA2H expression but not 2hFA-SL levels in various cancer types. FA2H knockdown in D6P2T Schwannoma cells stimulated cell proliferation by inhibiting cAMP-induced cell cycle arrest [135]. Further studies revealed an association between the FA2H expression level and tumor growth in different cancers, e.g., breast cancers, prostate cancer, gastric cancer and colorectal cancer: a low FA2H expression was associated with a reduced (disease-free) survival [136], reduced sensitivity against chemotherapeutic drugs [137] and, in general, a poor prognosis [138,139,140]. The over-expression of FA2H in tumor cell lines decreased cell proliferation, induced apoptosis and inhibited the epithelial–mesenchymal transition-associated gene expression [141,142]. Reduced tumor sensitivity towards the chemotherapeutic drug cisplatin [137] could be reversed by FA2H over-expression or treatment with (R)-2-hydroxypalmitic acid. Similarly. sensitivity to the drug PM02734 is significantly enhanced in tumor cells that over-express FA2H [143]. Taking all the studies together, we can observe increased malignancies with low FA2H expression on one side and with high levels of 2hFA-SL on the other side. One possible explanation for this apparent contradiction could be that increased levels of hFA-SL in many tumors depend on the not-yet-identified alternative 2-hydroxylase enzyme(s) mentioned above or the α-oxidation of phytosphingosine (Section 3), which could also have different substrate specificities. Since cytochrome P450 enzymes are often upregulated in tumor cells to confer drug resistance, some of them could potentially be involved in fatty acid 2-hydroxylation. Moreover, the 2-hydroxyl group may also have different effects depending on which sphingolipids are synthesized by a given tumor cell. Different signaling pathways affected by FA2H over-expression have been identified: a higher chemosensitivity in gastric cancer cells depends on the inhibition of the mTOR/S6K1/Gli1 pathway by FA2H (through activation of AMPK) [137]; FA2H suppresses cancer stemness by inhibiting STAT3 and NF-κB signaling (through reduced phosphorylation of STAT3 and NF-κB) [144] and FA2H reduces metastasis in colon cancer through phosphorylation and the cytosolic retention of the transcription factor YAP1 [140]. Through which mechanisms FA2H influences these signaling pathways is, however, unclear at present. Not much is known about the transcriptional regulation of the FA2H gene. In a breast cancer cell line, peroxisome-proliferator-activated receptor (PPAR)-α mediates the induction of FA2H by Δ(9)-tetrahydrocannabinol [145,146,147]. Zhou et al. [148] provided evidence that TNF-α, via the upregulation of FOXC2, increases FA2H expression in esophageal cancer. Several micro-RNAs target the human FA2H gene and may play important roles in its regulation in cancer or other diseases that have been identified [125,141,142,149]. 2-hydroxylated oleic acid (2OHOA, Minerval) is an anti-cancer drug that is able to induce apoptosis in various cancer cells [150]. Free 2-hydroxylated fatty acids insert into membranes and significantly affect the membrane structure by reducing the lipid order and interfering with the tight packing of lipid side chains [151]. It is assumed that free 2OHOA affects signaling pathways in this way [152]. 2OHOA disturbs mitochondrial function by the uncoupling of oxidative phosphorylation and mitochondrial fragmentation [153]. Exogenously supplied 2OHOA is incorporated into triglycerides, diacylglycerides and phosphoglycerolipids [154,155]. However, there is no report describing the incorporation of 2OHOA into sphingolipids. It is therefore unclear whether the anti-tumor and pro-apoptotic pathways activated by 2OHOA treatment and FA2H overexpression are related. Sphingolipids containing 2-hydroxylated acyl residues are present in many (if not all) cell types and tissues. While in many cases high levels of 2hFA-SL correlate with a high expression of FA2H, there is clear evidence that additional fatty acid 2-hydroxylase enzyme(s) exist. This or these currently unknown enzyme(s) and FA2H and their reaction products may, in part, fulfill opposing roles, as suggested by the analysis of tumor cells. They may also be potential targets in tumor therapy. Thus, an important task in the field of 2hFA-SL is the identification of this/these hydroxylases. In parallel, it must be established to what extent 2hFA synthesis occurs via the α-oxidation pathway in the endoplasmic reticulum. Given their abundance and important roles in different cellular processes and the important roles of sphingolipids in many diseases, alterations in the 2-hydroxylation of sphingolipids may be relevant in more diseases than currently anticipated.

PMC10002950

Bianca Giuliani,Chiara Tordonato,Francesco Nicassio

Mechanisms of Long Non-Coding RNA in Breast Cancer

25-02-2023

LncRNAs,cancer,breast,gene expression,MicroRNA,chromatin

The landscape of pervasive transcription in eukaryotic genomes has made space for the identification of thousands of transcripts that are difficult to frame in a specific functional category. A new class has been broadly named as long non-coding RNAs (lncRNAs) and shortly defined as transcripts that are longer than 200 nucleotides with no or limited coding potential. So far, about 19,000 lncRNAs genes have been annotated in the human genome (Gencode 41), nearly matching the number of protein-coding genes. A key scientific priority is the functional characterization of lncRNAs, a major challenge in molecular biology that has encouraged many high-throughput efforts. LncRNA studies have been stimulated by the enormous clinical potential that these molecules promise and have been based on the characterization of their expression and functional mechanisms. In this review, we illustrate some of these mechanisms as they have been pictured in the context of breast cancer.

Mechanisms of Long Non-Coding RNA in Breast Cancer The landscape of pervasive transcription in eukaryotic genomes has made space for the identification of thousands of transcripts that are difficult to frame in a specific functional category. A new class has been broadly named as long non-coding RNAs (lncRNAs) and shortly defined as transcripts that are longer than 200 nucleotides with no or limited coding potential. So far, about 19,000 lncRNAs genes have been annotated in the human genome (Gencode 41), nearly matching the number of protein-coding genes. A key scientific priority is the functional characterization of lncRNAs, a major challenge in molecular biology that has encouraged many high-throughput efforts. LncRNA studies have been stimulated by the enormous clinical potential that these molecules promise and have been based on the characterization of their expression and functional mechanisms. In this review, we illustrate some of these mechanisms as they have been pictured in the context of breast cancer. The next-generation sequencing era has strongly increased the number of annotated non-canonical transcripts, such as lncRNAs. There are several factors that make the current annotation of these non-coding transcripts challenging compared to protein-coding genes, since lncRNAs are (i) weakly conserved at the sequence levels during evolution, (ii) generally low-expressed and (iii) strongly context-dependent, meaning that their levels of expression can differ greatly between tissues or even different cell types within a tissue. So, it is not surprising that several databases such as LNCipedia, lncRNADisease 2.0, LncATLAS, LncRNAdb and Lnc2Cancer are not coherently concordant and need to be updated timely and be supported by biological validation [1,2,3,4,5]. The use of high-throughput data (including CAGE, RNA-seq and polyA site-seq) from available consortia such as ENCODE (https://www.encodeproject.org, accessed on 20 February 2023) or FANTOM (https://fantom.gsc.riken.jp, accessed on 20 February 2023) can be useful for characterizing the expression of a given candidate in a specific tissue/cell type. Multiple studies have highlighted the role of lncRNAs in diseases [6]. Expression studies comparing normal vs. cancer tissues have revealed many lncRNAs to be regulated in cancer, often with a very high cancer specificity. In addition, cancer pathways have been found to be regulated by intricated networks of coding and non-coding transcripts. As for coding transcripts, lncRNAs can have either tumor-suppressing or oncogenic functions [7]. Among cancers, breast cancer is a life-threatening disease that mirrors the complexity and heterogeneity of the mammary gland. In this context, investigations on lncRNAs have been frequently aimed at the identification of novel or more accurate biomarkers for diagnosis and, above all, the search of novel therapeutic targets that are potentially useful in treating the most-lethal forms of the disease. Importantly, several molecular mechanisms involving lncRNAs have emerged in breast cancer studies and can be considered prototypical for their mode of action. In this review, we aimed at illustrating the complexity of lncRNA mechanisms and their mode of action, focusing on breast cancer as a unifying model system, which is useful for illustrating the biological role and, at the same time, the therapeutic potential of lncRNAs. A comprehensive list of lncRNAs with their mechanisms involved in breast cancer is summarized in Table 1. Below, we will discuss in detail the main mechanisms of lncRNAs, distinguishing those that occur in the nucleus from those that require cytoplasmic localization, as depicted in Figure 1. For each mechanism, we focused on a few lncRNAs with large support from the literature and evidence in breast cancer, which can be used as a prototypical example. A large fraction of lncRNAs is expressed almost exclusively in the nucleus [60,61] and, hence, exhibits functions related to nuclear processes, such as the regulation of RNA transcription and RNA splicing or the organization of functionally distinct nuclear domains. Various mechanisms contribute to the nuclear localization of lncRNAs. In general, we can distinguish “passive” mechanisms, favoring the nuclear accumulation of lncRNAs, such as inefficient transcription and low-yield RNA processing (i.e., splicing) [62], from “active” mechanisms based on nuclear retention signals that allow interaction with protein complexes and ribonucleoproteins localized in the nucleus, [63]. Overall, the nuclear functions of lncRNAs are related to the control of gene expression and, hence, fall into two main categories, cis- or trans-acting, depending on whether the lncRNA influences nearby genes or acts on long-distance regions [64]. Similarly, the activity of lncRNAs can be also categorized as sequence-dependent or -independent, as it may or may not depend on their exact nucleotide sequence. A recurring theme of nuclear functions is the regulation of the chromatin status. LncRNAs have been shown to influence chromatin organization at different levels. Indeed, the mere act of transcription can modulate the chromatin accessibility of a locus and, thus, lncRNA transcription can function as a cis-acting mechanism, influencing the expression of nearby protein-coding genes in a sequence-independent manner [65]. Alternatively, lncRNAs can interact with chromatin modifiers through the recognition of specific binding sites or secondary structures in the lncRNA transcript. Their interaction with proteins can have multiple readouts: lncRNAs can act as a molecular scaffold, bridging multiple proteins in a single macromolecular complex, or as a molecular decoy, coordinating the regulatory activity in a locus. In both cases, there are examples of cis- and trans-acting lncRNAs (some of them are reviewed in [66]). HOX transcript antisense intergenic RNA (HOTAIR) is one of the most strikingly cancer-associated lncRNAs [67] and is a typical example of a nuclear lncRNA acting both as a molecular guide and as a scaffold. HOX genes are a group of conserved protein-coding genes used in the control of the correct body patterning and are organized into different clusters in the genome. HOX genes are tightly regulated during their development and are frequently over-expressed in cancer [68]. The lncRNA HOTAIR is a conserved 2.1 kb transcript produced from the HOXC locus on chromosome twelve and is composed of six exons, which are actively spliced and polyadenylated [69]. Initially, HOTAIR has been suggested to regulate chromatin in trans at the distal HOXD cluster. Indeed, the knock-down of HOTAIR by siRNAs induces a de-repression of the locus and a reduction in the repressive histone modification H3K27me3 [70]. Further studies have suggested that HOTAIR acts as a scaffold, coordinating two different chromatin-modifying activities: the deposition of H3K27me3 mediated by Polycomb-repressive complex (PRC2) and the simultaneous demethylation of H3K4me3 by lysine-specific demethylase 1 (LSD1). Two loops in HOTAIR’s secondary structure, at the 5′ and 3′ ends, have been proposed to mediate its interaction with PRC2 and LSD1, respectively [70]. This lncRNA is frequently found as dysregulated (mostly over-expressed) in different cancer types. As it relates to breast cancer, HOTAIR has been reported to aberrantly target genomic regions other than the HOXD cluster, mediating chromatin dysregulation and promoting breast tumor metastasis [8,71]. Enhancers are regions of open chromatins which act as hubs for different transcription-factor-binding sites and operate in a cell-type-specific fashion to activate the expression of target genes (reviewed in [72,73]). Enhancers function on nearby genes (cis-acting), which can even be placed at several kb distances thanks to the formation of long-range chromatin interactions. As enhancers are actively transcribed, they also generate non-coding transcripts, which can either be shortly and rapidly degraded (eRNAs) or longer and more frequently processed [74]. These non-coding RNAs may participate in an enhancer function by several types of mechanisms. Here, we describe two lncRNAs involved in breast cancer with their reported enhancer-like functions. Colon-cancer-associated transcript-1-long isoform (CCAT1-L) is a lncRNA gene, so named as it was found to be highly expressed in colorectal cancer (CRC) samples [75]. CCAT1-L is a 5.2 kb long RNA that is enriched at its site of transcription and is chromatin-bound. It is expressed from the 8q24 genomic region, 500 kb upstream of the myelocytomatosis (MYC) locus. The CCAT1-L locus has been associated with several chromatin marks, which are typical of enhancer regions, such as high levels of H3K27Ac and H3K4Me1, low levels of H3K4Me3 and the presence of DNase-I-hypersensitive sites [72,76]. According to these epigenetic marks, the 150 kb long region encompassing CCAT1-L has been proposed to act as a putative super-enhancer responsible for controlling MYC expression via a regulatory element embedded in a lncRNA promoter (MYC-515) and a downstream regulatory element (MYC-335) [77,78]. Three-dimensional conformation capture data have supported the molecular interaction occurring among MYC-515, MYC-335 and MYC promoter. Strikingly, the downregulation of the CCAT1-L transcript by antisense oligonucleotides (ASOs) corresponds to a reduction in MYC expression and a decreased contact frequency among MYC, MYC-335 and MYC-515. These findings highlight the importance of the lncRNA transcript in mediating enhancer activities, other than DNA features occurring at the locus of its transcription. Overall, the proposed model suggests that the CCAT1-L transcript operates in cis and participates in establishing long-range contacts that bring the MYC locus into proximity with its enhancers thanks to its direct interaction with CCCTC-binding factor (CTCF) [79]. Given the wide oncogenic role of MYC, it is not surprising that CCAT1-L is frequently expressed at elevated levels in many cancer types. In breast cancer, CCAT1-L is a promising prognostic biomarker, as its expression correlates with a decreased overall survival and progression-free survival independently from the receptor status of the disease [80]. In some cases, processed (mature) lncRNAs, rather than primary unprocessed transcripts, may directly contribute to enhancer function control. This is the case of A-ROD, a lncRNA involved in the regulation of a downstream gene, namely a negative regulator of the Wnt pathway named Dickkopf-1 (DKK1) [81]. A-ROD is a non-coding transcript originating from a locus acting as an enhancer and is located 130 kb upstream of the DKK1 locus. In breast cancer cell lines (MCF-7) and samples from breast cancer patients, the two loci showed a correlated expression and were found to be involved in chromatin looping [17]. Interestingly, ASOs targeting the nascent A-ROD transcript had no effect on DKK1 mRNA levels, while siRNAs targeting the mature transcript were able to reduce the expression level of DKK1 and, at the same time, increase the pausing of RNA polymerase 2 at the DKK1 transcription start site. The proposed model suggests that A-ROD is not involved in chromosomal looping, conversely to CCAT1-L. A pre-existing conformation maintains the A-ROD locus in proximity to DKK1, and the A-ROD mature transcript recruits the transcriptional activator EBP4 to enhance DKK1 transcription. Experiments on the splicing inhibition and transcriptional termination of this lncRNA both supported the fact that the enhancer-like function of A-ROD is mediated by the mature transcript. Interestingly, Ntini et al. [17] provided data in support of many other lncRNAs with similar features, as they are transcribed from regions involved in chromatin loops and with a poor association with chromatin, suggesting that the mature form of the lncRNA plays a functional role in gene expression control. In support of this, bioinformatic analyses have proposed that the activity of enhancers is correlated with both the transcription and splicing of their encoded lncRNAs [82,83]. Recently, lncRNAs were shown to exploit another mechanism of gene expression control by affecting gene splicing. Splicing is a fundamental step in mRNA maturation that allows the excision of introns from transcripts, and the usage of alternative splice sites can affect the production of multiple isoforms subjected to differential regulation in physiology and disease [84]. An emblematic case is the stress-induced lncRNA known as lncRNA associated with SART3 regulation of splicing (LASTR), which is induced by c-JUN together with other survival genes during hypoxia and DNA damage. As c-JUN is frequently overexpressed in epithelial tumors, LASTR was found to be highly expressed in most breast cancer subtypes, as reported in The Cancer Genome Atlas—TCGA [21]. This lncRNA is a 714 nt transcript composed of two exons expressed mainly in the nucleus and has been found to interact with SART3, a splicing protein involved in the assembly of the U4/U6 ribonucleic complex, by RNA pulldown assays followed by mass spectrometry [85]. LASTR seems to have an impact on splicing control at a global level, as shown by knock-down experiments with ASOs, which resulted in the impairment of the SART3 disassembly from the U4 snRNA and the prevention of the recycling of spliceosome components, increasing intron retention, exon skipping and the non-sense-mediated decay of mRNAs [86]. In normal mammary epithelial cells, the expression of LASTR induced by hypoxia facilitates the dissociation of SART3 from the U4/U6 snRNP, preserving cell physiology when stress conditions are present [87]. Similarly, the constitutive overexpression of LASTR helps cancer cells to increase their cell fitness by avoiding splicing defects. Strikingly, the knockdown of LASTR can sensitize the triple-negative breast cancer cell line MDA-MB-231 to irradiation and impair the tumor growth in mice xenografts, suggesting that this lncRNA is a potential therapeutic target. This work exemplifies how the dynamic regulation of one single lncRNA can largely impact fundamental physiological cellular processes and how cancer cells favorably exploit these simple but effective mechanisms. Some lncRNAs that are abundantly expressed in the nucleus can function in coordinating the organization and activity of functionally distinct nuclear compartments [88]. This is the case of two well-known lncRNAs, named nuclear enriched abundant transcript 1 (NEAT1) and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) (also known as NEAT2). These lncRNAs are transcribed from proximal loci but are then localized in separate compartments. NEAT1 is localized and is essential for the assembly of paraspeckles, a dynamic compartment responsible for transcription and RNA processing. NEAT1 is associated with actively transcribed genes [89]. Thanks to the different protein interacting domains in its sequence, NEAT1 realizes the precise localization of proteins in this compartment [90]. NEAT1 expression is dysregulated in many cancer types and is found in the peripheral blood of breast cancer patients [24]. The increased expression of NEAT1 is associated with a poor prognosis and overall survival [91]. The expression of NEAT1 is regulated by several tumorigenic transcription factors such as STAT3 or NFkB [92] and contributes to the regulation of the genes responsible for invasion, metastasis and chemoresistance [91]. MALAT1 is a conserved lncRNA [93] that localizes in nuclear speckles, a subnuclear domain where components of the spliceosome concentrate [94]. The current model suggests that MALAT1 functions in the periphery of nuclear speckles and participates in the positioning of the speckles towards actively transcribed genes, contributing to pre-mRNA splicing [89,95]. Consistent with this model, MALAT1 knockdown does not impair the formation of nuclear speckles but changes their composition and functionality. The down-modulation of the phosphorylation levels of serine/arginine-rich proteins, which are key splicing components, has been observed upon MALAT1 silencing, which may explain the impact it has on splicing. MALAT1 expression has been frequently associated with a poor prognosis, metastasis [26] and chemo- and radio-resistance in several human tumors and in breast cancer [96]. Tandem duplications of the MALAT1 gene have also been reported [97]. However, Kim et al. provided evidence of a tumor-suppressive role of MALAT1 in breast cancer cells and primary mammary tumors [25]. According to this work, MALAT1 interacts with TEAD, preventing the association with the YAP co-activator and the expression of pro-metastatic target genes. These opposite views may not be mutually exclusive but may co-exist in the interpretation of a complex and abundant lncRNA such as MALAT1. A large portion of lncRNAs can exert their functions on the cytoplasm after being transported from the nucleus. A very recent study highlighted that long transcripts that are A/U-rich and with few exons, such as the vast majority of lncRNAs, are dependent on the NXF1 factor for export [98]. Upon arrival, lncRNAs can be sorted into different organelles [99] (i.e., mitochondria or exosomes) or be associated with proteins/nucleic acids. One representative example is the nuclear-encoded lncRNA SAMMSON, which is expressed in melanoma cells and is re-located into mitochondria and plays a fundamental role in the regulation of mitochondrial metabolism through the interaction with p32 [57]. How the sorting occurs into different cellular compartments still needs better elucidation; however, it is commonly accepted that it depends on the interaction of lncRNAs with RNA-binding proteins (RBPs) and/or with other RNA species, such as for most (if not all) of the cytosolic functions of lncRNAs. An important caveat for lncRNA/target interaction is represented by the critical stoichiometric ratio between the lncRNA and its target molecule, either a protein or an RNA molecule. In fact, in the case of cis-acting lncRNAs, few copies are sufficient to exert a biologically relevant function on a single target gene located in proximity. However, for trans-acting lncRNAs, such as all cytoplasmic lncRNAs, it is essential to start with a clear copy number quantification of both the target and the lncRNA in order to verify if a proposed biological mechanism is plausible [64,65]. This especially applies to those lncRNAs acting as competing endogenous RNAs (ceRNAs). This is a mechanism where an lncRNA acts as sponge, soaking up many molecules of a given miRNA and, hence, competing for the interaction of the miRNA with its own set of mRNA targets. A seminal work by Bartel’s group focused on miR-122 as a proof-of-principle in order to challenge the contention that a change in the copy number of a single miRNA target could compete with other shared targets in such a way as to result in a variation in the miRNA’s effects. This work suggests that the miRNA:ceRNA stoichiometry should be better investigated, as the upregulation/downregulation of a single ceRNA may not be sufficient to exert a measurable effect on miRNA activity [100]. Moreover, to further complicate this scenario, lncRNA expression could be associated to a specific tissue (normal vs. cancer) or even restricted to a specific cell type (i.e., rare cell types as stem cells). Thus, to understand the biological effects mediated by the lncRNA, a careful stoichiometric quantification is advisable, accounting for sample purity rather than using a bulk population, which can contain different cell types. LncRNA-regulator of reprogramming, a.k.a., Linc-ROR, was initially identified as a competing endogenous RNA (ceRNA) involved in hESC self-renewal. Linc-ROR levels are high in hESC and drop down during differentiation [101]. The ceRNA activity was dependent on the microRNA responsive elements (MREs) within Linc-ROR sequence and matching with miR-145. This resulted in the sequestering of miR-145 molecules and maintaining the hESC’s pluripotent state by avoiding the miRNA-mediated repression of several embryonic transcription factors (ETFs) [101]. In the breast, Linc-ROR was reported to have an impact on the regulation of the epithelial-to-mesenchymal transition (EMT) and the acquisition of chemoresistance and cancer stem cell traits. One of the first pieces of evidence came from a study using MCF10A, a normal breast epithelial cell line, which described Linc-ROR as a ceRNA that was able to sponge miR-205, thus causing an increase in ZEB2 levels, a TF-promoting EMT and a well-known target for miR-205. This mechanism can explain the increase in the expression of mesenchymal markers and the effects on proliferation, cell migration and the acquisition of some traits observed upon Linc-ROR expression, such as the increased CD44high/CD24low population and its capability of forming non-adherent spheroids (mammosphere) [36]. A more recent study on MCF7 cells suggests that Linc-ROR acts as ceRNA for miR-194-3, causing an increase in MECP2 levels and, thus, promoting the proliferation, invasion and resistance to rapamycin treatment of breast cancer cells [37]. Linc-ROR was also described with another type of mechanism, supporting the estrogen-independent growth of ER+ breast tumors and their resistance to tamoxifen [102]. The proposed mechanism involves the direct inhibition of the phosphatase DUSP7 and the consequent activation of MAPK/ERK signaling, which, in turn, phosphorylates the estrogen receptor and fosters the growth of breast cancer cells and resistance to hormonal chemotherapy [102]. The transcript from the H19 locus was one of the first lncRNAs to be acknowledged. It belongs to a conserved imprinted region located on the human chromosome 11, encoding for a 2.3 kb long cytosolic transcript associated with the epigenetic silencing of the IGF2 locus [103]. In mouse embryonic and extra-embryonic cell lines, H19 has also been described as a precursor for miR-675 and capable of regulating placental development by regulating the abundance of IGF2 at two levels through the imprinting of the gene locus and the silencing of the IGF1R receptor via miR-675 [104]. In breast cancer cells, H19/miR-675 expression has been associated with increased proliferation, tumor growth aggressiveness and metastases in vivo. Mechanistically, this was suggested to be dependent on miR-675 activity in b-Cbl and c-Cbl mRNAs, which, in turn, leads to the hyperactivation of EGFR and c-Met and the consequent activation of Akt and Erk signaling [38]. In addition, H19 has also been described as an miRNA sponge for Let-7, highlighting a prototypical ceRNA mechanism active during muscle differentiation, as shown by Kallen et al. [105]. The ceRNA mechanism was also reported to occur in breast tumors in several reports. For instance, the interaction of H19 with Let-7c was shown to influence the type of division (symmetric or asymmetric) of cancer stem cells (CSC) by controlling WNT signaling [39]. In another report, H19 was associated to Let-7a/b and the core pluripotency factor LIN28, a transcription factor critical for stem cells. A positive feedback loop mechanism was described, with H19 competing with LIN28 for Let-7a/b binding, leading to an increase in LIN28 levels, which, in turn, inhibits the generation of mature Let-7a/b molecules from precursors, derepressing all the target genes for Let-7 miRNAs [40]. Lastly, under hypoxic conditions, H19 was reported to sequester Let-7 miRNAs and to relieve HIF1α mRNA levels. In this report, the H19/Let-7/HIF-1α axis was shown to act as metabolic gatekeeper under hypoxia, controlling the switch from OXPHOS to glycolysis [106]. Besides acting as sponges for miRNAs, lncRNAs in the cytosol can also affect mRNA stability, by acting as guide controlling mRNA degradation or mRNA translation. One representative example is the non-coding RNA activated by DNA damage (NORAD). This lncRNA is very abundant in the cytoplasm, where it is bound to PUMILIO1/2 proteins and acts as a decoy. This mechanism depends on the sequence of NORAD, which contains several PUMILIO response elements (PRE), a stretch 8 nt long, which is typically located in the in 3′ UTR of PUMILIO target mRNAs. Upon genotoxic stress, NORAD acts as reservoir of PUMILIO1/2 proteins and controls genomic stability. In fact, the loss or downregulation of NORAD causes a sudden release of PUMILIO1/2 proteins, which bind and accelerate the mRNA turnover of targets involved in DNA repair and DNA replication, thus driving chromosome instability [51]. In colon cancer cells, by combining RNA antisense purification (RAP) and quantitative MS, NORAD was identified as a necessary component for the assembly of a ribonucleic complex (NORAD-activated ribonucleoprotein complex 1, NARC1) involved in genome stability maintenance. Cells depleted for NORAD have increased defects in chromosome segregation, reduced replication fork speed and an altered cell cycle [107]. In breast cancer, NORAD was suggested to act as tumor suppressor. A report showed NORAD under transcriptional repression by the YAP/TAZ and NuRD complexes, which usually act as oncogenic factors. In addition, NORAD was shown to act as a decoy for S100P, counteracting its pro-migratory and pro-invasive activity [52]. According to their definition, lncRNAs should not have coding functions. However, some studies suggested that small polypeptides can be synthetized from small open-reading frames (ORFs) and can participate in lncRNA-regulatory functions. For instance, in breast cells, LINC00665 was shown to encode for a micropeptide of 5.5 kDa named CIP2A-BP, which binds CIP2A and competes with the subunit PP2A, an oncogene that promotes tumor progression [31]. Of note is the fact that the translation of LINC00665 is under the control of the TGFβ and SMAD pathways, while the overall levels are not affected. Consistent with this model, the migration and invasion properties of triple-negative breast cancer cells can be inhibited both in vitro and in vivo by the overexpression of the CIP2A-BP protein but not by LINC00665 expression [31]. LncRNA EPR (epithelial cell program regulator) was found to be a typical breast epithelial lncRNA, whose expression is inhibited by TGFβ treatment. LncRNA EPR was shown to encode for an ~8 kDa small peptide, which localizes at the epithelial cell junctions of mammary glands together with junctional proteins such as ZO-1, CGNL1 and Cortactin [32]. LncRNA EPR was suggested to have a dual mechanism. At the RNA level, it can interact with the Cdkn1a gene on chromatin and can sustain the expression and stability of Cdkn1a mRNA, thus promoting epithelial phenotype and cell cycle arrest [32]. Many lncRNAs display multiple regulatory functions that are associated with complex and sometimes conflicting phenotypes. In this category, one representative example is plasmacytoma variant translocation 1 (PVT1), a long non-coding RNA. The human PVT1 gene shows a high level of homology with mouse and rat genomes [108,109]. Six different transcription start sites (TSS) can drive the expression of PVT1 lncRNA and are distributed in a region of 300 kb and are located downstream of the promoter of the MYC oncogene [110]. MYC and PVT1 belong to the 8q24 genomic region, which is frequently altered in cancer. Specifically, this locus is mostly susceptible to amplifications and other structural alterations that lead to the co-amplification of the two genes [111]. Similarly to MYC, high expression levels of PVT1 have been associated with a poor prognosis in breast cancer and other human malignancies [112,113]. The pro-tumorigenic function of PVT1 can be explained by the activity miRNAs embedded in the lncRNA transcript. PVT1, indeed, hosts a miRNA cluster composed of miR-1204, -1205, -1206, -1207-5p and -3p and -1208, which can act as oncomiRs, promoting cell proliferation [114], increasing glycolytic metabolism [115] and suppressing stress-induced apoptosis [116]. However, other studies reported tumor-suppressive functions for the same miRNAs [117,118], suggesting that tissue-specific targets and effects may be involved. In addition, the PVT1 sequence holds several sites matching miRNAs (MREs), invoking a potential molecular sponge mechanism for the transcript [119]. Indeed, different reports support the possibility that the PVT1 transcript may sequester miRNAs with tumor-suppressive functions, thus leading to the activation of proliferative and survival pathways [120,121] and the acquisition of metastatic traits. Moreover, the PVT1 transcript was shown to interact with the MYC protein in trans, regulating MYC stability by interfering with Threonine 58 phosphorylation and proteosome-mediated degradation. MYC, in turn, binds the PVT1 promoter in two E-boxes sites, creating a positive feedback loop that sustains MYC expression and MYC-induced proliferation [122,123]. In breast cancer, the amplification of the 8q24 region leads to both a gain in the copy number of the PVT1 gene and the accumulation of genetic alterations at the level of the promoter region of PVT1, which abrogates its expression [124]. Starting from this observation, Cho et al. showed that the most-upstream promoter of PVT1 has a tumor-suppressive function that is independent from the transcription of the lncRNA and aids in tightly regulating the expression of MYC [110]. In breast cancer cell lines, the promoters of PVT1 and MYC compete for the binding of intragenic enhancers that are located within the gene body of PVT1. When the promoter of PVT1 is functional, it interacts with the enhancers, which are closer, sustaining the expression of PVT1 transcript only. When the promoter of PVT1 is non-functional, the intragenic enhancers rewire it towards the promoter of MYC with a topological rearrangement in the 3D genome that boosts the oncogenic expression of MYC, thus enhancing cancer cell proliferation [110]. This mechanism of enhancer retargeting seems to be not restricted to the case of the PVT1-MYC pair. Oh et al. [125] showed that cancer cells often accumulate mutations in the promoters of genes owing to topological rearrangements of the genome that are able to reinforce the expression of oncogenes. In addition to this, a recent work by Oliviero et al. [126] described an alternative type of relationship occurring between the Pvt1-Myc pair in mouse embryonic fibroblasts (MEFs). In this work, a p53-responsive element was found on a downstream TSS for Pvt1 that, in stress conditions and upon p53 binding, could elicit the expression of the Pvt1b isoform and the concurrent repression of Myc transcription. The authors suggested that this mechanism is RNA-dependent, as the repression of Myc occurs in cis in the absence of topological rearrangements and that it is abrogated in the presence of antisense oligonucleotides targeting Pvt1b [126]. This mechanism still needs to be clarified in human malignancies, but it highlights a role for lncRNA in adjuvating key stress response pathways such as the one coordinated by p53. More than 30 years of study have just scratched the complexity of the PVT1 locus and show the contextual presence of enhancer-like functions of lncRNAs, the trans-activity of the PVT1 transcript in regulating the stability of MYC protein, the contribution of DNA-regulatory elements within a non-coding locus as well as RNA-dependent functions occurring in cis. Moreover, this illustrates how cells regulate non-coding RNAs to coordinate multiple physiological or oncogenic activities and realize the fine dosing of key factors. The molecular mechanisms of lncRNAs are manifold, as are their implications in cellular and tumor biology. In this review, we summarized some of the most representative examples that have emerged in recent years and illustrated, in the context of breast cancer, one of the most-studied tumor types. Although it is a common belief that lncRNAs contribute to the key steps of gene expression regulation at either the global level or by optimizing target gene dosage, addressing the complexity of their function or biological activity still represents a major challenge in lncRNA research. Recent technological advances that allow the endogenous investigation of the regulatory function of RNAs together with the development of new sequencing approaches other than short-reading sequencing promise to give new life to this research field and contribute to the development of new fundamental discoveries. In addition to participating in the definition of cancer phenotypes, lncRNAs currently represent promising biomarkers of pathological states and promising therapeutic opportunities. RNA is, by its nature, easier to target and degrade (as compared to proteins or DNA), and the high tissue- and cell-type specificity of lncRNA expression is compatible with highly targeted approaches. All these characteristics make the study of lncRNAs in pathology extremely valuable.

PMC10002952

Yun Mi Lee,Eunjung Son,Seung-Hyung Kim,Dong-Seon Kim

Protective Effects of Glycine soja Leaf and Stem Extract against Chondrocyte Inflammation and Osteoarthritis

02-03-2023

Glycine soja,leaf and stem extract,inflammation,chondrocyte,osteoarthritis

Wild soybean, also known as Glycine soja Sieb. et Zucc. (GS), has long been known for its various health benefits. Although various pharmacological effects of G. soja have been studied, the effects of GS leaf and stem (GSLS) on osteoarthritis (OA) have not been evaluated. Here, we examined the anti-inflammatory effects of GSLS in interleukin-1β (IL-1β)-stimulated SW1353 human chondrocytes. GSLS inhibited the expression of inflammatory cytokines and matrix metalloproteinases and ameliorated the degradation of collagen type II in IL-1β-stimulated chondrocytes. Furthermore, GSLS played a protective role in chondrocytes by inhibiting the activation of NF-κB. In addition, our in vivo study demonstrated that GSLS ameliorated pain and reversed cartilage degeneration in joints by inhibiting inflammatory responses in a monosodium iodoacetate (MIA)-induced OA rat model. GSLS remarkably reduced the MIA-induced OA symptoms, such as joint pain, and decreased the serum levels of proinflammatory mediators, cytokines, and matrix metalloproteinases (MMPs). Our findings show that GSLS exerts anti-osteoarthritic effects and reduces pain and cartilage degeneration by downregulating inflammation, suggesting that it is a useful therapeutic candidate for OA.

Protective Effects of Glycine soja Leaf and Stem Extract against Chondrocyte Inflammation and Osteoarthritis Wild soybean, also known as Glycine soja Sieb. et Zucc. (GS), has long been known for its various health benefits. Although various pharmacological effects of G. soja have been studied, the effects of GS leaf and stem (GSLS) on osteoarthritis (OA) have not been evaluated. Here, we examined the anti-inflammatory effects of GSLS in interleukin-1β (IL-1β)-stimulated SW1353 human chondrocytes. GSLS inhibited the expression of inflammatory cytokines and matrix metalloproteinases and ameliorated the degradation of collagen type II in IL-1β-stimulated chondrocytes. Furthermore, GSLS played a protective role in chondrocytes by inhibiting the activation of NF-κB. In addition, our in vivo study demonstrated that GSLS ameliorated pain and reversed cartilage degeneration in joints by inhibiting inflammatory responses in a monosodium iodoacetate (MIA)-induced OA rat model. GSLS remarkably reduced the MIA-induced OA symptoms, such as joint pain, and decreased the serum levels of proinflammatory mediators, cytokines, and matrix metalloproteinases (MMPs). Our findings show that GSLS exerts anti-osteoarthritic effects and reduces pain and cartilage degeneration by downregulating inflammation, suggesting that it is a useful therapeutic candidate for OA. Osteoarthritis (OA) is a chronic progressive degenerative joint disorder characterized by cartilage degradation and physical disability [1]. The development and progression of OA lead to cartilage matrix degradation caused by inflammation, which results in the degradation of the extracellular matrix (ECM) [2]. Many proinflammatory cytokines participate in OA pathogenesis, with interleukin 1 beta (IL-1β), IL-6, and tumor necrosis factor-alpha (TNF-α) being the most important proinflammatory mediators [3,4]. IL-1β is a key inducer of inflammation and directly participates in the generation of multiple inflammatory mediators such as nitric oxide (NO) and prostaglandin E2 (PGE2) [5]. Additionally, cartilage-degrading enzymes such as matrix metalloproteinases (MMPs), which are upregulated by IL-1β in chondrocytes, degrade collagen type II (COL-II) and accelerate the decomposition of the ECM during OA progression [6]. Thus, candidate drugs capable of targeting IL-1β-induced inflammation may be effective as novel therapeutic strategies for OA. Natural products have been evaluated for their potential in the prevention and treatment of OA, providing an effective and safe adjunctive therapeutic approach. Many studies have investigated herbal medicines and natural products for their suppressive effects on chondrocytes apoptosis, induction of ECM degradation, and prevention of ECM decomposition in articular cartilage [7,8]. Glycine soja Sieb. et Zucc. (GS), wild soybean regarded as the progenitor of cultivated soybean has a long history of use in China dating back more than 2000 years; it is considered an excellent source of soybean-derived drugs [9]. GS exhibits various clinically relevant effects, including improvement in blood lipid profile and reduction in hepatic steatosis and adipocyte size in high-fat diet mice [10]. The health benefits associated with polyphenols in soybean are attributed to phenolic acids, flavonoids, and anthocyanins [11,12]. In addition, according to records of folk remedies in an ancient Chinese book, Material Medical for Famines, aerial parts of the plant have proven clinical effects, such as controlling excessive sweating and tonifying the kidneys and spleen [13]. Flavonoids and triterpenoids from the aerial parts of GS exert growth-inhibitory effects against insect pests [14]. However, to date, no studies have reported the therapeutic effects of GS leaf and stem (GSLS), particularly in OA. Therefore, in this study, we investigated the effects of GSLS against inflammation and ECM degradation through the downregulation of MMPs (MMP-1, MMP-3, and MMP-13) via activation of the NF-κB signaling pathway in IL-1β-treated SW1353 cells. We further investigated the potential of GSLS in preventing inflammatory responses and protecting against articular cartilage degradation in a rat model of monosodium iodoacetate (MIA)-induced OA. Our findings reveal that GSLS significantly attenuates the levels of inflammatory markers in chondrocytes and reduces pain and cartilage damage in MIA-induced rats. Based on the absorption profile and retention time, GSLS contained 3.10 ± 0.008 mg/g daidzin, 2.22 ± 0.039 mg/g genistin, 0.71 ± 0.014 mg/g daidzein, and 7.75 ± 0.343 mg/g soyasaponin Bb. Mass spectroscopy data of GSLS predict the presence of apigenin ([M + H]+, 271.12), formononetin ([M + H]+, 269.10), and soyasaponin II ([M − H]−, 911.46) (Figure 1). The effect of GSLS on cell viability in SW1353 chondrocytes was examined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. IL-1β and/or GSLS treatment had no significant effect on cell viability after 24 h of incubation (Figure 2a). Therefore, GSLS concentrations at 200 μg/mL or less were used for all subsequent experiments. The effects of GSLS on the expression of inflammatory factors, IL-1β, TNF-α, IL-6, and PGE2 were analyzed using an enzyme-linked immunosorbent assay (ELISA). As shown in Figure 2b–e, PGE2, IL-1β, TNF-α, and IL-6 levels were significantly increased in the culture medium of the IL-1β-stimulated SW1353 cells. In contrast, the expression of PGE2 was decreased when the cells were treated with GSLS (200 µg/mL) and indomethacin (INN, 2 ug/ml), a positive control, by 21.76%, and 65.97%, respectively. The IL-1β level was markedly reduced (by 14.98%) in cells treated with GSLS (200 μg/mL) along with IL-1β, compared with those treated with IL-1β alone (Figure 2c). In addition, GSLS treatment significantly decreased TNF-α production in IL-1β-stimulated cells in a dose-dependent manner; at GSLS concentrations of 50, 100, and 200 μg/mL, TNF-α levels were decreased to 79.29%, 84.95%, and 97.09% at concentrations 50, 100, and 200 μg/mL, respectively (Figure 2d). IL-6 was significantly suppressed by 31.47% and 34.71% after GSLS treatment at concentrations of 100 and 200 μg/mL, respectively (Figure 2e). COL-II is the primary component of the ECM and contributes significantly to the support of the cartilaginous structure. ECM degradation during OA is caused by matrix-degrading enzymes such as MMPs [15]. To evaluate chondrocyte degeneration, we investigated the effects of GSLS extract on COL-II levels in IL-1β-treated SW1353 chondrocytes by performing ELISA and immunofluorescence analyses. As shown in Figure 3, COL-II levels were significantly decreased after IL-1β treatment; however, pre-treatment with GSLS at 200 μg/mL prevented this decrease by 49.04%. In addition, immunofluorescence analysis showed that in contrast to the IL-1β group, treatment with GSLS also inhibited IL-1β-stimulated cytoplasmic COL-II degradation. To further investigate how GSLS suppressed IL-1β-induced chondrocyte degeneration, we analyzed the MMP production using ELISA. The results (Figure 4a–c) showed that IL-1β treatment stimulated the protein expression levels of MMP-1, MMP-3, and MMP-13 and increased them to 23.62, 132.35, and 1.90 ng/mL, respectively. However, treatment with 200 μg/mL GSLS decreased these levels to 11.92, 88.72, and 1.05 ng/mL, indicating inhibition of 49.52%, 32.96%, and 44.80%, respectively. In parallel, the effects of GSLS on MMP-1, MMP-3, and MMP-13 mRNA expression were studied using RT–qPCR. As shown in Figure 4d–f, the elevated mRNA expression levels of MMP-1, MMP-3, and MMP-13 were significantly suppressed after GSLS (200 μg/mL) treatment to 59.76%, 45.28%, and 44.13%, respectively. Furthermore, immunofluorescence analysis showed that GSLS protected against IL-1β-induced elevated expression of MMP-1 and MMP-13, which was consistent with the results of mRNA analysis and ELISA (Figure 5a,b). Thus, GSLS exhibits a protective effect on the cartilage matrix by inhibiting ECM degradation via the downregulation of matrix-degrading enzymes and COL-II degradation induced by IL-1β in SW1353 chondrocytes. To explore the underlying mechanism of the cartilage protective effect of GSLS, western blot and immunofluorescence analyses of NF-κB p65 were performed to examine the effect of GSLS on the NF-κB pathway. IL-1β significantly upregulated p65 phosphorylation (p < 0.05), whereas GSLS markedly reduced IL-1β-induced NF-κB activation in a dose-dependent manner (Figure 6a). Furthermore, immunofluorescence analysis revealed that IL-1β-induced nuclear translocation of p65 was significantly blocked by pre-treatment with 200 μg/mL GSLS (Figure 6b). This observation was consistent with the western blotting results. Taken together, these findings demonstrate that GSLS effectively inhibits IL-1β-induced NF-κB signal activation in SW1353 chondrocytes. Weight-bearing distribution was measured in sensitized contralateral hind limbs to assess joint pain. We evaluated hind paw weight bearing using an incapacitance tester on days 0, 7, 14, and 21. The weight-bearing in the MIA group decreased rapidly and became significantly different from that of the saline group on day 7 post-MIA injection and was maintained for at least 21 days. These values increased slightly in the GSLS-treated groups on day 7 compared with those in the MIA group. However, in these groups, the balance between the hind legs was restored after 21 days. The 200 mg/kg GSLS and GLM (green-lipped mussel oil) as positive control groups showed maximum pain reduction of 32.4% and 51.9% 21 days post-MIA induction, respectively. These results demonstrated significant recovery of hind paw weight bearing in the GSLS-treated groups (Figure 7). As shown in Figure 8, the levels of inflammatory mediators and cytokines were significantly elevated in the MIA group compared with those in the control group. In contrast, the GSLS-treated group showed remarkably decreased serum levels of IL-1β (64.8%), TNF-α (comparable to levels in control), IL-6 (51.7%), 5-lipoxygenase (5-LOX, 66.0%), cyclooxygenase-2 (COX-2, 68.1%), leukotriene B4 (LTB4, 87.7%), and PGE2 (79.4%) in rats with MIA-induced OA at a dose of 200 mg/kg (Figure 8a–g). These results suggest that GSLS suppresses inflammatory responses by inhibiting the production of inflammatory cytokines and mediators in rats with MIA-induced OA. To assess the inflammatory mediator-promoted secretion of MMPs during the inflammatory process, we next examined whether GSLS inhibited the secretion of MMP-2 and MMP-9 in the knee joint tissues of rats with MIA-induced OA. The MIA group showed elevated mRNA levels of MMP-2 and MMP-9 compared with those in the control group. However, the 200 mg/kg GSLS-treated group showed a significant decrease in MMP-2 and MMP-9 levels (Figure 9a,b). Conversely, mRNA expression of ECM genes such as aggrecan (ACAN), and COL-II, was dramatically reduced in MIA-induced articular cartilage. However, increased ACAN and COL-II mRNA expression levels were observed in the GSLS-treated groups compared with that in the MIA-induced group. These data suggest that GSLS may inhibit cartilage degradation in MIA-induced OA. OA is a chronic and degenerative joint disease characterized by the destruction of articular cartilage due to an imbalance between biosynthesis and degradation of the ECM, and it leads to physical disability [16]. Although the underlying pathological mechanism of OA remains unclear, inflammatory responses contribute significantly to the symptoms and progression of OA [17]. Various potential natural products and herbal resources have been used to treat OA and/or to delay disease progression [18,19]. The therapeutic effects of GSLS on OA have remained unknown so far. Here, we investigated the effects of GSLS against inflammation and ECM degradation using in vitro and in vivo models and investigated the potential of GSLS in preventing inflammatory responses and protecting against articular cartilage degradation in OA. Our findings reveal that GSLS significantly attenuates the levels of inflammatory markers in chondrocytes and reduces pain and cartilage damage in MIA-induced rats. In previous studies, proinflammatory cytokines, such as TNF-α, IL-1β, IL-6, and IL-10, were detected in synovial fluid from patients with OA and in several experimental animal models of cartilage degradation [20,21,22]. In particular, IL-1β, known as the master regulator of inflammation, has been reported to be directly involved in the generation of multiple inflammatory mediators associated with cartilage degeneration, such as pro-inflammatory factors, PGE2, NO, and MMPs. TNFα is involved in driving the inflammation process [4,5]. Furthermore, the upregulation of IL-1β and TNF-α in articular cells stimulates the production of proinflammatory cytokines such as IL-6 [23] and chemokines such as IL-8 [24]. Hence, in this study, we used IL-1β-stimulated SW1353 cells as an inflammatory chondrocyte model and evaluated the anti-inflammatory effect of GSLS by measuring the changes in the levels of the inflammatory mediators PGE2, IL-1β, IL-6, and TNF-α. Our data revealed that GSLS significantly attenuated these changes in IL-1β-treated chondrocytes. Previous studies have demonstrated that daidzin, genistin, daidzein, and soyasaponin Bb, the main ingredients in GSLS, play roles in the suppression of LPS-stimulated inflammation in macrophages [25,26,27]. Considering these reports of representative compounds, it can be inferred that the therapeutic effects of GSLS could be due to the synergistic anti-inflammatory effects of these compounds. INN, one of the NSAID drugs that reduce the synthesis of prostaglandin by inhibiting cyclooxygenase (COX) to reduce pain, inflammation, and fever, was used as a positive control [28]. INN significantly inhibited the production of PGE2, which was increased by IL-1β in SW1353 cells, but did not show other cytokines inhibitory activities. IL-1β induces catabolic responses by suppressing the expression of cartilage-related genes, such as that encoding COL-II [29] and promoting the expression of matrix-degradation-related genes, including those encoding MMP-1, MMP-3, MMP-9, and MMP-13 [30]. The degradation of collagen, one of the ECM components, is an important process in the development, morphogenesis, tissue repair, and remodeling [31]. ECM degradation involves different types of proteases; however, the MMP family members including gelatinases (MMP-2 and -9), collagenases (MMP-1, -8, and -13), stromelysins (MMP-3, -7, -10, and -11), membrane type (MT)-MMPs, and matrilysins are the major enzymes that degrade ECM components [32,33]. In particular, collagenases, including MMP-1, -8, and -13, facilitate the formation of a suitable microenvironment for the development and progression of OA and specifically degrade COL-II and proteoglycans through other MMPs in the cartilage matrix [34]. The activity of gelatinases is higher on the subchondral bone rather than on cartilage ECM [35]. Among MMPs, MMP-3 (also known as stromelysin) activates MMP-1 (also known as collagenase-1) and cleaves a broad range of matrix proteins [36]. MMP-1 is expressed ubiquitously and is found in various normal tissue cells, including chondrocytes, whereas MMP-13 (also known as collagenase-3) is more closely linked to COL-II degradation rather than MMP-1 and MMP-8 and is usually produced only by cartilages and bones during development and by chondrocytes during OA [37,38]. Therefore, the levels of COL-II and MMPs can be used as indicators to investigate the progression of cartilage destruction. In the present study, GSLS inhibited the IL-1β-induced secretion of MMP-1, -3, and -13 in SW1353 chondrocytes. In addition, mRNA and immunofluorescence analyses showed that GSLS treatment reduced the expression of MMP-1 and -13 and increased COL-II in chondrocytes induced by IL-1β. GSLS treatment thus shows a protective effect against ECM degradation and delays OA progression. The NF-κB pathway mediates important events in the inflammatory response of chondrocytes, leading to progressive ECM damage and cartilage erosion. NF-κB is activated by the inflammatory cytokines IL-1β and TNF-α and mediates the expression of MMPs, including MMP-1, -3, and -13 [34,39,40]. Therefore, NF-κB pathway activation is blocked by drugs currently used for the treatment of OA, such as nonsteroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids, and is a promising strategy for developing novel therapeutics [41]. In our study, GSLS suppressed the signal activation of NF-κB by inhibiting nuclear translocation of p65 induced by IL-1β in chondrocytes. Thus, GSLS has protective effects against inflammation and collagen degradation associated with increased MMPs expression. Considering its anti-inflammatory activity and protective effect against cartilage degradation in vitro, we evaluated the therapeutic potential of GSLS for OA in MIA-induced rats by measuring joint pain, levels of inflammatory cytokines and mediators, and cartilage degradation. GLM, used as a positive control, is produced as a variety of therapeutic supplements and is taken orally as a whole powder or oil extract. GLM is beneficial in relieving pain, reducing inflammation, and ameliorating other debilitating symptoms associated with inflammatory diseases such as OA without the adverse side effects of NSAIDs [42]. The pain-relieving effect of GSLS in MIA-induced rats, as measured by weight-bearing distribution, was markedly higher than that in the MIA-induced group. We observed that GSLS inhibited the production of inflammatory mediators and cytokines, including IL-1β, TNF-α, IL-6, 5-LOX, COX-2, LTB4, and PGE2, in MIA-induced rats. We demonstrated the ECM degradation effect of GSLS by MMP-1, MMP-3, and MMP-13 in SW1353 cells. Furthermore, to confirm the ECM degradation effect by gelatinase (MMP-2, MMP-9) in animal models, we tested the mRNA expression levels of MMP-2, MMP-9, ACAN, and COL-II in animal joint tissues. As shown in Figure 9, treatment with GSLS significantly reduced MMP-2 and MMP-9, while it increased mRNA expression levels of ACAN and COL-II. These results suggest that GSLS blocks gelatinase activity, thereby protecting ECM degradation in MIA-induced OA rats. Compared to GLM, GSLS has a similar effect and has demonstrated statistical significance in several biomarkers. Considering that the GLM dosage was administered at a higher concentration than that obtained by converting the animal dose to human equivalent doses based on body surface area, the GSLS extract also showed potential as an excellent therapeutic option for OA. Collectively, these results demonstrated that GSLS could ameliorate OA progression by inhibiting the expression of inflammatory factors, relieving pain, and protecting against cartilage damage in MIA-induced rats. The leaves and stems of GS were collected from the fields of Munkyeong (Chungbuk, Republic of Korea), 100 g of which was extracted with 1.5 L of 70% aqueous ethanol for 3 h under reflux, concentrated under reduced pressure, and freeze-dried. The extraction yield was 12.3%. A Waters Acquity UPLC system equipped with a quaternary pump, auto-sampler, photodiode array detector, and QDa detector with an Acquity UPLC® BEH C18 column (100 × 2.1 mm, 1.7 μm) was used for the analysis (Waters, Milford, MA, USA). Solvent A (water) and solvent B (acetonitrile) were used for gradient elution at a flow rate of 0.5 mL/min, which was carried out as follows: 0–2 min, 5–5% B; 2–5 min, 5–15% B; 5–30 min, 15–55% B; 30–35 min, 55–72% B; 35–40 min, 72–90% B; 40–42 min, 90–100% B; 42–44 min, 100–5% B; and 44–45 min, 5–5% B. The detection wavelength was set at 200 nm. The column temperature was maintained at 40 °C, and the injection volume was 2 µL. A QDa detector equipped with an electrospray ionization (ESI) source and mass spectrometer (MS) was used to obtain mass spectra. The ESI source was analyzed for both negative and positive ions. The optimized ESI source parameters were: capillary voltage 8 kV and probe temperature 600 °C. Nitrogen was used as a curtain, collision, nebulizer, and heating gas. SW1353 human chondrocytes were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA) and cultured in Dulbecco’s Modified Eagle’s Medium/Nutrient Mixture F-12 (DMEM/F12), supplemented with 10% heat-inactivated fetal bovine serum (FBS) and 1% penicillin (100 IU/mL) at 5% CO2 and 37 °C. The medium was replaced with serum-free DMEM/F12, and 10 ng/mL IL-1β (Sigma-Aldrich Chemical Co., St. Louis, MO, USA) with or without GSLS (50, 100, or 200 µg/mL) was added for an additional 24 h to stimulate the cells. GSLS was dissolved in 100% DMSO, stored at −20 °C, and diluted in PBS immediately before use to obtain a final concentration of 0.1% DMSO. DMSO (0.1%) was used as control (Con). The effects of GSLS on chondrocytes were determined using the MTT (Sigma-Aldrich Chemical Co., St. Louis, MO, USA) assay. SW1353 cells were seeded into 96-well plates (5000 cells/well) at 37 °C for 12 h and then treated with GSLS at 37 °C for 1 h before IL-1β (10 ng/mL) treatment at 37 °C for 24 h. In each well, 50 μg MTT solution was added and incubated for 4 h at 37 °C. The supernatant was removed, and the formazan crystals were dissolved in 100 µL dimethyl sulfoxide (DMSO). Absorbance was measured at 570 nm using a microplate reader (Bio-Rad, Hercules, CA, USA) to assess cell viability. Male Sprague Dawley (SD) rats (7 weeks old, 190–210 g body weight) were purchased from Orient Bio (Seongnam, Republic of Korea). After acclimation, rats were housed in individual cages and familiarized with the testing procedure. Male Sprague Dawley rats (8 weeks old) were randomly divided into four groups with seven rats in each group: (1) control group, (2) MIA group with MIA injection, (3) GSLS-treated group (200 mg/kg body weight) with MIA injection, and (4) GLM (green-lipped mussel oil, positive control drug)-treated group (100 mg/kg body weight) with MIA injection. MIA solution (3 mg/50 µL in 0.9% saline) was administered as an intra-articular knee injection in the right knee of anesthetized rats under a mixture of ketamine (25 mg/0.5 mL) and xylazine (20 mg/0.2 mL). All drugs were dissolved in 0.5% carboxymethyl cellulose (CMC)-containing saline immediately before use. The rats received 2 mL GSLS or GLM via oral gavage once daily for 21 days after MIA injection until the end of the experiment. Control and MIA group were given the same volume of 0.5% CMC. After GSLS treatment, no evidence of systemic adverse effects was observed in any study group. Changes in the hind paw weight-bearing were determined by the incapacitance tester (Bioseb Co.; Pinellas Park, FL, USA) on days 0, 7, 14, and 21 after intra-articular MIA induction. The hind paw weight-bearing distribution between the right knee joint (with the MIA injection) and the left knee joint (control side) was evaluated as an index of joint pain in the OA joint. All experiments involving animals were approved by the Institutional Animal Care and Use Committee of Daejeon University (DJUARB2022-027, Daejeon, Republic of Korea) and conducted in accordance with the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (Bethesda, MD, USA). The levels of proinflammatory cytokines and mediators (IL-1β, TNF-α, IL-6, PGE2, LTB4, 5-LOX, and COX-2), MMPs (MMP-1, MMP-3, and MMP-13), and COL-II were determined using commercial ELISA kits (MyBioSource, San Diego, CA, USA and R&D Systems, Minneapolis, MN, USA), according to the manufacturer’s protocols. The cells were lysed using Laemmli sample buffer (Bio-Rad, Hercules, CA, USA), heated at 100 °C for 5 min, and electrophoresed with 30 µg protein/lane on denaturing sodium dodecyl sulfate–polyacrylamide (SDS-PAGE) gel. Proteins were then transferred onto polyvinylidene fluoride membranes (Bio-Rad, Hercules, CA, USA). The protein-blotted membranes were probed with specific targeting primary antibodies (1:1000 dilution, Santa Cruz Biotechnologies, Santa Cruz, CA, USA) for 1 h, washed, and then incubated with horseradish peroxidase-linked secondary antibodies (1:2000 dilution). After 1 h, the membranes were washed three times, and the signals were detected with SuperSignal Chemiluminescence Reagent (cat no. 46640; Thermo Scientific, Atto Corporation, Tokyo, Japan) using an image analyzer (LAS 4000 mini, GE Healthcare Bio-Sciences, NJ, USA). The cells were stimulated with IL-1β alone or with GSLS and fixed in 4% (v/v) methanol-free formaldehyde solution (pH 7.4) for 25 min at room temperature. The cells were permeabilized in 0.3% (w/v) Triton X-100 for 15 min and then blocked in 5% (w/v) bovine serum albumin for 30 min. Subsequently, the cells were incubated with anti-NF-κB p65 (1:200 dilution, Santa Cruz Biotechnologies, Santa Cruz, CA, USA) and Texas Red-conjugated secondary antibodies (1:100 dilution). The slides were covered with mounting medium containing 4′,6-diamidino-2-phenylindole (DAPI; Vector Laboratories Inc., Burlingame, CA, USA) and visualized using a Fluoview FV10i confocal microscope (Olympus, Tokyo, Japan). Total RNA was extracted using the RNeasy Mini Kit (Qiagen Inc., Valencia, CA, USA), according to the manufacturer’s instructions. cDNA was synthesized from total RNA using an iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA) and amplified with SYBR Green Supermix on an ABI StepOnePlus™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) according to following conditions: 30 s of denaturation, followed by 40 cycles at 94 °C for 5 s and 60 °C for 35 s. The relative expression of gene-specific products was analyzed using the comparative Ct (2−ΔΔCt) method and normalized to the reference gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The sequences of primers constructed were as follows: GAPDH: F, 5′-CACCCACTCCTCCACCTTTG-3′ R, 5′-CCACCACCCTGTGCTGTAG-3′; MMP-1: F, 5′-GACAGAGATGAAGTCCGGTTT-3′ R, 5′-GCCAAAGGAGCTGTAGATGTC-3′; MMP-3: F, 5′-ATTCCATGGAGCCAGGCTTTC-3′ R, 5′-CATTTGGGTCAAACTCCAACTGT-3′; MMP-13: F, 5′-AGCCACTTTATGCTTCCTGA-3′ R, 5′-TGGCATCAAGGGATAAGGAAG-3′; ACAN: F, 5′-GAAGTGGCGTCCAQAAACCAA-3′ R, 5′-CGTTCCATTCACCCCTCTCA-3′; COL-II: F, 5′-GCAACAGCAGGTTCACGTACA-3′ R, 5′-TCGGTACTCGATGATGGTCTTG-3′. All data were analyzed using Prism 7.0 software (GraphPad Software, Boston, MA, USA). Differences were considered statistically significant at p < 0.05. Dunnett’s test was used for multiple comparisons among different groups. Data are represented as the mean ± standard error of the mean (SEM). One-way analysis of variance was used to detect significant differences between the control and treatment groups. This study demonstrated that GSLS can inhibit chondrocyte inflammation and have a protective effect on MIA-induced OA. GSLS inhibited chondrocyte inflammation and ameliorated cartilage degeneration by suppressing the NF-κB signal activation in SW1353 cells. In an MIA-induced OA rat model, GSLS administration relieved the pain and reversed cartilage degeneration in joints by inhibiting inflammatory responses. Overall, our findings suggested the potential of GSLS as a therapeutic supplement for relieving inflammation in OA.

PMC10002961

Alessandra Scagliola,Annarita Miluzio,Stefano Biffo

Translational Control of Metabolism and Cell Cycle Progression in Hepatocellular Carcinoma

03-03-2023

eIF4E,eIF6,Non-Alcoholic fatty liver disease (NAFLD),Fatty Acid Synthesis (FAS),Fatty Acid Oxidation (FAO)

The liver is a metabolic hub characterized by high levels of protein synthesis. Eukaryotic initiation factors, eIFs, control the first phase of translation, initiation. Initiation factors are essential for tumor progression and, since they regulate the translation of specific mRNAs downstream of oncogenic signaling cascades, may be druggable. In this review, we address the issue of whether the massive translational machinery of liver cells contributes to liver pathology and to the progression of hepatocellular carcinoma (HCC); it represents a valuable biomarker and druggable target. First, we observe that the common markers of HCC cells, such as phosphorylated ribosomal protein S6, belong to the ribosomal and translational apparatus. This fact is in agreement with observations that demonstrate a huge amplification of the ribosomal machinery during the progression to HCC. Some translation factors, such as eIF4E and eIF6, are then harnessed by oncogenic signaling. In particular, the action of eIF4E and eIF6 is particularly important in HCC when driven by fatty liver pathologies. Indeed, both eIF4E and eIF6 amplify at the translational level the production and accumulation of fatty acids. As it is evident that abnormal levels of these factors drive cancer, we discuss their therapeutic value.

Translational Control of Metabolism and Cell Cycle Progression in Hepatocellular Carcinoma The liver is a metabolic hub characterized by high levels of protein synthesis. Eukaryotic initiation factors, eIFs, control the first phase of translation, initiation. Initiation factors are essential for tumor progression and, since they regulate the translation of specific mRNAs downstream of oncogenic signaling cascades, may be druggable. In this review, we address the issue of whether the massive translational machinery of liver cells contributes to liver pathology and to the progression of hepatocellular carcinoma (HCC); it represents a valuable biomarker and druggable target. First, we observe that the common markers of HCC cells, such as phosphorylated ribosomal protein S6, belong to the ribosomal and translational apparatus. This fact is in agreement with observations that demonstrate a huge amplification of the ribosomal machinery during the progression to HCC. Some translation factors, such as eIF4E and eIF6, are then harnessed by oncogenic signaling. In particular, the action of eIF4E and eIF6 is particularly important in HCC when driven by fatty liver pathologies. Indeed, both eIF4E and eIF6 amplify at the translational level the production and accumulation of fatty acids. As it is evident that abnormal levels of these factors drive cancer, we discuss their therapeutic value. The liver is at the crossroads of two remarkable observations: on one side, it is the mammalian organ with the highest rate of protein synthesis and regulates multiple metabolic processes; on the other, it is the organ with the highest regenerative capability in adults. However, the liver is also the target of hepatocellular carcinoma (HCC), the 6th most common cancer in terms of frequency and the 4th in terms of mortality [1]. What is the relationship between protein synthesis, metabolism, and hepatocellular carcinoma? Clearly, this high capability of protein production is necessary during regeneration, to sustain the cell growth necessary for the G1/S phase transition [2], and it can be harnessed by oncogenic mutations. However, we notice that the mechanistic correlation between protein synthesis and metabolism has not been adequately addressed. Lipid synthesis, nucleotide synthesis and protein synthesis are all anabolic processes and, as such, are addressed in biochemistry or nutritional textbooks. In addition, protein synthesis is characterized by the specifics of the process of translation; consequently, it not only generates mass but also specific information [3]. Thus, the translation of specific mRNAs can result in dramatic biological effects. In this review, we will discuss how translational control exacerbates liver disease, and identify potential therapeutic targets. The liver is necessary for life and end-stage liver disease is the third most common cause of premature death in Western Europe [4]. Liver function comprises several aspects that make this organ an essential metabolic hub. In short, the normal liver weighs approximately 2.5% of the total body weight but receives 25% of the cardiac output. Accordingly, the liver is the main producer of proteins that are massively secreted in the blood, such as albumin. The liver’s contribution to the blood includes the regulated secretion of hormones such as hepcidin, which is necessary for iron metabolism [5], and thrombopoietin [6], in conjunction with the kidneys, which stimulates platelet generation, as well as others. The liver is connected to the intestine by the common bile duct, where liver-produced digestive enzymes are secreted and brought to the duodenum [7]. The massive production of blood proteins and the digestive activity of the liver imply the synthesis of secreted proteins. Accordingly, liver cells have a massive rough endoplasmic reticulum, used for the synthesis of secreted proteins, which is dynamically assembled according to the body’s needs [8]. One additional feature of liver circulation is the portal system, which directly supplies the blood collected in the intestine to the liver via the portal vein. The portal venous blood contains all the products of digestion that have been absorbed from the gastrointestinal tract. In the liver, a specialized vascular endothelium, which is highly fenestrated, allows the efficient exchange of molecules between the main cellular type of the liver, the hepatocyte, and the portal blood. Absorbed molecules include metabolic intermediates, such as glucose and lipids, and orally absorbed drugs. These molecules are processed in the liver before either being released back into the hepatic veins or stored in the liver for later use. The direct connection to the blood collected in the intestine has implications for the protein apparatus, although in this case, it is less apparent. The intense metabolic activity of the liver, which is associated with preferential exposure to the molecules that are absorbed in the intestine, has posed a great challenge to the evolution of this organ. This exposure to a variety of absorbed molecules and the enormous blood flux also risks the threat of a number of potentially cytotoxic compounds such as alcohol or viruses. As a necessary evolutionary solution, the liver is the only mammalian organ able to massively regenerate following a cytotoxic insult [9]. The regenerative property of the liver has been known since ancient times and is reflected in the myth of Prometheus. Hepatocytes die following chemical or viral damage, but the surviving cells re-enter the cell cycle and can regenerate the entire liver mass in a few days. The amazing regenerative capacity of the liver is evident in rat and mouse models, where two-thirds of the mass can be surgically removed and will grow back in one week [10]. This demand for growth and cell cycle progression is obviously accompanied by the need for a powerful capability to produce proteins. Feeding increases liver translation by up to 50% [11,12]. We define the general increase of all proteins following stimulation as an increase in global translation and define the mRNA-specific increase as an increase in specific translation. Given that, in normal conditions, the postprandial liver does not regenerate, what are the synthesized proteins? Amino acids induce both global and specific translations [13]. Ribo-seq is one of several technologies allowing analysis at the codon level of translation [14]. In the context of normal liver biology, Ribo-seq has shown that translation elongation rates in the liver are the highest among organs [15]. Translation efficiencies vary across diurnal time and feeding regimen, whereas codon dwell times are highly stable [16]. A study has demonstrated that a subset of genes harboring 5′-terminal oligo pyrimidine (TOP) tracts or translation initiators of short 5′-UTR (TISU) elements encoding proteins involved in translation and mitochondrial activity, respectively, exhibit rhythmic translation that is mainly regulated by feeding [17]. Our lab has shown that specific mRNA translation is stimulated by postprandial insulin [12]. In conclusion, at least three distinct biological activities of the liver require an intense protein synthesis capability: (a) the production of plasma proteins, (b) the regenerative capability, and (c) postprandial biosynthetic activity. All these facts make the liver the organ with the highest rate of protein synthesis of all the body’s organs [18]. The crucial question is whether the high levels of translational machinery in liver cells have an impact on the evolution of diseases, in particular that of liver cancer. We will not discuss the effect of branched amino acids as this has recently been addressed elsewhere [19]. We will focus on the basics of the translational machinery in cancer, and the particular features of liver cancer that are relevant to translational regulation. Several reviews of high quality have described in detail the impact of various aspects of translation on cancer development and tumor progression [20,21,22,23]. We will briefly summarize (a) some mechanisms of translational control, (b) nodes where translational mechanisms crosstalk with oncogenic signatures, (c) the impact of ribosome biogenesis, and (d) specific HCC mutations that act on the translational machinery. In recent years, studies have promoted the concept that translational control is a major, if not the most important, regulator of gene expression [24]. According to the central dogma of molecular biology, translation is the second step of gene expression and consists of the decoding of an mRNA into a protein [25]. For decades, translation has been considered an energy-consuming and totally passive step that faithfully converted each mRNA into a protein. The progressive accumulation of evidence, via the combination of “omics” and individual studies, has demonstrated that the relationship between mRNA and protein levels is, in reality, rather poor [26]. Translation can be divided into four phases, initiation, elongation, termination, and recycling. For a given mRNA, initiation is the rate-limiting phase [21]. The discrepancy between mRNA levels and protein levels is, therefore, due to the action of initiation factors. Initiation is controlled by eukaryotic initiation factors (eIFs): each eIF performs a mechanistic step, under the control of signaling pathways. A crucial concept is that untranslated region sequences (UTRs) on the mRNA regulate the sensitivity to eIF activity. Notably, mRNAs can have very long UTRs and even transcript isoforms, with different UTRs that confer differential translational activity [27,28]. In addition, eIF activity is controlled by signaling pathways [29]. It is, therefore, the interplay between eIFs, mRNA sequences, and signaling pathways that generates the specificity and flexibility of translational control. In the first step, the ribosomal 40S subunit binds the ternary complex formed by tRNAiMet, GTP, eIF2, to form 43S (Figure 1). This step is limited by four independent eIF2α kinases activated by several stresses [21]. The formation of 43S can be also stimulated by oncogenic signaling, as exemplified by PI3K-mTOR [30]. Then, 43S binds mRNA to form the 48S complex. The formation of 43S is controlled, mainly, by eIF4F assembly under the PI3K/mTORc1 and ERK-Mnk(s) signaling cascades [22]. Lastly, 48S binds a free 60S subunit to form 80S. The availability of 60S is controlled by eIF6 [31]. Notably, the steps so far described mainly refer to canonical cap-dependent translation that accounts for most of the translation (Figure 1). However, cap-independent [22] or non-canonical cap-dependent mechanisms have recently been discovered [32]. eIF3 is a multiprotein complex that exists in several subcomplexes and participates in several steps of translation [33]. eIF3d acts as a non-canonical 5′ cap-binding protein that is activated in response to metabolic stress in human cells [32]. m(6)A RNA modification in the 5′-UTR stimulates cap-independent translation by the recruitment of the initiation factor, eIF3 [34]. eIF3a and -b facilitate the assembly of the translation-initiation complex and promote the translation of over 4000 mRNA transcripts [35], exploiting m(6)A modification of the mRNA. Other characterized eIFs are eIF1, eIF1A, eIF2B complex, eIF5, and eIF5B [36]. eIF1 and eIF1A have a role in the selection of start codons [37]. Notably, in the context of start codon selection, although the AUG codon in the Kozak context is considered the classical start codon [38], relatively high efficiency can also be given by cognate start codons [39], thus greatly increasing alternative products and regulation. eIF2B acts as a regulator of eIF2 activity [40,41]. eIF5, with the assistance of eIF5B, catalyzes the hydrolysis of GTP bound to the 40S ribosomal initiation complex, with the subsequent joining of a 60S ribosomal subunit resulting in the release of eIF2 and the guanine nucleotide [42]. In short, the specific activity of translation factors accounts for specific gene expression, and the number of molecular mechanisms so far identified is probably only a small part of all the possible ones. As we will see, some of these initiation factors play a dominant role in tumorigenesis and cancer progression, both inside and outside of the liver. In human cancers, the upregulation of several members of the translational machinery is associated with reduced survival [43]. The simple explanation for all these findings is that several oncogenic mRNAs (e.g., cyclins [44], proangiogenic factors [45], the regulators of metabolism [46], and immune modulators [47]) are regulated at the level of translation [22]. Specific genetic evidence for the essential role of initiation factors in cancer progression has been obtained for some of them. The gene dosage reduction of eIF6 greatly impairs oncogene-induced mortality [48] and the translation of 5′UTR with G/C-rich regions and uORFs [12]. Several elements of the eIF4F complex are essential for malignancy [49]. eIF4F consists of eIF4A1, eIF4E, and eIF4G. eIF4E, as part of the eIF4F complex, promotes the recruitment of the 40S ribosomal subunit by interacting with the 5′ terminus of the mRNA. eIF4E levels are rate-limiting for cancer development, as shown by the fact that in mice, a reduced dosage of eIF4E, while compatible with normal development and global protein synthesis, significantly impeded cellular transformation through its action on specific 5′UTRs [50]. The 40S-eIF4F complex scans the 5′-untranslated region (UTR) for the AUG initiation codon. Notably, ribosomes have a weak capacity to unwind mRNA secondary structures, while eIF4A1 has the ability to unwind stable secondary structures in the 5′-UTR during scanning. Given the fact that several structured 5′UTRs encode for oncogenic mRNAs, eIF4A1 is essential for tumorigenesis [51]. The 4E-BPs are negative regulators of eIF4E (Figure 1) that are inactivated by mTORc1 phosphorylation; the knock-in of 4E-BP phosphomutants reduces the tumor burden [52]. Consistently, pathways that converge on translation are mutated in cancer cells. The Myc oncogene acts as a global activator of the entire ribosomal machinery [53]. The PI3K-mTOR and the RAS-ERK are nutrient-sensing pathways almost invariantly activated in cancer that play prominent roles in translational control [21,22,29]. The complexity with which signaling pathways converge on the translational machinery has been described in detail in an earlier paper [29]. In short, oncogenic mutations must take control of specific translation factors in order to be effective. eIF6 is a specific translation factor that is also essential for ribosome biogenesis [54]. Ribosomes are assembled in the nucleolus through a complicated series of events that include rRNA synthesis and the nuclear transport of ribosomal proteins, which are then assembled on the rRNA with the assistance of more than 100 trans-acting factors in ribosome biogenesis. Details of this process and its relevance to cancer have been recently reviewed [55,56]. In short, several reports estimate that ribosomes are rate-limiting for cellular growth. The alterations in nucleolar morphology observed in cancer cells directly reflect the greatly increased ribosome production. Increased ribosome production in cancer cells is caused by the dysregulation of the three RNA polymerases (Pol) by molecular mechanisms, involving major oncogenic and tumor suppressive pathways, such as c-Myc [57,58], mTOR [59], p53 [58], pRb [56], and PTEN [60]. Proof-of-concept that targeted therapies that selectively inhibit ribosomal subunit biogenesis are efficient at killing cancer cells has been obtained; these observations are discussed in detail in Ref. [61]. In addition to the “quantitative” hypothesis, the qualitative hypothesis predicts that tissue-specific alterations in the number of ribosomal proteins may lead to the heterogeneity of ribosomes and oncogenic translation [62]. As we will see, alterations in ribosomal proteins are a prominent feature of liver cancer. One important issue is the intersection of the translational machinery with the oncogenic mutations found in the liver. Hepatocellular carcinoma is considered heterogenous; hence, the correlation between the translational machinery and the mutational burden can be variable among patients. However, a few facts can be stated without uncertainty. Most liver cancers occur in a situation where there is a chronic disease, characterized by inflammation and local regeneration [1]. Ribosomal proteins, such as rpS6, are mandatory for liver regeneration [63]; thus, high levels of the ribosomal machinery are essential for the normal reaction of the liver to acute insults. Tumors with a high proliferative index are, perhaps not surprisingly, characterized by the presence of phosphorylated rpS6 as a marker, thereby activating the PI3K-mTORc1 pathway (Figure 1). The relationship between mTOR, eIFs, and HCC has recently been described in detail [64]. The role in the translation of the specific phosphorylation of rpS6 by the mTOR cascade is often debated. Years of research have clearly established that rpS6 is the most prominent phosphorylated substrate after mTORC1 stimulation, but the molecular consequences are far from clear [65]. However, in the liver, rPS6 phosphorylation may contribute to the specific translation of long ORFs [66]. Following this line, hepatocellular carcinomas with a high proliferation rate have a mutation of either RPS6KA3 or TSC1/TSC2. RPSKA3 is a member of the p90 family of ribosomal protein S6 kinases, is a MAP kinase-activated protein kinase 1b, and has, as its major substrates, rPS6 and eIF4B, following stimulation of the RAS-ERK pathway [67]. TSC1/2 mutations constitutively activate the mTORC1 pathway, thus leading to the direct phosphorylation of 4EBPs, and, indirectly, to rPS6 phosphorylation through the p70 family of RSKs. In conclusion, it is evident that all proliferative HCCs have mutations that massively control the eIF4F axis and ribosomal phosphorylation. As a general rule, all mutations in the growth factor cascade converge on the translational machinery. A common mutation in HCC occurs at the level of the Wnt/β−catenin pathway. Here, an interesting mutation-translation crosstalk involving FGF19 is recurrently amplified in HCC and acts upstream of the Wnt/β−catenin pathway. A large part of FGF19-mediated activation occurs translationally. Some WNT pathway components have long and structured 5′ UTRs, with a high frequency of polypurine sequences folding into either stable G-quadruplexes or stable secondary structures. The FGF-mediated increase in the translation of WNT pathway components is driven by the RNA helicase and a component of the eIF4F complex, eIF4A [68]. Last, but not least, the crosstalk with the mutational landscape includes c-MYC. In human HCC, c-Myc is frequently overexpressed, and high levels of c-Myc are associated with a poor prognosis [69]. In this context, it is very well known that Myc acts as a powerful transcriptional stimulator of multiple members of the ribosomal machinery [70]. An in vivo mouse model of liver cancer shows that MYC overexpression synergizes with mutated KRASG12D to induce an aggressive liver tumor, leading to metastasis formation. Genome-wide ribosomal footprinting revealed alterations in the translation of mRNAs, including programmed death-ligand 1 (PD-L1). Further analysis revealed that PD-L1 translation is repressed in KRASG12D tumors by functional, non-canonical upstream open reading frames (uORFs) in its 5′ untranslated region [71]. We will start our survey with the essential machinery of the translational apparatus, ribosomes. In general, and as expected, rRNA and ribosome synthesis are greatly induced during both regeneration and HCC onset [72]. Ribosomes are constituted by ribosomal proteins and rRNA, which are assembled in the nucleolus. Nucleolar size can be assessed via argyrophilic nucleolar organizer staining with AgNOR. The number of AgNOR-stained nucleoli is an indicator of the grade of malignancy and a predictor of the prognosis of patients with HCC without portal vein involvement [73]. Specific factors necessary for ribosome biogenesis and ribosomal proteins may play an additional role in HCC development and malignancy. Treacle ribosome biogenesis factor 1 (TCOF1) is a nucleolar factor that regulates ribosomal DNA (rDNA) transcription in the nucleolus and is mutated in Treacher Collins–Franceschetti syndrome (TCS), a congenital disorder affecting craniofacial development. TCOF1 promotes tumorigenesis and the progression of HCC [74]. RACK1 is a structural protein of 40S ribosomal subunits, originally described as a receptor for activated PKC that is necessary for specific translation [75,76] and dendritic arborization [77]. RACK1 promotes chemoresistance in HCC [78] and the self-renewal of cancer stem cells [79]. One important question is whether the upregulation of ribosomal proteins increases cancer malignancy because it simply augments the growth capability of cells, or whether it changes the specificity of translation. This hotly debated issue has received considerable attention; in general, evidence for the existence of subtle variations in ribosome structure that may affect the translation of specific mRNAs has been obtained in several models and is extensively discussed in Ref. [62]. Recently, the 60S ribosomal protein RPL23 has been shown to be a tumor metastasis driver in HCC via its capability of regulating the mRNA stability and translation of MMP9 [80]. An interesting study in HepG2 cells has identified RPL28 as the key gene involved in drug resistance to Sorafenib [81]. In another classical study, rPL36a was found to be overexpressed in HCC and led to enhanced colony formation [82]. Overall, we can conclude that a global upregulation of the ribosomal machinery is a conditio sine qua non for HCC development. In this respect, it is not surprising that the loss of or functional changes in the two major tumor suppressor proteins, pRB and p53, cause an up-regulation of ribosome biogenesis [83]. This being said, we should also consider that ribosomal proteins are highly abundant, and even if their half-life in cells is heavily regulated by their specific association with ribosomes, i.e., several ribosomal proteins are unstable if not bound to ribosomes, the possibility that ribosomal proteins exert ribosome independent functions cannot be discarded. Ribosomal protein rPL11 interacts with and inhibits HDM2 tumor-suppressor function, thus leading to the stabilization and activation of p53 [84]. This observation is the tip of the iceberg of a number of findings indicating that free ribosomal proteins may impair cancer progression [56]. In conclusion, HCC development and progression strongly depend on an increase in ribosomal capability and the generation of ribosomes that increase the translation of oncogenic mRNAs. However, some free ribosomal proteins are part of tumor suppression circuits that may have evolved under the pressure to avoid the excessive synthesis of ribosomes. The role of some translation factors in the progression and malignancy of HCC is, at first sight, puzzling. As described in the previous paragraphs, most initiation factors perform specific mechanistic steps downstream of oncogenic activation. The classic eIF4F complex is constituted by eIF4A, eIF4G, and eIF4E. The general involvement of eIF4F in the progression of cancer is well established and is part of a complex research area that aims at its pharmacological targeting [20,49,85]. Direct analysis in mice during hepatocarcinogenesis confirmed, as expected, the oncogenic activation of the eIF4F complex. AKT and N-Ras proto-oncogenes in mice require the activation of the 4EBP1/eIF4E and p70S6K/RPS6 axes [86]. However, the link in humans between the expression of eIF4F members and HCC development is not equally impressive. In general, a comparison between the levels of eIF4F members between the normal liver and neoplastic HCC tissue does not lead to evident overexpression/overphosphorylation. This may be due to the relatively high levels of initiation factors already present in the normal tissue. It should be noted that several translation factors have been isolated from the normal mammalian liver that constituted a rich source, as described in Refs. [87,88]. In addition, as discussed later, different types of HCC cancer may present interesting variations [89]. Thus, most translation factors are certainly altered in HCC: first, the degree of overexpression is limited; second, their impact on HCC development must be individually addressed by targeted genetic analysis. Database analysis shows that high eIF6 mRNA levels are dramatically associated with HCC lethality [90]. Indeed, genetic and expression studies show that eIF6 is fundamental for the progression of Non-Alcoholic Fatty Liver Disease (NAFLD) to HCC [91] and the progression of HCC itself [92,93]. We conclude that abnormal translation may be an early event of HCC progression and contributes to its malignancy. Whatever the status of translation factors in HCC, reliable evidence shows that translation is greatly altered in HCC. Ribo-seq analysis has contributed to our knowledge of aberrant translation. Physiologically controlled translation is disrupted in obesity [94] and in hepatocellular carcinoma [95]. In human hepatocellular carcinoma, direct analysis of translated mRNAs reveals that the consensus top 100 translationally up-regulated genes show significant enrichment in the biological processes related to extracellular matrix (ECM) organization and collagen catabolism [95]. These data suggest that abnormal translation is an early step in the oncogenic program. In general, molecular signatures that mark the different stages of liver disease progression can be identified using transcriptomics studies [96]. These studies include microarray and RNA-Seq analyses, which have defined the transcriptional profiles of liver biopsies, ranging from human obesity to NAFLD patients with different stages of severity [97,98,99,100]. Recently, a broad and detailed RNA-Seq study in patient liver tissue from across the full spectrum of NAFLD and its evolution to HCC has been reported [101]. Interestingly, one of the stronger pathways positively regulated during the evolution from NAFLD to HCC is the KRAS signaling pathway, whereas one that is downregulated is the mTOR pathway. This situation is highly similar to the one we observed at the translational level, characterized by an increase in eIF6, downstream of RAS/PKC, and a decrease in phosphorylated rpS6 S240/244, downstream of mTOR [91]. Indeed, at the transcriptional level, we confirmed that selected eIFs decrease in NAFLD patients compared to obese patients (eIF1, eIF4b, eIF3a), which can possibly be explained by a progressive decrease in the hepatic global translational rate during the worsening of hepatic steatosis to NAFLD [91]. In short, during NAFLD’s evolution to HCC, we observed a marked reduction in translational capability with the notable exception of eIF6 levels, which increase in order to sustain lipid metabolism at the translational level [12]. Once the transition from NAFLD to HCC is completed, a general overexpression of eIFs is found in HCC conditions. Many studies have demonstrated an upregulation of eIFs in HCC samples, both at mRNA and protein levels: eIF4E and EIF4G2 [102], eIF4A3 and eIF5B in HCC cell lines [103,104], eIF3S3 [104], and eIF3I [105]. High EIF4G2 expression indicates a poor prognosis [106]. In general, the mechanism by which the expression of single eIFs increases during tumorigenesis has not been fully addressed. This being said, as described in detail before, several oncogenes act on the translational machinery. In particular, the Myc oncogene plays a major role in the transcriptional upregulation of the translational machinery [53]. The major problem of bulk RNA-Seq studies in the contest of liver disease progression is that RNA is derived from mixed cell populations; therefore, its levels are heavily biased toward hepatocytes, which constitute most of the mass. In other words, it is possible that the activity of translation factors considerably changes in specific cell types involved in disease, but the event is missed in the global cell population. In the last decade, single-cell RNA sequencing (scRNA-seq) has been widely used to define cell-type specific molecular profiles, identifying previously unknown cell sub-populations in normal and diseased livers [107]. One seminal study has investigated hepatic injury in the context of human cirrhosis. Using this available single-cell RNA-seq data set, we found that eIF6 mRNA expression levels are higher in two cell lineages derived from human cirrhotic livers, cholangiocytes, and hepatocytes [108]. A similar approach could be used to identify eIF expression in progressive stages of liver disease in different hepatic cell types [109,110], which is certainly an area that deserves further attention. As a note of caution, however, we should remember that mRNA expression does not predict protein levels. HCC can have viral and non-viral predisposing factors: alcohol abuse, non-alcoholic fatty liver disease (NAFLD), and viral hepatitis are the main risk factors for HCC development. The viral causes of HCC principally arise from the Hepatitis B virus (HBV) and Hepatitis C virus (HCV). Several notable reviews fully discuss the etiological factors of HCC and the specific features of viral hepatitis-driven HCC [1]. In the context of hepatitis driven by HCC, the host translational machinery is hijacked by the presence in the HCV of a very efficient IRES or internal ribosomal entry site, known as HCV IRES. HCV IRES is a highly structured RNA that mediates cap-independent translation. It is essential for HCV replication, requires eIF3, and has been widely studied since the late 1990s [111,112]. The use of IRES elements circumvents the need for some eukaryotic initiation factors (eIFs) [113]; indeed, the initiation factors eIF2, eIF2A, eIF2D, eIF4A, and eIF4G are not involved in translation that is driven by HCV IRES [114]. In addition to mTOR, eIF3, eIF4, and eIF5 can serve as biomarkers for non- and virus-related HCC [115]. The elevated expression of eIF3H is consistently associated with proliferation, invasion, and tumorigenicity in human hepatocellular carcinoma [116]. A detailed study explored the expression of eIF subunits in 235 cases of virus-related human HCC. Phosphorylated (p)-eIF2α, eIF2α, eIF3B, eIF3D, eIF3J, p-eIF4B, eIF4G, and eIF6 were upregulated in HCV-associated HCC. eIF2α, p-eIF4B, eIF5, and various eIF3 subunits were significantly increased in chronic hepatitis B (HBV)-associated HCC. HCC without a viral background displayed a significant increase for the eIF subunits, p-2α, 3C, 3I, 4E, and 4G [89]. Overall, the data support a model wherein during tumor evolution, the host translational machinery may be inhibited by the stress response and/or progressively adapt to viral infection. The evidence that patients with HCV-induced cirrhosis continue to have a persistent risk of also developing HCC after HCV eradication underlines the fact that the strongest risk factor for HCC is cirrhosis, regardless of cancer etiology [117]. Unlike viral hepatitis, NAFLD has rapidly become the leading etiology of HCC incidence; its contribution to HCC onset is expected to grow in the next few years owing to the increasing rate of obesity and metabolic syndrome in the West [118]. NAFLD is caused by a build-up of fat in the liver, ranging from the excessive cytoplasmic retention of triglyceride in isolated hepatocytes to steatosis (accumulation of lipid droplets in more than 5% of hepatocytes), without alcohol as a cause. We can summarize NAFLD progression to hepatic failure in four stages: (i) liver fat accumulation; (ii) early NASH (Non-Alcoholic Steatohepatosis), characterized by steatosis, ballooned hepatocytes, and lobular inflammation; (iii) the onset of fibrosis, caused by chronic liver inflammation and injury; (iv) liver cirrhosis, a condition involving a permanently damaged liver in which healthy liver tissue is replaced with scar tissue. Approximately 5–12% of individuals progress over time, from NASH to fibrosis, and thence to hepatic failure, especially when associated with metabolic syndrome or diabetes mellitus. While NAFLD and NASH are considered dynamic diseases able to either reverse or progress, the onset of hepatic fibrosis reflects an irreversible process and is the strongest predictive factor for HCC onset and liver-related mortality [119]. Increasing evidence suggests that NAFLD might be a risk factor for HCC, independently of cirrhosis [120]. Multiple parallel hits that comprise metabolic dysregulations and other hepatic insults have been proposed for the pathogenesis of NAFLD [119]. However, the molecular mechanisms leading to disease progression and liver cancer are not completely clarified. It is known that in the early steatotic phase of NAFLD, the Fatty Acids (FA) that accumulate in hepatic cells are stored in lipid droplets. However, chronic lipid over-accumulation in the hepatocytes results in an excessive production of FFAs (Free Fatty Acids), which causes cellular metabolic reprogramming and lipotoxicity. The excessive accumulation of these fatty acids increases β-oxidation and ROS production, impairing mitochondrial function and causing oxidative stress [121]. ER stress, autophagy dysregulation, and metabolic and mitochondrial dysfunction cause hepatocyte damage, cell death, and chronic inflammatory hepatic reaction [122]. During hepatic chronic damage, hepatic stellate cells undergo cellular activation, starting to synthesize the extracellular matrix components that promote fibrosis, which are mostly collagen and growth factors. The consequent alteration of the hepatic architecture due to fibrotic niche and hepatic regenerating nodules leads to the establishment of cirrhosis and to permanent liver damage [123]. In addition, premalignant hepatocytes secrete chemokines that interfere with immune surveillance and impair immune-mediated tumor suppression. Thus, besides fibrosis, the impairment of tumor surveillance contributes substantially to cancer onset in HCC, but exactly how an inflammatory microenvironment, altered immune function, and continued liver regeneration contribute to genetic instability and cancer is still poorly understood, rendering specific features of NASH-derived HCC somewhat unclear [124]. In the last few years, original studies have started to clarify the role of translational regulation in immune cells and in tumor-infiltrating immune cells [47,125,126], implying that translation factors could be targeted for novel immunotherapeutic approaches. Importantly, it has been demonstrated that the translational regulation of immune regulators facilitates tumor cell evasion from the immune response to promote HCC progression. In particular, MYC activates PD-L1 translation in response to tumor environment changes, allowing for immune evasion, HCC progression, and metastasis formation [71]. Studies have provided proof-of-concept that a translation inhibitor that reduces eIF4E phosphorylation impairs the aggressiveness of liver cancer in mice, potentially enhancing the anti-tumor immune response [71]. In conclusion, translation may control the local activity of immune cells in both the early and late phases of liver disease. A remarkable observation is the detection of the crosstalk between translation, lipid metabolism, and HCC progression (Figure 2). Translation and cellular metabolism are closely connected: changes in the translation of specific mRNAs involved in glycolytic, fatty acids and nucleotide synthesis pathways support the cells’ ability to rapidly store energy when there is a burst of growth factors and nutrients and to fuel tumorigenesis [127,128]. Protein synthesis is stimulated by nutrient availability [129]. This biological perspective implies that translation is not a cellular passive mechanism but that translational control of metabolic processes and energy storage could have a role in the onset and evolution of metabolic dysfunction in NAFLD, and, consequently, that specific translation factors could become new therapeutic targets in metabolic disorders. eIF4E dosage is important for the translation of the mRNAs involved in cellular transformation and metabolic fluxes [50]. In response to lipid overload, proteins involved in fat deposition are altered in eIF4E-deficient mice. This is due to the fact that distinct mRNAs involved in lipid metabolic processing and storage are enhanced at the translation level by eIF4E. eIF4E inhibition results in increased fatty acid oxidation, which enhances energy expenditure. The additional inhibition of eIF4E phosphorylation, both genetically and by eFT508, a clinical compound, restrains weight gain following the intake of a high-fat diet [130]. These data favor a mechanism by which hyperactivation of the translational machinery increases lipid-induced damage and the progression to HCC. Importantly, eFT508 treatment is reported to reduce tumor growth in multiple models [131]. eIF6 has a dual function and is necessary for both ribosome biogenesis and translation in the cytoplasm [54]. eIF6 activity is rate-limiting for insulin and growth factor-mediated protein synthesis [12,132]. In mice, eIF6 haploinsufficiency causes less postprandial liver translation, associated with a reduction in blood cholesterol and triglyceride levels, and a deficit in fat deposition in white adipose tissue and liver. Mechanistically, eIF6 activity potentiates the translational reinforcement of de novo lipogenesis, regulating the translational efficiency of mRNAs encoding for lipogenic and adipogenic transcription factors that contain an uORF in their 5′UTR, such as C/EBPβ, C/EBPδ, and ATF4 [12]. This model implies feed-forward anabolic transcriptional reshaping, driven by translation (Figure 2). Analyses of human study databases showed that eIF6 levels increase in NAFLD progression, unlike structural proteins of the small and large ribosomal subunits, while eIF1, eIF4B and eIF3A levels decrease. Genetic eIF6 depletion reduces NAFLD to NASH evolution in mice, impacting obesity, steatosis, and fibrosis progression, and restoring insulin sensitivity. Data-mining analysis showed that eIF6 mRNA levels are dramatically associated with HCC progression and lethality in humans and that eIF6 could be a potential diagnostic and prognostic biomarker for HCC patients [93]. In the context of liver cancer, eIF6 genetic reduction affects the incidence and size of surface HCC nodules in mouse models of NAFLD/NASH rapid progression into HCC and blocks the in vitro growth of HCC spheroids. eIF6 depletion reduces fibrotic areas, proliferating cells and liver tumor markers. Thus, the targeting of eIF6-driven translation hinders NAFLD-HCC progression, interfering with FAS and lipid accumulation and preserving mitochondrial bioenergetic activity and FAO [91]. In conclusion, the increased translation activity of eIF4E and eIF6 generates a specific increase in lipid synthesis and a reduction in lipid oxidation. Other initiation factors seem essential in the progression of NAFLD. eIF5A acts in multiple phases of the translation process. eIFA is modified by hypusine, a natural amino acid derived from the polyamine spermidine and occurring only in eIF5A [133]. In a recent study, it has been demonstrated that exogenous fatty acids administration decreases hypusination and global eIF5A levels. Reduction of eIF5A hypusination impairs the protein synthesis rate and mitochondrial function. Co-treatment with spermidine, a substrate for eIF5A hypusination, reverts the phenotype. Treatment with spermidine also slows down hepatosteatosis and liver inflammation, damage, and fibrosis in a dietary model of NASH, partially preserving the mitochondrial components. Finally, Zhou and colleagues provided evidence that eIF5A hypusination could be reduced in NASH patients and in mice [134]. The connection between eIF5A and HCC has been well-known for some time, wherein aggressive HCCs are characterized by increased eIF5A activity [135]. The fact that eIF5A activity improves the NASH score before tumor onset and worsens the prognosis after HCC onset is not surprising because it depends on the cellular context, highly proliferative in HCC, versus requiring fatty acid oxidation in preventing NAFLD evolution. In this context, we conclude: (1) that the activity of initiation factors is essential, both for NAFLD evolution to HCC and for HCC progression, marking an evident difference between HCCs driven by viral infection and HCCs driven by lipid accumulation, and (2) eIF6 is the only translation factor consistently upregulated through the transition from NAFLD to HCC, and then, HCC progression. Since it is evident that translation and the ribosome factor exert a pivotal role in the progression of HCC, can they become therapeutic targets? In general terms, the main factor against the targeting of translation factors is that they are also essential to normal physiological processes. In short, potential limits to the pharmacological targeting of initiation factors include non-specific targeting since many initiation factors are ubiquitously expressed and could potentially affect healthy cells as well. Unintended side effects that could be harmful to the patient can, therefore, arise. Other potential problems are the development of resistance and limited efficacy. This is partly due to the complex nature of mRNA translation and the redundancy of the initiation factors, which makes it difficult to develop drugs that target this process effectively. It should be noted that these limits are common, to a different extent, to multiple strategies. However, we have plenty of evidence that some translational mechanisms are specifically amplified in HCC and play a role in the evolution of the disease from NAFLD to HCC. In general, the targeting of translation factors can either hit the signaling pathways upstream of translation factors or their mechanistic action. The therapeutic inhibition of the translational machinery is a common and well-known effect of tyrosine kinase inhibitors. The tyrosine kinase inhibitor, sorafenib, was the main systemic drug approved for anti-HCC treatment until the advent of immune checkpoint inhibitors (ICI). Currently, in patients with advanced hepatocellular carcinoma, the combination of an immune checkpoint inhibitor, atezolizumab, with bevacizumab, an antiangiogenic agent, has shown greater benefits and more significant improvements in overall survival and progression-free survival (PFS) than sorafenib [136]. However, the administration of tyrosine kinase inhibitors is still recommended if any contraindications for the treatment exist with first-line therapy. The employed tyrosine kinase inhibitors include sorafenib and lenvatinib, as well as regorafenib and cabozantinib [137]. Sorafenib and its similar compound, regorafenib, are oral multi-kinase inhibitors that target VEGFR2, VEGFR3, PDGFR, c-kit, FLT-3, and RET [138]. Lenvatinib targets the VEGF receptors 1–3, FGF receptors 1–4, PDGF receptor α, RET, and KIT and is an effective inhibitor of tumor angiogenesis [137]. Cabozantinib is a broad-spectrum tyrosine kinase inhibitor [139]. Several studies have addressed the way that tyrosine kinase inhibitors affect translation and ribosome biogenesis. As a general rule, drugs such as sorafenib repress the initiation of translation via inhibition of the mTOR [140] and RAS/ERK pathways [141]. Consistently, the combination of sorafenib with the eIF4E-eIF4G inhibitors 4E1RCat (structural) or 4EGI-1 (competitive) synergistically inhibits the cell viability and colony-formation ability of HCC cells [142]. However, the clinical value of the co-inhibition is limited, due to toxicity and resistance. Similarly to the inhibition of translation, tyrosine kinase inhibitors impact ribosome biogenesis, as thoroughly discussed in Ref. [143]. The important role of therapeutic inhibition of ribosome biology is shown by the fact that, for instance, overexpression of the ribosomal protein L28 induces sorafenib resistance [81]. These observations demonstrate the importance of ribosome biogenesis and translation in HCC progression and, at the same time, define the presence of conspicuous adaptive changes linked to clonal variability in the tumor microenvironment [144]. The targeting of intermediate signaling pathways upstream of initiation factors is practically achieved by a variety of drugs that hit either the growth factor cascade or the eIF2α kinase cascade. The rationale has been thoroughly described [20]. A pivotal role is driven by inhibitors of the mTORc1 cascade, such as rapalogs, which have been widely described in several reviews [20,49,145]. As of today, their clinical effect has been modest. Probably the most promising drug target is phosphorylated eIF4E, its pivotal function in tumor progression having been described before [130]. The crucial aspect of eIF4E phosphorylation is that it completely depends on Mnk1/2 kinases and is dispensable for embryonic growth and adult life [146]. Mnk kinase inhibitors such as eFT508 (Tomivosertib) may, therefore, have tumor-specific effects [147]. eFT508 is currently being tested in several clinical trials. The phosphorylation of eIF2α is a key regulatory target for translation control that is important in regulating translation during normal and stress conditions. The regulation of eIF2α phosphorylation is a promising therapeutic, mainly in the context of the treatment of neurological diseases [148]. The mechanistic targeting of initiation factors can be achieved using a variety of compounds. Omacetaxine, previously known as homoharringtonine, inhibits protein synthesis by blocking the formation of the first peptide bond during polypeptide synthesis. Mechanistic studies have established that omacetaxine inhibits global protein synthesis, with a stronger effect on short–half-life proteins. High-throughput expression screening identified the molecular targets for omacetaxine, including key oncogenes such as PLK1 [149]. As a result, omacetaxine represses growth and increases apoptosis in HCC patient-derived organoids, blocking the formation of crucial oncoproteins such as MYC, β-catenin, cyclin D1, and MET [150]. Silvestrol is isolated from plants of the genus Aglaia and is a potent inhibitor of translation initiation. Mechanistically, it interacts with polypurine sequences in the 5′-untranslated region (UTR) of selected mRNAs, thereby clamping the RNA substrate into eIF4A and causing inhibition of the translation initiation complex [151]. Early studies applied silvestrol to HCC models, obtaining specific growth inhibition [152]. Zotatifin (eFT226) is a derived eIF4A inhibitor that blocks tumor growth in receptor tyrosine kinase-driven tumors [153]. Clinical trials evaluating its antiviral and antitumor activities are in progress. Recently, our group has shown that eIF6 haploinsufficiency protects from hepatic steatosis fibrosis and the progression to hepatocellular carcinoma in vivo [91]. We isolated a number of inhibitors of eIF6 binding to 60S ribosomal subunits [154] that are effective in reducing the translation of lipogenic transcription factors [91] and the growth of HCC spheroids in vitro [92]. eIF4E-eIF4G complex inhibition can be achieved using 4E1RCat or 4EGI-1 inhibitors [155]. The combination of 4E1RCat or 4EGI-1 with eIF4E-eIF4G inhibitors synergistically inhibited the cell viability and colony formation ability of HCC cells [142]. In conclusion, we provide an overview of the relevance of translational control in hepatocellular carcinoma onset and progression. Targeting “emerging” hallmarks belonging to the translational machinery, even when in combination with current systemic therapies, can be considered an innovative therapeutic avenue against human HCC.

PMC10002964

Yuxiang Dai,Ngarmbaye Masra,Lu Zhou,Chen Yu,Wei Jin,Hongbin Ni

Hederagenin suppresses glioma cell biological activities via Nur77 in vitro study

07-12-2022

AKT,glioma,Hed,Nur77,PI3K,U251,U87

Abstract The aim of this research was to discuss Hederagenin's antitumor effects on glioma by in vitro study. U251 and U87 cell lines were used as research target in our research. In the first step, the different Hed concentrations were treated to U251 and U87 cell lines, and the second step is Nur77 transfection in U251 and U87 with Hed treatment; measuring cell proliferation by MTT and EdU staining; evaluating cell invasion and migration abilities by transwell assay and relative gene and protein expressions by RT‐qPCR and WB assay. Compared with NC group, U251 and U87 cell proliferation were significantly depressed with cell apoptosis significantly increasing, and cell invasion and migration abilities were significantly inhibited in Hed‐treated groups (p < .05, respectively); however, with Nur77 transfection, the Hed's antitumor effects disappeared. Meanwhile, with Hed supplement, Nur77, PI3K, and AKT gene expressions were significantly downregulated (p < .05, respectively) in Hed‐treated groups; and Nur77, p‐PI3K, and p‐AKT protein expressions were significantly decreased (p < .05, respectively) in Hed‐treated groups. Hed had antitumor effects on glioma cell biological activities via Nur77/PI3K/AKT pathway in vitro study.

Hederagenin suppresses glioma cell biological activities via Nur77 in vitro study The aim of this research was to discuss Hederagenin's antitumor effects on glioma by in vitro study. U251 and U87 cell lines were used as research target in our research. In the first step, the different Hed concentrations were treated to U251 and U87 cell lines, and the second step is Nur77 transfection in U251 and U87 with Hed treatment; measuring cell proliferation by MTT and EdU staining; evaluating cell invasion and migration abilities by transwell assay and relative gene and protein expressions by RT‐qPCR and WB assay. Compared with NC group, U251 and U87 cell proliferation were significantly depressed with cell apoptosis significantly increasing, and cell invasion and migration abilities were significantly inhibited in Hed‐treated groups (p < .05, respectively); however, with Nur77 transfection, the Hed's antitumor effects disappeared. Meanwhile, with Hed supplement, Nur77, PI3K, and AKT gene expressions were significantly downregulated (p < .05, respectively) in Hed‐treated groups; and Nur77, p‐PI3K, and p‐AKT protein expressions were significantly decreased (p < .05, respectively) in Hed‐treated groups. Hed had antitumor effects on glioma cell biological activities via Nur77/PI3K/AKT pathway in vitro study. Glioma is a common malignant brain tumor in the nervous system; proportions taken by it in intracranial tumors and malignant intracranial tumors are known to be 45% and 80%, respectively. In terms of incidence and mortality, glioma ranks first among malignant central nervous system (CNS) neoplasms (Tsang et al., 1993). Glioma cells show infiltratively growth; and, the boundary between these cells and normal brain tissues is still not clear. In addition, these cells are also featured with high incidence, short disease course, high morbidity, a high recurrence rate, and a low cure rate (Hamada et al., 1996). At present, the major glioma treatment approach is a combination of surgical operation and chemoradiotherapy. Although symptoms of patients can, thus, be improved in a short time, it is apt to recur due to residual diseases; and, the corresponding prognosis is also rather poor (Li et al., 2016). In recent years, a variety of natural products have shown good effects in the prevention and treatment of glioma (Cao et al., 2017; Lin et al., 2021; Park et al., 2018). Hederagenin (Hed) belongs to triterpenoid acids, which are abundant in ivy leaves and have a wide range of biological activities (Rodríguez‐Hernández et al., 2015). Relative studies found that Hed had antitumor effects in NSCLC, colon cancer, and leukemia in previous research (Chen et al., 2019; Liu et al., 2014; Mimaki et al., 1999). Our present study firstly discussed Hed's antitumor effects on glioma and observed Hed depression on cell proliferation, apoptosis, invasion, and migration abilities in glioma cell lines (U87 and U251) and relative mechanisms by in vitro study. Heb was purchased from Sigma (cat.no. H3916; USA); U251 and U87 cell lines were from the Cell bank of typical culture collection Committee of Chinese Academy of Sciences. Medium and fetal bovine serum – BI, USA; MTT kit – Sigma, USA; EdU kit – Keygen, Nanjing, China; BCA protein concentration kit – Keygen, Nanjing, China; antibodies including Nur77, PI3K, AKT, p‐AKT, p‐PI3K, and GAPDH – Abcam, USA. Cells were routinely cultured in DMEM containing 10% fetal bovine serum at 37°C and 5%CO2; moreover, the humidity is saturated. The culture medium was changed every other day and passage was conducted once every 3 days. Once cell growth was completed by 60–70% and confluence took place, the serum concentration was lowered to 5%; afterward, 1‐μg plasmids were mixed with 100 μl pcDNA3.1 for 20 min and their mixture was added into the medium. Four hours later, the preceding medium was replaced with a 20% serum‐containing medium in which cell culturing proceeds. Moreover, Nur77 was designed in Jiangsu KeyGEN BioTECH Co., Ltd. NC: the cells (U251 and U87) were treated with normal; Heb‐L: the cells (U251 and U87) were treated with 5 μM Hed; Hed‐M: the cells (U251 and U87) were treated with 10 μM Hed; Hed‐H: the cells (U251 and U87) were treated with 20 μM Hed; pcDNA3.1: the cells (U251 and U87) were transfected with pcDNA3.1; Hed: the cells (U251 and U87) were treated with 20 μM Hed; Hed + Nur77: the cells (U251 and U87) transfected with Nur77 by pcDNA3.1 and were treated with 20 μM Hed. After 0 h, 24 h, 48 h, and 72 h of cell treatment, 20 μl MTT (5 mg/ml) was added into each well, then the well was incubated and removed after 4 h. The liquid in the 96‐well plate was removed using suction and 150‐μl DMSO was added to each well. Subsequent to a 15‐min reaction at room temperature, the plate was placed in a microplate reader to determine the absorbance value at a wavelength of 490 nm. Each experiment was repeated in triplicate. After 48 h of cell treatment, using EdU infiltrate working fluid to incubate at 37°C for 3 h, 4% paraformaldehyde fixation for 30 min, after neutralization of excess paraformaldehyde with glycine, adding 0.5%Trition X‐100 to incubate 10 min, washing by PBS, adding dye solution to incubate at 37°C for 30 min, wash off excess staining solution with PBS, Nuclei were stained with DAPI for 3 min, pictures were taken under the fluorescence microscope. Blue is the nucleus, and green is the EdU‐positive cells, that is, newly proliferated cells. Randomly select five fields to obtain the average value under 200‐fold, counting EdU‐positive cell number to reflect the cell proliferation ability. After 48 h of cell treatment, the cells were collected and rinsed with PBS according to the instructions provided with the Annexin V‐FITC Apoptosis Detection Kit. A flow cytometer was used to determine the rate of apoptosis. Each experiment was repeated in triplicate. After blending Matrigel with DMEM at a ratio of 1:2 on ice, the mixture was added into the transwell cabin (30 μl in each well). Together with a 24‐well plate, the transwell cabin was placed in an incubator for 1 hour and then taken out to remove the nonsolidified Matrigel using suction. 100 μl of cells (treated and cultured using various methods) and 100 μl of serum‐free DMEM were added to the upper cabin. A serum‐containing DMEM corresponding to the concentration of a drug was added to the lower cabin. Next, the transwell cabins were placed in an incubator to culture for 24 h and then removed. The medium was abandoned and the cells were fixed for 10 minutes using 4% paraformaldehyde, any cells failing to penetrate through the Matrigel were wiped away using swabs. After staining using 0.1% crystal violet, the excess crystal violet was rinsed away using PBS. Once dried, photographs were taken by optical microscope (CX23, Olympus, Japan). The cells were counted using the photographs of each group. Each experiment was repeated in triplicate. Inoculated cells, adjust the cell density to 1 × 105cell/ml, take 100 μl of cell suspension and add it into the Transwell chamber, and add 500 μl of FBS‐containing medium into the lower chamber; The 24‐well cell culture plate was placed in a 5% CO2 incubator at 37°C for 24 h; Wipe the Matrigel and the cells in the upper chamber with a cotton swab, remove the Transwell, invert, air dry, add 500 μl of 0.1% crystal violet into the 24‐well plate, place the chamber in it, immerse the membrane in the dye, take it out after 30 min at 37°C, clean it with PBS, take three fields of view on the diameter, and take photos (magnification: 200×), Counting. To extract the total RNA, cells were added to TRIzol reagent to perform pyrolysis. A 10‐μl cDNA reaction system (reaction conditions: 42°C for 60 min, 70°C for 10 min) and a 20‐μl qRT‐PCR reaction system (reaction conditions: 90°C for 15 min, 95°C for 2 min, 95°C for 5 s, 60°C for 25 s, and a cycle of 65–95–65°C for 30 min) were both prepared. After 40 circulations, fluorescence detection was performed. Here, the relative expression of the gene was determined using the delta–delta CT method. Each experiment was repeated in triplicate. The sequence as follows: PI3K: F: 5′‐TATTTGGACTTTGCGACAAGACT‐3′ and R: 5′‐TCGAACGTACTGGTCTGGATAG‐3′; AKT: F: 5′‐AGCGACGTGGCTATTGTGAAG‐3′ and 5′‐GCCATCATTCTTGAGGAGGAAGT‐3′; GAPDH: F: 5′‐GATTCCCTGGACCTAAAGGTGC‐3′ and R: 5′‐AGCCTCTCCATCTTTGCCAGCA‐3′; Nur77: F: 5′‐TCATGGACGGCTACAGAG‐3′; R: 5′‐GTAGGCATGGAATAGCTC‐3′. After 48 h of cell treatment, a protein lysis buffer was used to extract the total protein and the protein concentration was determined using a BCA kit (CoWin Biosciences, Beijing). Following the addition of the same amount of protein, polyacrylamide gel electrophoresis was implemented using 100 g/L sodium lauryl sulfate. Once the electrophoresis was completed, the protein was transferred onto a 0.45 μm PVDF membrane, which was then sealed in a confining liquid. The phosphorylated and nonphosphorylated proteins were sealed using 5% fetal bovine serum and 50 g/L skimmed milk powder, respectively. After sealing, the primary and secondary antibodies were added accordingly. This point represents the completion of the method development. The primary antibodies used here were as follows: rabbit anti‐GAPDH (1:5000, Affinity, USA); rabbit anti‐Nur77 (1:1000, Proteintech, USA); and rabbit anti‐CXCR4, rabbit anti‐PI3K and p‐PI3K, AKT, and p‐AKT (all 1:1000, Abcam, UK). The secondary antibody used here was goat anti‐rabbit IgG (1:1000, CST, USA). Each experiment was repeated in triplicate. The relevant statistical analyses were performed using SPSS 22.0. The corresponding data were expressed as the mean ± standard deviation (mean ± SD), where the t‐test was applied. It was found that the value of p was below 0.05 (p < .05), indicating that there are statistically significant differences between the data. By MTT assay, compared with NC group, the cell proliferation rate of U251 and U87 cell lines was significantly depressed at 24 h, 48 h, and 72 h in Hed‐L, Hed‐M, and Hed‐H groups (p < .05, p < .01, or p < .001, respectively, Figure 1a). By EdU assay, compared with NC group, EdU‐positive cell number of U251 and U87 cell lines was significantly reduced in Hed‐L, Hed‐M, and Hed‐H groups (p < .001, respectively, Figure 1b,c). By flow cytometry (Annexin V‐FITC/PI double staining apoptosis analysis), compared with NC group, apoptosis cell rate of Hed‐L, Hed‐M, and Hed‐H groups was significantly upregulated in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 2a,b). By transwell assay to observe cell invasion and migration abilities, compared with NC group, the invasion and migration cell number of Heb‐L, Hed‐M, and Hed‐H groups were significantly depressed in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 3a,d). By RT‐qPCR assay, compared with NC group, Nur77, PI3K, and AKT mRNA expressions of Hed‐L, Hed‐M, and Hed‐H groups were significantly downregulated in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 4a,b). By WB assay, PI3K and AKT protein expressions had no significant differences among NC, Hed‐L, Hed‐M, and Hed‐H groups in U251 and U87 cell lines (p > .05, respectively, Figure 5a,b); however, compared with NC group, Nur77, p‐PI3K, p‐AKT, p‐PI3K/PI3K, and p‐AKT/AKT were significantly different in Hed‐L, Hed‐M, and Hed‐H groups in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 5a,b). Compared with NC group, cell proliferation rates of Hed groups in 24 h, 48 h, and 72 h were significantly depressed in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 6a); however, with Nur77 supplement, compared with Hed group, cell proliferation rates of Heb+Nur 77 groups in 24 h, 48 h, and 72 h were significantly increased in U251 and U87 cell lines (p < .05, p < .01, or p < .001, respectively, Figure 6a). By EdU assay, compared with NC group, EdU‐positive cell number of Hed groups was significantly decreased in U251 and U87 cell lines (p < .001, respectively, Figure 6b); with Nur 77 transfected, EdU‐positive cell number of Hed+Nur 77 groups was significantly increased in U251 and U87 cell lines compared with Hed groups (p < .001, respectively, Figure 6b). Compared with NC group, the cell apoptosis rate of Hed groups was significantly upregulated in U251 and U87 cell lines (p < .001, respectively, Figure 7a,b); with Nur 77 supplement, compared with Hed group, the cell apoptosis rate of Hed+Nur 77 groups was significantly downregulated in U251 and U87 cell lines (p < .001, respectively, Figure 7a,b). Using transwell assay to detect cell invasion and migration, compared with NC group, invasion and migration cell number of Heb groups were significantly suppressed in U251 and U87 cell lines (p < .001, respectively, Figure 8a–d); with Nur 77 transfection, compared with Hed group, invasion and migration cell number of Hed+Nur 77 groups were significantly enhanced in U251 and U87 cell lines (p < .001, respectively, Figure 8a–d). By RT‐qPCR assay, compared with NC group, Nur77, PI3K, and AKT mRNA expressions of Hed groups were significantly depressed in U251 and U87 cell lines (p < .001, respectively, Figure 9a,b); with Nur77 supplement, compared with Hed group, Nur77, PI3K, and AKT mRNA expressions of Hed+Nur77 groups were significantly increased in U251 and U87 cell lines (p < .001, respectively, Figure 9a,b). By WB assay, compared with NC group, Nur77, p‐PI3K, p‐AKT, p‐PI3K/PI3K, and p‐AKT/AKT of Hed groups were significantly depressed in U251 and U87 cell lines (p<.001, respectively, Figure 10a,b); with Nur77 supplement, compared with Hed group, Nur77, p‐PI3K, p‐AKT, p‐PI3K/PI3K, and p‐AKT/AKT of Hed+Nur77 groups were significantly improved in U251 and U87 cell lines (p < .001, respectively, Figure 10a,b). The research and development of natural products have always been an important means to find new drugs and fight against cancer. The structure leading, modification, and transformation of natural products have also promoted the rapid development of antitumor drugs. Paclitaxel and irinotecan (camptothecin derivative) are widely used in clinics (Basade & Mane, 2021; Shi & Sun, 2017). In addition, a variety of anticancer substances exist in vegetables, fruits, edible fungi, spices, and other foods, which are beneficial to the prevention and treatment of human cancer. Like as, EGCG, the main component of green tea polyphenols, and resveratrol, a polyphenol compound extracted from grapes, all showed significant antitumor activity (Rauf et al., 2018; Romano & Martel, 2021). Hed is a triterpene acid compound extracted from ivy leaves, which also exists in the leaves of Cyclocarya paliurus and Ailanthus vulgaris (Gao et al., 2016; Liu et al., 2014; Zhang et al., 2012). Research (15) found that Hed was the main active ingredient in the leaves of Cyclocarya paliurus, which inhibits the proliferation of non‐small‐cell lung cancer cell line A549. Hed could significantly inhibit the cell viability of large cell lung cancer cell NCI‐H460, colon cancer cell HT‐29, and leukemia cell CEM (Zhang et al., 2012). Further studies (Liu et al., 2014) found that Ivy saponin induces apoptosis of colon cancer cell LoVo by regulating mitochondrial pathway. The present study found that Hed had effects to suppress glioma cell activities including depressing cell proliferation, invasion, and migration. In order to discuss the clear mechanism, the results found that Hed could inhibit Nur77 mRNA and protein expression in U251 and U87 cell lines; however, with Nur77 transfection in U251 and U87, Hed's antitumor effects disappeared. Depending on these results, we inferred that Hed's antitumor effects were closely correlated with Nur77. Nur77, also known as NR4A1, TR3, or NGF‐IB, is a member of the steroid/thyroid hormone receptor superfamily. As a transcription factor and early response gene, Nur77 in different types of cells and tissues can be induced by many irritants, including serum, inflammatory factors, growth factors, and pressure (Winoto & Littman, 2002). At present, there are still disputes about the role of Nur77 in tumors (Lee et al., 2010; Liu et al., 1994; Wu et al., 2011). In our present study, the results suggested that Hed had anticancer effects to depress Nur77, and the data also found that Nur77 was a key role in Hed's antitumor effects in glioma. Some research also found that Nur77 could target PI3K/AKT activities (Bai et al., 2015; Han et al., 2006; Huang et al., 2016; Shi et al., 2021). PI3K/AKT, an important signaling pathway in cells, gains control over multiple biological processes of cells, such as their proliferation, growth, apoptosis, transcription, translation, cytoskeletal rearrangement, and cell cycles. In addition, it also plays a crucial role in tumor occurrence and development (Deng et al., 2020; Xue et al., 2020). As far as our research findings are concerned, with Nur77 depressing, p‐PI3K and p‐AKT protein expressions and p‐PI3K/PI3Kand p‐AKT/AKT rates were significantly depressed, which might be correlated Hed's antitumor mechanism. In conclusion, Hed had effects to depress glioma cell biological activities in vitro study. Hed suppressed glioma cell biological activities via depressing Nur77, meanwhile, Nur77 downstream which was PI3K/AKT signaling pathway was also inhibiting in our in vitro study. None. The authors declare that they have no competing interests.

PMC10002966

Mengchi Chen,Haotian Jiang,Chunping Zhang

Selected Genetic Factors Associated with Primary Ovarian Insufficiency

23-02-2023

POI,genetics,mutations,folliculogenesis,ovary

Primary ovarian insufficiency (POI) is a heterogeneous disease resulting from non-functional ovaries in women before the age of 40. It is characterized by primary amenorrhea or secondary amenorrhea. As regards its etiology, although many POI cases are idiopathic, menopausal age is a heritable trait and genetic factors play an important role in all POI cases with known causes, accounting for approximately 20% to 25% of cases. This paper reviews the selected genetic causes implicated in POI and examines their pathogenic mechanisms to show the crucial role of genetic effects on POI. The genetic factors that can be found in POI cases include chromosomal abnormalities (e.g., X chromosomal aneuploidies, structural X chromosomal abnormalities, X-autosome translocations, and autosomal variations), single gene mutations (e.g., newborn ovary homeobox gene (NOBOX), folliculogenesis specific bHLH transcription factor (FIGLA), follicle-stimulating hormone receptor (FSHR), forkhead box L2 (FOXL2), bone morphogenetic protein 15 (BMP15), etc., as well as defects in mitochondrial functions and non-coding RNAs (small ncRNAs and long ncRNAs). These findings are beneficial for doctors to diagnose idiopathic POI cases and predict the risk of POI in women.

Selected Genetic Factors Associated with Primary Ovarian Insufficiency Primary ovarian insufficiency (POI) is a heterogeneous disease resulting from non-functional ovaries in women before the age of 40. It is characterized by primary amenorrhea or secondary amenorrhea. As regards its etiology, although many POI cases are idiopathic, menopausal age is a heritable trait and genetic factors play an important role in all POI cases with known causes, accounting for approximately 20% to 25% of cases. This paper reviews the selected genetic causes implicated in POI and examines their pathogenic mechanisms to show the crucial role of genetic effects on POI. The genetic factors that can be found in POI cases include chromosomal abnormalities (e.g., X chromosomal aneuploidies, structural X chromosomal abnormalities, X-autosome translocations, and autosomal variations), single gene mutations (e.g., newborn ovary homeobox gene (NOBOX), folliculogenesis specific bHLH transcription factor (FIGLA), follicle-stimulating hormone receptor (FSHR), forkhead box L2 (FOXL2), bone morphogenetic protein 15 (BMP15), etc., as well as defects in mitochondrial functions and non-coding RNAs (small ncRNAs and long ncRNAs). These findings are beneficial for doctors to diagnose idiopathic POI cases and predict the risk of POI in women. Female infertility refers to the inability to conceive after 6 months (for women over the age of 35) to 1 year of regular and unprotected sex. According to the Office on Women’s Health (OWH) of America, premature ovarian insufficiency (POI) is one of the most common causes of female infertility. POI, which is also known as primary ovarian insufficiency or premature ovarian failure, refers to female amenorrhea before the age of 40 due to non-functional ovaries caused by follicle atresia and the rapid loss of germ cells [1]. POI is manifested as primary or secondary amenorrhea with hormonal changes, such as increased gonadotropin levels (FSH > 25 IU/L) and decreased estradiol and anti-Müllerian hormone levels [1,2]. Moreover, there are many clinical presentations in POI women. Hot flashes, night sweats, and insomnia are all classic symptoms of POI, which coincide with reduced estrogen condition [3]. The increase in the POI cases, among which there is a vast number of POI women with unclear genetic diagnoses, justifies investigating the etiology of POI, which may be critical in the early diagnosis, treatment, and prevention [3]. Although POI is heterogenous and the causes of many cases remain unclear, various types of etiologies, such as genetic, autoimmune, iatrogenic, infectious, environmental, chemotherapeutic, and radiotherapeutic causes, have been determined [4,5,6]. Previous research established a relationship between the genetic effects and POI by studying POI in families (the prevalence of familial POI ranges from 4% to 31%) [7,8,9]. Moreover, there is an increasing prevalence of POI in adolescents. In a recent study, the research group gathered information on women under 21 years of age diagnosed with POI in 2000–2016 from all pediatric endocrinology units in Israel [10]. Among the 130 women with POI, the most common cause was Turner syndrome/mosaicism, accounting for 43% of cases. For non-Turner POI cases in this group, a significant increase in the incidence of POI was observed. This is due to new and more effective gene technology and the frequent occurrence of autoimmune diseases. The incidence rate of new POI diagnoses per 100,000 person-years increased year-by-year, especially in 2009–2016, indicating the remarkable incidence rate of POI in adolescents. Furthermore, the overall prevalence of genetic-associated POI is approximately 20–25% [11]. Therefore, taking genetic factors into account often leads to a more straightforward POI diagnosis. Previous reviews on the genetic factors of POI often focus on one or more aspects, such as the POI-related genes involved in meiosis or DNA repair, or they reveal a certain type of chromosomal mutation associated with POI, such as X-autosome translocations. In addition, the broader reviews only pay attention to the single gene mutations of POI and so on. In this review, we reasonably classify the genetic factors and non-syndromic POI-related genes (according to the biological process in which genes participate), based on previous research, so that the genetic factors and corresponding mechanisms of POI are more comprehensively and carefully summarized. We divided genetic causes of POI into four categories after reviewing and analyzing the content of other previous literatures: chromosomal abnormalities, single gene variants in non-syndromic and syndromic POI, mitochondrial dysfunction, and abnormal levels of non-coding RNAs (Figure 1). Thus, the present review provides essential information to help us better understand POI caused by genetic factors. We hope that this will act to improve the efficacy of diagnosis and treatment for POI patients. We entered the following keywords “POI and genetic factors” (219), “POI and gene mutation” (217), “POI and variants” (209), “POI and a certain gene name”, “POI and mitochondria” (18), and “POI and non-coding RNA” (54) in Pubmed to search the articles and reviews on POI-related genetic factors in the past ten years. Overall, we searched for more than 717 articles. For the studies to be included in this review, the selected publications had to focus on the following: identifying the POI genetic factors in different POI populations via chromosomal analysis, candidate gene screening, genome wide association study, and various genome sequencing strategies. In addition, the role of POI candidate genes in animal models and studies on mitochondrial genes and non-coding RNAs associated with POI were also included. However, the literature identified was restricted to English language. Chromosomal abnormality is defined as a variation resulting from aneuploidy or structural defects in chromosomes. This can lead to many harmful and even lethal human genetic diseases, such as trisomies 21, 18, and 13 and sex chromosomes rearrangements. On this basis, researchers attempted to detect chromosomal variations using prenatal testing, which can be used to effectively avoid human genetic diseases caused by chromosomal abnormalities [12,13]. In addition, recent studies have shown that chromosomal abnormalities are responsible for POI [1,6,14]. The prevalence of POI caused by chromosomal abnormalities varies in different populations, with the values ranging from approximately 10% to 13% [4,15,16]. Chromosomal disorders cause POI via the depletion of primordial oocytes during early female development [1]. However, the mechanism involved in the loss of oocytes is not clearly understood. Moreover, defects in both the X chromosome and autosome can contribute to POI. Specifically, all X monosomies and trisomies, X chromosome deletions, X-autosome translocations, and autosomal translocations represent chromosomal abnormalities that can lead to POI. Turner syndrome is a critical sex chromosomal disease in females with a 1 in 2500 incidence. It is caused by the complete or partial deletion of one sex chromosome [17,18]. TS has many hallmarks, including ovarian failure, and it is the most common genetic cause of POI, accounting for 4–5% of all POI cases [7,11,19]. Primordial follicle atresia and a reduction in the ovarian reserve are the circumstances under which TS causes POI, but its mechanism is unknown. A recent review suggested that TS-related POI was associated with the function and length of telomeres and epigenetic modifications [20]. Moreover, many scientists have shown that ovary-related genes were also responsible for the ovarian phenotype in TS patients [21]. The severity of TS patients’ symptoms depends on whether their genotype is 45X or mosaicism, such as 45X/46XX. The TS patients with a mosaic genotype are characterized by secondary amenorrhea, which means that this group of patients is fertile (producing a lower level of follicles) at first. However, fertility reduces over time, and eventually, POI develops [22,23]. In contrast, TS patients who lose a complete X chromosome are characterized by primary amenorrhea with a small chance of menarche [11]. Trisomy X syndrome (TXS) with a karyotype 47XXX is another sex chromosome aneuploidy that contributes to POI [24]. A relatively small body of literature is concerned with the connection between X trisomy and POI. In 2020, Shanlee et al. performed a case-control study and demonstrated that the level of anti-mullerian hormone (AMH) in TXS patients was lower than in healthy females, indicating that TXS females had a higher risk of suffering from POI [25]. In addition, in females with TXS, increasing follicle-stimulating hormone (FSH) and luteinizing hormone (LH) can cause menstrual cycle disturbance, which is associated with POI [26]. A previous survey also reported a patient with both blepharophimosis-ptosis-epicanthus syndrome (BPES) and TXS presenting with POI. However, this patient had a normal level of gonadotropins, which is rare in POI cases [27]. A number of studies have established a relationship between X chromosomal structural disorders (mainly X chromosomal deletions), X-autosomal translocations, and POI [11,26,28]. Furthermore, a recent study posited the existence of POI critical regions 1 and 2 on the X chromosome, which define the positions of the breakpoints for X chromosomal deletions and X-autosomal translocations related to ovarian functions, respectively [22]. The POI1 region consists of a part of the long arm of the X chromosome ranging from Xq24 to Xq27, but does not conclude the fragile X mental retardation 1 (FMR1) gene, while the Xq13.1 to Xq21.33 region belongs to the POI2 region. Although a considerable body of research has demonstrated the pathogenic role of structural X chromosomal abnormalities in POI, much less attention has been paid to this area over the past decade. By comparing and analyzing the statistics from four studies, the reasonable prevalence of X chromosome structural anomalies and X-autosome translocations related to POI was calculated to range from 4.2% to 12.0% [29,30,31,32]. Moreover, many POI candidate genes on the X chromosome can be found by analyzing the X-autosome translocations, some of which are introduced below. Autosomal translocations, microdeletions, specific gene mutations, epistasis, and epigenetics associated with autosomal genes are all responsible for POI [33,34]. As has been previously reported, for chromosome variations, most POI cases are caused by X chromosome variations, while autosomal variations account for only a small number of POI cases [16,29,35]. The majority of previous and current studies focus on autosomal translocations and gene variants. According to a recent literature review, only 23 cases exhibited autosomal abnormalities (Robertsonian translocation, reciprocal translocation, and chromosomal inversion) associated with POI, which were identified in different POI populations with different ethnicities, including Chinese, Thai, and American [36]. Many autosomal genes associated with ovarian functions are discussed in the next section. Aside from chromosomal abnormalities, single gene variations can also cause POI. The classical candidate gene approach is based on genes with known functions and experimental models in mice. In these, scientists establish a hypothesis regarding the connection between candidate genes and POI. Using this method, many genes, such as BMP15, NOBOX, and FMR1, have been discovered [37]. However, the range of candidate genes is restricted in this traditional approach. The appearance of many new strategies, such as genome-wide association studies (GWAS), can overcome the shortcomings of the traditional method. However, as a result of the low prevalence and high heterogeneity of POI, it is challenging to perform replicated experiments to prove the causation of these candidate genes using GWAS. Therefore, the majority of recent studies that investigate POI-related genes utilize another method, known as whole exome sequencing (WES). Moreover, next-generation sequencing (NGS) is also responsible for identifying variants. The associated genes identified in the last 10 years are classified according to the biological processes they participate in (Table 1), which are introduced below. A normal oocyte reserve is essential for females of reproductive age to give birth to a healthy baby. However, if any error occurs during meiosis, DNA replication, or DNA repair, the genetic information is negatively affected, leading to germ cell apoptosis and infertility. Therefore, collecting and investigating the genes involved in the critical processes of meiosis, DNA replication, and DNA repair is beneficial for obtaining a better understanding of POI. HFM1 exists on chromosome 1p22 and encodes DNA helicase, which is only expressed in the ovary and testis. There are numerous studies that demonstrate the connection between HFM1 and POI. A recent study conducted WES in a Chinese POI cohort containing two POI patients (the proband and her mother) and found a novel missense mutation of HFM1 (c.3470G> A), which can affect mRNA transcription [88]. However, its role in protein levels needs further investigation. Moreover, one out of twenty-four POI patients in a cohort harbored two disease-causing variants in HFM1 (c.3100G > A and c.1006 + 1G > T) [41]. Similar to c.3470G> A, c.1006 + 1G > T also disrupts RNA splicing. In addition, another mutation, c.3100G > A, alters the amino acid of the protein (p.G1034S). The way in which mutant HFM1 causes POI is its ability to damage meiosis in the oocyte. However, the definite role of the HFM1 gene in meiosis remains uncertain. The majority of associated studies have shown that the HFM1 gene is involved in homologous recombination (HR) and synapsis [38,39,40]. Moreover, in 2020, Wang et al. was first to demonstrate that HFM1 gathers at the spindle pole and is responsible for normal spindle formation and function during meiosis in female mice oocytes via maintaining the usual activities of GM130 and p-Mapk proteins [89]. PRIM1 is a protein-coding gene and is located at 12q13.3. It is one of the subunits of DNA primase, which is essential for DNA replication by synthesizing RNA oligonucleotide primers, so as to promote the production of new lagging and leading strands through DNA polymerase [42]. In addition, PRIM1 is also related to DNA repair [90]. As previously reported in a meta-analysis, many loci in the corresponding genes were identified using GWAS that are associated with natural menopause age in European women. In this, PRIM1 (SNP rs2277339) was the second strongest candidate gene [43]. Perry et al. proved that non-synonymous SNP rs2277339 in PRIM1 was responsible for POI [91]. Another meta-analysis also recognized the relationship between PRIM1 (SNP rs2277339) and natural menopause age in African American women [92]. However, the further consequences of mutations in SNP rs2277339 remain unclear. However, in 2016, Wang et al. published a paper concluding that perturbations in the coding region of PRIM1 were not common among Chinese POI patients [93]. STAG3 (7q22.1) is also an important candidate gene in POI. Much of the current literature on gene mutations that cause POI pays particular attention to the effects of STAG3 variants. Over the last 5 years, scientists have conducted WES in consanguineous families [94,95,96] and showed various novel homozygous pathogenic STAG3 variants that cause POI, which included a missense variant (NM_012447.3:c.962G > A), two novel in-frame variants (c.877_885del, p.293_295del; c.891_893dupTGA, p.297_298insAsp), and a donor splice site variant (NM_012447.2: c.1573 + 5G > A). In addition, a series of reports focusing on different ethnicities (Senegalese, white British, and Brazilian POI patients) also revealed many POI-related pathogenic mutations in STAG3 (c.3381_3384delAGAA, p.Glu1128Metfs*42; c.1336G > T, p.Glu446Ter; c.291dupC, p.Asn98Glnfs*2; and c.1950C > A, p.Tyr650*) [45,97,98]. As such an important causative gene, understanding the mechanism of action of STAG3 is crucial. Synapsis mainly occurs during prophase I of meiosis, and it refers to the pairing of homologous chromosomes for DNA exchange of non-sister chromatids, also known as crossover. The synaptonemal complex (SC) acts as a zipper and is responsible for normal synapsis. Cohesin is another essential protein that contributes to establishing SC, ensuring the correct separation of pairing chromatids, DNA repair, and transcriptional regulation [59,99]. Moreover, STAG3 encodes the corresponding protein, which functions as a subunit of the cohesin complex [44]. Therefore, defects in STAG3 will lead to abnormal folliculogenesis and, eventually, POI. MCM8 and MCM9 are homologous to the MCM 2-7 complex, and all belong to the MCM family. Similar to other members of the MCM family, MCM8 and MCM9 contain the highly conserved helicase domain that can open up DNA strands [100]. MCM8 dimerizes with MCM9, giving rise to a hexameric helicase that is responsible for homologous recombination (HR) initiated by DNA double strand breaks (DSB) and facilitating DNA synthesis in a RAD51-dependent manner [46]. The presence of DSB can lead to a loss of DNA integrity, eventually causing follicular apoptosis and degeneration. Therefore, mutations in MCM8 and MCM9 are associated with infertility. In female mice, loss of MCM8 and MCM9 contributes to sterility [101]. By performing the NGS approach (mainly WES) in POI consanguineous families from various ethnicities (Han Chinese, Arab, Turkish, and Tunisian), new deleterious homozygous mutations in MCM8 or MCM9 were identified (c.351_354delAAAG, p.Lys118Glufs*5; c.1483G > T, p.E495*, and c. 482A > C, p.His161Pro) [48,102,103]. These variants cause chromosomal instability and reduce the DNA repairing capacity. In addition, the members of these consanguineous families with heterozygous variants of MCM8 and MCM9 are healthy. However, a considerable body of work investigating POI causal genes in several cohorts from different ethnic groups also provides evidence for heterozygous mutations in MCM8 and MCM9, such as c.2488G > A, p.A830T; c.482A.G, p.His161Arg; c.548A.G, p.Asn183Ser; c.686T.G, p.Val229Gly, etc. [41,104,105,106,107,108]. However, not all of the aforementioned mutations have been shown to be harmful. The nature of certain variations has not been determined, and some of the variants are benign. Moreover, The T allele and C allele in two MCM8 single-nucleotide polymorphisms (SNPs) (rs16991615 and rs451417) were found to be associated with susceptibility to POI in a cross-sectional study [109]. Moreover, Wang et al. reported the first family presenting with a disease-causing MCM8 mutation (c.724T > C, p.C242R, and c.1334C > A, p.S445*) in adolescence and childhood [47]. DMC1 is an autosomal POI candidate gene that is located at 22q13.1. Its protein product works with RAD51 and RPA to repair DSBs during mammalian meiosis. In this repairing process, DMC1 plays an important role in strand exchange [49]. In addition, DMC1 is associated with fertility capacity. Failure of folliculogenesis and spermatogenesis can be observed in DMC1 knockout murine models [110]. Moreover, previous studies emphasized its disease-causing role in POI. He et al. investigated DMC1 mutation in a consanguineous family with POI and non-obstructive azoospermia (NOA) members through WES and found a new missense mutation in DMC1, which was the causal mutation in both POI and NOA (c.106G > A, p.Asp36Asn) [50]. Another study performed NGS in 269 POI patients from Caucasian, sub-Saharan African, North African, and Asian origin to screen mutant genes. It was reported that 7% of POI patients in this cohort harbored DMC1 variants (c.449G > A, p.Gly150Asp; c.598A > G, p.Met200Val) [111]. According to the results of the mutation taster algorithm, c.449G > A is a disease-causing alteration and c.598A > G is a polymorphism. These scientists also used sorting intolerant from the tolerant (SIFT) and PolyPhen-2 algorithms, with all the results indicating that the two DMC variants were damaging, except for the PolyPhen-2 result for c.598A > G (benign). In contrast to these results, many articles report no connection between DMC1 and POI or female mice fertility. Thus, the level of influence DMC1 has in female sterility remains unclear [110,112,113]. MCL-1 exists at chromosome 1 and can encode an antiapoptotic protein, a BCL-2 family member, necessary for regulating the cell cycle. In oocytes, MCL-1 mutations affect the transition from mitosis to meiosis, resulting in reduced original follicles [51]. Previous research demonstrated the association between female fertility and MCL-1. In a study investigating the therapeutic effect of optimized platelet-rich plasma in POI mice, the MCL-1 expression level was lower in the POI group than in the controls, while MCL-1 had a higher level of expression after treatment [114]. In contrast to the protective factor, a deleterious factor for female fertility, known as cadmium (Cd), could cause decreased MCL-1 expression [115]. Cadmium is a heavy metal and is a known toxin with effects on the reproductive system. It has many effects on various cellular processes. In addition, it was demonstrated in other studies that MCL-1 is expressed in primordial and preantral follicles, contributing to the normal development of follicles [116]. Moreover, MCL-1-depleted mice exhibited similar presentations to POI patients [52]. However, the authors in one work of literature failed to reveal the causal connection between the MCL-1 gene and Chinese idiopathic POI patients [51]. Recently, MSH4 (1p31) and MSH5 (6p21.31) became POI candidate genes, due to their roles in chromosomal synapsis and meiotic recombination through forming a dimer [38]. Both are members of the MutS family, which is associated with DNA mismatch repair. By performing WES in Iranian, Chinese, and Colombian families, two homozygous missense variants from MSH4 and MSH5 (NM_002440.4: c.2261C > T, p.Ser754Leu; ENST00000375755: c.1459G > T, p.D487Y) and a homozygous donor splice-site MSH4 variant (p.Ile743_Lys785del) were identified [53,117,118]. These two mutations in MSH4 are harmful to the ATP binding site, affecting the gene’s normal function. In a MSH5 variant-finding study, the scientists also identified infertile female mice with a mutation of the gene homologous to MSH5 p.D487Y. In addition, three other unconfirmed heterozygous MSH5 variants were also revealed by screening 200 patients with sporadic POI. Moreover, two novel mutations in MSH5 were recently identified in two POI cohorts (c.1264C > T, p.Arg422Cys and c.C1051G, p.R351G) [54,119]. Scientists in these studies explored the effects of these variants via yeast assay and C. elegans, respectively. However, only the c. C1051G; p.R351G variant, tested using C. elegans, exhibited obvious defects. MEIOB (16p13.3) is another mandatory gene associated with RAD51 and DMC1 stabilization, meiotic homologous recombination, and DSB repairing. The MEIOB protein binds to single-strand DNA and dimerizes with spermatogenesis-associated 22 (SPATA22) [55]. Both are important for fertility in males and females. Two recent studies identified two homozygous MEIOB mutations that affect female fertility in Arab and Pakistani consanguineous families (c.1218G > A and c.683-1G > A) [120,121]. They also revealed infertile female mice with homozygous deletion of MEIOB. The mutation identified in the Arab family was responsible for the failure of MEIOB–SPATA22 binding and then POI, while the other variant was unrelated to the interaction between these two proteins. As regards the relationship between MEIOB and SPATA22, another study showed that SPATA22 contributed to the localization of MEIOB [122]. In addition, a research group found many new pathogenic homozygous MEIOB variants (c.258_259del, c.1072_1073del and c.814C > T) in three consanguineous Chinese families containing POI and NOA patients [56]. All the variants give rise to truncated proteins, the functions of which are affected. PSMC3IP (17q21.2) is also known as homologous-pairing protein 2 (HOP2), and its protein product forms a complex with Mnd1 to activate DMC1 and Rad51 recombinases using the same protein domains [57]. Therefore, it is also necessary in HR and fertility. In PSMC3IP knockout female mice, smaller ovaries and a depletion of follicles can be observed [40]. In female members with POI and primary amenorrhea from a Yemeni consanguineous family, a deleterious homozygous stop gain mutation of PSMC3IP (c.489 C.G, p.Tyr163Ter) was identified, which caused the partial deletion of the C-terminal portion in the PSMC3IP protein [58]. This deletion led to failed interaction with RAD51 and DMC1, contributing to impaired HR and DNA repair. Aside from the POI patients with primary amenorrhea, two compound heterozygous PSMC3IP mutations (c.206_208delAGA and c.189 G > T) in a secondary amenorrhea POI patient was discovered in 2022 [123]. Another two compound heterozygous mutations (c.597 + 1G > T and c.268G > C p.D90H) in a Chinese POI woman have also been reported [124]. Conversely, no PSMC3IP mutations were observed in a POI cohort from Sweden, which indicates that more studies are required to establish causal PSMC3IP variants in POI cohorts from different populations and containing different ethnicities [125]. Fanconi anemia (FA) is a heterogeneous recessive human genetic disease caused by mutations of one of the genes in the FANC group. These mutations usually lead to impaired meiosis and folliculogenesis [59]. Among genes in the FANC group, many are associated with female fertility. It was reported that FANCI, FANCB, FANCA, and FANCE mutations could affect fertility in female mice [126,127,128,129]. In addition, the FANCL, FANCA, and FANCM variants were identified in non-syndromic POI patients (c.1048_1051delGTCT, p.Gln350Valfs*18; c.739dupA, p.Met247Asnfs*4; c.1772G > A, p.R591Q; c.3887A > G, p.E1296G; and c.5101C > T, p.Gln1701*) [60,130,131,132]. There exist other rare and novel POI candidate meiotic genes (SYCP2L, HSF2BP, and ZSWIM7) [61,62,63,64,133]. These studies expand the range of POI-causing genes. Although transcription factors cannot directly participate in many vital biological processes, they all play crucial parts in regulating physical activities by controlling various target genes. As regards female fertility, they control the expression time, the site, and the expression level of reproductive genes to ensure the smooth functioning of every reproductive process. NR5A1 is located at 9q33.3 and encodes an orphan nuclear receptor. It is expressed in the gonads and adrenals, and the NR5A1 protein acts as a transcription factor, regulating the expression of genes involved in steroidogenesis, reproduction, and gonadal and adrenal development in human, such as Eps15 homology domain-containing protein 3 (EHD3), anti-Mullerian hormone (AMH), and Wilms’ tumor 1 (WT1), etc. In addition, a previous research study emphasized the importance of screening NR5A1 variants for POI women with a family member suffering from disorders related to gonadal development [134]. In women, NR5A1 is mainly expressed in the granulosa and theca cells to control ovarian folliculogenesis and steroidogenesis [135], but the POI pathogenic role in NR5A1 variants is controversial. Certain NR5A1 variants (p.Ser54Arg, p.Pro198Leu, p.Pro129Leu, and p.Gly123Ala) found in POI patients are not pathogenic, and the pathogenicity of some mutations, such as c.437G > C, IVS4-20C > T, has not been confirmed via functional tests [136,137]. There also exist other NR5A1 variants that have been shown to be deleterious. For example, a heterozygous missense NR5A1 variant (c.74A > G, p.Y25C), a rare missense NR5A1 variant (c.1063G > A, p.(Val355Met)), and the p.Val15Met NR5A1 variant were demonstrated to be deleterious in POI patients [65,138,139]. NOBOX (7q35) is expressed in oocytes and granulosa cells and is responsible for early folliculogenesis. In one study, which established a NOBOX-deficient female mice model, a reduced number of primordial follicles (due to abnormal germ cell cysts) and adherens junctions between unseparated oocytes was observed, which indicated the important role of NOBOX in female mice fertility [66]. In addition, it also indicated the significance of oocyte–somatic cells signaling for mice POI. KIT-L is one of the target genes of NOBOX and is present in granulosa cells. Kit-L can transmit the signals of granulosa cells to oocytes via the phosphatidylinositol 3-kinase/AKT pathway [140]. Moreover, other ovarian-specific genes, including growth and differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15), and POU class 5 Homeobox1 (POU5F1) are under the control of NOBOX [141,142,143]. Aside from regulating target genes, NOBOX can also interact with FOXL2; however, mutant NOBOX affects this interaction, leading to POI [144]. A previous study conducted in China demonstrated that a homozygous NOBOX mutation (c.567delG, p.T190Hfs*13) failed to arrest G2/M, causing disrupted cell cycles in meiotic oocytes [67]. According to recent articles, NOBOX is a strong candidate gene for causing POI in humans, due to its high prevalence in different POI populations (5.6–6.5%) [140,142,145]. In addition, these researchers confirmed various NOBOX variants (p.Gly91Thr, p.Gly111Arg, p.Arg117Trp, p.Lys371Thr, p.Pro619Leu, p.Gly91Trp, p.R44L, p.G91W, p.G111R, p.G152R, p.K273*, p.R449*, and p.D452N) to be deleterious. SOHLH1 (9q34.3) and SOHLH2 (13q13.3) are only expressed in germ cells, primordial follicles, and primary follicles, and their protein products can form a heterodimer, which functions as master–master regulators of other master transcription factors to ensure the normal development of gonadal glands and primordial follicles [68,70]. In a murine model, deficiency of at least one of these two genes caused reduced ovarian sizes and a decreased number of primordial follicles and primary follicles [146]. SOHLH1 and SOHLH2 are POI candidate genes, but few studies have investigated their POI-causative roles in the last 10 years. POI-related SOHLH1 variants (p.Ser317Phe, p.Glu376Lys, and c.*118C > T) were first observed in 2015 [69]. These three deleterious variants were identified in Chinese POI cases, while the variants in Serbian POI cases were synonymous. Two causative variants, p.Ser317Phe and p.Glu376Lys, altered the transactivation capacity of the SOHLH1 gene, resulting in lower expression levels of its target genes, including LIM homeobox 8 (LHX8) and zona pellucida glycoprotein 1 (ZP1) and 3 (ZP3). Additionally, scientists identified five heterozygous nonsynonymous SOHLH2 mutations in a POI cohort of the same ethnicity as the cohort discussed before [70]. They were c.235G > A, p.Glu79Lys; c.314A > G, p.Glu105Gly; c.961A > C, p.Thr321Pro; c.360A > T, p.Leu120Phe and c.610C > T, p.Leu204Phe. Among these variants, only c.235G > A and C.314A > G proved to be deleterious. Moreover, this study firstly demonstrated the association between SOHLH2 and idiopathic POI. Furthermore, two more recent studies performed next-generation sequencing in a POI cohort containing 100 patients and a cohort containing 36 Turkish families with POI members, and both showed deleterious SOHLH1 mutations [72,147]. LHX8 (1p31.1) is expressed in germ cells and is essential for early oogenesis. In mice ovaries without the LHX8 gene, remarkably decreased expression levels of other genes associated with oogenesis are observed, which indicates that LHX8 functions as a transcription factor [71]. This study also demonstrates that LHX8, SOHLH1, and FIGLA can interact with each other, forming a nuclear complex and regulating the expression of various oogenesis-related genes. Aside from mice, LHX8 contributes to oogenesis in rainbow trout [148]. In 2016, Bouily reported a missense mutation of LHX8 (c.974C > T, p.A325V) in a Caucasian POI women cohort and verified its damaging effect on POI [72]. In addition, a recent study also revealed a disease-causing LHX8 variant (c.974C > T p.Ala325Val) in POI patients [111]. However, it was reported that there were no causative LHX8 mutations in 95 US Caucasian women with POI [149]. Therefore, LHX8 may be a relatively rare candidate POI-causing gene in the US Caucasian population, and more research is needed to this end. FIGLA is located at 2p13.3. It is mainly expressed in female germ cells and plays an important role in oogenesis. In female mice without FIGLA, the genes involved in different processes (meiosis, growth, and differentiation) of oogenesis are downregulated, such as Rad51, SYCP3, NOBOX, LHX8, SOHLH1, and SOHLH2, which indicates an association between FIGLA and female fertility [71]. In addition, zona pellucida glycoprotein genes, which are important in folliculogenesis, also fall under the control of FIGLA [14,28]. Aside from oogenesis disruption, impaired secondary follicles maturation may also be a pathogenesis of POI caused by FIGLA variations. A recent article showed that FIGLA had the ability to support the development of secondary follicles in mature female mice [150]. Moreover, many researchers have attempted to evaluate the impact of FIGLA mutations on POI, with various deleterious FIGLA variants (c.364del p.Glu122Lysis*45 and c.2 T > C, p.Met1Thr) in consanguineous and non-consanguineous families being reported [73,139,151]. All these variants were homozygous with the autosomal recessive inheritance mode. Signaling molecules, such as hormones, have the ability to transmit information between cells to regulate cellular activities through binding to receptors outside or inside cells. A variety of hormones and receptors are involved in many important processes related to female reproduction and fertility capacity. Their expression levels in human bodies can be considered indicators of female reproductive status and have strong diagnostic significance. Follicle-stimulating hormone (FSH) is a glycoprotein essential for the development of antral follicles. It also promotes hormone secretion, such as estradiol, and indicates the ovarian reserve level by binding to FSHR. Therefore, mutations in the FSHR gene may negatively affect FSH-FSHR signaling, arresting folliculogenesis and causing POI. Data from several studies identified detrimental FSHR variants associated with POI. A novel missense FSHR mutation (I423T), a homozygous FSHR variant (c.1253T > G, p.Ile418Ser), and two compound heterozygous missense FSHR variants (c.646 G > A, p.Gly216Arg and c.1313C > T, p.Thr438Ile) were observed in different POI women from various ethnicities [74,75,152]. All these mutations can affect the expression of FSHR, forming different partial FSHRs at granulosa cell membranes with impaired function. However, various studies failed to establish a causative relationship between FSHR mutations and some POI cases [153,154,155]. Woad et al. found no harmful FSHR variants in exons 7 and 10 from a population of POI women from New Zealand. Another two studies revealed both positive and negative results. In 192 Han Chinese participants with POI, the p.L5971 variant was deleterious, while mutation p.M265V was harmless. In addition, according to a meta-analysis, a FSHR polymorphism (rs6166) was regarded as a genetic biomarker exclusively in POI cases from Asia. In summary, FSHR is a rare POI candidate gene in certain ethnic populations, and researchers should focus on screening FSHR mutations in more POI patients from different countries to provide further evidence of the role of FSHR in POI. Inhibin genes can be divided into two types: inhibin alpha (INHA) (2p35) and inhibin beta (INHB), which includes inhibin beta A (INHBA) (7p15-p13) and inhibin beta B (INHBB) (2cen-q13). They encode the corresponding subunits to give rise to two forms of dimeric glycoproteins (inhibin A and inhibin B) belonging to the transforming growth factor-beta (TGF-beta) family. As regards the mechanism of function, inhibins cause downregulated FSH through the inhibin/beta glycan complex, and they compete with activins (a FSH promoting factor) for binding to ACVR2 [33]. Inhibins and activins act opposingly, but regulate the FSH level together, associating with folliculogenesis. However, there is only evidence of a causative link between inhibin genes and POI. In a 136 Korean POI population, the effect of the T–G haplotype and the CT + TT/GG genotype of two INHA polymorphisms (c.-16C > T and c.-124A > G) were related to the susceptibility to POI [156]. In a recent study, both homozygous and heterozygous c.769G > A variants of INHA were shown to be correlated with POI patients from a Kashmiri cohort [76]. This study also showed increased FSH levels in POI patients, which caused accelerated follicle recruitment and premature loss of the follicular pool. This phenomenon is consistent with the characteristics observed in female mice, with an inactivated INHA mutation. An increased FSH expression level, a high ovulation rate, and impaired ovarian function appeared in the affected mice [157]. However, INHA is heterogeneous in different populations. For example, an INHA variant (G769A) is uncommon in Brazilian and Argentina POI patients, while there is a higher prevalence of G796A in Indian and Italian POI women [158]. Moreover, Ma et al. suggested that INHBB mutation (c.1095C > A) may be the cause of POI cases in Chinese Hui women [159]. Further research is warranted to elucidate the causative role of INHBB. The AMH gene is located at chromosome 7, and its protein product can only bind to AMHR2. This ensures the successful control of the AMH signaling pathway, which plays a crucial role in the development of follicles. It has been suggested that AMH can work synergistically with INHA to prevent the formation of FSH-initiated progesterone and estradiol and eventually contribute to mice reproduction [77]. Various recent studies investigated the connection between AMHR2 and POI. In 2014, two novel missense AMHR2 variants (p.I209N and p.L354F) were identified in a Chinese POI cohort [78]. However, the functional assays were not performed to establish their role in AMH signaling. Their effects were confirmed by silico analysis in 2016 [160]. The scientists chose another Chinese Han POI patient population and found a novel missense AMHR2 variant, p.Ala17Glu (A17E). Moreover, they demonstrated that p.I209N, p.L354F, and p.Ala17Glu (A17E) were all detrimental, but only the 1209N mutation harmed the AMH signaling pathway. In addition, it has been shown that other deleterious rare missense AMH mutations are associated with POI [161]. BMP15 (Xq11.22) and GDF9 (5q31.1) belong to the TGF-beta superfamily and are expressed exclusively in oocytes. They are essential for many processes associated with female fertility via forming heterodimers or homodimers to induce downstream signaling pathways [162]. BMP15 is involved in promoting follicle development during primordial gonadotropin-independent phases, controlling the sensitivity of GCs to FSH and ovulation, and avoiding depletion of GCs. GDF19 is responsible for the maturation of follicles from the primary to the secondary stage, stimulating GC proliferation, regulating various GC enzymes related to cumulus expansion, etc. [1,80]. To date, many researchers have attempted to investigate the impact of GDF9 mutations on POI. Two homozygous variants from GDF9 (c.783delC and c.604C > T, p.Gln202*) were discovered in one Brazilian POI patient and two Caucasian siblings with POI [81,163]. These two mutations caused truncated GDF9 proteins, which negatively affected the biological function of the GDF9 protein. Furthermore, the first likely POI-causing mutation influencing the regulatory region of GDF9 was identified in 2014 via high-resolution array comparative genomic hybridization (CGH) analysis [164]. As regards BMP15, its heterozygous variants are the second-most frequent causative mutant gene causes of POI. Numerous studies have assessed the pathogenesis of BMP15 heterozygous variants. Similar to GDF9, BMP15 mutations were found in two POI siblings (c.791G > A, p.R264Q, and c.1076C > T, p.P359L) [79]. These variants conformationally affect protein-surrounding water molecules and the thermal stability of BMP15. Scientists also conducted in vitro cell line experiments, which showed impaired BMP15 function. Another two studies also identified deleterious heterozygous BMP15 variants (p.N103K, p.M184T, and c.406G > C (V136L) in POI patients [165,166]. Moreover, homozygous BMP15 mutations are also implicated in POI. Zhang et al. firstly predicted the pathogenic role of its homozygous variants (c.G1070A, p.C357Y) in a Chinses POI girl from a consanguineous family [167]. More recently, another biallelic missense variant (c.1076C >T, p.Pro359Leu) was identified in a case report [168]. Although the prevalence of GDF9 and BMP15 variants in POI patients is high, there still exist idiopathic POI cases without causative mutations in these two genes, indicating the presence of heterogeneity [169]. Many studies have focused on finding new POI-causing genes, which provide idiopathic POI patients with better diagnoses and treatments and broaden the spectrum of the genetic factors implicated in POI. For example, linkers for the activation of T cells (LAT), vascular endothelial growth factor A (VEGFA), and bone morphogenic protein receptors 1A (BMPR1A) and 1B (BMPR1B) were first linked to POI in the 5 five years [82,83,84]. RNAs connect DNAs and proteins. Therefore, impaired RNA activities, including metabolism and translation, have an adverse impact on protein production. These proteins may play important roles in various biological processes, such as folliculogenesis, steroidogenesis, cell proliferation, apoptosis, etc. It is known that the migration, development, and maintenance of primordial germ cells (PGCs) cannot be finished successfully without the involvement of NANOS3 (19p13.13). NANOS3 encodes an RNA-binding protein with anti-apoptotic and translation repressive abilities. In addition, mutations in NANOS3 are associated with POI, based on the function of this gene. According to a recent article, a homozygous mutation of NANOS3 (c.358G > A, p.Glu120Lys) was found in two sisters from a Brazilian POI cohort using a mutational analysis [85]. This mutation is located at the zinc finger domain and affects the interaction of the NANOS3 protein and its target mRNA. Moreover, in vitro experiments were also conducted to evaluate and confirm the accelerated apoptosis of PGCs caused by a p.Glu120Lys mutation. However, no causative mutation of NANOS3 was found in another population of Brazilian women with POI, which indicates the heterogenicity of NANOS3, depending on different populations [170]. Aside from the Brazilian population, a novel pathogenic heterozygous NANOS3 variant (c.457C4T; p.Arg153Trp) was identified in a Chinses POI cohort [171]. The researchers also established heterozygous and homozygous p.Arg153Trp knockout mice models and identified the relationship between the dosage of functional NANOS3 and the normal development of PGCs. EIF4ENIF1 (22q11.2) encodes a nucleocytoplasmic shuttle protein, which can transport a translation-induced protein called eIF4E to repress translation via interrupting eIF4E–eIF4G binding [86]. The disrupted translation activities caused by EIF4NIF1 mutations lead to increased mRNA expression and stability, which may result in disrupted ovarian follicles and enhanced oocyte apoptosis [87]. It has been demonstrated that EIF4ENIF1 mutations are implicated in POI. The first heterozygous EIF4NIF1 mutation (c. 1286C > G, p.Ser429X) was found in all POI patients from the same family in 2013 [87]. An additional pathogenic heterozygous variant (c.2525A > C, p.Q842P) was identified in both diminished ovarian reserve (DOR) and POI cases through whole-exome and Sanger sequencing [8]. Moreover, the secondary structure of the EIF4ENIF1 protein with a p.Q842P mutation revealed the abnormal structure and length of the alpha-helix, which can influence EIF4ENIF1’s ability to regulate the translation of mRNA. In addition, two more rare EIF4ENIF1 variants (c.9_11delGAG, p.R4del and c.2861G > C p.G954A) from two Han Chinese POI women were reported in 2022 [172]. However, multiple bioinformatic tools showed that only p.G954A was detrimental. Unlike non-syndromic POI, POI can also be present in syndromic or pleiotropic Mendelian diseases. Therefore, the gene mutations that cause POI-relevant Mendelian inheritable disorders can be considered to be the genetic factors contributing to POI. The fragile X mental retardation protein (FMRP) encoded by FMR1 (Xq27.3) acts as a type of RNA-binding protein and plays an important role in regulating translation. Any deleterious mutations in FMR1 can lead to abnormally expressed FMRP. However, the expansion of trinucleotide (CGG) repeats at 5′UTR in FMR1 is the most common cause [173]. This expansion can be regarded as a pathogenic variant that contributes to different and unrelated pathologies, depending on the expanded length of CGG repeats (pleiotropy). Normally, there is an AGG triplet after every nine to ten CGG repeats, which is called AGG interruption. This is due to the existence of a sufficient number of AGG triplets for the number of CGG repeats to be maintained within a stable range, i.e., the normal alleles contain 4–55 CGG repeats [174]. The most frequent CGG length varies among different populations [175,176]. Women with 45–54 CGG repeats and 55–200 CGG repeats have gray zone (GM)/intermediate alleles and premutation (PM) alleles, respectively. Both are related to fragile X-associated primary ovarian insufficiency (FXPOI) in women from various countries, such as Turkey, India, Argentina, Brazil, and China [175,176,177,178,179,180]. According to these studies, the prevalence of POI patients with GM and/or PM alleles ranges from 1% to 9.6%. This mutation is rare in Chinese and south Indian POI patients. Nevertheless, the premutation range of the FMR1 gene is the most common aetiology among POI cases caused by single gene mutations [7,14]. Approximately 16% of women with PM alleles suffer from POI [181]. In addition, a higher percentage (34.2%) was reported in a large Turkish cohort [177]. As compared to PM alleles, the GM/intermediate repeat size seems less implicated in POI. One recent meta-analysis failed to establish a connection between the GM CGG repeat length of FMR1 and susceptibility to, or severity of, POI [182]. Moreover, several studies also indicated that there was no correlation between GM alleles and POI [183,184]. In addition, the fully mutated alleles of FMR1 (>200 CGG repeats) initiated via maternal transmission from premutation or an intermediate size are significantly correlated with fragile X syndrome [173]. To date, numerous researchers have investigated how FMR1 variants cause FXPOI, and they have attempted to explain the potential mechanisms involved. Recently, a case report reported an FXPOI woman who became spontaneously pregnant with two healthy babies [185]. In this study, a FMR1 premutation mice model was also established. These experimental mice carried a normal number of primordial follicles, a reduced number of antral follicles and corpora lutea, and an increased number of atretic large antral follicles. Therefore, it was the disrupted follicular function, not the exhausted primordial follicles, that led to FXPOI. Furthermore, another murine model in which premutation FMR1 alleles were introduced was established by scientists in 2012 [186]. It showed the impaired development of immature follicles, except for primordial follicles, which is consistent with the results of the aforementioned article. In addition, impaired luteinizing hormone (LH) and Akt/mTOR-mediated biological pathways were also associated with inducing FXPOI. Finally, abnormal FMR1 alleles were shown to produce a higher risk of reduced functional ovarian reserve (FOR) in 30–38-year-old women because they were associated with skewed X-chromosome inactivation, which contributed to a low level of AMH [187]. FOXL2 is located at 3q23, and it can be found in the ovary. It encodes the forkhead transcription factor, which is essential for maintaining ovarian somatic cells’ (GCs and theca cells) identities by preventing the transdifferention to their testicular counterpart and regulating the expression of genes involved in estrogen production, folliculogenesis, and steroidogenesis [188,189]. Mice without FOXL2 manifest impaired maturation of follicles and altered gonadotrophic production, thus affecting their fertility [190,191]. In addition, the high expression level of FOXL2 in female mice can also affect their reproductive ability by destroying the differentiation of granulosa and theca cells, influencing steroidogenesis, etc. [192]. FOXL2 mutations are associated with a type of rare and autosomal dominant syndrome, known as blepharophimosis-ptosis-epicanthus-inversus syndrome (BPES). Two types of BRES are classified according to the consequences of different mutations. POI can only be identified in BPES type I [188]. Therefore, FOXL2 is responsible for syndromic POI, and it represents the first autosomal gene related to syndromic POI [191]. A great deal of previous research into FOXL2-implicated syndromic POI is focused on Chinese populations. In Chinese families, scientists discovered various disease-causing FOXL2 variants (c.307C > T p.Arg103Cys, c.462_468del, and c.988_989insG) from BPES type I members with POI [193,194]. Moreover, researches showed two new FOXL2 mutations in Chinese families with BPES type II, but failed to link this to POI [195]. However, a case report conducted in 2019 revealed one of the two aforementioned FOXL2 mutations, showing that the FOXL2 variant (c.223C > T p.Leu75Phe) was associated with women with typical POI hormonal alteration from a BPES type I Polish family [196]. Aside from syndromic POI, FOXL2 mutations are also responsible for non-syndromic POI [72,197]. The GALT gene exists at 9q13 and encodes one of the enzymes necessary in the main galactose metabolism pathway (the Leloir pathway). The other two enzymes are galactokinase (GALK) and UDP galactose 4-epimerase (GALE). The functional-affecting disorders of any of these three enzymes can lead to impaired galactose metabolism and eventually galactosemia. Recently, pathogenic mutations in the galactose mutarotase (GALM) gene were identified in patients with unexplained galactosemia, giving rise to a new type of galactosemic [198]. Classical galactosemia (GC) and Duarte galactosemia (DG) are caused by mutations in GALT. As a symptom of hypergonadotropic hypogonadism, POI is one of the long-term complications of GC, while it has not been observed in DG female patients [199,200,201]. Moreover, the prevalence of POI in GC patients is high. Over 90% of GC patients exhibited signs of POI [202]. Thus far, the exact mechanism of POI in galactosemia has not been discovered. However, studies over the past 10 years have highlighted many potential mechanisms, including (1) ovarian damage caused by the toxic effects from accumulated galactoses and/or their metabolisms; (2) alteration of the function of FSH resulting from impaired glycosylation; (3) defects in the development of follicles, germ cells functions, and steroidogenesis, due to low levels of UDP-glucose (UDP-Glc) pyrophosphorylase and UDP galactose (UDP-Gal); (4) aberration of cell signaling pathways, such as the PI3K/AKT/mTOR signaling pathway; and (5) epigenetic mechanisms [203,204]. As regards specific GALT variants in galactosemia patients with POI, p.Q188R and p.K285N are the most common mutations, accounting for 70% of cases [7]. Although a low pregnancy rate (5–10%) is generally reported among POI patients, women with POI and galactosemia can still become pregnant spontaneously [205,206]. Polyendocrinopathy candidiasis ectodermal dystrophy (APECED)/autoimmune polyendocrinopathy syndrome type I (APS1) is a rare monogenic autoimmune disease. It is characterized by two out of three of the following clinical manifestations: chronic mucocutaneous candidiasis (CMC), hypoparathyroidism, and primary adrenal insufficiency (Addison’s disease). In addition, deleterious mutations in the autoimmune regulator gene (AIRE) can confirm the diagnosis of APECED [207]. Aside from these three major clinical manifestations, other features, such as POI, are also observed in APECED patients. The literature review revealed that, in a large cohort of APECED patients from various countries, the prevalence of gonadal failure ranged from 0 to 70% [208]. It was also reported that the female-to-male ratio of hypergonadotropic hypogonadism was 7:1 in North America. Moreover, there is a considerable body of literature on finding AIRE variants in APECED patients. Various homozygous and heterozygous pathogenic AIRE variants (c.967_979delCTGTCCCCTCCGC, p.(L323SfsX51); c.995 + (3_5)delGAGinsTAT, NM_000383.2: c.623G > T, NP_000374.1: p.Gly208Val; c.967_979del13bp; c.396G > C (p.Arg132Ser; p.R132S) and (c.47C > T, p.Thr16Met)) were observed in APS1 women with POI as a symptom [209,210,211,212,213]. As regards the toxic effects of AIRE mutations on the ovaries, loss-of-function AIRE can cause ovarian autoimmune disease by repressing the antigen expression levels specific to the ovaries. In female mice without AIRE, follicular depletion and an exhausted ovarian reserve were observed, indicating a potential mechanism in female infertility [214]. Aside from the pleiotropic and syndromic disorders that were discussed in detail previously, there are also many studies from the last 10 years that revealed gene mutations that cause various syndromes (ataxia telangiectasia, Nijmegen breakage syndrome, Alagille syndrome, Mulibrey nanism disorder, and congenital disorders of glycosylation) that are characterized with POI [108,215,216,217,218]. The mitochondrion is a common organelle in most eukaryotic cells. It plays an essential role in producing energy via oxidative phosphorylation. Therefore, abnormalities in mitochondrial functions are associated with a wide range of human diseases, including POI. In fact, any perturbations in mitochondria can severely affect the ovaries because the ovaries contain the maximum number of mitochondria. As regards the genetic factors related to mitochondrial dysfunction, mutations in nuclear and mitochondrial genes are responsible for POI. According to recent studies, required for meiotic nuclear division 1 homolog (RMND1), mitochondrial cytochrome c oxidase 1 (MT-CO1), nuclear-encoded gene mitochondrial ribosomal protein S22, (MRPS22), caseinolytic peptidase B (CLPB), and mitochondrial transcription factor A (TFAM), variants were reported in POI, and their pathogenic roles were confirmed [219,220,221,222,223] (Table 2). In addition, mutations in the genes that regulate mitochondrial activities or functions can also lead to POI. In 2021, Feng et al. demonstrated that a leucyl-tRNA synthetase 2 (LARS2) variation increased the amount of mitochondrial reactive oxygen species (ROS), decreased the number of mitochondrial DNA (mtDNA) copies and ATP, and reduced the expression level of a mitochondrial fusion-related gene known as mitofusin-2 (Mfn-2), which is one of the pathogenic mechanisms of POI (impaired mitochondrial function in granulosa cells) [224]. Furthermore, by establishing a POI mice model, scientists observed conformational changes (swollen mitochondria, decreased matrix density, and marginally shifted cristae) in mitochondria from granulosa cells of POI mice [225]. In addition, a low level of mitochondrial oxidative phosphorylation complexes (OXPHOS) also existed in the POI group. This resulted from a Sirtuin 1 (SIRT1) mutation. Additionally, a new variation in alanyl-tRNA synthetase 2 (AARS2) was identified in a Chinese consanguineous family, resulting in impaired translation activity in mitochondria implicated in POI [226]. Establishing the role of non-coding RNAs (ncRNAs) in POI is an emerging research area. It will help us in understanding the genetic effects of POI and provide important information on POI pathogenesis. NcRNAs can be divided into small ncRNAs (sncRNAs) and long ncRNAs (lncRNA), and they contribute to regulating various biological processes, such as cell proliferation and apoptosis, rather than giving rise to proteins [227]. They usually have an influence on ovarian function by interacting with their corresponding target genes. MicroRNAs (miRNAs), as one essential sncRNA type, are closely related to POI. Increasing levels of both microRNA-379-5p and microRNA-127-5p were observed in the GCs of biological POI (bPOI) patients. They had an adverse impact on GCs proliferation and the ability to repair DNA damage through targeting poly ADP-ribose polymerase 1 (PARP1) (microRNA-379-5p), X-ray repair cross complementing 6 (XRCC6) (microRNA-379-5p), and high mobility group box 2 (HMGB2) (microRNA-127-5p) [228,229]. In addition, the suppression of the B-cell lymphoma 9 (BCL9) level initiated by upregulated microRNA-122-5p was shown to promote GCs apoptosis in POI mice [230]. Distinct from the miRNA mentioned previously, microRNA-22-3p acts as a protective factor for POI, which was demonstrated in a receiver operating characteristic (ROC) curve, logistic binary regression, and bioinformatics analysis [231]. Aside from miRNAs, lncRNAs are also critical in POI development. According to a recent study, accelerated GCs apoptosis was observed due to downregulated lncRNA HCP5 in a Chinese bPOI cohort, which led to a lower nuclear level of YB1 and eventually induced the obstructed transcription of a critical POI candidate gene, known as MSH5 [232]. Moreover, the lower expression of another lncRNA, known as PVT1, was also shown to disrupt ovarian function in POI patients. These deleterious effects were demonstrated in a POI mice model [233]. Many strategies are used to establish the genetic factors related to POI, and these factors will guide future POI prediction, diagnosis, and treatment protocols. Chromosome analysis (karyotyping) is the main method for discovering abnormalities in chromosomes. Approximately 10–13% of POI cases are associated with chromosomal abnormalities, such as mosaicism 45, X/46, XX. Therefore, chromosome analysis is not only helpful in identifying POI-related chromosomal variations, but also plays an important role in the clinical evaluation and diagnosis of POI. Moreover, for small duplications and deletions that cannot be detected under a microscope, array comparative genomic hybridization (CGH) is the better choice. In 2022, CGH was performed in a Tunisian family [234]. The study suggested that EIF1AX duplication might lead to POI after a familial tandem duplication in Xp22.12 was identified. In addition to chromosome variation, GWAS, WES, and NGS are used to more effectively and efficiently detect single gene mutations than classical methods. In addition, the strong POI component and the similar genetic background among family members make family analyses important in investigating the genetic causes of POI. As a result of GWAS, many loci that are potentially responsible for POI have been disclosed in Chinese, Korean, and Dutch women [14]. Moreover, via NGS, various POI-related genes involved in meiosis and DNA repair have been identified, enriching the genetic etiology of POI [235]. The contributions of GWAS and NGS are indisputable, and they will certainly be applied more widely in the future. As regards WES, it has revealed many POI-related genes involved in DNA damage repair and HR, and its application will also be of great importance in the future. Recently, several in vitro cellular models have been successfully used to demonstrate that certain rare genomic variants can cause mutations and dysfunction of the corresponding proteins, thus confirming the association between these variants and POI [236,237]. Once new deleterious variations are found, they can be used to predict the age of menopause [236]. Thus, this review may be useful in large genetic screening research for POI and in regulating fertility in women. Taken together, the genetic factors of POI confirmed in different tests can be used as the basis for POI diagnosis and risk prediction protocols. Reproductive and genetic counseling is essential for women with POI or those at risk of POI. It can help women select when to attempt pregnancy and increase the possibility of pregnancy through other methods, such as assisted reproductive technologies, oocyte or embryo cryopreservation, etc. [11]. In order to fully understand the genetic causes of POI, many challenges remain. Future research will be designed to this end. First, the mechanisms involved in POI that are caused by certain genetic factors are unclear. For example, although TS is ubiquitous in POI patients, the exact pathogenesis of TS-causing POI remains unknown. Second, less attention has been paid by scientists in recent years to certain areas, such as TXS and structural chromosomal abnormalities. Third, many genes, such as MCL-1, have been shown to be associated with POI, but their causative role has not been confirmed. Even for genes whose mutations have been demonstrated to cause POI, many of their variants have not been connected with POI. Fourth, because of the heterogeneous nature of POI and the multiple modes of mutational spread, the prevalence and type of gene mutations are distinct among POI women of different ethnicities and different POI populations. Therefore, in the future, population stratification will be vital when analyzing genetic alterations. Fifth, the experimental results obtained from mouse models are not all applicable to humans because there are genetic and physiological differences between mice and humans. Moreover, the mouse models cannot deal with the extremely complex interactions among molecules, cells, organs, organisms, and the environment. Finally, according to many recent studies, digenic and oligogenic effects on POI have been observed, demonstrating that POI may not be a completely monogenic disease [40,72]. These are the questions that need to be addressed in the future. In conclusion, the present review summarizes the genetic effects of POI in different fields (chromosomal variations, single gene mutations, impaired mitochondrial functions, and abnormal levels of non-coding RNAs). The findings clearly indicate that examining various genetic factors is crucial in determining the underlying etiologies of idiopathic POI cases. Therefore, this work summarizes and enriches our knowledge of POI etiology by providing the latest information concerning the selected genetic causes of POI obtained from patients and experimental animal models. However, this article is limited, as it only focuses on genetic causes.

PMC10002967

Elena V. Grigor’eva,Alena E. Kopytova,Elena S. Yarkova,Sophia V. Pavlova,Diana A. Sorogina,Anastasia A. Malakhova,Tuyana B. Malankhanova,Galina V. Baydakova,Ekaterina Y. Zakharova,Sergey P. Medvedev,Sofia N. Pchelina,Suren M. Zakian

Biochemical Characteristics of iPSC-Derived Dopaminergic Neurons from N370S GBA Variant Carriers with and without Parkinson’s Disease

23-02-2023

induced pluripotent stem cells,neural differentiation,dopaminergic neurons,glucocerebrosidase,mutation in the GBA gene,asymptomatic mutation carrier,ambroxol

GBA variants increase the risk of Parkinson’s disease (PD) by 10 times. The GBA gene encodes the lysosomal enzyme glucocerebrosidase (GCase). The p.N370S substitution causes a violation of the enzyme conformation, which affects its stability in the cell. We studied the biochemical characteristics of dopaminergic (DA) neurons generated from induced pluripotent stem cells (iPSCs) from a PD patient with the GBA p.N370S mutation (GBA-PD), an asymptomatic GBA p.N370S carrier (GBA-carrier), and two healthy donors (control). Using liquid chromatography with tandem mass spectrometry (LC-MS/MS), we measured the activity of six lysosomal enzymes (GCase, galactocerebrosidase (GALC), alpha-glucosidase (GAA), alpha-galactosidase (GLA), sphingomyelinase (ASM), and alpha-iduronidase (IDUA)) in iPSC-derived DA neurons from the GBA-PD and GBA-carrier. DA neurons from the GBA mutation carrier demonstrated decreased GCase activity compared to the control. The decrease was not associated with any changes in GBA expression levels in DA neurons. GCase activity was more markedly decreased in the DA neurons of GBA-PD patient compared to the GBA-carrier. The amount of GCase protein was decreased only in GBA-PD neurons. Additionally, alterations in the activity of the other lysosomal enzymes (GLA and IDUA) were found in GBA-PD neurons compared to GBA-carrier and control neurons. Further study of the molecular differences between the GBA-PD and the GBA-carrier is essential to investigate whether genetic factors or external conditions are the causes of the penetrance of the p.N370S GBA variant.

Biochemical Characteristics of iPSC-Derived Dopaminergic Neurons from N370S GBA Variant Carriers with and without Parkinson’s Disease GBA variants increase the risk of Parkinson’s disease (PD) by 10 times. The GBA gene encodes the lysosomal enzyme glucocerebrosidase (GCase). The p.N370S substitution causes a violation of the enzyme conformation, which affects its stability in the cell. We studied the biochemical characteristics of dopaminergic (DA) neurons generated from induced pluripotent stem cells (iPSCs) from a PD patient with the GBA p.N370S mutation (GBA-PD), an asymptomatic GBA p.N370S carrier (GBA-carrier), and two healthy donors (control). Using liquid chromatography with tandem mass spectrometry (LC-MS/MS), we measured the activity of six lysosomal enzymes (GCase, galactocerebrosidase (GALC), alpha-glucosidase (GAA), alpha-galactosidase (GLA), sphingomyelinase (ASM), and alpha-iduronidase (IDUA)) in iPSC-derived DA neurons from the GBA-PD and GBA-carrier. DA neurons from the GBA mutation carrier demonstrated decreased GCase activity compared to the control. The decrease was not associated with any changes in GBA expression levels in DA neurons. GCase activity was more markedly decreased in the DA neurons of GBA-PD patient compared to the GBA-carrier. The amount of GCase protein was decreased only in GBA-PD neurons. Additionally, alterations in the activity of the other lysosomal enzymes (GLA and IDUA) were found in GBA-PD neurons compared to GBA-carrier and control neurons. Further study of the molecular differences between the GBA-PD and the GBA-carrier is essential to investigate whether genetic factors or external conditions are the causes of the penetrance of the p.N370S GBA variant. Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer’s disease. There are over 90 known genetic loci associated with the development of PD [1]. Among them, genetic variants in the GBA gene attract special attention due to their prevalence and the emerging risk of developing PD associated with a decrease in lysosomal function [2]. It is known that, in PD, the frequency of GBA mutations reaches 10%, while the risk of PD development among individuals carrying GBA mutations increases up to 20 times based on ethnicity [3,4]. However, the penetrance of PD among carriers of GBA pathogenic variants is estimated at 10–30%, indicating that the majority of mutation carriers will never develop PD. Therefore, it is extremely important to understand the pathological molecular mechanisms leading to the development of the disease to search for targets and possible approaches to the treatment of PD associated with mutations in the GBA gene (GBA-PD). The GBA gene encodes the lysosomal enzyme beta-glucosylceramidase (GCase), which cleaves sphingolipids, in particular glucosylceramide, into glucose and ceramide. The homozygous state GBA mutations cause Gaucher disease, a systemic lysosomal storage disorder, characterized by a deficiency in GCase enzymatic activity and impaired glucolipids catabolism. More than 480 mutations are reported in the GBA gene (The Human Gene Mutation Database (HGMD) professional 2021.4.1, 5 March 2022). The two most common variants, N370S (43%) and L444P (20%), have different impacts on the GCase activity [5]. Both mutations are not located within the GCase active center but lead to GCase misfolding. Pharmacological chaperones are chemical compounds with low molecular weight, often hydrophobic, that can specifically bind to a mutant enzyme, correct its folding, and promote translocation into lysosomes [6]. Ambroxol, a well-known mucolytic agent, is currently one of the most promising GCase pharmacological chaperones. Ambroxol has been shown to restore GCase activity and protein levels, as well as reduce the lysosphingolipid concentration in different patient-derived cell types, including dopaminergic neurons [7,8,9,10]. Ambroxol has also demonstrated its efficiency in several ongoing clinical trials involving Gaucher disease and PD patients [11,12]. The mechanism of PD pathogenesis in GBA mutation carriers remains unclear. Previously, the decrease in GCase enzymatic activity in the blood of PD patients with mutations in the GBA gene was reported [13,14,15]. Recently, we have shown that GCase activity in blood is decreased in GBA mutation carriers, independently of PD status [16]. The technology of reprogramming somatic cells, such as peripheral blood mononuclear cells (PBMCs), to a pluripotent state makes it possible to create bioresource collections of immortal patient-specific induced pluripotent stem cells (iPSCs) with various pathologies caused by genetic mutations. The advantage of the technology is its capability to produce any type of highly specialized cell through the direct differentiation of iPSCs. This method allows for the in vitro modeling of almost any genetic disorder by generating relevant cell types suffering from the disease of interest. Today, numerous iPSCs-derived dopamine neuronal cells have been obtained from patients with Gaucher disease and GBA-PD [17,18,19,20]. The N370S mutation lines are characterized by reduced GCase activity and protein levels compared to controls [19,20]. Recently, the decrease in GCase activity was also demonstrated in a cholinergic N370S GBA mutation model [7]. However, there is only one study that estimated the GCase activity in a neuronal model of healthy GBA mutation carriers [21]. Here, we obtained dopaminergic (DA) neurons from iPSCs from GBA-PD and non-manifesting GBA-carrier individuals to compare the biochemical effects of the N370S GBA mutation and evaluate the influence of ambroxol on GBA expression, GCase activity, and protein levels. We measured GCase enzymatic activity as well as the activity of five other lysosomal hydrolases (galactocerebrosidase (GALC, EC 3.2.1.46, deficient in Krabbe disease), alpha-glucosidase (GAA, EC 3.2.1.20, deficient in Pompe disease), alpha-galactosidase (GLA, EC 3.2.1.22, deficient in Fabry disease), sphingomyelinase (ASM, EC 3.1.4.12, deficient in Niemann–Pick disease types A and B), and alpha-iduronidase (IDUA, EC 3.2.1.76, deficient in mucopolysaccharidosis type I)) in DA neurons from the GBA-PD and GBA-carrier. Further studies of the molecular differences between the GBA-PD and GBA-carrier DA neurons are essential for an investigation into whether genetic factors or external conditions play a role in the penetrance of the p.N370S GBA variant. The analysis of the clinical exome sequencing data of two individuals (a 56-year-old woman (PD30) with PD and her healthy 32-year-old son (PD31)) was performed. Bioinformatic analysis revealed that both patients harbor a pathogenic heterozygous missense mutation c.1226A>G (p.N370S, rs76763715) in the GBA gene. Here, we referred to the PD30 patient as a GBA-PD and the asymptomatic carrier PD31 as a GBA-carrier. We identified around 15000 SNVs in each patient, including around 8500 SNVs reported in the ClinVar database (Table S2). The clinically significant SNVs are reported in Table S3. The pathogenic and risk factor genetic variants in the SOX2, FBXO38, and RNASEL genes are the possible candidates for the modifiers of the disease manifestation, since the mentioned SNVs were found in the GBA-PD patient’s exome and were absent in the GBA-carrier (FBXO38 and RNASEL), or were present in the homozygous state of GBA-PD and are heterozygous in the GBA-carrier (SOX2) (Table S3). The search for polymorphisms in PD-associated genes revealed 48 SNVs, all of which are marked as benign in the ClinVar database (Table S4). Therefore, it seems unlikely that the identified SNVs in PD-associated genes have an effect on the GBA mutation penetrance. PBMCs-derived IPSC lines from the GBA-PD patient (https://hpscreg.eu/cell-line/ICGi034-A; https://hpscreg.eu/cell-line/ICGi034-B; https://hpscreg.eu/cell-line/ICGi034-C; all accessed on 17 February 2023) [22] and GBA-carrier (https://hpscreg.eu/cell-line/ICGi039-A; https://hpscreg.eu/cell-line/ICGi039-B; https://hpscreg.eu/cell-line/ICGi039-C; all accessed on 17 February 2023) were characterized and registered in the Human Pluripotent Stem Cell Registry (hPSCreg). The detailed characteristics of three GBA-carrier lines are presented in the Supplementary Materials (Figures S1–S3). As the control lines, we used iPSCs obtained from healthy individuals (https://hpscreg.eu/cell-line/ICGi021-A; https://hpscreg.eu/cell-line/ICGi022-A; all accessed on 17 February 2023) [23]. To create a cell platform for drug screening, the cells of iPSC lines derived from GBA-PD, GBA-carrier, and control lines were differentiated into DA neurons, which are the relevant type of cells affected in PD. Directed differentiation was carried out according to the previously published protocols [24,25,26,27,28]. The cells were cultured in a dense monolayer on the growth factor-reduced extracellular matrix Matrigel (Matrigel-GFR) in the culture medium containing growth factors and inhibitors that promote the triggering of signaling pathways that simulate neurulation during the early development of the embryo in vivo. Figure 1a shows the complete differentiation scheme. At the preparatory stage, iPSCs (Figure 1b,e) were transferred from mouse embryonic fibroblasts (MEF) onto Matrigel-GFR. It should be noted that the most efficient differentiation occurs when a dense monolayer of iPSCs (90–100% of confluency) is plated onto Matrigel for 24 h before the start of differentiation. At the first stage, iPSCs differentiation in the neuroectodermal direction was stimulated using double SMAD inhibition [25], with the addition of the small molecules LDN193189 and SB431542. These factors suppress pluripotency gene expression and inhibit differentiation in the mesodermal and endodermal directions. The addition of CHIR99021 on days 3–13 of differentiation directs neural progenitor cells to midbrain cells and contributes to a better output of DA neurons. Sonic hedgehog (SHH), FGF8b, and purmorphamine also increase the efficiency of directed differentiation into DA neurons [28,29,30]. During the 11 days of cultivation, there was a multifold increase in cell number with the formation of convex structures consisting of one type of cell (Figure 1c). These cells express the early markers of neuroectoderm (PAX6, SOX1, and OTX2), as well as the marker of DA neuron precursors, LRTM1 [31] (Figure 1f). On day 11, a dense monolayer of cells was disaggregated and seeded onto Matrigel-GFR with the addition of a ROCK inhibitor to the culture medium. On the 13th day of differentiation, the factors necessary for obtaining mature neurons (BDNF, TGFb3, GDNF, and dbcAMP) were added to the cells, and cell cultivation continued at a high density with weekly passaging and the freezing of some leftover cells. The advantage of this protocol is the possibility of collecting a large mass of DA neuron progenitor cells, some of which can be frozen and, if necessary, thawed, and further terminal differentiation can be carried out. This greatly simplifies further experiments on obtaining terminally differentiated DA neurons and their use in various experiments. We analyzed the expression of the genes specific for neuronal DA precursors (LMX1A) and neuroectodermal markers (SOX1 and OTX2) in progenitor cells at differentiation day 34 after 23 days of cultivation at high density in the presence of BDNF, GDNF, TGFb3, and cAMP. Using flow cytometry, we showed that the majority of differentiated cells (98.5–99.6%) were precursors of DA neurons (Figure 2b and Figure S4). For terminal differentiation into DA neurons, neural progenitors were seeded in low density with the addition of the gamma-secretase inhibitor Compound E to the culture medium. Neurons were characterized by immunofluorescence staining and qPCR, which demonstrated expression of tyrosine hydroxylase (TH), a specific marker of DA neurons, and DA-specific transcription factors LMX1A, LRTM1 [28], and a member of the nuclear receptor superfamily of transcription factors NURR1 [29], as well as the common neuronal marker Tubulin β3 (TUBB3/TUJ1) (Figure 1g). The qPCR analysis showed a significant increase in the expression of the TH, LMX1A, and NURR1 genes in DA neurons compared to the expression in iPSCs (Figure 2a). The resulting neural derivatives were cultured for 3 weeks in the presence of 50 μM ambroxol. We performed qPCR analysis of GBA expression in DA neurons derived from the GBA-PD, GBA-carrier, and control iPSCs before and after ambroxol treatment, in triplicate for each group. B2M and TFRc served as reference genes for data normalization. Our data demonstrated the absence of significant differences in GBA expression between the studied groups (Figure 2c). Measuring the enzymatic activities of six lysosomal enzymes (GCase, GALC, GAA, GLA, ASM, and IDUA) was carried out by liquid chromatography combined with tandem mass spectrometry (LC-MS/MS). We used substrates and internal standards of the Centers for Disease Control and Prevention (Atlanta, GA, USA) as described earlier for primary macrophage culture [15] with modifications. GCase activity was lower in iPSCs-derived DA neurons from the GBA-PD and GBA-carrier compared to controls (p-value < 0.0001 and p-value = 0.018, respectively) (Table 1) (Figure 3, blue). Moreover, we found differences in GCase activity between the GBA-PD and GBA-carrier (p-value = 0.025) (Table 1). In our study, activity of the GLA and IDUA enzymes was higher in DA neurons from GBA-PD patients compared to controls (p-value = 0.008 and p-value < 0.0001, respectively) as well as the GBA-carrier (p-value = 0.002 and p-value < 0.0001, respectively) (Table 1). GALC activity was lower in DA neurons from the GBA-PD compared to the GBA-carrier (p-value = 0.045) (Table 1). We analyzed GCase enzyme activity before and after ambroxol treatment. Ambroxol caused a significant increase in GCase activity in iPSCs-derived DA neurons of both mutation carriers (GBA-PD and GBA-carrier) compared to untreated cells (Figure 3, red). Western blot analysis was performed on samples of iPSCs-derived DA neurons with the GBA mutation and the control group to quantify the GCase protein (Figure 4 and Figure S5). We showed a decrease in the GCase protein level in neurons obtained from GBA-PD compared to the control (p-value = 0.021) (Figure 4, blue). Ambroxol led to a significant increase in the amount of the protein, both in the DA neurons of the GBA-carrier (p-value = 0.038) and the GBA-PD (p-value = 0.021) (Figure 4, red). Our study describes the difference in biochemical characteristics between DA neurons obtained by the differentiation of iPSCs from heterozygous GBA N370S carriers with and without PD and the effect of ambroxol on GCase activity and protein level. PBMC reprogramming technology allowed us to generate iPSC lines from two patients carrying the heterozygous N370S mutation in the GBA gene (https://hpscreg.eu/cell-line/ICGi034-A; https://hpscreg.eu/cell-line/ICGi034-B; https://hpscreg.eu/cell-line/ICGi034-C and https://hpscreg.eu/cell-line/ICGi039-A; https://hpscreg.eu/cell-line/ICGi039-B; https://hpscreg.eu/cell-line/ICGi039-C; all accessed on 17 February 2023). The iPSC lines obtained meet all the criteria for pluripotent stem cells. These lines, as well as previously obtained control iPSCs from healthy individuals, were differentiated into DA neurons using growth factors and inhibitors that simulate events occurring in the embryo during neurogenesis in vivo. Expression of the transcription factors, such as PAX6, SOX1, and OTX2, at the early stages of differentiation indicated that iPSCs were successfully differentiated in the neuroectodermal direction. Moreover, we carried out the long-term cultivation of cells at high density for three weeks in the presence of BDNF, GDNF, TGFb3, and cAMP. It was shown that 98.5–99.6% of cells were SOX1-, OTX2-, and LMX1A-positive, which indicates that the cells can be maintained in the state of precursors for a long time. Cultivation in a low density in the presence of Compound E caused maturation and aging of neurons, resulting in a significant increase in the expression of specific markers of DA neurons TH, NURR1 and LMX1A. Previously, lower GCase activity in GBA-PD compared to controls was shown using various biological samples and in vitro models (including blood, CSF, postmortem brain, mononuclear cells, fibroblasts, and iPSC-derived neurons) [10,17,32,33,34,35]. Later, we and other researchers assessed GCase activity in the blood and mononuclear cells of GBA-carriers and demonstrated that GCase activity is also reduced in healthy GBA mutation carriers without PD and could not discriminate PD status in GBA mutation carriers [16,36]. The lysosphingolipid concentration was suggested as a more sensitive biomarker of GCase deficiency in patients with Gaucher disease [37]. Few studies compared lysosphingolipid concentrations in the blood of GBA-PD and GBA-carriers [16,38]. We were the first to demonstrate that GBA-PD patients had increased blood hexosylsphingosine concentrations compared to GBA-carriers [16]. However, biochemical characteristics in the blood may not reflect those in DA neurons. Here, for the first time, we measured the activities of six lysosomal enzymes (GCase, GALC, GAA, GLA, ASM, and IDUA) in DA neurons from the GBA-PD and GBA-carrier. In this study, we found that GBA-PD had lower GCase activity and higher GLA and IDUA activities compared to controls as well as the GBA-carrier. Recent studies in sporadic PD have identified variants in multiple genes linked to lysosomal storage disorders [39]. The activity of GLA (deficient in Fabry disease) in the blood was found to be reduced in PD [40,41,42] and GBA-PD patients [15]. Interestingly, elevated GLA activity in the blood was reported in LRRK2-PD patients [41] and patients with one of the forms of synucleinopathies (multiple system atrophy) [43]. Previously, we showed increased GLA expression levels and activity in the blood of patients with multiple system atrophy but not in PD [43]. Mutations in the ASM gene (SMPD1), responsible for Niemann-Pick type A/B, have also been associated with PD [44]. Previously, Alcalay et al. showed decreased ASM activity and increased alpha-synuclein levels in the blood of PD patients [44]. In our study, we did not observe any differences in ASM and GALC activity in GBA mutation carriers (with and without PD). The reason for the increased GLA and IDUA activity in DA neurons in GBA-PD patients is currently unclear. Further research is required to assess the role of lysosomal enzymes and their interactions in the pathogenesis of GBA-PD. We discovered decreased GCase activity in DA neurons of N370S GBA mutation carriers independent of PD status. However, a reduction in GCase activity was more evident in DA neurons obtained from PD patients than in the non-manifesting GBA-carrier. Woodard et al. studied midbrain dopaminergic neurons derived from twins carrying heterozygous GBA N370S and showed lower GCase activity and protein levels as well as an increase in alpha-synuclein levels in GBA-PDs and GBA-carriers [21]. Compared to Woodard et al.’s observations, in the present study, we showed reduced GCase protein levels in DA neurons from the GBA-PD compared to controls, but not in DA neurons from the healthy GBA-carrier. Previously, McNeill et al. showed reduced GCase activity and protein level in fibroblasts from GBA mutation carriers (with and without PD) [10]. In contrast to our data, McNeill did not report any differences between GBA-PD and GBA-carrier iPSC-derived DA neurons in GCase activity. It should be noted that in McNeill’s study, both groups included subjects with different severities of GBA mutations. On the other hand, we could not exclude the possibility that a reciprocal relationship between alpha-synuclein level and GCase activity resulting in a GCase trafficking defect, lysosomal dysfunction, and substrate accumulation depends on cell type and could be detected in DA neurons. While we have not measured the lysoshingolipid and alpha-synuclein levels, further investigations are warranted to clarify the relationship between GCase deficiency and neurodegeneration in PD. A promising GCase-targeted therapy is molecular chaperones. Two types of molecular chaperones exist: inhibitory chaperones, which bind to the active site of the GCase protein, and noninhibitory chaperones, which bind to an alternate site on the GCase surface [45]. Ambroxol is a pH-dependent mix-type chaperone of GCase [46]. Previously, we constructed an atomistic model of the mutant N370S GCase, and using molecular docking and molecular dynamics, we confirmed that ambroxol appeared to be a mixed-type inhibitor of GCase. A novel allosteric binding site for ambroxol on the GCase surface was identified, located next to the substituent residue S370 under loop L1 (311–319 amino acid residues) [9]. Previously, ambroxol was shown not only to increase GCase activity but also to reduce lysosphingolipids and alpha-synuclein pathology in DA and cholinergic neurons of N370S GBA-PD [20,46]. The ambroxol efficiency was also demonstrated in patent-derived fibroblasts [10] and primary macrophages culture [9] as well as on animal models of GBA-PD (Drosophila, mouse midbrain and non-human primate brain) [47,48,49]. In accordance with all previous data, we showed that ambroxol successfully chaperoned GCase activity in iPSC-derived DA neurons from GBA-PD patient. In addition, we showed the same effect on iPSC-derived DA neurons from healthy GBA mutation carrier. Ambroxol increased both GCase activity and protein level in DA neurons independently from PD status and did not alter GBA expression. Thus, we first showed that biochemical characteristics, namely the activities of lysosomal hydrolases, may differ in iPSC-derived DA neurons from GBA-PD patients and healthy GBA-carriers. The biomaterial was collected at the FSBI Federal Neurosurgical Center with the permission of the ethics committee (Protocol number 1, 14 March 2017) and after the patients signed the informed consent and information sheet. All research is conducted anonymously. Clinical exome sequencing was performed on DNA samples from the patients’ PBMCs. The library was made using the NEBNext Ultra DNA Library Prep Kit (New England Biolabs, Ipswich, MA, USA) for Illumina, followed by double barcoding with NEBNext Multiplex Oligos for Illumina (New England Biolabs, Ipswich, MA, USA), quality control with the Agilent Bioanalyzer 2100, enrichment with the SureSelectXT Target Enrichment System (Agilent Technologies, Santa Clara, CA, USA), and sequencing in Rapid Run Mode. Raw reads obtained from Illumina HiSeq 2500 (PRJNA563295, BioSample accession SAMN22788974 (https://www.ncbi.nlm.nih.gov/biosample/22788974, accessed on 17 February 2023), and SAMN26587088 (https://www.ncbi.nlm.nih.gov/biosample/26587088, accessed on 17 February 2023)) were cleaned, filtered, and aligned to the GRCh37 human reference genome with appropriate quality control. Germline variants were called with the GATK pipeline using best practices, annotated with several databases, carefully filtered, and prioritized. The Genomenal NGSWizard software (https://genomenal.com/, accessed on 17 February 2023) was used to run data processing pipelines. Pipelines are the launch of the following programs: FastX Toolkit for reads processing, BWA MEM for aligning reads to the reference genome (hg38), GATK v.4.1.0.0 for calling SNP with subsequent annotation. The single nucleotide polymorphism rs76763715 (c.1226A>G, p.N370S), which was found in the GBA gene, was confirmed by Sanger sequencing. PCR was performed using primers from Table S1. Reactions were run on a T100 Thermal Cycler (Bio-Rad Laboratories, Singapore) using BioMaster HS-Taq PCR-Color (2×) (Biolabmix, Novosibirsk, Russia) with the following program: 95 °C for 3 min; 35 cycles: 95 °C for 30 s; 60 °C for 30 s; 72 °C for 30 s; and 72 °C for 5 min. Sanger sequencing reactions were performed with the Big Dye Terminator V. 3.1. Cycle Sequencing Kit (Applied Biosystems, Austin, TX, USA) and analyzed on an ABI 3130XL Genetic Analyzer at the SB RAS Genomics Core Facility (http://www.niboch.nsc.ru/doku.php/corefacility, accessed on 17 February 2023). DNA was isolated using Quick-DNA Miniprep Kit (Zymo Research, Irvine, CA, USA) for STR analysis or extracted by QuickExtract™ DNA Extraction Solution (Lucigen, Madison, WI, USA) for the GBA gene mutation analysis PCR, episome and mycoplasma detection. iPSCs were cultivated in the growth medium containing KnockOut DMEM, 15% KnockOut Serum Replacement, GlutaMAX-I, 0.1 mM NEAA, 1% penicillin-streptomycin (all from Thermo Fisher Scientific, Waltham, MA, USA), 0.1 mM 2-mce (Sigma-Aldrich, Darmstadt, Germany), and 10 ng/mL bFGF (SCI Store, Moscow, Russia) onto a gelatin-coated plate with mouse embryonic fibroblasts (MEF) treated with Mitomycin C from Streptomyces caespitosus (Sigma-Aldrich, Darmstadt, Germany). For DA differentiation, iPSCs were passaged onto Matrigel-GFR (Corning, New York, NY, USA) in Essential 8 Medium (Thermo Fisher Scientific, Waltham, MA, USA). iPSCs were passaged 2 times a week at a ratio of 1:8–1:10 with the addition of 2 μg/mL Thiazovivin (Sigma-Aldrich, Darmstadt, Germany). Dissociation of iPSC colonies was carried out using TrypLE (Thermo Fisher Scientific, Waltham, MA, USA). Cells were cultured in a CO2 incubator (37 °C, 5% CO2). Directed differentiation of iPSCs into DA neurons was performed according to a previously published protocol [26], with modifications. The iPSCs were plated at a high density onto Matrigel-GFR-treated plates so that the cell monolayer reached 80–100% confluency the next day. The culture medium was changed to one containing F12/DMEM:Neurobasal (1:1), 0.5× N-2 Supplement, 0.5× B-27 Supplement minus vitamin A, GlutaMAX™ Supplement, 1× penicillin-streptomycin (all from Thermo Fisher Scientific, Waltham, MA, USA), and 200 µM ascorbic acid (Sigma-Aldrich, Darmstadt, Germany). Next, growth factors, inhibitors, and small molecules were added to the cells according to the scheme (Figure 1). Concentrations of growth factors, inhibitors, and small molecules are presented in Table 2. On the 11th day of differentiation, the cell monolayers were passaged using StemPro™ Accutase™ (Thermo Fisher Scientific, Waltham, MA, USA) in the ratio 1:2 with the addition of ROCK inhibitor. On the next day, BDNF, GDNF, TGFb3, and dbcAMP (all from PeproTech, Cranbury, NJ, USA) were added to the culture medium. Cells were passaged once a week in the ratio of 1:3–1:4. After 30 days, the cells were seeded at a density of 105 cells/cm2 in the medium containing 0.1 µM Compound E (Sigma-Aldrich, Darmstadt, Germany) for 10–14 days. Immunofluorescent staining was performed according to the previously described procedure [50]. Briefly, cells were grown on cell culture imaging plates for microscopy, fixed for 10 min in 4% PFA, and washed twice in DPBS. Permeabilization was performed in 0.5% Triton ×100 for 30 min, and nonspecificity was blocked with 1% BSA for 30 min. Exposure with primary antibodies diluted in 1% BSA was performed overnight at +4 °C. The secondary antibodies were then exposed for 1.5 h at room temperature. The list of antibodies is presented in Table 3. Cells were disaggregated with TrypLE Express and fixed in 2% paraformaldehyde (Sigma-Aldrich, Darmstadt, Germany). The cell membrane was permeabilized in 100% methanol at −20 °C for 10 min, washed once with DPBS (Biolot, Saint-Petersburg, Russia), and stained with the first antibodies diluted in 1% BSA in DPBS at 4 °C overnight. The next day, cells were washed once with DPBS, and secondary antibodies diluted in 1% BSA in DPBS were added for 1 h. Secondary antibodies were used as isotype controls. A cell count was performed by the BD FACSAria™ III (BD Biosciences, Franklin Lakes, NJ, USA) using the BD FACSDiva software. All the measurements were made using four replicates. The list of antibodies used in the FACS analysis is presented in Table 3. Reverse transcription of 1 µg of RNA was performed using M-MuLV revertase (Biolabmix, Novosibirsk, Russia). Quantitative PCR was performed on a LightCycler 480 real-time PCR system (Roche, Basel, Switzerland) with a BioMaster HS-qPCR SYBR Blue 2× kit (Biolabmix, Novosibirsk, Russia) using the following program: 95 °C for 5 min; 40 cycles at 95 °C for 10 s and 60 °C for 1 min. ACTB, B2M, and TFRC were chosen as reference genes. Quantitative analysis of the qPCR results was performed using the generalized ΔΔCt method, taking into account the reaction efficiency calculated from the results of constructing a five-point calibration curve [51]. The list of primers is presented in Table 4. To examine the effects of ambroxol treatment, DA neurons derived from patient-specific iPSCs were grown in a complete medium containing 50 µM ambroxol (Sigma-Aldrich, Darmstadt, Germany) for 21 days. Each line of DA neurons was cultured in 3 wells of a 12-well plate with ambroxol and 3 wells without ambroxol (null point) with a daily change of the medium. Cells were lysed with a total protein extraction kit (Millipore, Burlington, VT, USA). Total protein concentration was measured using a Pierce BSA Protein Assay kit (Thermo Scientific, Waltham, MA, USA). A total of 30 µg of total protein extract was loaded onto a 7.5% mini-protean TGX stain-free precast gel (Bio-Rad Laboratories, Hercules, CA, USA) with Tris/Glycine/SDS running buffer (Bio-Rad Laboratories, Hercules, USA) and transferred to a PVDF membrane (Bio-Rad Laboratories, Hercules, CA, USA). The membrane was probed with primary antibodies (rabbit anti-GBA monoclonal antibody (1:500, ab125065, Abcam, Cambridge, UK) or rabbit anti-glyceraldehyde 3-phosphate dehydrogenase (GAPDH) polyclonal antibody (1:18,000, SAB2108266, Sigma-Aldrich, Darmstadt, Germany). The goat anti-rabbit HRP conjugate (1:5000, ab6721, Abcam, Cambridge, UK) was used to detect both anti-GBA and anti-GAPDH antibodies. Digital images were obtained using the chemiluminescence system ChemiDoc (Bio-Rad Laboratories, Hercules, CA, USA) and quantified using ImageJ software. The activity of six lysosomal enzymes—GCase, GALC, GAA, GLA, ASM, and IDUA—was measured in triplicate for each line of DA neurons derived from patient-specific iPSC using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) as described previously [9,53]. The neurons were lyophilized and then resuspended in DPBS. Enzyme activities were normalized to the total protein concentration. Statistical significance in value differences among experimental groups was calculated by an ANOVA test in Microsoft Excel (Microsoft Office 2013) software and a Wilcoxon’s t-test in R version 4.2.2 (R Core Team, 2021, Vienna, Austria). The 10–30% penetrance of GBA genetic variants raises the question of why some carriers get sick and others do not. Asymptomatic GBA mutation carriers are an interesting group for genetic studies, as they might carry protective genetic variants, either generally neuroprotective or counteracting the effect of lower GCase activity. We have shown a decrease in GCase activity in iPSC-derived DA neurons in both asymptomatic N370S GBA carriers and PD patients. A decrease in the amount of GCase protein was shown in GBA-PD neurons but not in GBA-carrier. Moreover, GBA-PD DA neurons are characterized by a disbalance in other lysosomal enzyme activities and have higher GLA and IDUA activities compared to both control and GBA-carrier DA neurons. The imbalance of sphingolipid metabolism carried out by lysosomal enzymes may lead to lysosomal dysfunction, which could promote the pathogenesis of diseases associated with GCase deficiency.

PMC10002968

36811277

Sixian Zhu,Huiting Xu,Runzhi Chen,Qian Shen,Dongmei Yang,Hui Peng,Jin Tong,Qiang Fu

DNA methylation and miR‐92a‐3p‐mediated repression of HIP1R promotes pancreatic cancer progression by activating the PI3K/AKT pathway

21-02-2023

DNA methylation,HIP1R,miR‐92a‐3p,pancreatic cancer (PAAD),PI3K/AKT

Abstract Pancreatic cancer (PAAD) is a highly malignant tumour characterized of high mortality and poor prognosis. Huntingtin‐interacting protein 1‐related (HIP1R) has been recognized as a tumour suppressor in gastric cancer, while its biological function in PAAD remains to be elucidated. In this study, we reported the downregulation of HIP1R in PAAD tissues and cell lines, and the overexpression of HIP1R suppressed the proliferation, migration and invasion of PAAD cells, while silencing HIP1R showed the opposite effects. DNA methylation analysis revealed that the promoter region of HIP1R was heavily methylated in PAAD cell lines when compared to the normal pancreatic duct epithelial cells. A DNA methylation inhibitor 5‐AZA increased the expression of HIP1R in PAAD cells. 5‐AZA treatment also inhibited the proliferation, migration and invasion, and induced apoptosis in PAAD cell lines, which could be attenuated by HIP1R silencing. We further demonstrated that HIP1R was negatively regulated by miR‐92a‐3p, which modulates the malignant phenotype of PAAD cells in vitro and the tumorigenesis in vivo. The miR‐92a‐3p/HIP1R axis could regulate PI3K/AKT pathway in PAAD cells. Taken together, our data suggest that targeting DNA methylation and miR‐92a‐3p‐mediated repression of HIP1R could serve as novel therapeutic strategies for PAAD treatment.

DNA methylation and miR‐92a‐3p‐mediated repression of HIP1R promotes pancreatic cancer progression by activating the PI3K/AKT pathway Pancreatic cancer (PAAD) is a highly malignant tumour characterized of high mortality and poor prognosis. Huntingtin‐interacting protein 1‐related (HIP1R) has been recognized as a tumour suppressor in gastric cancer, while its biological function in PAAD remains to be elucidated. In this study, we reported the downregulation of HIP1R in PAAD tissues and cell lines, and the overexpression of HIP1R suppressed the proliferation, migration and invasion of PAAD cells, while silencing HIP1R showed the opposite effects. DNA methylation analysis revealed that the promoter region of HIP1R was heavily methylated in PAAD cell lines when compared to the normal pancreatic duct epithelial cells. A DNA methylation inhibitor 5‐AZA increased the expression of HIP1R in PAAD cells. 5‐AZA treatment also inhibited the proliferation, migration and invasion, and induced apoptosis in PAAD cell lines, which could be attenuated by HIP1R silencing. We further demonstrated that HIP1R was negatively regulated by miR‐92a‐3p, which modulates the malignant phenotype of PAAD cells in vitro and the tumorigenesis in vivo. The miR‐92a‐3p/HIP1R axis could regulate PI3K/AKT pathway in PAAD cells. Taken together, our data suggest that targeting DNA methylation and miR‐92a‐3p‐mediated repression of HIP1R could serve as novel therapeutic strategies for PAAD treatment. Pancreatic cancer (PAAD) is a highly malignant pancreatic adenocarcinoma which is characterized of high rate of metastasis, rapid development of drug resistance, high mortality and poor prognosis. , Patients with PAAD usually show no specific symptoms in early stage, posing a critical challenge for early diagnosis. Due to the aggressiveness of the diagnosed PAAD in advanced stage, the mortality rate of PADD is high and the 5‐year survival rate is only about 7%. , The choice of therapeutic strategies for PADD mainly depends on the stage of diagnosis, and the commonly used treatment approaches include surgical resection, chemotherapy, radiotherapy, interventional therapy and targeted therapy. , A considerable number of patients with early PADD diagnosis can be cured by surgical resection, while the treatment outcome for advanced patients with metastasis or drug resistance remains dismal. Understanding the molecular mechanisms underlying the progression of PADD is the key to providing insights into the formulation of novel targeted therapy in advanced stage. The majority of current studies investigated the upregulated genes and their contributions to the progression of PAAD. For example, epiregulin is reported to be upregulated in pancreatic cancer to stimulate cell growth. The upregulation of telomerase in pancreatic cancer cells could support its resistance to etoposide treatment, and VEGF‐C overexpression is modulated by circNFIB1 to support the metastasis of PAAD cells. On the other hand, tumour suppressor genes represent important barriers for tumorigenesis and cancer progression, which are frequently mutated or down‐regulated in cancer cells. , Functional restoration of tumour suppressor genes are also attractive strategies to curb the progression of cancer. However, there is a lack of characterization of tumour suppressor genes in PAAD. A recent study reported that Huntingtin‐interacting protein 1‐related (HIP1R) functions as a tumour suppressor in gastric cancer by inducing apoptosis and suppressing migration and invasion through targeting Akt. HIP1R has been recognized as a key component of clathrin‐coated pits and vesicles which links the endocytic machinery to the actin cytoskeleton. It also binds to 3‐phosphoinositides via ENTH domain to regulate signalling transduction and promotes cell survival by stabilizing receptor tyrosine kinases following ligand‐induced endocytosis. In colorectal cancer, HIP1R was reported to alter T cell‐dependent cytotoxicity by facilitating the lysosomal degradation of PD‐L1, which assists in the escape of immune surveillance of tumour cells. However, the biological functions of HIP1R in the progression of PAAD remain to be explored. DNA methylation is an important epigenetic modification governing gene expression, which can be passed from parental cells to the next generation during DNA replication through the action of DNA methyltransferase. , The expression of oncogenes or tumour suppressor genes could be dysregulated by abnormal DNA methylation pattern. Aberrant DNA methylation has been implicated in cancer biology and is closely related to the occurrence and the progression of different types of cancer. , In addition, non‐coding RNAs such as microRNAs (miRNAs) add another layer of post‐transcriptional control on gene expression. miRNAs play regulatory roles in gene expression by targeting the complementary mRNA for degradation or arresting the translation. The deregulation of miRNAs contributes to the progression of cancer by modulating the expression of oncogene target or silencing tumour suppressor genes. , As a typical example, miR‐92a‐3p has been recognized as an oncogenic factor and its overexpression supports the uncontrolled proliferation and survival of tumour cells, , which has been proposed as an anticancer target for leukaemia and colorectal cancer. In this study, we showed the downregulation of HIP1R in PAAD tissues and cell lines, and demonstrated that HIP1R serves as a tumour suppressor in PAAD since the overexpression of HIP1R suppressed the proliferation, migration and invasion, and induced apoptosis in PAAD cells. The promoter region of HIP1R was heavily methylated in PAAD cell lines, and the treatment of a DNA methylation inhibitor 5‐AZA increased HIP1R expression and impaired the malignant phenotype of PAAD cells. We further demonstrated that HIP1R was negatively regulated by miR‐92a‐3p, which modulates the malignant phenotype of PAAD cells in vitro and the tumorigenesis in vivo by targeting PI3K/AKT pathway. Taken together, our data showed that both DNA methylation and miR‐92a‐3p‐mediated repression of HIP1R contribute to the malignant progression of pancreatic cancer. Targeting DNA methylation and miR‐92a‐3p could serve as novel therapeutic strategies for PAAD treatment. The tumour and para‐tumour tissue specimens were obtained from 106 PAAD patients at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. All experimental procedures were approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. All patients had signed the informed consent. The collected tissues were snap‐frozen in liquid nitrogen and stored at −80°C until further analysis. PAAD cell lines including PANC‐1, SW1990, BXPC‐3, AspC‐1 and normal pancreatic duct epithelial cell line HPDE‐6, and 293 T cell line were purchased from Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. Cells were cultured in DMEM (HyClone) complete medium containing 10% fetal bovine serum (Gibco) bovine serum, 100 μg/ml penicillin, 100 μg/ml streptomycin and 2 mmol/L glutamine in an incubator at 37°C with 5% CO2. 1 μM 5‐AZA (Sigma) was added in the cells to inhibit the DNA methyltransferase for 7 days, and the cells were collected for DNA and total RNA extraction. QIAamp DNA Mini Kit (Qiagen) was used to extract genomic DNA from cells. DNA was denatured by adding NaOH for 10 min at 37°C and then mixed with freshly prepared sodium bisulphite mixture (Qiagen). After bisulphite modification at 50°C for 16 h, the DNA sample was purified by ethanol precipitation and re‐dissolved in solution with 10 mM Tris/0.1 mM EDTA. PCR reaction was performed to amplify the bisulphite‐treated DNA using the following program: 95°C for 5 min, followed by 35 cycles of 94°C for 35 s, 60°C for 35 s, and 72°C for 35 s. Finally, the methylated primers were substituted by unmethylated primers to perform PCR amplification (using an annealing temperature of 58°C for 35 cycles). For BSP analysis, the EZ DNA Methylation‐Gold™ Kit (ZYMO RESEARCH) was used in this study according to the manufacturer's instructions. Total RNA from the tissues and cells was extracted using MiniBEST Universal RNA Extraction Kit (TaKaRa) according to the instruction manual. The extracted total RNA was dissolved in DEPC water, and its concentration was measured with NanoDrop. 5 μg of total RNA was used for reverse‐transcription into cDNA using PrimeScript™ RT reagent kit (TaKaRa) The relative expression of HIP1R, DNMT1, DNMT3A, DNMT3B and miR‐92a‐3p was determined by SYBR Premix EX Taq™ kit (TaKaRa) in a 7500 Real‐Time PCR System (Applied Biosystems). The following cycling condition was used for qPCR: 95°C for 30 s, followed by 40 cycles of 95°C for 5 s, and 60°C for 10 s. The relative expression level was quantified by 2−ΔΔCt approach with the internal control of GAPDH and U6 snRNA gene. Primers used for qPCR were synthesized by Sangon Biotechnology Co., Ltd. (Shanghai, China): HIP1R: F‐ CGAGCAGTTCGACAAGACC; R‐ GTGTGCCCAGAATGATGCG. DNMT1: F‐ CCTAGCCCCAGGATTACAAGG; R‐ ACTCATCCGATTTGGCTCTTTC. DNMT3A: F‐ CCGATGCTGGGGACAAGAAT; R‐ CCCGTCATCCACCAAGACAC. DNMT3B: F‐ AGGGAAGACTCGATCCTCGTC; R‐ GTGTGTAGCTTAGCAGACTGG. miR‐92a‐3p: F‐ GCAATCATGTGTATAGATATG; R‐ CTCCACTCACAGAGGTGTC. GAPDH: F‐ CTGGGCTACACTGAGCACC; R‐ AGTGGTCGTTGAGGGCAATG. U6: F‐ TGCGGGTGCTCGCTTCGGCAGC; R‐ CCAGTGCAGGGTCCGAGGT. The miR‐92a‐3p mimic and miR‐92a‐3p inhibitor and the corresponding controls were purchased from General Biosystem (General Biosystem). The cDNA of HIP1R was cloned into pcDNA3.1 plasmid for overexpressing HIP1R, and siRNA targeting HIP1R and scramble control siRNA were produced by Guangzhou RiboBio. All these above molecules were transfected into cells using Lipofectamine 2000 (Thermo Fisher Scientific). Briefly, 60% confluent cells in 6‐well plate were transfected with 50 nM of microRNA mimic or inhibitor or 6 μg of pcDNA3.1‐HIP1R plasmid according to manufacturer's instruction. Transfected cells were subjected to subsequent analysis 48 h post‐transfection. Cell proliferation was examined by Cell Counting Kit‐8 (CCK8, Dojindo Laboratory) according to manufacturer's instructions. 48 h after transfection, cells were seeded into a 96‐well plate at a density of 1500 cell/well and cultured for 0, 24, 48, 72 and 96 h, respectively. Subsequently, 10 μl CCK8 reaction solution was added to each well at indicated time point and incubated for 1 h. The light absorption value (OD value) in each condition was captured at 450 nm wavelength on a Synergy H1 microplate reader. Cells were trypsinized and seeded into a 6‐well plate at the density of 2000 cells/well. The culture medium was changed every 3 days for 2 weeks. Cells were then fixed with 4% paraformaldehyde (BD Biosciences) at room temperature for 10 min and stained with 0.5% crystal violet (Beyotime) for 20 min. The number of stained colonies was counted under an inverted microscope (Olympus). Cells were trypsinized and re‐suspended in serum‐free medium. The transwell upper chamber (Corning) without Matrigel (BD Biosciences) was used for migration assay, while transwell upper chamber coated with Matrigel was used for invasion assay. 5 × 105 cells were inoculated into the transwell upper chamber in serum‐free medium and 500 μl of 10% serum‐containing medium was added to the lower chamber. After 24 h, culture medium was discarded and the cells were fixed with 4% paraformaldehyde for 10 min and stained with 0.5% crystal violet (Beyotime) for 20 min. Cells were photographed under an inverted microscope (Olympus), and cells from five randomly selected fields in each sample were counted. Annexin‐V fluorescein isothiocyanate/PI apoptosis detection kit (Invitrogen Life Technologies) was used for apoptosis detection. Briefly, cells with different treatments were trypsinized and re‐suspended in 1000 μl staining buffer with 1 million cells. 1 μl Annexin V‐FITC and 1 μl PI were added to the cell suspension for 30 min incubation in the dark. Stained cells were centrifuged and washed twice with 1xPBS and resuspended in 400 μl staining buffer. The BD FACS CantoTM II Flow Cytometer (BD Biosciences) was used to determine cell apoptotic populations. Immunohistostaining was performed on 5‐μm sections of formalin‐fixed paraffin‐embedded (FFPE) tissues. The sections were deparaffinized and hydrated by three washes of xylene for 5 min each, two washes of 100% ethanol for 10 min each, two washes of 95% ethanol for 10 min each, and in two washes in dH2O for 5 min each. After antigen retrieval with citrate buffer at 95°C for 10 min, the sections were washed in dH2O three times and then incubated in 3% hydrogen peroxide for 10 min. After three times washes in TBST buffer for 5 min, the section was blocked for 1 h using 10% goat serum (Sigma, Germany) at 37°C, followed by the incubation with primary antibodies (HIP1R: Abcam ab226197; Ki67: Abcam ab15580) overnight at 4°C. Next day, the slides were washed 3 times with PBS and incubated with SignalStain® Boost Detection Reagent (HRP Rabbit, Cell Signaling Technologies) and incubated in a humidified chamber for 30 min. The signal development was performed for 5 min using 400 μl SignalStain® substrate (Cell Signaling Technologies). The section was washed in dH2O two times and mounted with coverslips using the mounting medium (Cell Signaling Technologies) before imaging under an inverted microscope (Olympus). The IHC staining was examined and scored independently by two experienced pathologists. The HIP1R 3’‐UTR containing the wildtype binding site of miR‐92a‐3p (WT) or the mutated binding site (MUT) was cloned into the psiCHECK2 dual‐luciferase reporter vector (Promega, WI, USA). 293 T cells were transfected with WT or MUT luciferase reporter with either miR‐92a‐3p mimic or miR‐NC using Lipofectamine 3000 (Invitrogen). After 48 h, the relative luciferase activities were measured using Dual‐Luciferase Reporter Assay Kit (Promega) on a luminescence microplate reader (Infinite 200 PRO, Tecan). The relative firefly luciferase activity in the reporter plasmid was normalized to that of Renilla luciferase. Total protein from cells and tissues was extracted by ice‐cold RIPA lysis buffer (Beyotime) containing 1% PMSF. Cells suspended in RIPA buffer were lysed on ice for 10 min and lysates were centrifuged at 13000 g for 10 min. The supernatant was quantified by a BCA Protein assay kit (Beyotime Biotechnology Shanghai, China). 10 μg of total protein was used for SDS‐PAGE electrophoresis and transferred onto the PVDF membrane (Bio‐Rad). After blocking with 5% skimmed milk for 1 h, the membrane was then incubated with primary antibodies: HIP1R (1:1000; Abcam ab226197), β‐Actin (1:2000, Abcam ab8227), Akt (1:1000, Abcam ab8805), p‐Akt (1:2000; Abcam ab18206), mTor (1:1000; Abcam ab2732), p‐mTor (1:1000; Abcam ab131538), S6K (1:1000; Abcam ab9366), p‐S6K (1:1000; Abcam ab131436) for overnight at 4°C. The membrane was washed 3 times with TBST buffer and incubated with HRP‐linked secondary antibody (1:3000; Cell Signaling Technologies). The protein bands were developed using an enhanced ECL chemiluminescence kit (Solarbio) and photographed on a gel imager system (Bio‐Rad). ImageJ software (Bethesda) was used for the densitometry analysis. Animal experiments were approved by the Institutional Animal Care and Use Committee of the Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. 1 × 106 SW1990 PAAD cells were subcutaneously injected into 18 nude mice to establish xenograft. The mice were divided into three groups: miR‐92a‐3p mimic injection, inhibitor miR‐92a‐3p injection and PBS injection (n = 6 in each group). All the injections were performed intravenously twice a week for 2 weeks until the tumour volume reached approximately 50 mm3. Tumour volume was continuously monitored for 24 days and all the mice were euthanized by CO2 asphyxiation and cervical dislocation. The xenograft tumours were removed and weighed, and the samples were subject to further analysis. UCSC Genome Database (http://genome.ucsc.edu) was used to locate the HIP1R gene locus and multiple CpG islands in the promoter region. To identify the potential microRNAs targeting HIP1R, miRWalk (http://mirwalk.umm.uni‐heidelberg.de/), miRTarbase (http://mirtarbase.mbc.nctu.edu.tw/index.html) and Targetscan (http://www.targetscan.org/vert_72/) online databases were used to search for the interacting miRNAs of HIP1R mRNA. To understand the gene programs regulated by HIP1R, GSEA (Gene Set Enrichment Analysis) was performed (http://www.gsea‐msigdb.org/gsea/index.jsp) to identify gene sets correlated with high or low HIP1R expression. All data were analysed by SPSS 20.0 software (IBM Corp). The difference between two groups was analysed by Student's t‐test (two‐tailed), and one‐way anova was performed for comparisons among multiple groups, with Dunn's test for correction of multiple comparisons. Spearman correlation analysis was employed to determine the relationship between HIP1R and miR‐92a‐3p expression levels. The overall survival rate was analysed by Kaplan–Meier Survival curve and log‐rank test. Data were displayed as mean ± standard deviation (x ± s) of at least 3 independent experiments. p < 0.05 was considered as statistically significant. To explore the potential role of HIP1R in PAAD, the mRNA and protein levels of HIP1R were compared between PAAD tumour tissues (n = 106) and the matched pericarcinomatous tissues (n = 106) by qRT‐PCR and IHC. The results showed that compared with the adjacent normal tissues, HIP1R level was significantly lower in PAAD tissues (Figure 1A,B and Figure S1). We also evaluated the mRNA and protein levels of HIP1R in PAAD cell lines (PANC‐1, SW1990, BXPC‐3 and AspC‐1) and normal pancreatic duct epithelial cell line HPDE‐6. The results also showed that HIP1R expression level was significantly reduced in PAAD cell lines (Figure 1C,D). To evaluate the association between HIP1R and the survival of PAAD patients, the PAAD patients were divided into HIP1R low‐expression group (n = 53) and high‐expression group (n = 53) according to median expression level of HIP1R measured by qRT‐PCR, and their clinicopathological characteristics were summarized in Table 1. Chi‐square test showed that low HIP1R expression was significantly correlated with more advanced TNM stages, larger tumour sizes and more lymph node metastasis (Table 1). Furthermore, Kaplan–Meier curve analysis revealed that low HIP1R expression was associated with a poorer overall survival (OS) and disease‐free survival (DFS) in PAAD patients (Figure 1E). Together, these data indicate that HIP1R may act as a tumour suppressor which is downregulated in PAAD tissues and cells. To validate the tumour suppressor role of HIP1R, we constructed pcDNA3.1‐HIP1R expression vector to overexpress HIP1R in PAAD cells. As compared to the cells transfected empty vector (NC), pcDNA3.1‐HIP1R transfection significantly increased the mRNA and protein level of HIP1R in PANC‐1 and SW1990 cells (Figure 2A). CCK‐8 proliferation assay and colony formation assay demonstrated that HIP1R overexpression suppressed cell proliferation and colony formation ability in PAAD cells (Figure 2B,C). In contrast, HIP1R overexpression induced more apoptotic events in both cell lines (Figure 2D). The transwell migration and invasion assay also revealed that HIP1R overexpression could impair the abilities of cell migration and invasion (Figure 2E,F). We also applied siRNA targeting HIP1R to reduce the expression of HIP1R in PAAD cells (Figure S2A,B). Upon HIP1R knockdown, PANC‐1 and SW1990 cells showed augmented cell proliferation (Figure S2C), enhanced colony formation ability (Figure S2D) and stronger migratory and invasive capabilities (Figure S2E,F). Taken together, these data indicate that HIP1R functions as a tumour suppressor to negatively regulate the malignancy of PAAD cells. To understand the mechanism underlying HIP1R downregulation, UCSC Genome Database (http://genome.ucsc.edu) was used to locate the HIP1R gene and multiple CpG islands in the promoter region (Figure 3A). We then performed methylation‐specific PCR (MSP) to compare the methylation level at the CpG islands between PAAD cell lines and normal pancreatic duct epithelial cell line HPDE‐6, which showed an elevated methylation level in PAAD cell lines (PANC‐1, SW1990 and BxPC3) (Figure 3B). We also conducted bisulphite sequencing PCR (BSP) in PAAD cell lines, HPDE‐6 cell line and PAAD tissues. The methylation levels of HIP1R promoter in PAAD cell lines (PANC‐1: 81%, SW1990: 73%, BxPC‐3: 71%) and PAAD patient tissues (76% and 65%) were much higher than that of normal pancreatic duct epithelial cell line HPDE‐6 (39%) (Figure 3C). Additionally, qRT‐PCR analysis revealed that multiple DNA methyltransferases, including DNMT1, DNMT3A and DNMT3B, were considerably upregulated in PADD cells than in normal pancreatic duct epithelial cells (Figure 3D). To confirm that the downregulation of HIP1R was dependent on DNA methylation, we treated PAAD cells with 5‐AZA (a DNA methylation inhibitor) for 48 h. The inhibition of DNA methylation increased HIP1R in a dose‐dependent manner (Figure 3E). Together, these data suggest PAAD downregulation is mediated by DNA hypermethylation in PAAD tissues and cell lines. To investigate the impact of DNA hypermethylation on the malignant phenotype, PANC‐1 and SW1990 cells were treated with 2.5 μM 5‐AZA for 48 h with or without HIP1R silencing by siRNA. We observed that compared to the control (NC), 5‐AZA treatment significantly impaired the malignant phenotypes including cell proliferation, clonogenic ability, cell migration and invasion and induced apoptosis. (Figure 4A–E). The co‐transfection of si‐HIP1R largely attenuated the effect of 5‐AZA (Figure 4A–E). Therefore, DNA hypermethylation contributes to the malignant phenotype by modulating HIP1R expression. To explore whether non‐coding RNAs such as microRNAs also mediates the downregulation of HIP1R, miRWalk (http://mirwalk.umm.uni‐heidelberg.de/), miRTarbase (http://mirtarbase.mbc.nctu.edu.tw/index.html) and Targetscan (http://www.targetscan.org/vert_72/) online databases were used to search for the interacting miRNAs of HIP1R mRNA. It was found that there were potential binding sites between miR‐92a‐3p and the 3' UTR (untranslated region) of HIP1R mRNA (Figure 5A). To validate the functional interaction, the HIP1R 3' UTR containing the wildtype binding site of miR‐92a‐3p (WT) or the mutated binding site (MUT) was cloned into the dual‐luciferase reporter vector, and 293 T cells were transfected with WT or MUT luciferase reporter with either miR‐92a‐3p mimic or miR‐NC. miR‐92a‐3p mimic significantly decreased the luciferase activity of the WT reporter, while the effect was abrogated when the binding sites were mutated (Figure 5B). qRT‐PCR analysis further showed that miR‐92a‐3p level was significantly upregulated both in PAAD tissues and cells, when compared to normal tissues and cell line (Figure 5C,D). Besides, the Spearman coefficient test revealed a negative correlation between miR‐92a‐3p expression and HIP1R level in PAAD tissues (Figure 5E), which suggests that the miR‐92a‐3p upregulation may control HIP1R expression in PAAD cells and tissues. Furthermore, the Kaplan–Meier curve analysis demonstrated that PAAD patients with high miR‐92a‐3p expression were associated with a poorer prognosis in both overall survival and disease‐free survival (Figure 5F). To investigate the effect of miR‐92a‐3p on HIP1R expression, miR‐92a‐3p mimic or miR‐92a‐3p inhibitor was transfected into PANC‐1 and SW1990 cells to increase or decrease miR‐92a‐3p expression (Figure 5G). Upon the transfection of miR‐92a‐3p mimic, HIP1R expression was significantly reduced at both mRNA and protein level (Figure 5H), while miR‐92a‐3p inhibition increased HIP1R expression (Figure 5I). These data indicate that miR‐92a‐3p overexpression contributes to the downregulation of HIP1R in PAAD tissue and cells. However, when cells were treated with 5‐AZA, the expression level of miR‐92a‐3p was not affected, which suggests that the expression of miR‐92a‐3p is not regulated by DNA methylation (Figure S3). To investigate whether miR‐92a‐3p regulates the phenotype of PAAD phenotype, we transfected PANC‐1 and SW1990 cells with miR‐92a‐3p mimic. Compared to the cells transfected with miR‐NC control, the cell proliferation, colony formation ability, cell migration and invasion were significantly augmented and the apoptotic events were reduced in cells transfected with miR‐92a‐3p mimic (Figure S4A‐E). When HIP1R‐pcDNA3.1 was co‐transfected, the effects of miR‐92a‐3p mimic were partially suppressed (Figure S4A‐E). These results indicate that miR‐92a‐3p regulates HIP1R expression to modulate the phenotypes of PAAD cells. To further study the role of miR‐92a‐3p in the tumorigenesis, SW1990 cells were subcutaneously injected into nude mice to establish xenograft, and the mice were divided into three groups: miR‐92a‐3p mimic injection, inhibitor miR‐92a‐3p injection and PBS injection. The results showed that miR‐92a‐3p mimic promoted tumour growth while the inhibition of miR‐92a‐3p impaired the tumour volume (Figure 6A). Consistently, IHC staining of the cell proliferation marker Ki67 demonstrated that miR‐92a‐3p mimic increased the number of Ki67 expressing cells, while miR‐92a‐3p inhibitor reduced the number of cells stained positive for Ki67 (Figure 6B). We also quantified the expression of HIP1R in the xenograft samples using qRT‐PCR and IHC staining. As expected, the mRNA level and protein level of HIP1R were decreased in the xenograft samples with miR‐92a‐3p mimic injection, and miR‐92a‐3p inhibitor increased HIP1R expression (Figure 6C,D). These results further corroborate the functional role of miR‐92a‐3p in the tumorigenesis of PAAD. To understand the mechanisms by which HIP1R modulates the malignancy of PAAD cells, we performed GSEA (Gene Set Enrichment Analysis) (http://www.gsea‐msigdb.org/gsea/index.jsp), which indicates that high HIP1R expression is negatively associated with PI3K/Akt pathway (Figure 7A). We therefore performed Western blot to examine the relative activation status of PI3K/Akt signalling pathway by measuring the phosphorylation level of Akt, mTOR, S6K and S6 in cells of different groups (NC, HIP1R overexpression, miR‐92a‐3p mimic miR‐92a‐3p mimic + HIP1R overexpression). The results showed that HIP1R overexpression suppressed the phosphorylation of Akt, mTOR, S6K and S6, while miR‐92a‐3p mimic promoted their phosphorylation. The co‐transfection of miR‐92a‐3p mimic suppressed the effect of HIP1R overexpression (Figure 7B). Using Rigosertib (a PI3K/AKT inhibitor), we further demonstrated the effects of miR‐92a‐3p mimic on cell proliferation and apoptosis were largely abrogated by Rigosertib (Figure 7C,D). Besides, miR‐92a‐3p mimic also increased the phosphorylation of AKT in the xenograft tumour samples, while miR‐92a‐3p inhibitor decreased the level of p‐AKT (Figure 7E). Collectively, these results indicate that miR‐92a‐3p/HIP1R axis regulates the malignant progression of PAAD by targeting PI3K/AKT signalling pathway. PAAD is a common tumour of the digestive system with a high degree of malignancy and a poor prognosis. More than half of PAADs are located in the head of the pancreas, and most of PAADs are ductal adenocarcinomas originating from the epithelium of the pancreatic ducts. , It is a big challenge for the early diagnosis of PAAD and the mortality rate remains high after surgical resection or chemotherapies. Previous studies have suggested that functional restoration of tumour suppressor genes are attractive strategies to curb the progression of cancer. HIP1R belongs to an evolutionarily conserved family of proteins implicated in the regulation of cell proliferation. , It has been reported that HIP1R acts as a tumour suppressor to limit cancer progression in gastric cancer and colorectal cancer. , In this study, we also found the upregulation of HIP1R in PAAD tissues and cells, and the overexpression of HIP1R suppressed the cell proliferation, migration and invasion and induced cell apoptosis, while HIP1R silencing impaired the malignant phenotype of PAAD cells. These data suggest that HIP1R also function as a tumour suppressor gene in PAAD. Epigenetic changes, such as altered patterns of genomic DNA methylation, are associated with human malignancies. In the past 20 years, the aberrant methylation of CpG islands in the gene promoters was frequently reported in cancers, , which predominantly affect the expression of tumour suppressor genes. Because abnormal methylation is one of the earliest molecular changes, it has been considered as a biomarker for early cancer diagnosis. For example, in clear renal cell carcinoma, hypermethylation of the tumour suppressor gene ADAMTS18 facilitates the proliferation, migration and invasion of tumour cells. , A non‐coding RNA HOTAIR could induce the promoter DNA methylation of tumour suppressor gene PCDH10 in gastric cancer and modulate DNMT1 expression by sponging miR‐148b. In PAAD, the levels of DNA methylation at tumour suppressor genes such as ADAMTS18 and HPP1 genes in cancer tissues are also higher than that in normal tissues. , In this study, we found that the CpG islands at the promoter region of HIP1R were hypermethylated in PAAD tissues and cell lines. Importantly, the treatment of a DNA methylation inhibitor 5‐AZA could increase the protein and mRNA expression of HIP1R. Moreover, 5‐AZA treatment impaired the malignancy of PAAD cells in a HIP1R‐dependent manner. Together, these results indicate that the silencing of HIP1R in PAAD tissues is induced by DNA hypermethylation, and demethylation reagent undermines the malignancy of PAAD cells. The DNA hypermethylation is correlated with the upregulation of several DNA methyltransferases, and future works are needed to understand how these methyltransferases are upregulated in PAAD. Another post‐transcriptional regulation mechanism which is frequently disrupted is the aberrant expression of non‐coding RNAs. Non‐coding RNAs such as miRNAs participate in a wide range of biological processes, including proliferation, migration, metabolism, apoptosis, and epithelial‐mesenchymal transition. miRNAs usually interact with the target mRNAs and degrade the mRNAs or blocks the translation by binding to the 3' UTR. The dysregulation of miRNAs has also been reported in PAAD. For instance, Lv et al reported that miR‐4668‐5p is overexpressed in serum samples of PAAD patients, and miR‐324‐5p upregulation could promote cell proliferation in PAAD cells by suppressing the protein expression of KLF3. Besides, miR‐887‐3p is also upregulated in PAAD, which promotes the malignant progression of PAAD by down‐regulating STARD13. In this study, we found that miR‐92a‐3p was upregulated in tumour tissues and cells of PADD, and miR‐92a‐3p overexpression using miR‐92a‐3p mimic enhanced the cell proliferation, migration and invasion and suppressed apoptosis in PAAD cells. These findings seem to be consistent with previous studies in which miR‐92a‐3p were reported as an oncogenic factor to mediate the malignant progression in oesophageal squamous cell cancer, glioma, liposarcoma and hepatocellular carcinoma. , , , Moreover, this study further demonstrated that miR‐92a‐3p augmented the malignancy of PADD cells by negatively regulating HIP1R and could promote the tumorigenesis of PAAD cells in vivo. We also showed that miR‐92a‐3p/HIP1R axis modulates the activation status of PI3K/Akt signalling. The inhibition of miR‐92a‐3p suppresses the malignancy of PAAD cells by targeting PI3K/Akt pathway. However, the DNA methylation seems not to affect the expression of miR‐92a‐3p, and it remains to be further investigated what are the mechanisms underlying the upregulation of miR‐92a‐3p in PAAD. In summary, this study demonstrated that HIP1R acts as a tumour suppressor which is downregulated in PAAD tissues and cells, and its reduced expression predicts a poor prognosis in PADD patients. We further elucidate that both DNA hypermethylation at the promoter region of HIP1R and the upregulation of miR‐92a‐3p contributes to the repression of HIP1R expression. These findings add novel insights into the functions of HIP1R in PAAD, which are of valuable clinical significance: HIP1R could serve as a potential prognostic marker in PAAD, and targeting DNA methylation and miR‐92a‐3p could be used as a strategy to restore the tumour suppressor function of HIP1R to curb the progression of PAAD. Future efforts are required to assess whether targeting DNA methylation and miR‐92a‐3p could synergize with the existing chemotherapeutics to improve the treatment outcome. Huiting Xu: Data curation (equal); formal analysis (equal); methodology (equal); writing – original draft (equal). Runzhi Chen: Methodology (equal); software (equal). Qian Shen: Methodology (equal); software (equal). Dongmei Yang: Methodology (equal); software (equal). Hui Peng: Methodology (equal); software (equal). Jin Tong: Methodology (equal); software (equal). Qiang Fu: Conceptualization (equal); funding acquisition (equal); writing – review and editing (equal). This work was supported by the National Natural Science Foundation of China (No. 81974381). The authors declare no competing financial interest. Informed consent was obtained from all individual participants included in the study. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.

PMC10002976

36824012

Abhilok Garg,Sheeba Khan,N. Luu,Davies J. Nicholas,Victoria Day,Andrew L. King,Janine Fear,Patricia F. Lalor,Philip N. Newsome

TGFβ1 priming enhances CXCR3 ‐mediated mesenchymal stromal cell engraftment to the liver and enhances anti‐inflammatory efficacy

23-02-2023

homing,immunomodulation,macrophages

Abstract The immunomodulatory characteristics of mesenchymal stromal cells (MSC) confers them with potential therapeutic value in the treatment of inflammatory/immune‐mediated conditions. Previous studies have reported only modest beneficial effects in murine models of liver injury. In our study we explored the role of MSC priming to enhance their effectiveness. Herein we demonstrate that stimulation of human MSC with cytokine TGβ1 enhances their homing and engraftment to human and murine hepatic sinusoidal endothelium in vivo and in vitro, which was mediated by increased expression of CXCR3. Alongside improved hepatic homing there was also greater reduction in liver inflammation and necrosis, with no adverse effects, in the CCL4 murine model of liver injury treated with primed MSC. Priming of MSCs with TGFβ1 is a novel strategy to improve the anti‐inflammatory efficacy of MSCs.

TGFβ1 priming enhances CXCR3 ‐mediated mesenchymal stromal cell engraftment to the liver and enhances anti‐inflammatory efficacy The immunomodulatory characteristics of mesenchymal stromal cells (MSC) confers them with potential therapeutic value in the treatment of inflammatory/immune‐mediated conditions. Previous studies have reported only modest beneficial effects in murine models of liver injury. In our study we explored the role of MSC priming to enhance their effectiveness. Herein we demonstrate that stimulation of human MSC with cytokine TGβ1 enhances their homing and engraftment to human and murine hepatic sinusoidal endothelium in vivo and in vitro, which was mediated by increased expression of CXCR3. Alongside improved hepatic homing there was also greater reduction in liver inflammation and necrosis, with no adverse effects, in the CCL4 murine model of liver injury treated with primed MSC. Priming of MSCs with TGFβ1 is a novel strategy to improve the anti‐inflammatory efficacy of MSCs. Mesenchymal stromal cells (MSC) represent a promising therapeutic approach in many conditions, including inflammatory liver disease and graft versus host disease, as a consequence of their potent immunomodulatory properties. However, their efficacy in rodent and human models of liver injury has been variable, with some studies demonstrating benefit from MSC infusions , , whilst others report that infusion of conditioned medium from MSC cultures was sufficient to confer efficacy. Moreover, the mechanism of action by which MSC exert their effects in models of liver damage is poorly delineated with reports suggesting they may be mediated by a reduction in oxidative stress and/or reduced lymphocytic ingress to the injured liver with a secretome analysis suggesting this latter effect may be chemokine dependent. Whilst others have suggested that a component of MSC action may occur remotely without requirement for homing to the injured organ, , the relative lack of efficacy of MSC in models of liver injury has been attributed to low levels of MSC engraftment in the damaged liver. Using flow‐based assays we and other groups have demonstrated that β1 integrin and CD44 are involved in the firm adhesion of MSC to hepatic sinusoidal and human umbilical endothelium. , Notably, chemokine receptors did not appear to contribute significantly to human MSC recruitment, which was unexpected considering chemokine receptors play a significant role in leukocyte recruitment. Moreover, studies using murine MSC adhesion to murine aortic endothelium suggest a functional role of chemokine receptors in the firm adhesion, crawling and transmigration of MSC, although expression of chemokine receptors on human MSC such as CCR4 and CXCR3 may be modest and different to murine cells. This variation in functional chemokine receptor profiles of MSC in reports from various groups , , has proven problematic in understanding the role of chemokine receptors in MSC homing and function. However, we have demonstrated that MSC detachment from tissue culture plastic can markedly affect expression of chemokine receptors, which may contribute to the variation in expression and function of MSC reported in the published literature, and also impact upon subsequent targeting in tissue. To mitigate for this, cell surface glycans on MSC have been chemically engineered into an E‐selectin binding motif in order to encourage engraftment to endothelium that expresses high levels of E‐selectin. Similarly pre‐loading of therapeutic MSC with paramagnetic nanoparticles has been utilized to allow specificity of delivery ; however, these methods of enhancing MSC migration are unlikely to be acceptable for clinical practice for logistical, safety and cost reasons. Therefore, we explored the consequences of cytokine stimulation of MSC upon their hepatic engraftment and efficacy. We used cytokines known to increase inflammatory cell ingress and that are elevated in liver disease such as TNFα, IFNγ, TGFβ1, LPS, IL1β, IL4, IL6, IL8 and IL10. , , , Importantly, MSC have been reported to have receptors for these cytokines including TNFRI and IIR, IFNγR, TLR4, IL‐1R, IL‐4R, IL‐6R, IL8R (CXCR1) and IL10R. Herein we report that pre‐stimulation of clinically relevant human MSC with TGFβ1 enhances their binding/engraftment to hepatic sinusoidal endothelium ex vivo and in vivo in a CXCR3‐dependent manner and results in greater potency to reduce liver damage in an acute model. Human liver tissue used in this study was obtained from patients at the Queen Elizabeth Hospital Birmingham, UK. Normal tissue was surplus to transplantation requirements or from tumour margin samples and diseased tissue was also obtained during transplantation for end‐stage disease (Primary Biliary Cirrhosis [PBC], Primary Sclerosing Cholangitis [PSC], Autoimmune hepatitis [AIH], Non‐alcoholic steatohepatitis and Alcoholic Liver Disease [ALD]). All samples were collected with local research ethics committee approval (reference number 06/Q2702/61) and informed, written patient consent. Freshly collected liver tissue was either snap frozen and sectioned to 10 μm for Stamper Woodruff adhesion assays or used for the isolation of hepatic sinusoidal endothelial cells (HSEC), biliary epithelial cells and hepatic myofibroblasts as previously described. Where indicated, cultured primary cells were treated with 10 ng/mL TNFα and IFNγ (both Peprotech) for 24 h prior to use in adhesion assays. Human MSC from healthy donors were purchased from Lonza Group Ltd, (MSC: Lonza Poietics®) which are cryopreserved at Passage 2 and conform to International society of cellular therapy (ISCT) standards for surface marker expression (CD73+, CD90+, CD29+, CD105+, CD166+ and CD44+, CD14−, CD19−, CD34−, CD45− and HLA DR−) and trilineage differentiation (Osteogenic, chondrogenic and adipogenic). Cells were cultured in human MSC Growth Medium (hGM) according to manufacturer's instructions and they were fully phenotypically characterized as we have described previously. Where indicated, MSC were stimulated with predetermined optimal concentrations of cytokines (TGFβ1, 5 ng/mL, IL‐4 10 ng/mL or IL‐10 50 ng/mL, all from Peprotech) or media alone, for 10 min to 24 h in hGM at 37°C. Adhesion of MSC to cultured cell monolayers, human liver tissue sections or mouse liver sections (control and CCl4 treated) was assessed using a modified Stamper Woodruff static adhesion assay. To assess migration of control or TGFβ1‐stimulated MSC we used a modified 48‐well Boyden chamber as previously described. All animal procedures were conducted in accordance with UK laws with the approval of the Home Office and local ethics committees (PPL 40/3201). Carbon tetrachloride (CCl4; Sigma Aldrich) diluted 1/4 in mineral oil (Sigma) was administered by intraperitoneal injections (1 mL/kg, twice weekly for 8 weeks or acutely as a single injection) into 9‐week‐old C57Bl/6 wild type male mice. Where indicated, MSC were pre‐incubated with blocking antibodies raised against chemokine receptors (anti human CXCR3, CCR5 or CXCR4 at 20 μg/mL, all from R+D systems) for 15 min at 37°C, washed and re‐suspended in PBS 0.1% BSA. To study engraftment of MSC into liver and non‐hepatic organs, MSC (control or 5 ng/mL TGFβ1‐stimulated) were labelled with Direct red (DiR 5 μM; Invitrogen) or CFSE according to manufacturer's instructions. Cells 1 × 106 were either injected into the hepatic portal or tail vein of mice that had been acutely injured with CCl4 (1 mL/kg IP, 72 h). Organs were harvested 72 h later and imaged using an IVIS Spectrum Imaging System (Perkin Elmer). Fluorescent and photographic images of individual organs were analysed using Living Image software. Full details of all experimental protocols are available in Appendix S1. Statistical analysis was performed by Student's t test or ANOVA using Prism software. Data are expressed as mean with standard errors. A value of p < 0.05 was considered significant. Infusion of 0.5 and 1 × 106 MSC reduced serum ALT and tissue necrosis area 72 h after CCl4 administration as depicted in Figure 1A. This effect was associated with a concomitant reduction in inflammation with reduced numbers of hepatic CD45 positive cells (Figure 1B). To understand the potential role of MSC chemokine receptors in mediating engraftment to the injured liver their chemokine receptor expression profile was studied. A large percentage of MSC contained intracellular stores of CCR4 (95.84 ± 0.88%), CCR5 (67.96 ± 5.54%), and CXCR3 (92.69 ± 1.26%) with correspondingly high MFI values (Figure 1C,D). A smaller percentage of MSC expressed CCR6 (18.92 ± 7.56%), CCR9 (13.2 ± 7.16%), CCR10 (13.99 ± 6.39%), CXCR1 (22.1 ± 7.12%), and CXCR7 (25.02 ± 8.22%), albeit at lower levels. Supportive immune‐histochemical staining and basal gene expression for these receptors is presented in Figure S1. Of a large panel of cytokines tested (Figure S2), only TGFβ1, IL4 and IL10 stimulation led to significant increases in the proportion of MSC expressing CCR4, CXCR3 and CCR5 (Figure 1C,D) by flow cytometry, although qPCR suggested no significant change in mRNA levels after stimulation (Figure 1D). Of these three cytokines only TGFβ1‐stimulated MSC demonstrated increased binding to cytokine‐stimulated (TNFα/IFNγ) human liver cell monolayers (HSEC, BEC and MF) or liver sections (Figure 2A). TGFβ1‐stimulated MSC (7.69 ± 0.59 cells per field of view [fov]; p < 0.001) exhibited increased adherence to stimulated HSEC compared with unstimulated MSC (4.18 ± 0.66 cells/fov), (Figure 2A, left panel). In addition, TGFβ1‐stimulated MSC were significantly more adherent to liver sections prepared from explanted diseased human livers of hepatitic nature, which was a pool of non‐alcoholic steatohepatitis/alcohol‐related liver disease cases (unstimulated 2.43 ± 0.13 cells/fov vs. stimulated 3.87 ± 0.23; p < 0.000) compared with cholestatic (primary biliary cholangitis/primary sclerosing cholangitis) sections (unstimulated 1.13 ± 0.11 vs. stimulated: 1.77 ± 0.13) and normal tissue (unstimulated 1.43 ± 0.15 vs. stimulated: 1.47 ± 0.16). Of note, IL4 and IL10 stimulation had no effect on MSC binding to liver sections (Figure 2A, right panel). To test adhesion and engraftment of MSC in injured liver in vivo CFSE‐labelled MSC were infused into control or acutely CCl4‐injured C57 Bl/6 mice via the portal vein. MSC were infused either unstimulated, or stimulated with TGFβ1, IL4 or IL10. We observed increased engraftment of TGFβ1‐stimulated MSC in injured mouse livers (2.29 ± 0.08 fold increase; p < 0.001) compared to unstimulated MSC (Figure 2B or C), whereas IL4 and IL10‐stimulation had no impact on engraftment. Since TGFβ1‐stimulation of MSC (Figure 3A) increased surface expression of CCR4, CCR5 and CXCR3 without any change in mRNA levels, this suggested redistribution of these receptors to the cell surface. Confocal analysis confirmed redistribution of CXCR3 from the cytoplasm to the cell surface (Figure 3B right panel). Receptor redistribution was functional as TGFβ1‐stimulated MSC showed enhanced migration towards to CCL22 (3.07 ± 0.39 c/fov; p < 0.05) and the CCR5 ligands; CCL4 (unstimulated: 1.23 ± 0.21 c/fov vs. stimulated: 2.53 ± 0.45 c/fov; p < 0.01) and CCL8 (unstimulated: 1.23 ± 0.16 c/fov vs. stimulated: 2.27 ± 0.25 c/fov; p < 0.001), but not CCL5. The greatest increase in migration after TGFβ1 stimulation was in response to the CXCR3 ligands CXCL10 (unstimulated: 1.73 ± 0.26 c/fov vs. stimulated: 3.33 ± 0.41 c/fov; p < 0.01) and CXCL11 (unstimulated: 1.60 ± 0.25 c/fov vs. stimulated: 3.07 ± 0.40 c/fov; p < 0.01) (Figure 3C). As migration of MSC towards CXCR3 ligands and CCR5 was most impressive after TGFβ1 stimulation, we used function blocking antibodies for these receptors in Stamper Woodruff assays (Figure 4). TGFβ1‐stimulated MSC bound in significantly higher numbers (4.60 ± 0.50 c/fov) to injured mouse liver sections compared to unstimulated MSC (1.29 ± 0.13 c/fov), and CCR5 and CXCR3 blockade reduced binding to injured liver sections back to basal levels (Figure 4A). We then infused CFSE‐labelled MSC into CCl4‐injured mice via the portal vein, and observed increased engraftment of TGFβ1‐stimulated MSC in mouse livers. Whilst blocking CXCR3 on unstimulated MSC had no effect on their engraftment in injured mouse livers, there was a marked effect on TGFβ1‐stimulated MSC with engraftment reducing from a 2.32 ± 0.22 fold increase from baseline to a 0.63 ± 0.11 fold reduction (p < 0.001; Figure 4B). In contrast, blockade of CXCR4 and CCR5 blockade on MSC had no effect on engraftment of either control or stimulated MSC in injured mouse livers. To define the duration of TGFβ1 exposure required to induce CXCR3 expression we looked after 10 min, 1, 4 and 24 h stimulation. At 24 h there was a marked increase in surface CXCR3 expression by flow cytometric and confocal analysis. It is important to highlight however, that transcriptional upregulation of chemokine expression cannot be completely excluded although the changes seen within 24 h suggest the receptor mobilization plays a much more significant role following cytokine treatment. Mice were acutely injured with CCl4 and 4 h later received Direct red‐labelled untreated MSC or TGFβ1 stimulated MSC (or PBS control). After 68 h, murine liver fluorescence (Radiant Efficiency) was quantified using an IVIS imager and there were significantly higher levels of fluorescence in the livers of mice receiving TGFβ1‐stimulated MSC (Figure 5A). Fluorescent activity was also detected in the lungs (2.38 × 109 ± 5.81 × 108), liver (1.31 × 1010 ± 4.29 × 109) and spleen (2.44 × 109 ± 3.72 × 108) with minimal activity in the kidneys and heart. Notably TGFβ1 stimulation of MSC specifically increased their liver homing (2.61 × 1010 ± 2.87 × 109; p < 0.01) with no increase in levels of fluorescence activity elsewhere (Figure 5B). These findings were also validated by FACS analysis of single cell digests of harvested organs. Again significantly greater numbers of MSC were retrieved from the livers from TGFβ1‐stimulated MSC‐treated mice (12,146 ± 3569 cells/μL) compared to untreated MSC (2024 ± 676.4 cells/μL; p < 0.05). As with the IVIS analysis there was no significant difference between numbers of MSC or TGFβ1‐stimulated MSC in lungs or spleen (Figure 5C). To determine the impact of MSC infusion on the pathogenesis of CCl4‐induced injury, livers were harvested 72 h after infusion. Mice receiving untreated MSC had fewer CD45+ cells (33.18 ± 1.68 c/fov; p < 0.05) than control mice (42.27 ± 3.06 c/fov), whilst those receiving TGFβ1‐stimulated MSC had the fewest CD45+ cells (20.02 ± 1.80 c/fov; p < 0.001, Figure 6A). Similarly, the injury‐associated increase in serum ALT levels was less pronounced in mice receiving TGFβ1‐stimulated MSC (228.1 ± 26.52 IU/L; p < 0.05) as compared to PBS‐treated mice (404.7 ± 53.62 IU/L, Figure 6B). Serum Bilirubin levels were also reduced in mice receiving TGFβ1‐stimulated MSC (2.77 ± 0.33 IU/L; p < 0.05) compared to PBS‐treated mice (4.25 ± 0.58 IU/L). Similarly AST levels were also reduced with TGFβ1‐stimulated MSC (265.5 ± 20.66 IU/L; p < 0.05) as compared to PBS‐treated mice (394.5 ± 45.49 IU/L) as shown in (Figure 6B). The impact of infusions of MSC on macrophage numbers and polarization was assessed by flow cytometric quantification of digested murine livers (Figure 7A). Both unstimulated and TGFβ1‐stimulated MSC resulted in reductions of the numbers of M1‐macrophages (gated CD45+CD3−CD11b+F4/80+Ly‐6G‐Ly‐6C high) with a variable increase in M2‐macrophages (gated CD45+CD3−CD11b+F4/80+Ly‐6G‐Ly6‐C low) as well as an overall reduction in the Ly‐6Chi/Ly‐6Clo (M1‐like to M2‐like) ratio within the liver (Figure 7B or C). TGFβ1‐stimulated MSC also demonstrated a greater ability to inhibit proliferation of co‐cultured, activated CD3+CD4+CD25− T effector cells in vitro (Figure 8A) which were abrogated by the addition of the non‐steroidal anti‐inflammatory drug indomethacin (Figure 8B or C). Indomethacin acts as a nonselective cyclooxygenase (COX) inhibitor that interferes with prostaglandin E2 biosynthesis thereby interfering with leucocyte proliferation/activation. Moreover, MSC stimulated with TGFβ1 for 24 h secreted greater amounts of PGE2 (Figure 8D) than unstimulated MSC. Quantitative analysis of total collagen‐1 and αSMA gene levels in stimulated MSC demonstrated no significant effect of TGFβ1 on either Col1 or αSMA expression. We have demonstrated that TGFβ1 stimulation of MSC more than doubles their homing to the acutely injured liver and is associated with a resultant further reduction in inflammation and hepatic damage. Increased hepatic homing is mediated by a TGFβ1‐dependent increase in MSC surface expression of CXCR3, which promotes binding to hepatic endothelium in vitro and organ‐specific migration to the injured liver in vivo. Use of TGFβ1 stimulation to enhance MSC function represents a novel strategy to improve therapeutic use of MSC in inflammatory liver injury. Previous studies have reported modest beneficial effects of rodent and human MSC in models of liver injury such as carbon tetrachloride , , galactosamine, , chemical‐induced primary biliary cirrhosis or models of hepatic transplantation. , Our data provide additional support for the efficacy of unprimed human MSC in liver injury, but demonstrate that significantly greater efficacy can be achieved by cytokine priming. Use of rodent MSC in such models causes improvements in liver damage which appear to be, in part mediated by a reduction in oxidative stress and cellular infiltrates. Human MSC infusions have been reported to show similar benefit in CCl4 injury , although the mechanism of action is unclear apart from reduction in oxidative stress. Many have reported that MSC may exert their anti‐inflammatory actions remotely through either the release of mediators such as TSG6 and/or modulation of circulating effectors such as myeloid derived suppressor cells. These findings do not preclude an added action of MSC at the site of injury, and in that regard enhanced hepatic homing is a logical target. We have previously shown that trypsin‐detached MSC use β1‐integrin and CD44 to mediate hepatic engraftment and others have reported they use chemokine receptor CXCR4 for migration/engraftment in other settings. , Notably, we have demonstrated that the method of cell detachment is critical in preserving basal chemokine receptor expression on MSC. Our data demonstrate that whilst priming with IL4/IL10/TGFβ1 can significantly increase surface expression of a range of chemokine receptors, only TGFβ1‐stimulated MSC displayed an increased hepatic recruitment in both in vitro and in vivo settings (Figure 2B), and this effect appeared to be mediated by the increased surface expression of CXCR3. Notably increased organ homing following TGFβ1‐stimulation was liver‐specific, in keeping with other studies, , reflecting the targeting of infused cells to the inflamed site. There is precedent for such a role for CXCR3 as Curbishley et al., have previously demonstrated that CXCR3 expression is the major determinant for lymphocyte adhesion/trans‐migration in the injured liver. Thus, similar mechanism may operate to maintain surface expression of CXCR3 on MSC through inhibition of degradation and internalization. Other mechanisms implicated in the TGFβ induced increased expression of CCRs include activation of p38/MAPK signalling pathways, as seen in immune cells and inhibition of Metalloproteinases, involved in cleavage of CCRs at the cell surface. Our data suggest that TGFb stimulation does not have a major impact on transcriptional regulation (Figure S2B) indicating that in this setting the dominant mechanism driving increased chemokine expression on our MSCs is recirculation or inhibition of MMP cleavage. Recent studies suggest that allogeneic MSC, although hypo‐immunogenic, are not intrinsically immune privileged and that allogeneic MSC induce a memory T‐cell response resulting in rejection. Although human MSC are even more likely to generate an immune response after infusion into mice, we did not see an increase in CD45+ cells within the liver in our acute injury models and thus this approach provides an important method for obtaining in vivo data relevant for subsequent clinical trials, especially given the knowledge that human MSC use different mechanisms to immunomodulate compared to murine MSC. In our study, stimulation with TGFβ1 had no discernible effect on other properties of MSC including differentiation to myofibroblasts, and importantly MSC were cleared rapidly after infusion, rendering it highly unlikely that they could contribute directly to fibrogenesis. This also suggests that repeated infusions of pre‐stimulated cells may prolong benefit without increasing risk of fibrosis. A recent study and comprehensive review indicate that adoptively transferred MSC make no contribution to fibrosis, despite contrasting studies, , which is in keeping with our data. Indeed, adoptively transferred MSC have been shown to induce a reduction in fibrosis when infused in models of chronic liver damage with CCl4. This effect would appear to be mediated by blockade of Dlk1 activation thus causing a reduction in activation of hepatic stellate cells, along with increased MMP13 activity promoting fibrinolysis within the liver. A range of mechanisms have been reported by which MSC can mediate their immunomodulatory effects: MSC inhibit T cell activation induced by an anti‐CD3/CD28 antibody stimulus, mitogens, and allo‐antigens. They also inhibit NK cell activation, as well as B cell terminal differentiation, and dendritic cell maturation and functionality. In addition, MSC can inhibit homing of immune cells to lymph nodes and impair T‐cell priming in vivo. , However the precise molecular mechanisms responsible for the anti‐inflammatory effects of MSC in liver disease are still unknown, although MSC can reduce oxidative stress and CD45 infiltration. We saw a reduced CD45+ infiltrate after administration of MSC, by immunohistochemistry and flow cytometric analysis of digested murine liver, which correlated with reduced tissue necrosis and ALT in serum. Our data suggest that TGFβ1 stimulation also enhances the ability of MSC to suppress T cell proliferation or recruitment, and thus this may be a factor in the superior efficacy seen with primed cells. However, further work is required to establish whether the efficacy seen with TGFβ1‐dependent priming of MSC is predominantly driven by enhanced immunomodulatory action of MSC or their increased hepatic homing. Furthermore, our data indicate that hepatic macrophage profile changes significantly following administration of MSC, with or without, TGFβ1 stimulation. Our data indicate that MSC infusion is associated with a reduction in differences in the proportion of macrophage subsets expressed as a ratio of Ly‐6Chi/Ly‐6Clo (M1‐like to M2‐like) macrophages. The differential expression of Ly‐6C has been used to identify monocyte subsets in rodent models of liver injury where Ly‐6Chi monocytes exhibit pro inflammatory phenotype (M1) and Ly‐6C− monocytes exhibit the restorative phenotype (M2). As recognized by the literature, surface marker expression of macrophages is likely to be more complex and dynamic and thus even more extensive panels (CD163, CD206, CD68 and TLR4) do not completely characterize the full phenotype of macrophages in vivo and our panel is acceptable with these caveats. MSC have also been reported to mediate some of their anti‐inflammatory effects by inducing secretion of IL10 from macrophages and by inducing an M2 phenotype in unpolarised monocytes. Indeed phagocytosis of MSC by monocytes can trigger acquisition of an immunosuppressive M2 phenotype which enhances the immunoregulatory response to MSC infusion. Thus, some of the hepatic M2 macrophages (Figure 7C) present after MSC treatment may have differentiated locally in response to phagocytosis of hepatic MSC. However, there is also evidence that lung‐resident monocytes can also phagocytose trapped MSC and differentiate to regulatory macrophages which can then migrate to distant sites. Given we did indeed see a background level of MSC entrapment in the lungs (Figure 5), it is also possible that cells trafficking from this site could contribute to the pool of M2 macrophages we identified in our injured livers. Thus, in our model, the hepato‐protective effects of TGFβ1 primed MSC may be linked to a direct suppression of T cell activation and recruitment, and enhanced macrophage recruitment and differentiation within the liver, thus shifting the hepatic microenvironment towards a more reparative situation. Further study of the phenotype of hepatic myeloid cell subsets would be of value. In conclusion, we have demonstrated that priming of MSC with TGFβ1‐ enhances hepatic homing and anti‐inflammatory efficacy, without evidence of off‐target effects. This provides new opportunities to develop more clinically effective regimens of MSC therapy in clinical trials. Potential limitations include the heterogeneity of BM MSCs used due to batch to batch variation from different donors, stem cell aging and associated vulnerability, which can affect the conclusions drawn. To address this we used BM MSC from a minimum of three independent donors in our studies. Also BM MSC from Lonza are in themselves pooled samples from multiple donors which minimizes some of the afore‐mentioned risks. There is evidence that alternative sources of MSCs such as human‐induced pluripotent stem cells (hiPSCs) may be less impacted by aging with higher potency in immunomodulatory properties. Abhilok Garg: Data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); writing – original draft (lead). Sheeba Khan: Writing – original draft (supporting); writing – review and editing (supporting). N. Luu: Formal analysis (supporting); investigation (supporting); supervision (supporting); validation (supporting). Davies J. Nicholas: Data curation (supporting); formal analysis (supporting); investigation (supporting); supervision (supporting); visualization (supporting); writing – review and editing (supporting). Victoria Day: Funding acquisition (supporting); resources (supporting). Andrew L. King: Writing – review and editing (supporting). Janine Fear: Data curation (supporting); formal analysis (supporting); investigation (supporting); validation (supporting). Patricia F. Lalor: Conceptualization (lead); data curation (supporting); formal analysis (supporting); funding acquisition (lead); investigation (supporting); methodology (supporting); project administration (lead); resources (lead); software (supporting); supervision (lead); validation (supporting); visualization (lead); writing – original draft (supporting); writing – review and editing (supporting). Philip N. Newsome: Conceptualization (lead); data curation (supporting); formal analysis (supporting); funding acquisition (lead); investigation (supporting); methodology (supporting); project administration (supporting); resources (lead); software (supporting); supervision (lead); validation (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing (supporting). This work was supported by University Hospital Birmingham Charities. PNN is supported by the NIHR Birmingham Biomedical Research Centre based at University Hospitals Birmingham and the University of Birmingham. The views expressed are those of the author and not necessarily those of the NHS, the NIHR or the Department of Health. There are no relevant disclosures. Click here for additional data file. Click here for additional data file.

PMC10002977

Hyun Seung Shin,Soo Min Choi,Seung Hyun Lee,Ha Jung Moon,Eui-Man Jung

A Novel Early Life Stress Model Affects Brain Development and Behavior in Mice

28-02-2023

early life stress,behavior,mice,calbindin-D28k,parvalbumin

Early life stress (ELS) in developing children has been linked to physical and psychological sequelae in adulthood. In the present study, we investigated the effects of ELS on brain and behavioral development by establishing a novel ELS model that combined the maternal separation paradigm and mesh platform condition. We found that the novel ELS model caused anxiety- and depression-like behaviors and induced social deficits and memory impairment in the offspring of mice. In particular, the novel ELS model induced more enhanced depression-like behavior and memory impairment than the maternal separation model, which is the established ELS model. Furthermore, the novel ELS caused upregulation of arginine vasopressin expression and downregulation of GABAergic interneuron markers, such as parvalbumin (PV), vasoactive intestinal peptide, and calbindin-D28k (CaBP-28k), in the brains of the mice. Finally, the offspring in the novel ELS model showed a decreased number of cortical PV-, CaBP-28k-positive cells and an increased number of cortical ionized calcium-binding adaptors-positive cells in their brains compared to mice in the established ELS model. Collectively, these results indicated that the novel ELS model induced more negative effects on brain and behavioral development than the established ELS model.

A Novel Early Life Stress Model Affects Brain Development and Behavior in Mice Early life stress (ELS) in developing children has been linked to physical and psychological sequelae in adulthood. In the present study, we investigated the effects of ELS on brain and behavioral development by establishing a novel ELS model that combined the maternal separation paradigm and mesh platform condition. We found that the novel ELS model caused anxiety- and depression-like behaviors and induced social deficits and memory impairment in the offspring of mice. In particular, the novel ELS model induced more enhanced depression-like behavior and memory impairment than the maternal separation model, which is the established ELS model. Furthermore, the novel ELS caused upregulation of arginine vasopressin expression and downregulation of GABAergic interneuron markers, such as parvalbumin (PV), vasoactive intestinal peptide, and calbindin-D28k (CaBP-28k), in the brains of the mice. Finally, the offspring in the novel ELS model showed a decreased number of cortical PV-, CaBP-28k-positive cells and an increased number of cortical ionized calcium-binding adaptors-positive cells in their brains compared to mice in the established ELS model. Collectively, these results indicated that the novel ELS model induced more negative effects on brain and behavioral development than the established ELS model. Early life is a period sensitive and vulnerable to environmental influences, such as stress, and the negative influences of early life impact later life [1]. It has been demonstrated that exposure to stress in early life may increase susceptibility to metabolic, cardiovascular, and mental diseases in organisms [2,3]. The experimental model of early life stress (ELS) mimics stresses that make up human adversity, including deprivation, maltreatment, and maternal neglect [4,5]. Researchers using ELS models have shown that ELS is associated with aberrant brain plasticity, leading to memory dysfunction, mood disorders, and neurodegeneration [6,7]. In an ELS model with limited bedding material, mouse pups showed fear memory impairment [8]. In an amyloid-based mouse model of Alzheimer’s disease, the same ELS model was applied with added mesh platform conditions, which promoted amyloid plaque formation and altered neuroinflammatory responses in the hippocampus [9]. The maternal separation model alters the gene expression of glucocorticoid receptors related to the hypothalamus-pituitary-adrenal (HPA) axis in the dentate gyrus of offspring mice [10]. ELS, using the neonatal predator odor exposure paradigm, increased the expression level of long-interspersing element 1, a retrotransposon related to psychiatric disorders, such as schizophrenia and bipolar disorder, and induced social deficits in juvenile mice [11]. In the hippocampus of male offspring mice, the expression of cell proliferation and differentiation markers was reduced by an ELS model in which maternal care was inhibited during the developmental period [12]. Additionally, the maternal separation model alters gene expression related to oligodendrogenesis and immediate early gene expression in the medial prefrontal cortex of postnatal day 15 (P15) mice [13]. Based on these results, previous studies have investigated the impact of ELS on brain health but have only used a single ELS condition, such as maternal separation, maternal care fragmentation, or predator odor exposure. Research on the collective effects of diverse ELS conditions is unclear. In the postnatal period, maternal care is the most important factor for emotional and neural development in offspring [14]. Maternal care can contribute to the survival and growth of the infant and shape behavioral responses in adulthood [15]. In studies investigating the effect of impaired maternal care on offspring, the maternal separation paradigm has been actively used as an ELS model [16,17,18]. A previous study revealed that maternal separation may induce hyperactivity of the HPA axis, leading to psychiatric disorders, such as depression, in offspring mice [19]. An established ELS model, using the maternal separation paradigm, demonstrated that maternal separation causes anxiety-like behavior and elevated plasma adrenocorticotropic hormone levels in rat offspring [20]. Additionally, long-term maternal separation induces a neuroinflammatory response and reduces the expression of collapsing response mediator protein 2, a neuroprotective mediator, in the brains of offspring mice [21]. Currently, the effects of ELS on neurodevelopment are unclear. Thus, to further investigate the influence of ELS on the brains of offspring mice, and to manufacture a suitable ELS model for in-depth research on neurodevelopment, we established a novel ELS model in which the maternal separation paradigm and mesh platform condition were combined. We hypothesized that this model would lead to more negative effects on neurodevelopment in offspring mice than the established maternal separation ELS model. In addition, we focused on changes in behavior and alterations in brain cell distribution in the novel ELS model because previous studies reported that ELS disrupted normal behavior and the balance of cell distribution in the brain [22,23,24]. From our results, we propose that the novel ELS model is more suitable than the established ELS model in studies investigating the impact of ELS on brain development and behavior because of its enhanced negative effect on brain development and behavior in the offspring mice. Tail suspension and forced swimming tests were performed to assess whether the established and novel ELS models induced depression-like behavior in the offspring mice. In the tail suspension test, there was no significant difference in immobility time between the control and established ELS groups (Figure 1a). The novel ELS group displayed significantly higher immobility times than the control and established ELS groups (F2,37 = 7.818, p = 0.0015; control: 18 mice (11 males, 7 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 16 mice (9 males, 7 females); Figure 1a). In the forced swimming test, all ELS groups showed markedly higher immobility times than the control group. However, the immobility times in the novel ELS group were significantly higher than those in the control and established ELS groups (F2,42 = 33.86, p < 0.0001; control: 20 mice (8 males, 12 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 19 mice (8 males, 11 females); Figure 1b). These results indicated that the novel ELS model induced more severe depression-like behavior in the offspring mice than the established ELS model. To analyze anxiety-like behavior, an elevated plus-maze test (reflected by the percent time in the open arms) and an open-field test (reflected by the time spent in the center zone) were performed. First, the results of the elevated plus-maze test showed that the percent time in the open arms (F2,39 = 7.865, p = 0.0014) were significantly lower in the established and novel ELS groups than that in the control group (control: 19 mice (9 males, 10 females), established ELS: 5 mice (3 males, 2 females), and novel ELS: 18 mice (8 males, 10 females); Figure 1c). However, there was no significant difference in the results of the elevated plus-maze test between the established and novel ELS groups (Figure 1c). In the open-field test, the established ELS and novel ELS groups displayed significantly lower amounts of time spent (F2,34 = 8.798, p = 0.0008) and number of entries into the center area (F2,34 = 10.22, p = 0.0003) than the control group (control: 15 mice (12 males, 3 females), established ELS: 6 mice (3 males, 3 females), novel ELS: 16 mice (8 males, 8 females); Figure 1d–f). The results of the open-field test were not significantly different between the established and novel ELS groups (Figure 1d–f). These results indicate that the novel ELS model induced anxiety-like behavior in the offspring mice. A social interaction test was performed to evaluate the social interaction behavior of each group. In the social interaction test, there was a lower level of interaction observed in the established and novel ELS groups compared to that in the control group (general sniffing: F2,25 = 16.41, p < 0.0001; anogenital sniffing: F2,25 = 8.949, p = 0.0012) (control: 10 mice (6 males, 4 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 12 mice (5 males, 7 females); Figure 2a). These results demonstrated that the established and novel ELS models negatively alter social behavior in the offspring mice. Next, we used a three-chamber test to assess social interaction behavior and discrimination of social novelty in each group. First, the mice in each group explored the three-chamber apparatus in which an unfamiliar mouse existed in one of the side chambers (Figure 2b). In the sociability test, while the control group spent more time in the chamber containing the unfamiliar mouse (S1) than in the empty chamber, there was no significant difference in the time spent in the chamber containing the unfamiliar mouse (S1) and the time spent in the empty chamber between the established ELS and novel ELS groups (control; Empty = 204.52 ± 15.28, Stranger I = 313.39 ± 17.61, (t40 = 4.668, p < 0.0001); established ELS; Empty = 194.53 ± 17.58, Stranger I = 303.69 ± 53.43, (t10 = 1.941, p = 0.081); and novel ELS; Empty = 224.16 ± 10.41, Stranger I = 263.34 ± 19.88, (t32 = 1.746, p = 0.0904)) (control: 21 mice (12 males, 9 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 17 mice (9 males, 8 females); Figure 2c). In the social novelty test, while the control group spent more time in a novel chamber (S2) than in the familiar chamber (S1), the established and novel ELS groups spent almost a similar amount of time in the two chambers (control; Stranger I = 176.09 ± 15.06, Stranger II = 321.47 ± 18.65, (t40 = 6.065, p < 0.0001); established ELS; Stranger I = 240.31 ± 36.23, Stranger II = 257.04 ± 30.94, (t10 = 0.3512, p = 0.7327); and novel ELS; Stranger I = 235.12 ± 21.31, Stranger II = 260.24 ± 22.37, (t32 = 0.8128, p = 0.4223) (control: 21 mice (12 males, 9 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 17 mice (9 males, 8 females); Figure 2c). These results demonstrated that the novel ELS model induces social behavioral deficits in the offspring mice. Initially, the Morris water maze test was performed to assess the spatial learning and memory ability of each group. There was no significant difference in the time taken to arrive at the hidden platform in all groups during the first 3 days of the training phase (day 1: control = 57.10 ± 0.76, established ELS = 55 ± 1.77, novel ELS = 59.52 ± 0.46; day 2: control = 50.48 ± 2.83, established ELS = 45.25 ± 3.87, novel ELS = 50.18 ± 3.10; day 3: control = 36.82 ± 4.11, established ELS = 34.8 ± 3.33, novel ELS = 37.14 ± 3.79; Figure 3a). The average escape latency was significantly higher in the established and novel ELS groups than in the control group during training days 5 and 7 and between training days 4–7, respectively. The novel ELS group exhibited a markedly higher average escape latency, compared to that in the established ELS group, on training days 6 and 7 (day 4: control = 18.5 ± 2.52, established ELS = 24.75 ± 3.05, novel ELS = 31.25 ± 3.43 (F2,77 = 5.51, p = 0.0058); day 5: control = 14.14 ± 1.43, established ELS = 24.58 ± 2.34, novel ELS = 31.96 ± 2.67 (F2,77 = 17.36, p < 0.0001); day 6: control = 14.14 ± 1.36, established ELS = 24.58 ± 1.15, novel ELS = 31.96 ± 2.04 (F2,77 = 12.78, p < 0.0001); day 7: control = 13.21 ± 0.65, established ELS = 17.75 ± 1.13, novel ELS = 24.36 ± 1.90 (F2,77 = 25.65, p < 0.0001); control: 6 mice (4 males, 2 females), established ELS: 5 mice (3 males, 2 females), and novel ELS: 6 mice (3 males, 3 females); Figure 3a). After the training phase, the platform was removed from the pool for probe testing. There was no significant difference in the crossing number of the area where the platform was previously located between the established ELS and control groups, whereas the novel ELS group exhibited a slightly lower value for the same than the control group (F2,14 = 6.091, p = 0.0125; control: 6 mice (4 males, 2 females), established ELS: 5 mice (3 males, 2 females), and novel ELS: 6 mice (3 males, 3 females); Figure 3c). The distance moved and velocity did not differ significantly between all groups (Figure 3d,e). Representative images of the swim track of all groups revealed that the novel ELS group showed lower proximity to the platform quadrant than the control group (Figure 3b). We analyzed the recognition memory of each group using the novel object test. The mice were allowed to explore two identical objects, and 6 h later, one of the two objects was replaced by a new novel object. The control group exhibited greater approach time and proximity to the novel object than the familiar object (control; familiar object = 37.90 ± 1.95, control; novel object = 62.10 ± 1.95, (t24 = 8.796, p < 0.0001)), but the established ELS and novel ELS groups displayed no difference in approach time and proximity between the familiar and novel objects (established ELS: familiar object = 44.35 ± 5.08, established ELS: novel object = 55.65 ± 5.08, (t10 = 1.573, p = 0.1468); novel ELS: familiar object = 45.85 ± 3.08, novel ELS: novel object = 54.15 ± 3.08, (t18 = 1.816, p = 0.0861)) (control: 13 mice (7 males, 6 females), established ELS: 6 mice (3 males, 3 females), novel ELS: 10 mice (6 males, 4 females); Figure 3f). Taken together, these results indicate that the novel ELS model impaired spatial learning and recognition memory in the offspring mice and induced more severe memory dysfunction than the established ELS model. We estimated the effects of all ELS models on the growth of the body and the brain of early-stage offspring mice. The novel ELS group showed a more significant reduction of body and brain weight on P14 than the control and established ELS groups (body weight: F2,17 = 113.9, p < 0.0001; brain weight: F2,17 = 53.01, p = 0.0012) (control: 6 mice (4 males, 2 females), established ELS: 5 mice (3 males, 2 females), and novel ELS: 6 mice (3 males, 3 females); Figure 4a–d). However, there were no marked differences in body and brain weight in P112 offspring mice for all groups (control: 7 mice (3 males, 4 females), established ELS: 4 mice (2 males, 2 females), and novel ELS: 8 mice (4 males, 4 females); Figure S1a–d). These results indicate that the novel ELS model delays normal brain development in the early stage, but does not persist in the adult stage. It is known that ELS induces the expression of the stress hormone arginine vasopressin (AVP) and corticotropin-releasing hormone, leading to HPA axis activation [25,26]. Additionally, it was reported that ELS disturbs the function of the inhibitory GABAergic interneuron in the brain development stage [23,27]. In this study, we evaluated the effects of the novel ELS model on the expression of genes associated with stress and GABAergic interneurons in brains of P14 offspring mice. First, AVP expression increased significantly in the novel ELS group compared to that in the control group (F2,17 = 5.72, p = 0.0134; control: 8 mice (5 males, 3 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 6 mice (2 males, 4 females); Figure 4e). Moreover, the expression of GABAergic interneuron marker genes, parvalbumin (PV) and calbindin-D28k (CaBP-28k), decreased significantly in the novel ELS group compared with that in the control and established ELS groups, and vasoactive intestinal peptide (Vip) expression also markedly decreased in the novel ELS group, more than that in the control group (Pavlb: F2,17 = 24.52, p < 0.0001; Vip: F2,17 = 3.527, p = 0.0523; CaBP-28k: F2,17 = 10.71, p = 0.001) (control: 8 mice (5 males, 3 females), established ELS: 6 mice (3 males, 3 females), and novel ELS: 6 mice (2 males, 4 females); Figure 4f). These results suggest that the novel ELS model induces a more severe stress response and has a more negative impact on GABAergic interneuron development than the established ELS model in the early stages of life. Previous studies have reported that the ELS model may alter a number of cortical GABAergic interneuron subpopulations and microglial cell populations in the offspring’s brains [28,29]. In this study, we investigated the changes in the densities of cortical PV+, CaBP-28k+, and Iba-1+ cells in the brains of P112 offspring mice, using established ELS and novel ELS models. The cortical PV+ cell densities in the brains of P112 offspring from the established ELS and novel ELS groups were significantly lower than those in the brains of P112 offspring from the control group (F2,12 = 8.761, p = 0.0045; 5 photographs of 0.58 mm2 cortical layer in mice (3 male, 2 female) for each group; Figure 5a,d). The cortical CaBP-28k+ cell densities were significantly reduced in the brains of the P112 offspring from the established ELS and novel ELS groups than those in the brains of the P112 offspring from the control group (F2,12 = 39.4, p < 0.0001; 5 photographs of 0.58 mm2 cortical layer in mice (3 male, 2 female) for each group; Figure 5b,e). Additionally, the cell densities of cortical Iba-1+ in the brains of P112 offspring from the established ELS and novel ELS groups were significantly higher than those in the brains of P112 offspring from the control group (F2,12 = 32.96, p < 0.0001; 5 photographs of 0.58 mm2 cortical layer in mice (3 male, 2 female) for each group; Figure 5c,f). The novel ELS groups showed markedly higher cell densities of cortical Iba-1+ in the brains of P112 offspring mice than in the established ELS group (Figure 5c,f). These results indicate that the novel ELS model downregulated the cell distribution of GABAergic interneurons and induced microglia reactivity in the brains of offspring mice compared to the established ELS model. During the lactation period, the interaction between infants and their dams supplies most of the requirements for brain development, survival, and growth [14,30]. Disturbances in the relationship between offspring and their dams may lead to stress responses during the postnatal period [31,32]. The correlation between maternal care and stress response in newborn infants has been previously reported [32,33,34]. Previous studies have demonstrated that the stress response induced during the postnatal period may affect brain function, neuroplasticity, neurodevelopment, and behavioral reactions [6,35]. To investigate the adverse effects of stress on brain health in the postnatal period of offspring, many researchers have used ELS models that apply the maternal separation paradigm, limited bedding material, and mesh platform conditions [36]. In the chronic ELS mouse model, ELS resulted in the disruption of maternal interaction and elevated basal plasma corticosterone levels, indicating induction of the stress response and memory impairment in the offspring mice [37]. Additionally, ELS delayed hippocampal development in P10 mice and reduced the number of hippocampal stem cells in P163 adult offspring mice [38]. In this study, we built a novel ELS model that combines diverse ELS conditions, such as the maternal separation paradigm, limited bedding material, and mesh platform conditions, thereby enabling a detailed study of the impacts of ELS on brain development. The novel ELS model triggered body and brain weight reduction; however, this was reversed in P112 mice. In addition, we found that the novel ELS model upregulated AVP gene expression in the brains of P14 offspring mice. Johnson et al. reported that ELS induced a reduction in body weight in P14 and P28 mice, but weight loss by ELS displayed a tendency to recover in P60 mice—the adult stage [39]. It was demonstrated that the brain weight change was not induced by the maternal separation model, which was similar to the established ELS model we applied [40]. In addition, the maternal separation paradigm did not induce activation of AVP expression in P15 mice brains [41]. These correspond with our results, and our results suggest that the novel ELS model may not only adversely affect mouse brain development in the early postnatal period, but may also be considered a more stressful condition than the established ELS model. Previous studies have suggested that early life adversity may predispose individuals to psychological disorders, such as depression, anxiety disorder, and anhedonia [42,43,44]. In a comparative research based on humans, women who suffered from abuse showed higher susceptibility to postpartum depression than women who did not [33]. A previous study reported that children who experienced early life adversity, such as physical abuse, violence, and parental absence, showed a higher incidence rate of anxiety disorder and depression in adulthood than children who did not [45]. Recent research on experimental animals has indicated that ELS induces anxiety-like behavior by enhancing neuronal excitability in the basolateral amygdala projection neurons [46]. The offspring mice that suffered from ELS showed impairments in social novelty behavior, but no memory impairments [47]. In addition, offspring rats suffering from ELS showed a reduction in body weight, as well as anxiety- and depression-like behavior [48]. In this study, the novel ELS model induced anxiety- and depression-like behavior in offspring mice. Moreover, the novel ELS model caused social deficiency and memory dysfunction in the offspring mice. This study demonstrated that depression-like behavior and memory impairments induced by the novel ELS model were more negative than the behavioral changes induced by the established ELS model. It was previously reported that the maternal separation paradigm induced memory dysfunction in the Morris water maze test; however, our study showed that the maternal separation paradigm (the established ELS model) tended to decrease memory function in the test trial of the Morris water maze test, but the decrease was not significant [49,50]. This was considered a result due to the relatively small number of animals subjected to the Morris water maze test compared to other behavioral experiments in this study. Collectively, these results suggest that the negative effects of ELS may differ in accordance with the conditions of ELS, and that the novel ELS model may cause more negative behavioral phenotypes than the established ELS model in offspring mice. Therefore, the novel ELS model may be more appropriate than the established ELS model for the in-depth study of behavioral responses caused by ELS. GABAergic interneurons regulate neural circuits and circuit activity by controlling the activity of principal neurons in the central nervous system and are known to contain calcium-binding proteins, such as CaBP-28k and PV, and neurotransmitters like Vip. [51,52,53,54]. In GABAergic interneurons, CaBP-28k and PV act as buffers for the maintenance of intracellular calcium ion concentration and contribute to the activation of calcium-dependent signaling [55,56]. In addition, Goff et al. reported that Vip is an important mediator that regulates neural dynamics in the brain, and that Vip interneuron dysfunction may cause neurodevelopmental disorders [57]. Several studies using the ELS model have found that ELS-induced changes in the expression of CaBP-28k, PV, and Vip are associated with behavioral alterations in mice. It has been demonstrated that downregulation of CaBP-28k levels, mediated by the ELS-induced elevated corticotropin-releasing hormone receptor type 1 pathway, contributes to memory impairment in the hippocampus of offspring mice [58]. Mouse brains, in which the expression of CaBP-28k was reduced by antisense transgenesis, induced dysfunction of long-term potentiation in the CA1 hippocampal region and memory deficit [59]. In juvenile female rats, ELS causes a reduction in PV protein levels in the prefrontal cortex and induces social deficits [23]. Lussier et al. reported that the reduction of PV+ GABAergic interneuron in the medial prefrontal cortex and hippocampus by prenatal stress leads to social deficits and anxiety behavior in adult mice [60]. It was reported that Methyl-CpG binding protein 2 deletion in Vip interneurons causes disturbance in cortical activity and dysfunction of social behavior [61]. In the dorsolateral prefrontal cortex of postmortem schizophrenia patients, the mRNA levels of PV and Vip were decreased compared with those of normal humans [62]. In the present study, the novel ELS model decreased PV, CaBP-28k, and Vip gene expression more than the established ELS model in the brains of P14 offspring mice. We found that the novel ELS model induced a more significant reduction in CaBP-28k+ cell numbers in the brains of offspring mice than the established ELS model. Additionally, the PV+ cell number was significantly reduced in the brains of the novel ELS group compared to that in the brains of the control group. These results indicate that the novel ELS model may affect GABAergic interneuron maintenance more negatively than the established ELS model and exacerbate abnormal behavioral phenotypes. In future studies, we will investigate whether the novel ELS model specifically impairs medial and caudal ganglionic eminences, the origin regions of PV and Vip interneurons [63]. Additionally, we will study the molecular mechanism associated with the downregulation of the GABAergic interneuron marker genes by a novel ELS model because the exact molecular mechanism was not investigated in this study. In this study, we found that the novel ELS model significantly increased the number of Iba-1+ cells, indicating increased microglia reactivity in the brains of the offspring mice. In the central nervous system, microglia are the main players of the innate immune system and are involved in the maintenance of normal brain functions, as well as immune surveillance in the brain [64,65]. Microglia, activated by damaged neurons and infectious agents, induce inflammatory effects by releasing cytokines, such as interferon-γ and interleukin (IL)-8, and phagocytosing various materials, such as cellular debris and apoptotic cells [66,67]. Previous studies have shown that the ELS induces immune responses through microglia reactivity in the brain. It has also been reported that ELS increases the number of Iba-1+ cells in the dorsal striatum and the mRNA level of IL6 in the hippocampus [24]. Moreover, ELS increased the phagocytic activity of microglia and induced the expression of pro-inflammatory genes, such as IL6, IL27, and Tnfrsf13b, in the hippocampus of P28 mice [68]. Studies with molecular mechanisms, however, are needed to further confirm that the novel ELS model induces microglia reactivity. Collectively, these results suggest that the novel ELS model described in this study may induce immune responses more actively in the brains of offspring mice than the established ELS model, and is therefore appropriate for investigating the exact molecular mechanisms of ELS-induced neuroinflammation. Specific pathogen-free adult C57BL/6J male and female mice (8 weeks old, 25–30 g) were obtained from Samtaco (Osan, Gyeonggi, Republic of Korea). Mice were group-housed and maintained for time-controlled breeding in standard cages. Mice were kept at 12/12 h light–dark cycle (lights on at 7 a.m.), water and food ad libitum, and conditioned rooms (22 °C, humidity 30%). After acclimatization, the female mice were mated with adult male mice overnight in a ratio of 2:1; subsequently, the day on which a vaginal plug was observed was considered as embryonic day (E) 0.5. The pregnant mice were only present in the home cage, individually, from gestation through weaning (P28.5). The dams were randomly divided into three groups: control, established ELS, and novel ELS (n = 4 dams/control group, n = 2 dam/established ELS group, n = 3 dams/novel ELS group, and 1 mouse per cage). After weaning (P28.5), the female and male offspring were separated and housed in groups of 3–5 animals until P112 (n = 26 (13 males, 13 females) for controls, n = 14 (6 males, 8 females) for established ELS, and n = 22 (10 males, 12 females) for novel ELS). To compare the effects of the established and novel ELS models on the brain development of early postnatal mice, the maternal mice were divided into three groups: control, established ELS, and novel ELS groups (n = 1 dam/group). On P14, the offspring mice from all groups were sacrificed (n = 8 (5 males, 3 females) for controls, n = 6 (3 males, 3 females) for established ELS, and n = 6 (2 males, 4 females) for novel ELS). The litter size per dam for each group, used for all experiments, is stated in Table S1. The Institutional Animal Care and Use Committee of Pusan National University approved all experimental protocols, and all experiments were conducted in accordance with the ARRIVE guidelines and the ILAR Guide to the Care and Use of Experimental Animals. Dams were monitored every 12 h to check for signs of birth. The day of parturition was designated P0. From P2 onwards, pups were assigned to either the control, established ELS, or novel ELS groups. The control group was provided with 400 mL of standard sawdust bedding and a sufficient amount of nesting material (4.8 g of Nestlet, Indulab, Gams, Switzerland). The control group’s mice were bred in maternity cages with their dams, without any interference (Figure 6a). The established ELS condition, as a maternal separation paradigm, was designed based on an established protocol, with minor modifications [69]. Additionally, we selected 2 weeks as a stress-inducing period based on previous research about the impact of ELS on brain health [13,70,71,72]. The mice of the established ELS group were separated from their dams for 4 h (11:00–15:00) daily, from P2 to P14, in a novel cage with 400 mL of standard sawdust bedding (Figure 6b). After 4 h of separation, the pups were returned to their home cages that contained their dams and were bred in the same conditions as that of the control group. The novel ELS group underwent a maternal separation paradigm in which pups and their dams were separated for 4 h (11:00–15:00) daily, from P2 to P14, in a novel cage with a fine-gauge aluminum mesh platform, unlike that applied for the established ELS group. The mice in the novel ELS group were bred from P2 to P14 in their home cage, which contained a fine-gauge aluminum mesh platform with no sawdust bedding and a limited amount of nesting material (2.4 g of Nestlet; Figure 6c). Experimental design: at 9 weeks of age, offspring mice were selected randomly for behavioral tests, as previously described [73,74]. All behavioral tests were conducted during the light cycle. On the testing days, mice were transferred to the testing room for at least 30 min before test commencement, and testing was conducted by laboratory technicians who were blinded to the mouse group information. All experiments were conducted between 8:00 a.m. and 2:00 p.m. and a resting period of 2 days per 1 week was provided between two consecutive tests. All the experimental areas were cleaned using 70% ethanol before conducting the tests and between each test. Each mouse was suspended by attaching (with adhesive tape) the tail to the edge of a shelf 50 cm above the surface of a table. The mice were allowed to move for 6 min, and their behavior was recorded with a camera. The videos were analyzed using EthoVision® XT16. The immobility time was recorded over the last 5 min of the experiment. Each mouse was gently placed in a glass cylinder (20 cm in height and 15 cm in diameter) filled with water (25 °C ± 2 °C), to a depth of 12 cm. For the pre-test, all mice underwent water exposure for 15 min. After 24 h, all mice were forced to swim for 5 min, and the duration of immobility was recorded by the camera. The videos were analyzed using EthoVision® XT16. The elevated plus-maze test was performed, as previously described [74]. The apparatus included two open arms (35 × 5 cm), two enclosed arms (35 × 5 × 15 cm), and a central platform (5 × 5 cm). The apparatus was elevated 45 cm above the floor. The mouse was placed on the central platform facing the open arms and allowed to roam freely for 5 min. The percentage of time in the arms was calculated as per the following formula: (time spent in open arms/time spent in total arms) × 100. The open-field test was performed on a large 50 cm tall and 60 cm wide acrylic cube with a white bottom. Briefly, to evaluate locomotor activity, mice were individually placed near the wall and allowed to move freely for 5 min. The movement of the mice was recorded and analyzed using the EthoVision® XT16 software (Noldus, Leesburg, VA, USA). The time spent in the center zone, frequency of entry into the center zone (15 × 15 cm imaginary square), velocity, and distance traveled were measured and documented. The experimental mouse and stranger C57BL/6J mouse were introduced into the open field from opposite sides of the apparatus and were allowed to explore it freely for 10 min. The interaction indices, including general sniffing, anogenital sniffing, and following, were counted manually. The three-chambered apparatus was composed of three Plexiglas chambers, each measuring 20 × 40 × 22 cm, and dividing walls with small square entrances (10 × 5 cm) that allowed free movement to each chamber. Both side chambers contained a cylindrical plastic cage (17 cm in height and a bottom diameter of 8 cm, with bars spaced 1 cm apart) in the corner that was used to confine the stranger mice. The three-chambered social test was then executed according to a previous study [75]. First, the subject mice were placed in the apparatus to freely explore all three chambers, with an empty plastic cage in each side chamber (5 min habituation period). For sociability testing, an unfamiliar C57BL/6J mouse (Stranger 1, “S1”) was confined in the cylindric plastic cage in one of the side chambers, and an empty cylindrical plastic cage (Empty “E”) was kept on the other side of the chamber. The subject mouse was then placed in the center chamber and allowed to freely explore all three chambers for 10 min. For the social novelty test, the empty plastic cage was replaced with another unfamiliar C57BL/6J mouse (Stranger 2, “S2”) and the subject mouse was again allowed to freely explore all the three chambers for 10 min. All stranger mice were of the same sex and age as the subject mice and were habituated to plastic cages. The time spent in the chamber, distance traveled, and heat-maps were measured using EthoVision® XT16 software. The Morris water maze test was performed in a circular pool (90 cm in diameter and 40 cm in height) filled with water (25 °C ± 1 °C). The water was made opaque by the addition of skim milk. The tank was divided into four equal sections (I, II, III, and IV). A circular platform (10 cm in diameter and 20 cm in height) made of Plexiglass was placed in the middle of the target quadrant (III; 12 cm from the edge of the pool and 1 cm below the surface of the water), with visual cues on the pool walls as spatial references. The mice received a two-phase training protocol for 7 days, comprising cue training for 3 days, followed by spatial training for 4 days. Four trials were conducted per mouse daily and the escape latency (time to locate the hidden platform) in each trial was recorded. For each trial, the subject mice were gently placed into the water facing the wall from one of three quadrants (I, II, and IV), which varied according to the day of testing. The mice were then given 1 min to locate the platform, and the trial was completed when the mice had located the platform. If the mouse failed to locate the platform within the 1 min period, it was gently guided onto the platform and allowed to rest for 30 s. The mean of the escape latencies (s) for the four trials is represented as the learning result for each mouse (training section). On day 8 (probe test day), the platform was removed from the pool and the mice were allowed to search for it for 60 s. The videos were recorded and analyzed using EthoVision® XT16 software. The amount of time spent on the target platform, number of crossings performed on the platform, distance, and velocity were measured to determine the memory results. First, the subject mice were placed in the open-field arena in the presence of two identical objects (2 × 5 × 9 cm) and were allowed to explore the open-field arena freely for 10 min. After 6 h, one of the objects was replaced by a novel object of different shape and color compared to the old object; the subject mice were again placed inside the open-field arena to freely explore it for another 10 min. The amount of time that the mice spent with the novel and old objects (sniffing or exploring at a distance within 2 cm of the object) was recorded. The recognition index was calculated as: (amount of time spent interacting with the novel object)/(amount of time spent with both the novel and old objects) × 100. The videos were analyzed using EthoVision® XT16 software. Total RNA was extracted from the whole brain of each mouse using the TRIzol reagent (Ambion, Austin, TX, USA), according to the manufacturer’s protocols. Extracted RNA was quantified using an Epoch microplate spectrophotometer (BioTek, Winooski, VT, USA). RNA purity was estimated by A260:A280 ratios. Subsequently, 1 μg of RNA was used for cDNA synthesis, and cDNA synthesis was performed using M-MLV reverse transcriptase (Invitrogen, Carlsbad, CA, USA), according to a previously described protocol [76]. Real-time PCR was performed using a SYBR Green system (Applied Biosystems, Foster City, CA, USA). Quantitative real-time PCR was performed using QuantStudio 3 (Applied Biosystems, Foster City, CA, USA). GAPDH served as an internal control. The expression of the target gene was normalized to the expression of the GAPDH gene by using the 2−ΔΔCt method [77]. Relative expression of the target gene in the established, novel ELS groups was calculated based on the gene expression of the control group as 100%. The primer sequences are as follows: AVP (F: 5′-TCGCCAGGATGCTCAACAC-3′; R: 5′-TTGGTCCGAAGCAGCGTC-3′), Pvalb (F: 5′-AGCCTTTGCTGCTGCAGACT-3′; R: 5′-GGCCCACCATCTGGAAGAA-3′), Vip (F: 5′-GCAGCAGCATCTCGGAAGAT-3′; R: 5′-TGTGAAGACGGCATCAGAGTGT-3′), CaBP-28k (F: 5′-GACGGAAAGCTGGAAACTGGAACTGAC-3′; R: 5′-AGCAAAGCATCCAGCTCATT-3′). Mice were anesthetized with avertin (2,2,2-tribromoethanol: T48402, Sigma-Aldrich, Burlington, MA, USA; ter-amyl alcohol: 240486, Sigma-Aldrich, USA; 0.018 mL (2.5%) per gram of body weight) before they were sacrificed. The extracted brains were briefly fixed in phosphate-buffered 4% paraformaldehyde at 4°C. They were transferred to 1x phosphate-buffered saline (PBS) and embedded in agarose. The embedded brain was sectioned coronally at 80 μm with a vibratome (Leica, VT1000S). The brain sections were permeabilized using PBS containing Triton™ X-100 (Sigma-Aldrich, USA) (0.5% for tissues). The tissues were then blocked using blocking buffer (PBS + 5% goat serum (Vector Laboratories, Burlingame, CA, USA) + 0.25% Triton™ X-100) for 1 h, followed by overnight incubation at 4 °C with primary antibodies against PV (catalog no. MAB1572, 1:500, Sigma-Aldrich, USA; CaBP-28k, catalog no. ABN2192, 1:1000, Millipore, Burlington, MA, USA; Iba-1, catalog no. 019-19741, 1:500, Wako, Richmond, VA, USA). For secondary staining, tissues were incubated for 1 h with a secondary antibody solution (Alexa Fluor™ 488 goat anti-mouse IgG, catalog no. A11001, 1:1000; Alexa Fluor™ 488 goat anti-rabbit IgG, catalog no. A11034, 1:1000, Invitrogen, Carlsbad, CA, USA) containing 100 ng/mL 4′,6-diamidino-2-phenylindole (Sigma-Aldrich, USA). The cells were then mounted in Fluoro-Gel (Emsdiasum, Hatfield, PA, USA). Fluorescently labeled cells in the brain tissue were visualized by a fluorescence microscope (Axio Observer 7 with Apotome 3; Zeiss, Oberkochen, Germany) and were quantified by Image J software [78]. All statistical analyses were conducted using a one-way ANOVA for more than two independent groups (Bonferroni’s multiple comparison test for comparing all pairs of columns) and an unpaired Student’s t-test (for comparing two independent groups). Data were collected randomly and analyzed using Prism software (GraphPad 5, San Diego, CA, USA). The results are presented as mean ± SEM, and the p-values for each comparison are described in the Results section. Each experiment was performed in a blinded and randomized manner. Animals were randomly assigned to different experimental groups, and data were collected and processed randomly. The allocation, treatment, and handling of the animals were similar across the study groups. The results of all ELS groups were compared with the results of the control group. All experiments were independently performed in triplicate. The novel ELS model was more effective in inducing anxiety-like behavior and promoting depression-like behavior than the established ELS model. Offspring mice exposed to the novel ELS model showed social deficits and more severe memory dysfunction than those exposed to the established ELS model. The novel ELS model induced a disturbance in the growth of the mice and altered the gene expression related to stress response and GABAergic interneurons in the brains of P14 offspring mice. The novel ELS model caused a decrease in the number of cortical GABAergic interneurons and induced microglia reactivity in the brains of adult offspring mice. Taken together, this novel ELS model of early postnatal manipulation will be able to contribute to a clearer understanding of the negative effects of ELS on brain health.

PMC10002979

36910192

Xinyu Zhang,Wei Wang,Zhijun Cao,Hongjian Yang,Yajing Wang,Shengli Li

Effects of altitude on the gut microbiome and metabolomics of Sanhe heifers

24-02-2023

different altitudes,gut microbiota,metabolites,Sanhe heifers,high-altitude adaptation

Introduction Extreme environments at high altitudes pose a significant physiological challenge to animals. We evaluated the gut microbiome and fecal metabolism in Sanhe heifers from different altitudes. Methods Twenty Sanhe heifers (body weight: 334.82 ± 13.22 kg, 15-month-old) selected from two regions of China: the Xiertala Cattle Breeding Farm in Hulunbeier, Inner Mongolia [119°57′ E, 47°17′ N; approximately 700 m altitude, low altitude (LA)] and Zhizhao Dairy Cow Farm in Lhasa, Tibet [91°06′ E, 29°36′ N; approximately 3,650 m altitude, high altitude (HA)], were used in this study. Fecal samples were collected and differences in the gut microbiota and metabolomics of Sanhe heifers were determined using 16S rRNA gene sequencing and metabolome analysis. Results and discussion The results showed that altitude did not significantly affect the concentrations of fecal volatile fatty acids, including acetate, propionate, butyrate, and total volatile fatty acids (p > 0.05). However, 16S rRNA gene sequencing showed that altitude significantly affected gut microbial composition. Principal coordinate analysis based on Bray–Curtis dissimilarity analysis revealed a significant difference between the two groups (p = 0.001). At the family level, the relative abundances of Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, and Family_XIII were significantly lower (p < 0.05) in LA heifers than in HA heifers. In addition, the relative abundances of Lachnospiraceae, Domibacillus, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, Porphyromonadaceae, and Spirochaetaceae were significantly higher in HA heifers than in LA heifers (p < 0.05). Metabolomic analysis revealed the enrichment of 10 metabolic pathways, including organismal systems, metabolism, environmental information processing, genetic information processing, and disease induction. The genera Romboutsia, Paeniclostridium, and g_unclassified_f_Lachnospiraceae were strongly associated with the 28 differential metabolites. This study is the first to analyze the differences in the gut microbiome and metabolome of Sanhe heifers reared at different altitudes and provides insights into the adaptation mechanism of Sanhe heifers to high-altitude areas.

Effects of altitude on the gut microbiome and metabolomics of Sanhe heifers Extreme environments at high altitudes pose a significant physiological challenge to animals. We evaluated the gut microbiome and fecal metabolism in Sanhe heifers from different altitudes. Twenty Sanhe heifers (body weight: 334.82 ± 13.22 kg, 15-month-old) selected from two regions of China: the Xiertala Cattle Breeding Farm in Hulunbeier, Inner Mongolia [119°57′ E, 47°17′ N; approximately 700 m altitude, low altitude (LA)] and Zhizhao Dairy Cow Farm in Lhasa, Tibet [91°06′ E, 29°36′ N; approximately 3,650 m altitude, high altitude (HA)], were used in this study. Fecal samples were collected and differences in the gut microbiota and metabolomics of Sanhe heifers were determined using 16S rRNA gene sequencing and metabolome analysis. The results showed that altitude did not significantly affect the concentrations of fecal volatile fatty acids, including acetate, propionate, butyrate, and total volatile fatty acids (p > 0.05). However, 16S rRNA gene sequencing showed that altitude significantly affected gut microbial composition. Principal coordinate analysis based on Bray–Curtis dissimilarity analysis revealed a significant difference between the two groups (p = 0.001). At the family level, the relative abundances of Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, and Family_XIII were significantly lower (p < 0.05) in LA heifers than in HA heifers. In addition, the relative abundances of Lachnospiraceae, Domibacillus, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, Porphyromonadaceae, and Spirochaetaceae were significantly higher in HA heifers than in LA heifers (p < 0.05). Metabolomic analysis revealed the enrichment of 10 metabolic pathways, including organismal systems, metabolism, environmental information processing, genetic information processing, and disease induction. The genera Romboutsia, Paeniclostridium, and g_unclassified_f_Lachnospiraceae were strongly associated with the 28 differential metabolites. This study is the first to analyze the differences in the gut microbiome and metabolome of Sanhe heifers reared at different altitudes and provides insights into the adaptation mechanism of Sanhe heifers to high-altitude areas. Areas with an altitude higher than 2,500 m, generally defined as high altitudes (Moore et al., 2010), pose challenges for the survival, growth, and development of local animals (Moore et al., 2010; Guo et al., 2014). As the highest plateau worldwide, the Tibetan Plateau is characterized by low pressure, low oxygen, strong ultraviolet rays, and low temperatures throughout the year (Zha et al., 2016; Sun et al., 2021). High altitude, low pressure, and hypoxia can cause various diseases such as pulmonary hypertension (Pasha and Newman, 2010; Khanna et al., 2018), high-altitude hypertension (Bilo et al., 2019), and vascular dysfunction. Additionally, numerous metabolic disorders in the digestive tract, such as enteritis and gastritis, can be caused by an imbalance in the gut microbiota under low pressure and hypoxic conditions (Khanna et al., 2018; Hill et al., 2020; Pena et al., 2022). Bacteria play a key role in many types of feed biopolymer fermentation and degradation processes (Bickhart and Weimer, 2018), and fecal samples mostly represent the distal portion of the gut microbiotathe (de Oliveira et al., 2013). Recent studies have reported the high-altitude adaptability of various animals such as cattle (Kong et al., 2021), yak (Ayalew et al., 2021), and rats (Murray, 2016). Recently, alterations in the gastrointestinal microbiota due to altitude changes were investigated in yak (Liu et al., 2021), sheep (Holman et al., 2019), and pigs (Zeng et al., 2020). However, the changes in the gut microbiota and the physiological and metabolic mechanisms in response to high altitudes have not yet been investigated in Sanhe heifers. Moreover, variations in the metabolic adaptability of the gut microbiota of Sanhe heifers at different altitudes are not well understood. As a dual-purpose breed, Sanhe cattle show excellent performance in both milk and meat production (Xu et al., 2017); their milk contains high concentrations of fat. In addition, Sanhe cattle exhibit strong adaptability, rough feeding tolerance (Hu et al., 2019), strong disease resistance (Usman et al., 2017), and stable genetic performance. Sanhe cattle originated from Inner Mongolia, China, and were bred to result in multiple breeds, including native Mongolian cattle, Simmental cattle, Siberian cattle, improved Russian cattle, Zabaikal cattle, Tagil cattle, Yaroslav cattle, Swedish cattle, and Hokkaido Dutch cattle. We examined whether Sanhe cattle can adapt to high-altitude environments, by evaluating the differences between Sanhe heifers in low-and high-altitude regions from a gut microbiota perspective. In this study, the gut microbiomes of Sanhe heifers being offered the same amount of nutrients by the total mixed ration (TMR) but living in two regions of different altitudes, were compared. Using high-throughput sequencing and LS-MS-based untargeted metabolome analyzes, we aimed to reveal the effect of altitude on the gut microbiome of Sanhe cattle and to improve the understanding of the role of the gut microbiome in high-altitude adaptability. In addition, the gut microbiome and metabolomics of Sanhe heifers from low-and high-altitude regions were compared to provide insights into the high-altitude adaptability of ruminants. The study protocol was approved by the Ethical Committee of the College of Animal Science and Technology of China Agricultural University (project number AW22121202-1-2). Twenty Sanhe heifers (body weight: 334.82 ± 13.22 kg, 15-month-old) fed in two different altitude regions of China were selected for the experiments. Ten Sanhe heifers were selected from each trial site. Cattle from two regions were analyzed: those from the origin of Sanhe cattle, including Hulunbuir, Inner Mongolia Autonomous Region (119°57′ E, 47°17′ N; approximately 700 m in altitude, LA group), and Lhasa, Tibet Autonomous Region (91°06′ E, 29°36′ N; approximately 3,650 m in altitude, HA group). Lhasa has an average annual temperature of 8.6 Â °C and annual precipitation of 472.5 mm (Fan et al., 2005), whereas Hulunbuir has an average annual temperature of 3.3°C and annual precipitation of 538.3 mm. To obtain representative samples, feces from Sanhe heifers were collected from the rectum using plastic gloves. The fecal samples used to analyze the gut microbiota were immediately frozen in liquid nitrogen (−80°C), and those used to analyze volatile fatty acids (VFAs) were stored at −20°C. For VFA analysis, the fecal sample from each animal was thawed, diluted, and centrifuged at 8,000 × g at 4°C for 10 min, and the supernatant was collected and evaluated using gas chromatography (Erwin et al., 1961). Total microbial genomic DNA was extracted from 1 g of fecal samples using an OMEGA kit (Omega Bio-Tek, Norcross, GA, United States), following the manufacturer’s instructions. A Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, United States) was used to confirm the purity and concentration of the extracted DNA. The V3–V4 region of the gut bacterial 16S rRNA gene was amplified using the forward primer 338F (5′-ACTCCTACGGGAGGCAGCA-3′) and the reverse primer 806R (3′-GGACTACNNGGGTATCTAAT-5′). The PCR conditions were as follows: denaturation at 95°C for 5 min, followed by 28 cycles at 95°C for 45 s, 55°C for 50 s, and 72°C for 45 s, with a final extension at 72°C for 10 min. Amplified fragments were visualized using 2% agarose gel electrophoresis, and the respective bands were purified using an Agencourt AMPure XP kit (Beckman Coulter Genomics, Brea, CA, United States) according to the manufacturer’s instructions and quantified using QuantiFluor-ST (Promega, Madison, WI, USA). Purified PCR products were sequenced on an Illumina MiSeq (Illumina, San Diego, CA, United States; Caporaso et al., 2012) using a 2 × 250 bp sequencing kit. Sequences with scores ≤20 (low quality), reads <200 bp, and reads containing ambiguous bases or unmatched primer sequences were filtered out using QIIME 1.8 (Caporaso et al., 2010), and barcode tags were removed. The obtained sequences were combined using PEAR 0.9.6 (Zhang et al., 2014) and demultiplexed using Flash (version 1.20; Mago and Salzberg, 2011). Reads with a combined length of <230 bp and chimeric sequences were removed using the UCHIME algorithm (Edgar et al., 2011). To reduce errors due to different sequencing depths, all samples were subsampled to an equal size of 31,719 for downstream alpha-and beta-diversity analyzes. To ensure comparability of species diversity between samples, standardized operational taxonomic unit (OTU) documents were used to analyze the species and diversity indices. The resulting sequences were clustered into OTUs based on a 97% sequence similarity threshold using the Ribosomal Database Project classifier (Cole et al., 2009) with a confidence threshold of 0.70 and compared against the SILVA 128 database for microbial species annotation (Quast et al., 2012). All OTUs were removed using UCLUST to generate the representative OTU table (Edgar, 2010). The OTU level alpha diversity of the bacterial communities was determined using the Chao1, Shannon, and Simpson indices and procedures within QIIME 1.8, and visualized using the “ggplot2” package of R (version 4.0.5; Wickham, 2009). Principal coordinate analysis (PCoA) based on the Bray–Curtis dissimilarity matrix was performed in R using the “vegan” package for beta diversity analysis (Oksanen et al., 2016). The cold extraction solvent methanol/acetonitrile/H2O (2:2:1, vol/vol/vol; 1 ml) was added to an 80 mg fecal sample and vortexed for 60 s to extract metabolites. The samples were incubated on ice for 20 min and centrifuged at 14,000 × g for 20 min at 4°C. The supernatant was collected for liquid chromatography (LC)-MS analysis. The samples were dissolved in 100 μl of acetonitrile/water (1:1, v/v) and transferred to LC vials. Gut microbiota metabolites were separated using an ultra-high-performance liquid chromatography system (1,290 Infinity LC, Agilent Technologies, Santa Clara, CA, United States) coupled to a quadrupole time-of-flight (TripleTOF 6,600, AB Sciex, Framingham, MA, United States). The fecal samples were analyzed using a 2.1 mm × 100 mm ACQUIY UPLC BEH 1.7 μm column (Waters, Milford, MA, United States). In both the positive and negative electrospray ionization modes, the mobile phase contained 25 mM ammonium acetate and 25 mM ammonium hydroxide in water and acetonitrile, respectively. The gradient was 85% acetonitrile for 1 min, which was linearly reduced to 65% in 11 min, reduced to 40% in 0.1 min and maintained for 4 min, and increased to 85% in 0.1 min, with a 5 min re-equilibration period. The electrospray ionization source conditions were as follows: ion source Gas1 as 60, ion source Gas2 as 60, curtain gas as 30, source temperature, 600°C; and ion spray voltage floating ±5,500 V. During MS acquisition, the instrument was set to acquire signals over an m/z range of 60–1,000 Da, and the accumulation time for the time-of-flight MS scan was set to 0.20 s/spectra. In the auto-MS/MS acquisition mode, the instrument was set to acquire signals over an m/z range of 25–1,000 Da, and the accumulation time for the production scan was set to 0.05 s/spectra. The production scan was acquired using information-dependent acquisition in high-sensitivity mode. The collision energy was fixed at 35 ± 15 eV. The declustering potential was set at ±60 V. Raw MS data (Wiff. scan files) were converted to MzXML files using ProteoWizard MSConvert, and processed using XCMS for feature detection, retention time correction, and alignment. The metabolites were identified using accuracy mass spectrometry (<25 ppm) and MS/MS data, which were matched with the standard database. For the extracted ion features, only variables with >50% of the nonzero measurement values in at least one group were retained. The MetaboAnalyst web-based system was used for multivariate statistical analysis. After Pareto scaling, PCoA and partial least squares discriminant analysis (OPLS-DA) were performed. Leave-one-out cross-validation and response permutation testing were conducted to evaluate the robustness of the model. Metabolites showing significant differences between the LA and HA groups were identified based on the combination of a statistically significant threshold of variable influence on projection (VIP) values obtained from the OPLS-DA model and a two-tailed Student’s t-test (p-value) on the raw data. The metabolites were considered significant when they had VIP values >1.0, VIP values <0.05, and p-values less than 0.05. Differential metabolites were identified using three databases, including the Kyoto Encyclopedia of Genes and Genomes (KEGG) , the human metabolome database, and the bovine metabolome database. The KEGG database was used to evaluate the enrichment analysis of KEGG metabolic pathways according to the differential metabolites (Kanehisa et al., 2012). Fisher’s exact test was used to determine the significance of enriched pathways. Fecal fermentation parameters were analyzed using the t-test in the SPSS software (version 22.0, SPSS, Inc., Chicago, IL, United States). Alpha diversity indices, which reflect the significance between the LA and HA groups, were analyzed using the Wilcoxon rank test with the “dplyr” package (authors, H. Wickham, R. François, L. Henry, K. Müller; published date, 2018; version, 0.7.6) in R. PCoA was performed based on the Bray–Curtis dissimilarity matrices in R, and “ggplot2” package in R was used to visualize the results. The differences in the relative abundance of organisms at the phylum, family, and genus levels and microbiota function between the two groups were tested using the Wilcoxon method in R (version 4.0.5). Spearman’s rank correlation was used to identify the relationship between the relative abundance of the core OTUs, altitude, fecal fermentation parameters, and serum antioxidant indices using the “Psych” package (author, W. Revelle; published date, 2016; version, 1.6.9) and visualized using the “corrplot” package (author, Taiyun Wei; published date, 2017; version, 0.84) in R. All data were reported as the mean, and differences with p < 0.05 were considered as significant. As shown in Table 1, there was no significant difference (p > 0.05) in the concentrations of acetate, propionate, butyrate, and total VFAs between fecal samples of Sanhe cattle reared at different altitudes. Compared with the LA group, the acetate-to-propionate ratio (A/P) increased significantly (p < 0.05) in the HA group. A total of 868,445 raw sequences were generated with an average of 43,422 ± 4,392.71 (mean ± SD) per sample. An average of 2,054 ± 133.75 OTUs across all samples were identified at 3% sequence dissimilarity. Rarefaction curves showed that the number of new OTUs decreased as the number of sequences per sample increased (Additional file: Supplementary Figure S1), indicating an adequate sampling depth to cover the tested gut bacterial composition. Good’s coverage for the Sanhe heifer samples showed a mean value of 0.97 across all 20 samples, indicating sufficient sequence coverage for all samples. The mean Shannon’s diversity and Chao1’s richness for all Sanhe heifer samples were 8.42 ± 0.49 and 2,674.69 ± 157.41 (Additional file: Supplementary Table S2), respectively. The most highly abundant phyla in all Sanhe heifer samples were Firmicutes (64.06%), Bacteroidetes (32.33%), Tenericutes (0.93%; Figures 1A,B). Among these phyla, the most abundant families were Ruminococcaceae (36.37%), Rikenellaceae (15.43%), Peptostreptococcaceae (12.23%), and Christensenellaceae (5.51%; Figures 1A,B). At the genus level, 11 genera showed >2% relative abundance (Figures 1A,B). The intestinal microbiome of the Sanhe cattle varies widely. Therefore, we focused on the core OTUs found in all the Sanhe heifers. We sought to identify the core microbiota across all Sanhe heifers and found 393 shared OTUs among all samples from LA and HA Sanhe heifers, as shown in Figure 1C. These OTUs included the following bacterial families with >10% total relative abundance: Ruminococcaceae (26.10%), Rikenellaceae (11.37%, Figures 1A,B). The shared genera among all samples showing >5% of the total relative abundance were Ruminococcaceae_UCG-005 (13.71%), Rikenellaceae_RC9_gut_group (7.74%; Figures 1A,B). To detect differences in the gut microbiota of LA and HA Sanhe heifers, we performed Bray–Curtis dissimilarity analysis. The results were visualized using a principal coordinate analysis (PCoA) plot, as shown in Figure 1D. The gut microbiota that differed between groups were analyzed using analysis of similarities and confirmed that the two groups significantly differed (R2 = 0.58, p = 0.001). However, we found no significant difference (p < 0.05) in Chao 1 richness, Shannon diversity index, and Simpson’s diversity index between the groups (Additional file: Supplementary Table S2). At the phylum level, the relative abundances of the phyla Firmicutes, Bacteroidetes, and Verrucomicrobia did not differ significantly (p > 0.05) between the LA and HA groups. In contrast, compared with the LA group, the relative abundances of the phyla Proteobacteria and Actinobacteria were significantly (p < 0.05) lower (Table 2), whereas that of the phylum Spirochaetae was significantly (p < 0.05) higher in the HA group. At the family level (family of relative abundance >0.01%), lower relative abundances of Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, Family_XIII, Acidaminococcaceae, Peptococcaceae, Enterobacteriaceae, Spirochaetaceae and Coriobacteriaceae were observed in the HA group than in the LA group (Table 2), and the relative abundances of Lachnospiraceae, Clostridiales_vadinBB60_group, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, and Porphyromonadaceae were higher in the LA group than in the HA group (Table 2). At the genus level (genera with relative abundance >0.01%), compared with the LA group, the relative abundances of 43 genera were significantly (p < 0.05) higher, and those of 15 genera were significantly lower in the HA group (Table 3); of these, eight genera showed a relative abundance >1%. The relative abundances of some genera differed by more than 10-fold, including Butyrivibrio (decreasing 20.59-fold, p = 0.002), Eubacterium_xylanophilum_group (decreasing 13.25-fold, p < 0.001), Corynebacterium (increasing 16.51-fold, p = 0.011), Escherichia-Shigella (increasing 213.31-fold, p < 0.001), and Domibacillus (increasing from 0.00 to 0.027, p < 0.001; Table 3). To explore the role of gut bacteria in production and fermentation of VFAs, we analyzed the relationship between fecal VFA concentration (acetate, propionate, butyrate, and total VFAs) and the relative abundance of OTUs using Spearman’s rank correlations, as shown in Figure 2. All OTUs with relative abundances <0.01% in all fecal samples were removed from the analysis. The relationship between OTUs and production and fermentation traits was visualized using a heat map (Figure 2). Fifty-Eight OTUs were significantly (p < 0.05) correlated with altitude; of these, 20 OTUs were negatively correlated with altitude, eight of which were in the family Ruminococcaceae (p < 0.05), four in the family Rikenellaceae (p < 0.05), and two in the family Lachnospiraceae (p < 0.05). Additionally, OTUs within unidentified_o_Clostridiales, Clostridiales_vadinBB60_group, Clostridiaceae_1, Bacteroidales_BS11_gut_group, Bacteroidales_RF16_group, and Spirochaetaceae were significantly negatively (p < 0.05) correlated with altitude. Thirty-eight OTUs were positively correlated with altitude, among which 14 were in the family Ruminococcaceae (p < 0.05), 11 in the family Christensenellaceae (p < 0.05), three in the family Family_XIII (p < 0.05), three in the family Lachnospiraceae (p < 0.05), and three in the family Peptostreptococcaceae (p < 0.05). In addition, OTUs within the families Erysipelotrichaceae, Acidaminococcaceae, Bacteroidaceae, and unidentified_o_Gastranaerophilales were significantly and positively correlated with altitude (p < 0.05). Fourteen OTUs were negatively (p < 0.05) correlated with the acetate-to-propionate ratio (AP), among which six and three were in the families Ruminococcaceae and Rikenellaceae, respectively. In addition, 23 OTUs were positively correlated (p < 0.05) with AP, of which eight were in the family Ruminococcaceae, six in the family Christensenellaceae, three in the family Peptostreptococcaceae, and two in the family Lachnospiraceae. Furthermore, OTUs within the families Family_XIII, Erysipelotrichaceae, unidentified_o_Gastranaerophilales, and Acidaminococcaceae were significantly and positively correlated with AP (p < 0.05). Analysis of VFAs showed that acetate concentration was negatively correlated with the relative abundance of OTUs in the Eubacterium coprostanoligenes group. Sixteen OTUs were significantly (p < 0.05) correlated with propionate concentration, among which 10 OTUs were negatively correlated with propionate concentration, three OTUs were in the family Christensenellaceae, three OTUs were in the family Peptostreptococcaceae, two OTUs were in the family Lachnospiraceae, and one OTU was in the family Erysipelotrichaceae. Six OTUs were significantly and positively (p < 0.05) correlated with propionate concentration; of these, four OTUs belonged to the family Ruminococcaceae, one OTU belonged to the family Bacteroidales_RF16_group, and one OTU belonged to the family Lachnospiraceae. The total VFA concentration was negatively (p < 0.05) correlated with the relative abundance within the family Ruminococcaceae. A total of 1,727 differential metabolites were identified in the gut metabolome; of these, 1,101 and 626 metabolites were detected in positive and negative ion modes, respectively. To compare the metabolome compositions of the gut samples in the two groups, the datasets obtained from LC–MS in the positive and negative ion modes were evaluated using PCA (Figures 3A,B). The metabolites between the two groups were well-separated in the PCA score plots of the positive and negative ion mode results. Volcano plots of the positive and negative ion modes for the two groups are shown in Figures 3C,D. The OPLS-DA score plots are shown in Supplementary Figure S2. OPLS-DA revealed a clear distinction between the LA and HA groups in both the positive (R2X = 0.351, R2Ycum = 0.995, Q2cum = 0.954) and negative ion modes (R2X = 0.351, R2Ycum = 0.995, Q2cum = 0.954), which was validated by permutation analysis (positive: Q2 intercept = −0.2568; negative: Q2 intercept = −0.2413). Based on the cutoff (VIP >1 and p < 0.05) for differential metabolites, 368 metabolites differed significantly between the LA and HA groups, of which 231 and 137 were detected in the positive and negative ion modes, respectively. Metabolic pathway analysis based on the significantly different gut metabolites revealed the enrichment of 10 metabolic pathways (Figure 4A), with “nicotine addiction,” “central carbon metabolism in cancer,” “mineral absorption,” “protein digestion and absorption,” “ABC transporters,” “neuroactive ligan-receptor interaction,” “cAMP signaling pathway,” “aminoacyl-tRNA biosynthesis,” “pyrimidine metabolism,” and “purine metabolism,” which belong to “environmental information processing,” “organismal systems,” “metabolism,” “human diseases,” and “genetic information processing,.” The differential metabolites in the differentially enriched KEGG pathways determined by hydrophilic interaction LC–MS analysis are shown in Table 4. In addition, the relationships between metabolic pathways were significantly different for the gut metabolites (Figure 4B). Spearman’s correlation network between the core gut microbiota and gut metabolites was analyzed, that revealed 28 significant correlations (relative abundance >0.1%, r > |0.8|, p < 0.05; Figure 4C). OTUs belonging to the genus Romboutsia were significantly negatively and positively correlated with seven and two metabolites. Respectively. OTUs belonging to the genus Paeniclostridium were significantly negatively and positively correlated with 13 and five metabolites, respectively. OTUs belonging to the genus unclassified_f_Lachnospiraceae were significantly positively correlated with a single metabolite. By integrating gut 16S rRNA high-throughput sequencing and LC–MS-based untargeted metabolomic analyzes, we investigated the gut microbiome and host metabolome mechanisms involved in high-altitude adaptability. We estimated the gut microbial composition, metabolites, and variations as well as the interactions between microorganisms and metabolites in different groups. VFAs did not differ in ruminal samples from cattle reared in different regions, suggesting that altitude does not strongly affect the fecal fermentation parameters in Sanhe heifers. Generally, the intestinal microbiota is stable over time in adult animals (Caporaso et al., 2011; Faith et al., 2013). In this study, we investigated the differences in the gut microbiota of Sanhe heifers reared at different altitudes. In the two groups, Firmicutes and Bacteroidetes, known to play a key role in maintaining gut homeostasis, were the most abundant phyla in the gut of Sanhe heifers, which agrees with the findings observed in yaks (Liu et al., 2021) and rats. Members of Bacteroides participate in the degradation of biopolymers and main polysaccharides, whereas bacteria from Firmicutes regulate the digestion and absorption of proteins and carbohydrates. At the phylum level, the enrichment of Proteobacteria in the gut represents an imbalanced and unstable microbiota structure or disease state in the host (Shin et al., 2015). Actinobacteria are thought to be involved in modulating gut permeability, immune system, metabolism, and the gut-brain axis, and their abundance represents the health state of the animal. The relative abundance of Spirochaetae was lower in the gut of HA heifers than in that of LA heifers, as observed previously in sub-adult Tibetan sheep (Li et al., 2020), which are saccharolytic and can use carbohydrates as substrates. Families showing differential abundances, including Peptostreptococcaceae, Christensenellaceae (Waters and Ley, 2019), Erysipelotrichaceae (Wu et al., 2021), Family_XIII, and Lachnospiraceae, Domibacillus (Sharma et al., 2014), Bacteroidales_S24-7_group (Gao et al., 2020), Bacteroidales_RF16_group, and Porphyromonadaceae (Sakamoto, 2014), most of which belonged to the phyla Firmicutes, Bacteroidetes, Actinobacteria, and Spirochaetae, are associated with fiber degradation, feed digestion, and inflammation induction. Butyrivibrio (Kelly et al., 2010) and Eubacterium_xylanophilum_group (Mukherjee et al., 2020) are butyrate-forming bacteria that play key roles in polysaccharide degradation. The relative abundances of Eubacterium_xylanophilum_group (Mukherjee et al., 2020), Corynebacterium (Salem et al., 2015), Escherichia-Shigella (The et al., 2016), and Domibacillus vary widely, and most of these organisms are pathogens, suggesting that changes in altitude affect the structure of the intestinal microbiota and the health of Sanhe heifers. Moreover, we considered the impact of altitude on the gut bacterial core OTUs of Sanhe heifers. Therefore, these OTUs may form the key bacterial community responsible for high-altitude adaptibilty in Sanhe heifers. The enriched differential metabolic pathways belonged to nucleotide metabolism, including pyrimidine and purine metabolism pathways. Purine and pyrimidine nucleotides are major energy carriers, subunits of nucleic acids, and precursors for the synthesis of nucleotide cofactors (Moffatt and Ashihara, 2002). The enriched differential metabolic pathways belonged to the digestive system of organismal systems, including mineral and protein digestion and absorption, suggesting that different altitudes affect the digestive system of Sanhe heifers. The enriched differential metabolic pathways belonged to environmental information processing, including “ABC transporters,” “neuroactive ligan-receptor interaction,” and “cAMP signaling pathway.” The cAMP signaling pathway regulates critical physiological processes, including metabolism, secretion, calcium homeostasis, muscle contraction, cell fate, and gene transcription (Ould Amer and Hebert-Chatelain, 2018). The cyclic nucleotide-gated ion channel regulates downstream pathways by activating calmodulin and calcium/calmodulin-dependent protein kinase. In addition, the cAMP pathway, also known as the protein kinase A pathway, directly regulates the transmembrane transport of calcium, potassium, sodium, and chloride ions through phosphorylation of channel proteins, transporters, and receptors on the cell membrane. ABC transporters exert a variety of physiological functions, such as the removal of foreign substances, nutrient intake, resistance to foreign invasion, antigen transmission, and inhibition of transportation, and are closely related to the health of the body (Liu, 2019; Thomas and Tampé, 2020). All these pathways were upregulated in the HA group compared to those in the LA group. In addition, the KEGG pathway was enriched in human diseases, suggesting that high altitudes affect the health of Sanhe heifers. Overall, untargeted metabolomics showed that high-altitude regions could alter organismal systems, metabolism, environmental information processing, genetic information processing, and even induce disease. Altitude also affects environmental information processing, organismal systems, human diseases, and genetic information processing. We found that OTUs belonging to the genus Romboutsia were associated with nine metabolites (melatonin, uracil, hypoxanthine, xanthine, guanine, monensin, heliotrine N-oxide, d-lyxose, and L-gulono-1,4-lactone). A previous study showed that Romboutsia encodes a versatile array of metabolic capabilities involved in carbohydrate utilization, fermentation of single amino acids, anaerobic respiration, and metabolic end-products (Gerrritsen et al., 2019), which is consistent with our results. OTUs belonging to the genus Paeniclostridium were associated with 18 metabolites (L-gulono-1,4-lactone, uracil, d-lyxose, chicoric acid, guanine, 5-(2-hydroxyethyl)-4-methyl thiazole, oxeladin, hypoxanthine, 2-aminoadipic acid, melatonin, 1,2-dimyristoyl-sn-glycero-3-phosphate, N-omega-propyl-l-arginine, artemisinin, heliotrine N-oxide, ondansetron, Cer 20:1-d7 (d18:1-d7/20:1), deoxyinosine, and d-fructose). Paeniclostridium is an anaerobic pathogen in animals (Kim et al., 2017). The OTUs belonged to the genus g_unclassified_f_Lachnospiraceae which is a member of the family Lachnospiraceae that is positively correlated with 1-palmitoylglycerol. Previous studies have shown that insoluble fatty acid soap might reduce the growth benefits in the intestine (Yaron et al., 2013; Wang et al., 2020), suggesting that excess 1-palmitoylglycerol causes intestinal damage. Therefore, Sanhe heifers are more prone to diseases in high-altitude environments. Overall, our results showed that the gut microbiome and metabolome of Sanhe heifers differed between the LA and HA groups. We found that the gut microbiota associated with digestion absorption of proteins and carbohydrates, including Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, Family_XIII, Lachnospiraceae, Domibacillus, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, Porphyromonadaceae, and Spirochaetaceae, differed between HA heifers and LA heifers. These findings indicate that the ability of the gut microbiota to ferment dietary substrates differs between LA and HA Sanhe heifers. The core OTUs in the phyla Bacteroidetes, Firmicutes, Spirochaetes, and Cyanobacteria differed between the gut microbiota of the LA and HA groups. Therefore, these organisms may be critical bacterial communities involved in determining the high-altitude adaptabilty of Sanhe heifers. In addition, untargeted metabolomics has shown that high-altitude regions could alter organismal systems, metabolism, environmental information processing, genetic information processing, and even induce diseases. The genera Romboutsia, Paeniclostridium, and g_unclassified_f_Lachnospiraceae were strongly associated with the 28 differential metabolites. In summary, when Sanhe heifers encounter the stress of high-altitude environments, they respond by regulating their gut microbiome and metabolome; however, changes in altitude negatively affect the digestive ability and health of Sanhe heifers. This study contributes to the understanding of the ability of dairy cows to adapt to high-altitude regions and provides insights into strategies for altering the gut microbiota for high-altitude adaptation through feeding management. We investigated the gut microbiome and metabolome mechanisms involved in the adaptation to high-altitude environments. Variations in the gut microbiome and metabolome, as well as the interaction of microorganisms and metabolites, were studied in the LA and HA groups by integrating gut 16S rRNA high-throughput sequencing and LC–MS-based untargeted metabolomic analyzes. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material. The sequence data supporting the results of this study are available in the NCBI Sequence Read Archive (SRA) under the accession number PRJNA821486. The animal study was reviewed and approved by the study protocol was approved by the Ethical Committee of the College of Animal Science and Technology of China Agricultural University (project number AW22121202-1-2). Written informed consent was obtained from the owners for the participation of their animals in this study. XZ performed experiments and wrote the manuscript. WW, ZC, HY, YW, and SL reviewed and provided guidance for the manuscript and experiment. All authors contributed to the article and approved the submitted version. The services used in this study were purchased by the Ministry of Agriculture and Rural Affairs of China: Experiment and Demonstration of Adaptive Production Technology for Dairy Cows in High Altitude Regions (no.16190319) and China Agriculture Research System of MOF and MARA (CARS36). The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

PMC10002980

Alexander A. Mironov,Maksim A. Savin,Galina V. Beznoussenko

COVID-19 Biogenesis and Intracellular Transport

24-02-2023

COVID-19,SARS-CoV-2,Golgi complex,virion budding,endocytosis,viral replication,intracellular transport,viral replication organelle

SARS-CoV-2 is responsible for the COVID-19 pandemic. The structure of SARS-CoV-2 and most of its proteins of have been deciphered. SARS-CoV-2 enters cells through the endocytic pathway and perforates the endosomes’ membranes, and its (+) RNA appears in the cytosol. Then, SARS-CoV-2 starts to use the protein machines of host cells and their membranes for its biogenesis. SARS-CoV-2 generates a replication organelle in the reticulo-vesicular network of the zippered endoplasmic reticulum and double membrane vesicles. Then, viral proteins start to oligomerize and are subjected to budding within the ER exit sites, and its virions are passed through the Golgi complex, where the proteins are subjected to glycosylation and appear in post-Golgi carriers. After their fusion with the plasma membrane, glycosylated virions are secreted into the lumen of airways or (seemingly rarely) into the space between epithelial cells. This review focuses on the biology of SARS-CoV-2’s interactions with cells and its transport within cells. Our analysis revealed a significant number of unclear points related to intracellular transport in SARS-CoV-2-infected cells.

COVID-19 Biogenesis and Intracellular Transport SARS-CoV-2 is responsible for the COVID-19 pandemic. The structure of SARS-CoV-2 and most of its proteins of have been deciphered. SARS-CoV-2 enters cells through the endocytic pathway and perforates the endosomes’ membranes, and its (+) RNA appears in the cytosol. Then, SARS-CoV-2 starts to use the protein machines of host cells and their membranes for its biogenesis. SARS-CoV-2 generates a replication organelle in the reticulo-vesicular network of the zippered endoplasmic reticulum and double membrane vesicles. Then, viral proteins start to oligomerize and are subjected to budding within the ER exit sites, and its virions are passed through the Golgi complex, where the proteins are subjected to glycosylation and appear in post-Golgi carriers. After their fusion with the plasma membrane, glycosylated virions are secreted into the lumen of airways or (seemingly rarely) into the space between epithelial cells. This review focuses on the biology of SARS-CoV-2’s interactions with cells and its transport within cells. Our analysis revealed a significant number of unclear points related to intracellular transport in SARS-CoV-2-infected cells. The first coronavirus was discovered in 1965 [1]. Now, there are seven members of the coronavirus category, which induce dangerous diseases in human beings [2]. Virions of SARS-CoV-2 are spherical. Their diameter is equal to 90–100 nm. On the surface of this virus there are 48 spikes or peplomers, with their length being equal to 23 nm. However, the spike number on each SARS-CoV-2 viral particle varies according to different sources in the literature. So, it should be considered as a range of about 25–50 [3,4,5,6,7,8,9,10,11,12]. The ultrastructures of SARS-CoV-2 and SARS-CoV are similar [3,4,5,6,7,8,9,10,11,12,13,14]. However, the number of peplomers is lower in SARS-CoV-2 [9]. The S-protein of SARS-CoV-2 differs by the presence of the unusual furin cleavage site situated between subunits of the S-protein. SARS-CoV-2 contains only one positive-sense RNA, and only its single chain. Its 5′ end exhibits a methylated cap, whereas its 3′ end contains several adenines. [15,16,17,18,19,20]. Also, there is a difference of one amino acid between the C-tails of spikes from SARS-CoV-2 and SARS-CoV: Cys1247 vs. Ala1229, respectively [21]. The RNA and nucleoproteins are surrounded with a lipid bilayer composed of phospholipids. Its thickness is lower (3.6 ± 0.5 nm) than that of the membranes of the host cell (3.9 ± 0.5 nm) because this bilayer is the derived from the ER membrane (see below). Among proteins synthesized on the basis of the RNA of SARS-CoV-2, there is a papain-like protease. The RNA is associated with the viral matrix proteins. Host ribosomes translate a large polypeptide using two-thirds of the RNA [4,5,22,23,24]. Being experts in intracellular transport [25,26,27,28], we tried to examine the problem of SARS-CoV-2 biogenesis from the point of view of intracellular transport. We used the available information on intracellular transport and in particular transport through the GC, with that describing virus trafficking, and tried to predict several important aspects of the interactions between cells and SARS-CoV-2 virions. The genome of SARS-CoV-2 (30 kb) is one of the largest among RNA viruses. The SARS-CoV-2 genome is composed of a single-stranded RNA of ~29,900 base pairs with a methylated cap at the 5′ end and a polyadenylated (poly-A) tail at the 3′ end [10]. It encodes 29 proteins (Table 1), including 4 structural proteins (Spike (S), Envelope (E), Membrane (M), and Nucleocapsid (N)), 16 non-structural proteins (NSP1–NSP16), and 9 accessory factors (ORF3a, ORF3b, ORF6, ORF7a, ORF7b, ORF8, ORF9b, ORF9c, and ORF10) [29,30,31]. The structural proteins are encoded by the one-third of the genome near the 3′-terminus [5,12,22]. The S, E, and M proteins are membrane-associated proteins, localized to the ER and GC. They interact with N proteins and drive the assembly of new virus particles, ensuring vRNP incorporation into the nascent virion [29,30,31,32]. The single-chain positive sense RNA of SARS-CoV-2 is used directly as mRNA [18]. Using this mRNA, ribosomes of the host cells synthesize two large polypeptides, rep1a and rep1a/1b. Then, rep1a and rep1b are proteolytically cleaved into 16 virally-encoded nonstructural proteins (NSPs) [33,34,35,36,37,38]. The spike S-protein is a 600 kDa trimeric transmembrane type I membrane glycoprotein that is composed of two subunits, S1 and S2 [31]. It forms peplomers [17,39,40,41]. The S-proteins of SARS-CoV and SARS-CoV-2 share 75% identity in amino acid sequences [18,19,20]. In the S-protein of SARS-CoV-2 there is a distinct four-amino-acid insert located at the interface between the S1 receptor-binding subunit and the S2 fusion subunit. These structural features of SARS-CoV-2 RBD increase its ACE2 binding affinity [42]. The high degree of glycosylation of the S-protein indicates that viruses pass through the GC. The S-protein binds to ACE2 through the receptor-binding domain [43,44,45,46]. Its 66 N-linked glycans are formed in the GC and contain a sialic acid-binding pocket that can mediate viral attachment by interactions with various sialoproteins, glycoproteins, and gangliosides on the cell membrane [47,48,49,50,51]. The S1 subunit is responsible for host cell receptor binding, while the S2 subunit participates in membrane fusion. The modified glycans shield about 40% of the protein surface of the S trimer. Most of glycans on the surface of the S-protein have sialic acid on their termini [31]. SARS-CoV-2 is decorated by a large number of highly glycosylated proteins, and its glycosylation (both N-linked and O-linked) extensively affects host recognition, penetration, binding, recycling, and pathogenesis. The extensive N-glycosylation of the SARS-CoV-2 spike protein could cause the negative effects of the virus interacting with the host cell ACE2 receptor [31]. Each subunit contains a single transmembrane domain, an N-terminal domain, and a C-terminal domain [17,18,19,20,21,41,44,45,46,51]. The fusogenic S2 subunit consists of the upstream helix region, the fusion peptide, the heptad repeat 1, the central domain, the heptad repeat 2, the transmembrane domain, and the cytoplasmic tail [51]. The cytoplasmic tail of the S-protein contains a di-lysine ER-retrieval signal, which interacts with COPI [41,52,53,54]. This ER retrieval motif is present in both SARS-CoV and SARS-CoV-2 [7,8,9,10]. It interacts with the whole COPI coatomer complex [21]. The S-protein interacts with the host Rab7A, Rab7B, and Rab7L1, as well as with VPS11 and VPS33A [55,56]. After binding of the S-protein subunits, the S1/S2 complex is subjected to cleavage by the human type II transmembrane serine protease 2 (TMPRSS2), dipeptidylpeptidase 4 (DPP4), and furin. This facilitates viral entry into the cytosol [23,44,53,54,55,56,57,58]. The SARS-CoV-2 S-protein may be more readily primed for membrane fusion than that of SARS-CoV because the latter requires two proteolytic events after receptor binding. [51]. The S-protein is cleaved at the multi-basic site into S1 and S2 subunits by either furin at the trans-Golgi network (TGN) or by another proprotein convertase [21]. During initial processing, after S1–S2 cleavage, the spike then either recycles back to the ER–Golgi intermediate compartment (ERGIC) for assembly into SARS-CoV-2 virions or traffics to the plasma membrane [21]. After its cleavage, the S-protein pierces the double paired membrane composed of the PM and viral membrane, and the nucleocapsid penetrates into the cytosol. On the other hand, binding of the S1 subunit to the ACE2 receptor triggers the cleavage of ACE2 by ADAM17/tumor necrosis factor-converting enzyme at the ectodomain sites. A soluble form of ACE2 is produced. It retains its catalytic activity [57]. A polybasic residue motif at the boundary between the S1 and S2 subunits is cleaved by furin and furin-like proteases during biogenesis and cell entry [16,43,51]. The 25 kDa type III transmembrane glycoprotein M binds to the nucleocapsid and favors the curvature of the host cell membrane. This triple-spanning membrane (M) protein is the most abundant membrane protein component of the viral envelope. The M protein exists as monomers in the ER, but it oligomerizes to form variously sized complexes during transport through the GC and trans-Golgi network (TGN). The cytoplasmic domains of M proteins homo-oligomerize. This contributes to its retention. The M protein and E protein do not increase the thickness of the viral membrane envelope [58,59,60]. The E-protein encoded in the genome of an RNA virus is crucial for the replication, budding, and pathophysiology of the virus. During virus budding, the E-protein is not specifically targeted at the membranes of ER exit sites but displays a broader distribution in the Golgi region. The N-protein forms biomolecular condensates with RNA. The SARS-CoV-2 envelope protein forms clustered pentamers in lipid bilayers. The M–E complex ensures the uniform size of viral particles for viral maturation and mediates virion release. It is not clear if polysaccharide chains on the M- and E-proteins exist. If they exist, it is not clear how glycosylation of these proteins and their transport through the GC occurs: in the form of a dietary supplement or separately [58,59,60]. The N-protein and the majority of the NSP proteins have not been studied intensively (Table 1). The fine structures of the most of SARS-CoV-2 NSP proteins have been deciphered [17,18,33,46,61,62]. For practical purposes, it is especially important to examine the infection of epithelial cells of the airways. It is important to understand how the SARS-CoV-2 penetrates not only into cells in culture, but also into polarized cells lining the respiratory tract. Therefore, we would like to mention that most cases of SARS-CoV-2 infection begin in the upper respiratory tract. The epithelium of the respiratory tract consists of ciliated cells, goblet cells, club cells, and underlying basal cells. The ciliated cells contain not only cilia, but also a significant number of short microvilli. The apical surface of the club cells is covered with microvilli. The fact that ciliated cells also contain cilia and microvilli can be observed in the following figure (http://histologyguide.com/EM-view/EM-077-respiratory-epithelium/17-photo-1.html, http://histologyguide.com/EM-view/EM-076-respiratory-epithelium/17-photo-1.html, http://histologyguide.com/EM-view/EM-070-respiratory-epithelium/17-photo-1.html (accessed on 2 February 2023). Ciliated cells, together with goblet-shaped and club cells, participate in catching inhaled particles in the secreted mucus. Then, the beating cilia transport it up into the mouth, where it is then swallowed or expectorated. Basal cells are able to differentiate into the other cell types mentioned above. Under normal conditions, mucus and cilia prevent the access of any possible irritants or large pathogens to epithelial cells [91,92,93,94]. Rare lymphoid follicles and single plasma cells producing IgA and are observed in the lamina propria of bronchi. After its secretion from plasma cells localized within the lamina propria, IgA should be delivered into the lumen of the airways. The most plausible candidate for this role are goblet cells, where after basolateral endocytosis IgA is transported towards the GC and then secreted together with mucus. Goblet cells are the main producer of mucus, and it is important to understand their role. The mucus produced by these cells could be protective and prevent much of the virus from accessing the goblet cell surface [35]. Heparan sulfate promotes SARS-CoV-2 infection in various target cells [51,92]. In lungs, DCs were not identified at the EM level [93,94]. Although human airways are not available for experimentation, airway cell-derived organoids that resemble the lungs’ structure and function ex vivo could be used now. The entry of SARS-CoV-2 into cells is based on its immobilization on the cell surface after its interaction with ACE2. Attachment of SARS-CoV-2 to the PM of cells is mediated with ACE2. Without ACE2 SUMOylation, SARS-CoV-2 infection could be blocked [95,96]. A549 cells exhibiting a low level of ACE2 expression are less sensitive to infection with SARS-CoV-2. Their transfection with ACE2 makes them sensitive to SARS-CoV-2 [43,97]. Also, the S-protein binds to Toll-like receptors of pneumocytes [98]. SARS-CoV-2 infection leads to increased activation of MT1-MMP that is colocalized with ACE2 and stimulates cell entry of SARS-CoV-2. Inhibition of MT1-MMP suppresses entry of SARS-CoV-2 into cells [99]. In epithelial cells, being localized on the APM of epithelial cells of airways. ACE2 serves not only as an enzyme but also as a chaperone controlling intestinal amino acid uptake, regulating gut amino acid transport into cells [100]. The SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2) or ACE homolog (ACEH), is a membrane protein of the first type consisting of 805 amino acids. The full-length metallocarboxyl peptidase angiotensin receptor (mACE2) is located on cell membranes and consists of a transmembrane anchor and an extracellular domain. Its gene is located within the X chromosome. ACE2 has 40% identity and 61% similarity to ACE metalloprotease [101]. It has a signal peptide, an extracellular N-terminal domain containing a conserved catalytically active HEXXH zinc-binding domain, a transmembrane domain (amino acids 740 to 763), and a C-terminal cytosolic tail (mostly in humans) close to the C-terminus (type I membrane protein) [102,103]. Its extracellular domain exhibits monocarboxypeptidase activity (it is a zinc metalloprotease) and binds to the S1 domain of the S-protein [14,15,17,61]. ACE2 converts Ang (angiotensin) I and Ang II into Ang 1–9 and Ang 1–7, respectively, and several other peptides. ACE2 can also act on [des-Arg 937]-bradykinin of the kinin–kallikrein system, regulating coagulation and inflammation [101]. Different proteases can cleave ACE2. The second form of ACE2 is a soluble form detectable in the blood, although rarely [57]. This form of ACE lacks membrane anchors and circulates in low concentrations. The analysis of ACE2 expression in experimental models and in the human transcriptome by using different databases revealed that its level is very low in the lung, being mainly limited to a small fraction of type II alveolar epithelial cells. ACE2 is normally localized on the plasma membrane (mACE2) with the N-terminal containing the catalytic site protruding into the extracellular space, using as substrates different active peptides present in the interstitial space. ACE2 is found on microvilli but not on the cilia of the APM of epithelial ciliary and club cells of the airways. No specific sorting signals and domains responsible for the apical sorting of ACE2 were found within the S-protein. It is possible that the transfer of ACE2 to APM is associated with an ultra-high level of glycosylation of the extracellular domain of ACE2 of these cells. The presence of a large number of sialic acids on polysaccharides synthesized on ACE2 is associated with its apical sorting. The hydrogen bonds formed at the acid ends polymerize the ACE2 molecules and make rafts out of them, which are then delivered to the APM. In the culture of unpolarized cells, ACE2 is located on BLPM due to the fact that there are domains on this PM that came from endosomes, as derivatives of the APM with a thick membrane [57]. SARS-CoV-2 is delivered to ACE2 localized on microvilli of ciliated or club cells due to the intensive movement of cilia. Motile cilia ensure SARS-CoV-2 delivery to the cell body through mucus layer entry. Depleting cilia inhibits COVID-19 [104]. The cystic fibrosis transmembrane conductance regulator (CFTR) channel regulates the expression and localization of ACE2. Due to impairment of the function of mucus, patients with cystic fibrosis are less sensitive to COVID-19. There is upregulation of ACE2 and TMPRSS2 expression in the airways of patients suffering from cystic fibrosis [105]. How ACE2 is transported and whether the COPII coat and COPII vesicles are involved in this process are not clear. ACE2 is widely expressed in various tissues and organs [78,106,107]. High levels of ACE2 expression are observed in the lungs, brain, kidneys [103,108], small intestine, testis, heart muscle, colon, and thyroid gland. However, no ACE2 is detected in blood cells [57,101]. SARS-CoV-2 was not detected on ciliary membranes but observed on the microvilli of ciliated cells. SARS-CoV-2 is associated with microvilli and the apical plasma membrane. ACE2 is not detected on the APM of goblet epithelial cells. Also, the apical plasma membrane of goblet cells does not contain endocytosis machinery suitable for the viral entry [35]. Labeling for ACE2 is visible in the brush border (microvilli) of differentiated enterocytes in the ileum, duodenum, jejunum, caecum and colon [109,110]. ACE2 is expressed in organoids composed of enterocytes. ACE2 was also present in endothelial cells from small and large arteries and veins in all the tissues studied. SARS-CoV-2 infects endothelial cells because they contain ACE2 [18,35,110,111,112,113,114]. It is unclear why labeling for ACE2 is present only in some cells, whereas in situ labeling for APM, i.e., in enterocytes, is extremely uniform [114,115,116,117,118,119]. In the olfactory mucosa, ACE2 is highly expressed on microvilli of the sustentacular cells, which form an epithelial monolayer around the olfactory neuronal outgrowths (bulbs) penetrating through this monolayer of cells and ending in olfactory pins. ACE2 is not detected on the olfactory sensory neurons themselves (olfactory neuronal bulbs) [111,120]. Thus, it seems that SARS-CoV-2 is not a neurotropic virus [110,120,121]. The problems with taste and smell in COVID-19 patients are not related to SARS-CoV-2 entry into neurons [111,122]. On the other hand, it is proposed that SARS-CoV-2 enters the central nervous system using different pathways [14]. Indeed, 7 days after cell entry, SARS-CoV-2 was observed in the olfactory cortex in the brains of rhesus monkeys [123]. Also, in patients who died with COVID-19, SARS-CoV-2 is demonstrated in several respiratory and non-respiratory tissues, including the brain [124,125]. ACE2 expression exhibits a gradient from upper to lower airways [109,110,111,113,114,126]. ACE2 is not present within goblet cells (secretory goblet cells make up ~20% of the epithelial cells) of the upper and lower respiratory tract [127]. MUC5B+ “club” and MUC5AC+ goblet cells were not infected in vivo [18]. The mucus produced protects goblet cells [35]. ACE2 is observed in the duct-lining epithelial cells and acinar cells of major salivary glands [109,114]. There is no evidence of virus entry into alveolar macrophages, whereas salivary glands are a target for SARS-CoV-2 [109]. Type II pneumocytes taken from dyed healthy lungs of non-human primates contain ACE2 (see Figure 1B of [15]). Expression of ACE2 and the above-mentioned accessory proteases is higher in males and increases with age [128,129,130,131]. SARS-CoV-2 infection depends also on cellular heparan sulfate, which changes the spike structure to an open conformation to facilitate ACE2 binding [132]. Children express less ACE2. As a result, they are more resistant to SARS-CoV-2 [128]. An increased level of soluble ACE2 correlates with disease severity. ACE2 expression is stimulated by a type I interferon gene in human airway epithelial cells [36,57]. IFN stimulation upon viral treatment induces the expression of a truncated ACE2 isoform, which lacks 356 N-terminal amino acids, is not able to bind SARS-CoV-2, and, therefore, does not contribute to the potentiation of the infection [57]. TMPRSS2 is the human type II transmembrane serine protease able to promote ACE2 proteolytic cleavage using different targets in the protein sequence. It cleaves ACE2 at the intracellular C-terminal domain and, differently from ADAM17 does not produce a soluble form that retains the catalytic function [57]. The host TMPRSS2 cleaves the S2 protein at the S1/S2 interface (the S2′ site) [43,51,133]. In addition to furin/furin-like proteases and TMPRSS2, other proteases may also be involved in the SARS-CoV-2 entry process, such as serine endoprotease proprotein convertase 1 (PC1), trypsin, matriptase (trypsin-like integral membrane serine peptidase), and cathepsins [51,100,128,129,130,134,135,136]. Proteases facilitate the infectivity of SARS-CoV-2 [51,137]. Labeling for TMPRSS2 is visible in the brush border (microvilli) of differentiated enterocytes in ileum, duodenum, jejunum, caecum, and colon [109,110]. TMPRSS2 is expressed in organoids composed of enterocytes, and ACE2 and TMPRSS2 are minimally expressed in blood cells [104]. TMPRSS2 is also observed within the respiratory epithelium [43]. TMPRSS2 is highly expressed on microvilli of the sustentacular cells, localized around the olfactory bulbs [111,120]. TMPRSS2 expression exhibits a gradient from upper to lower airways. TMPRSS2 is observed not only over microvilli membranes but also within the thin layer of the apical cytoplasm in ciliated cells and in only microvilli-containing cell [18,35,110,111,112,113,114]. However, it is not clear how TMDRSS2 is transported. Most likely, TMDRSS2 is localized in apical vacuoles and moves there with the help of actin comets. SARS-CoV-2 uses both clathrin-dependent and clathrin-independent endocytosis for cell entry [9,33]. The first step directed towards the entry of SARS-CoV-2 into cells lining human airways is its attachment to the plasma membrane (PM) with the help of ACE2. Cilia are an important mechanism promoting SARS-CoV-2 delivery to the cell bodies [34,35]. It was shown in a humanized in vitro model that the SARS-CoV-2 virus preferentially enters the tissues via ciliated cell precursors [36]. The binding of ACE2 to the S-protein induces endocytosis of the virion, after which the viral envelope fuses with the endosomal membrane to enable the release of the viral genome into the cytoplasm. However, direct fusion between membrane of the virion and the PM of the host cell cannot be excluded [51,95,101,138,139,140,141,142]. Alternatively, membrane fusion can also occur at the plasma membrane after receptor engagement, but only in cell cultures [51]. In vitro, viral particles are often observed along the filopodial membranes [10]. The necessity of an acidic environment for the processing of the S-protein also suggests the importance of endocytosis for SARS-CoV-2 entry into cells. Inhibition of TMPRSS2 activity blocks SARS-CoV-2 entry [15,17,18,43,143,144]. Rab5 is important for the delivery of SARS-CoV-2 to the early endosomes [145]. In pancreatic cells, ACE2, but not NRP1 and TMPRSS2, mediates SARS-CoV-2 entry [146]. Also, the endocytic cysteine proteases cathepsins B and L can cleave the subunits of the S-protein [130]. After cleavage of these subunits with proteases (including furin), the S-protein becomes more capable of “piercing” biological membranes [147,148]. Similarly, inhibitors of furin block entry of this virus into cells [32]. This suggests an endocytosis-dependent mechanism of SARS-CoV-2 entry. In furin-over-expressing cells, the expression of icSARS-CoV-2-GFP is higher than in wild-type cells. Labeling for TNPPSS2 was not observed on microvilli of the apical PM of sustentacular cells. This labeling was in dots below the APM (see Figure 3C presented in the paper by Khan et al. [120]). Enhanced expression of TMPRSS2 stimulates SARS-CoV-2 infection [120]. Of interest, the 611LY612 mutation impairs the glycosylation pattern of the S-protein and reduces its density on the surface of SARS-CoV-2. Mutations of cysteine-rich clusters I and II, the main palmitoylation sites, disrupt ER-to-Golgi transport of S-protein and reduce spike-mediated membrane fusion activity [47,149,150]. SARS-CoV-2-positive patients have higher expressions of ACE2, although the numerical density of TMPRSS2, BSG/CD147, and CTSB is lower than in patients with negative test for SARS-CoV-2 [34,48,97,126,138]. There are rare data suggesting that a low-pH environment is not a crucial determinant for the entry of SARS-CoV-2, similar to the previous observations on SARS-CoV, MERS-CoV and mouse hepatitis virus (MHV) [51,151]. Also, it was proposed that SARS-CoV-2 could enter cells directly without the participation of endocytosis [35]. According to this hypothesis, SARS-CoV-2 attaches to the cell surface in an ACE2-dependent manner and then, after cleavage of the S-protein, the membrane of the virus fuses with the APM, and the nucleocapsid enters the cytosol. From Figure 6C, presented by Pinto et al. [35], the authors conclude that the SARS-CoV-2 virion fuses to the plasma membrane. However, the so-called “fused virion” presented in this figure does not have enough peplomers (spikes) to prove that this protrusion is not a microvillus of the PM, but the real virion after its fusion with the PM. Even if the virus fused with the APM of the microvillus, there would be no space for the nucleocapsid to exit, and there are no mechanisms that would deliver the nucleocapsid components first to the apical part of the cell and after passing through the network composed of actin (and this is quite difficult if there are no special mechanisms) to the main body of the cell. On the contrary, if the virus is loaded via clathrin-dependent endocytosis into the apical endosome, then it has an actin comet that helps it pass through actin networks using actin and myosin located there or in the comet itself. After cutting off a part of S-protein, it becomes able to pierce the double membrane composed of the viral membrane and the part of the endosomal membrane to which the virus attaches. Calcium inhibits pore formation. It is present in the lumen of the endosome, but it is not present in the lumen of the airways. The membranes merge during bilayer dehydration with the help of polyethylene glycol. In order for the protein to be processed with TMPRSS2, it is necessary that the protein itself find it on the PM, which can be a very rare and random phenomenon. Also, it is important to understand that if SARS-CoV-2 fused with the APM of microvilli, there is no space for the nucleocapsid or machine for the delivery of the nucleocapsid into the cell body. The basal part of the APM contains clathrin-coated buds, and immediately after the binding of the S-protein to ACE2, this complex would be captured into already existing clathrin-coated buds. Thus, the second pathways could be important only for nonpolarized cells in culture. Therefore, according to the current consensus, the endosomal pathway has a preference. Buds coated with clathrin are on the basis of the APM, from which the microvilli extend. These buds are located between the microvilli. However, it is not established whether clathrin-dependent vesicles formed from clathrin-coated bud fuse with early endosomes or not [51,140]. SARS-CoV-2 induces fragmentation of the Golgi complex (GC), down-regulates GRASP55, and up-regulates TGN46 expression, while the expression of GRASP55 or the knockdown of TGN46 reduces the infection rate. Lipid metabolism is altered [1,2,3,4,5,6,7,8,9]. The number of mitochondria accumulated at the periphery of the replication organelle decreases. The cortical actin is accumulated near the plasma membrane of the infected cells [13,152]. The SARS-CoV-2-dependent ER stress induces mitochondria fusion. The microtubules are not necessary for the biogenesis of SARS-CoV-2 or other coronaviruses [14]. SARS-CoV-2 triggers Golgi fragmentation via the down-regulation of GRASP55 [153]. SARS-CoV-2 induces overexpression of several genes controlling the ER stress, i.e., glucose-regulated protein 78 (GRP78 or BiP) and glucose-regulated protein 94 (GRP94) [14]. More than 300 host proteins binding to the SARS-CoV-2 RNA during active infection were identified [153,154]. Inhibition of fatty-acid metabolism or VPS34 blocks SARS-CoV-2 replication [154,155]. SARS-2 inhibits methylation machinery from host RNAs [156,157], SNAREs, and autophagy, preventing the capture of the double membrane vacuoles (DMVs) formed by the virus into autophagosomes. [158]. Although the mechanisms of intracellular transport are under revision [159,160,161], the role of intracellular transport in SARS-CoV-2 infection is important. In the infected cells, the expression of ERGIC53 was slightly reduced. The GC appeared as small fragments dispersed in the cytoplasm. The spike was highly enriched in the Golgi fragments. These fragments did not contain stacks of cisterna but appeared as aggregates of convoluted tubules filled with virions (Figure 3P presented by Zhang et al. [153]). Thapsigargin (a SERCA calcium pump inhibitor), tunicamycin (a protein glycosylation inhibitor), and dithiothreitol (a reducing agent); brefeldin A (an inhibitor of ArfGEF) and monensin (an inhibitor of trans-Golgi transport); bafilomycin A1 (an inhibitor of vacuolar-type H+-ATPase), chloroquine (which increases the pH in endosomes), vacuolin-1 (an inducer of large and swollen lysosomes), E64d, leupeptin, and pepstatin (inhibitors of lysosomal hydrolases); or a cocktail of protease inhibitors can significantly reduce SARS-CoV-2 infection. Both autophagy inducers (torin-1) and autophagy inhibitors (3-methyladenine), as well as CID 1067700, displayed similar inhibitory effects [153]. Treatment of cells with latrunculin A, which blocks actin polymerization, or with nocodazole, which induces depolymerization of microtubules, did not affect SARS-CoV-2 replication, whereas vinblastine inhibiting the assembly of microtubules had a strong effect on the production of infectious extracellular virions [13]. Thus, the inhibition of intracellular transport and endocytosis blocks SARS-CoV-2 infection. This suggests that without these protein machines, SARS-CoV-2 infection would be stopped. SARS-CoV-2 induces acute respiratory distress syndrome, which is characterized by alveolar epithelial necrosis at an early disease stage. Epithelial necrosis markers and in particular high-mobility group box-1 (HMGB-1) are released into the blood. Serum level of HMGB-1 is one of the damage-associated molecular markers released from necrotic cells. Alveolar epithelial cell necrosis involves two types of programmed necrosis, namely, necroptosis and pyroptosis [162,163]. COVID-19 infection leads to the disassembly of the Golgi ribbon and the mobilization of host cell compartments and protein machineries that are known to promote Golgi-independent trafficking to the cell surface [153,164]. Mutation of the C488 residue of the S-protein impairs its delivery at the GC and PM [165]. Brefeldin A blocks the processing of the S-protein [165]. In SARS-CoV-infected cells, mitochondria are larger and appeared as being fused (see Figures 4B and 5B presented by Snijde et al. [166]). In SARS-CoV-2-infected cells, there is a significant induction of monocyte-associated chemokines such as CCL2 and CCL8 [101,167,168,169]. IL13, a cytokine associated with Th2-high asthma, inhibits ACE2 expression [18]. Growth factor receptor signaling inhibition prevents SARS-CoV-2 replication [170,171]. SARS-CoV-2 activates mostly type I interferon responses [67]. Additionally, cells use the complex consisting of Drosha, Dicer, and RISC to degrade newly formed viral dsRNA. Drosha, Dicer, and RISC family proteins are conserved core components of the RNAi (RNA interference) machinery and are involved in post-transcriptional as well as transcriptional gene silencing in many eukaryotes. These machineries are saturable, and therefore, if the production of dsRNA were high, the cells would have problems due to accumulation of dsRNA in the cytosol and nucleus [172]. In order to protect dsRNA from degradation by RISC, SARS-CoV-2 uses DMVc with pores which prevent the movement of cytosolic proteins inside the lumen of DMVs. The viral dsRNA is accumulated in the DMV lumen [93,173]. SARS-CoV-2 disrupts splicing, translation, and protein trafficking to suppress host defenses. The papain-like protease of SARS-CoV-2 destroys p53 and inhibits interferon production [67,174,175,176,177,178,179]. Also, SARS-CoV-2 inhibits autophagy and prevents glycolysis, which is important for autophagy [14,180,181,182]. In any case, transfection of cells with LC3 protects the cells from SARS-CoV-2 infection [175,176,177,178,179,180,181,182,183]. However, SARS-CoV-2 can infect cells lacking LC3, ATG5, and ATG7. SARS-CoV-2 replicates its genome in the cytoplasm using host ribosomes for the synthesis of its own proteins. The positive-sense genomic RNA is considered by host ribosomes as mRNA. A mega-polypeptide is synthesized at the ER on the basis of the SARS-CoV-2 genome [33,158]. Then, SARS-CoV-2 forms viral replication organelle (VRO). It is composed of the paired convoluted reticular network of the ER membranes or the zippered ER (ZER). Also, numerous DMVs are formed. They are interconnected or connected with the ER. The ZER is found also in cells infected with Alpha-, Beta-, Delta-, and Gamma-coronaviruses [14,32,156,158]. The viral replication organelle is necessary for the initiation of viral protein synthesis. The negative-strand RNA functions as a template for multiple rounds of positive-strand RNA synthesis. The ZER exhibits uniform invaginations known as spherules. Spherules are comprised of a double membrane. The ZER has no luminal space, and it is connected with the rough ER membranes. Ribosomes are not associated with the ZER [13,14,24,166,184]. Another characteristic organelle which is formed by SARS-CoV-2 and by other coronaviruses is the DMV. DMVs are composed of double-paired membranes without space between single membranes. This is especially evident when quick freezing is used for analysis. Isolated DMVs can fuse with late endosomes/lysosomes. This indicates that DMVs contain SNAREs, at least STX17 and SNAP29. DMVs are situated near the ZER. In infected cells, DMVs appear rather quickly (within 2 h) after infection, and no indication that the amount of SER is responsible for the synthesis of FFAs is presented. The diameter of DMVs ranges from 160 to 400 nm. Ribosomes were occasionally detected on the cytosolic side of DMVs. In cells infected with SARS-CoV-2, abundant perinuclear DMVs are present, with an average diameter of 257 ± 63 nm [8]. Coronavirus replicase proteins are mostly detected in the ZER but not in DMVs. Aggregates of small-sized DMVs (diameter 185 nm ± 28 nm) are observed already at 6 h after infection. Then, their number and diameter (298 nm ± 42 nm) increase. Thin tubules connect outer membranes of some (not all) large DMVs with the ER. Small DMVs (19%) are mostly isolated [113]. The space between membranes of a DMV is empty and narrow. After quick freezing this space is ZER is surrounded with DMVs (Figure 1A of [185]). Replication takes place in connection with the replication organelle consisting of DMVs and the ZER. In SARS-CoV-infected cells, DMVs are sites of vRNA synthesis [166]. The lumen of DMVs does not contain cytosolic proteins but instead is filled with molecules of double-stranded form RNA (dsRNA). Single-stranded RNAs are not observed [7]. The length of individual dsRNA filaments in DMVs varies from 4–263 nm, with an average length of 52 nm [23]. In other coronaviruses, dsRNA inside DMVs was detected with antibodies against dsRNA and electron cryomicroscopy [13,66,166,185]. The presence of helicases in the viral genome suggests an important role of dsRNAs for the biogenesis of SARS-CoV-2. Helicases are required for the unwinding or despiralization of the dsRNA helix and thus for the efficient replication of +RNA viral genomes. The three-dimensional structure of the helicase–polymerase coupling in the SARS-CoV-2 replication–transcription complex is resolved [186]. We hypothesized that dsRNA serves as a matrix for the synthesis of new viral RNA genomes, whereas pores in the DMV walls formed by coronaviruses are necessary for protection of viral dsRNA [187] because in the cytosol, there are many RNases that can easily destroy single-strand RNAs. When (+) RNA enters the cytosol of a cell, it, being composed of a single RNA chain, it is immediately attacked by cytoplasmic RNases. There should be mechanisms to protect it. One of these mechanisms is the synthesis of RNAs consisting of two chains that are packaged in DMVs. In order to have enough membranes for the treatment of DMVs within 4 h after the start of infection, a very rapid synthesis of fatty acids is necessary. However, it is very slow. Proteins that accelerate or stimulate the synthesis of additional lipids by the cell itself have not yet been found in the viral genome. Also, the molecular machines responsible for the synthesis of lipids are not found within viral proteins. Mitochondria-derived multilamellar organelles (MDMLOs) formed during mitochondrial fusion are better suited to explain such a rapid formation of DMVs. There is very little cholesterol in the OMM membrane and a lot of unsaturated LC; therefore, NSP6 with its 6 functioning TMDs, after being cut off from a giant polypeptide, can quickly penetrate into the lipid bilayer of the ER membrane [7]. DMVs are important for virion maturation and the protection of dsRNA from cytosolic RNases. If one assumes that DMVs are formed directly from the ER, several unknown mechanisms should be explained, namely, a mechanism for elimination of the ER matrix and mechanisms for the membrane attachment because NSP6 does not form dimers (see below). Until now, nobody has explained how the ER forms paired membranes, how NSP proteins and other viral proteins lacking signal peptides are inserted into the lipid bilayer, how the ER matrix is eliminated from the paired membrane domain, and how dsRNA is accumulated inside the DMV lumen (intermembrane space remains completely closed) using special pores similar to nuclear pores that apparently regulate the influx of proteins into the vacuole space [38,77,156]. As we indicated above, being transfected alone with NSP6 induces closure of the ER lumen with the formation of double paired membranes (DPMs) not containing lumen between two very tightly attached membranes [14,188]. This phenomenon cannot be explained by known mechanisms. Known mechanisms proposed for DMV biogenesis (see Figure 5 presented by van der Hoeven et al. [183]) cannot explain these problems [14]. Indeed, no evidence that paired ER domains formed by arteriviruses wrap around to form DMVs has been found [163]. Membranes of DMVs contain low levels of cholesterol [189]. Ribosomes were occasionally detected on the cytosolic side of DMVs formed by other coronaviruses [190]. Another possibility is to assume that two sheets of paired membranes attach to each other, as we found, and that their edges gradually would be transformed into a pore where proteins of nuclear pores would be accumulated; then, two sheets of paired ER would start to detach from each other, and the cavity filling would be regulated by the function of this pore, which would allow the passage of only dsRNA, as it was described for DMVs. Indeed, in SARS-CoV-2-infected cells, double paired membranes are observed when two DMVs make contact [7,14,138,156,163,183,188,189]. Of interest, after HPF and after a combination of chemical and cryo-fixation, quick-freezing demonstrated that DMVs of the hepatitis C virus also have almost completely closed space between membranes [190,191,192]. Very thin tubular junctions observed between the ER and the DMV induced the conclusion that DMV is formed from the ER [183,192]. During SARS-CoV-2 biogenesis, dsRNAs are formed. Viral dsRNA has been detected inside DMVs. DMVs prevent the Dicer-dependent degradation of dsRNA [8,15,112]. DMVs are identified as the main compartment where vRNA synthesis occurs for coronaviruses. In DMVs, there is no protein matrix in the intermembrane space, and the membranes are tightly glued to each other [6,138,166]. The excess of OMM formed after the fusion of mitochondria could be used for the formation of DMVs [193,194]. The synthesis (if lipids of DMVs are synthesized) and transformation of the ER cisternae (if membranes of DMVs are formed from the ER) should be very fast, otherwise RNA would be cleaved by cell RNases. However, cells cannot synthesize lipids with such high speed, and the molecular mechanisms responsible for the possible “cleaning” of the ER membranes are unknown. Transfection of NSP6 induces closure of the ER lumen [77,188]. Transfection of cells induces the formation of paired (without any space between membranes) membranes connected to the ER [77]. The protein transfection technique used by Ricciardi et al. [77] itself raises a number of questions. Ricciardi et al. [77] indirectly demonstrate that NSP6-containing ZER has a low concentration of cholesterol. NSP6 from several coronaviruses localizes to mitochondria [195,196,197]. The reason for this, apparently, is that the OMM originated from the outer membrane of the Gram-negative archaea. Indeed, it is not clear how the NSP6 protein with six functional TMDs and having no signal peptide is included in the lipid bilayer of the ER membrane; how the membranes draw closer and stabilize in this position (NSP6 proteins have no property of sticking to each other [77]); or how the protein matrix is removed from the ER lumen to allow the membranes to converge to the point where they are closer together than in gap junctions. Such a feature is found only in initial autophagic vacuoles [198]. In infected cells, NSP6 is formed directly from the mega-polypeptide. Therefore, it has no signal peptide-dependent mechanism. The insertion of such a protein directly from the cytosol into the cholesterol-containing ER bilayers is extremely difficult. The only membranes glued together in the cell are early autophagosomes [198]. It was demonstrated that more than 30% of eukaryotic genes encode for signal polypeptides, which ensure their targeting to the ER membrane. Signal polypeptides are necessary for the insertion of such proteins into membranes, especially those containing cholesterol. Signal polypeptides represent specialized and indispensable targeting mechanisms that lead them to the ER membrane. For instance, mitochondrial porin is a major integral membrane protein of OMM. After its synthesis, an authentic yeast porin molecule is integrated into OMM. This porin does not interact with the ER membrane [199]. However, NSP6 has no signal peptide, which helps to introduce proteins with several TMDs into the bilayer. It is important to stress that in really infected cells, NSP6 is formed from a long peptide by cutting off a part of this peptide. In experiments in vitro, such a situation is rarely used. In the majority of experimental studies, NSP6 is transfected. In conditions of viral infection, the NSP6 protein is formed from a giant polypeptide by cutting it out of the chain using the NSP5 peptidase. After excision, the polypeptide chain of the NSP turns out to have no signal peptide, and it is very difficult for it to be inserted into the lipid bilayer of the ER membranes, as suggested in the hypothesis published at the end of this work. One of the possibilities suitable for the insertion of just-cleaved NSP6 into the lipid bilayer could be an excess of OMM formed after the fusion of mitochondria which then detaches, generating mitochondria-derived multilamellar vesicles (MDMLO). Then, MDMLOs fuse with the ER and are used for the formation of DMVs [194]. This hypothesis deserves additional analysis. Coronaviruses (including SARS-CoV-2) use the host-cell proteins [200,201,202]. Intracellular transport of SARS-CoV-2 per se and its components could be used for the verification of the models describing this process. SARS-CoV-2 uses the ER for synthesis and processing of viral proteins, whereas membranes of ER exit sites (ERES) are used for the formation of viral lipid envelopes. The assembly of virions occurs on the cytoplasmic side of the ERES elements. A certain temperature range is necessary for SARS-CoV-2 assembly [203,204,205]. Upon co-expression of the E- or M-proteins, the S-protein is re-localized at ERES. The C-terminal retrieval motif within the cytoplasmic tail of the S-protein is necessary for its M-mediated retention in ERGIC. The E-protein is also involved in the retention of the S-protein [150]. S-protein is accumulated at the luminal side of the ERGIC membrane and forms a separate cylindrical complex [7]. A KxHxx motif in the cytosolic tail of the spike weakly binds the COPß’ subunit of the COPI coatomer, which facilitates some recycling of the spike within the Golgi, while releasing the remainder to the cell surface [21]. Protein/RNA complexes with reduced disorder are formed [14,206]. These complexes are composed of N-proteins and RNA, allowing efficient packing of the unusually large viral RNA genome into the small virus particles. Expression of S-, M-, E-, or NSP3 viral proteins triggers Golgi alterations [153]. Membrane proteins of SARS-CoV-2 are heavily glycosylated, suggesting their exit out of the ER and delivery at the GC [14,33,138,207]. Glycosylation of viral proteins occurs within 4 h after synthesis. This indicates that formation of DMVs, which need a huge amount of lipids, occurred during this time. The GC is required for glycosylation of viral proteins [14,129]. The numeric density of other coronaviruses is higher at the trans-pole of the GC [208]. The capsids could be formed during budding or assembled somewhere in the cytosol and then delivered to the site of virus budding. The size of SARS-CoV-2 virion suggests against the vesicular and the diffusion models of intra-Golgi transport. On the other hand, higher numerical densities of virions in cisternal distension at the trans-side of the GC suggests against the cisterna maturation–progression model of intra-Golgi transport [25]. There are images suggesting that SARS-CoV-2 particles budded in the post-Golgi vacuoles. In the vacuoles of infected cells, SARS-CoV-2 viruses are identical to particles found outside the cell membrane, suggesting that mature and infectious SARS-CoV-2 particles were already produced in the vacuoles [209]. The budding is observed only in the vacuoles, but not on the PM [210]. It is stated that coronaviruses use lysosomes for their secretion [209,211]. However, most of cargoes pass through endosomes, which are often LAMP1-positive [28,212,213,214,215]. Finally, the post-Golgi carrier (vacuole) filled with viruses fuses with the PM, and the viruses are secreted. It is not clear whether secretion occurs directly through APM, which is covered with mucus, or whether initially viruses are delivered at the BLPM and then into the lumen of airways. It is not clear whether the post-Golgi vacuoles could fuse with the BLPM. Analysis of the SNARE distribution is necessary to answer this question. After the luminal secretion, SARS-CoV-2 binds to the microvilli of the respiratory tract and induces the formation of apically elongated and highly branched microvilli that help SARS-CoV-2 pass through mucus [104]. These long microvilli explain why people who have recovered from COVID-19 suffer from coughing with much excreted mucus for a long time. We proposed the following scheme for SARS-CoV-2 biogenesis (Figure 1). This scheme is based on nondynamic observations and cannot explain many simple questions. Although significant progress was made in the study of SARS-CoV-2, mechanisms of interactions of the SARS-CoV-2 virus with cells and especially its transport mode contain many unclear issues. Moreover, there is an enormous number of details at the molecular level of the SARS-CoV-2 general plan, but there is no understanding of the pathogenesis of SARS-CoV-2. Why ACE2 is transported towards the APM, whereas no apical sorting signals for it are found, is unknown. If ACE2 is the apically directed protein, why in cell cultures can non-polarized cells be infected? What are the mechanisms involved in SARS-CoV-2 budding? How are immature virions transported at the GC? What is the mechanism of intra-Golgi transport of immature and mature virions? Secretory vacuoles filled with matured virions are secreted through the apical plasma membrane (APM) or baso-lateral PM (BLPM) in epithelial cells of airways. How do viral particles move towards the blood, passing the BM? How are RNAs protected against cytosolic RNases? Why it is important for SARS-CoV-2 to form dsRNA? Does dsRNA form the +RNA of the virion, and if so, how? What is the mechanism preventing movement of cytosolic protein inside DNVs, and how do pores in the double membrane of DMVs function? What is the mechanism involved in the insertion of NSP6 into the ER membrane, if the ER is the source for the formation of DMVs? What are the mechanisms responsible for the clearance of the lumen of the ER from its matrix proteins? Without knowledge on the structure and molecular biology of all abovementioned proteins and mechanisms of intra-Golgi transport, it is rather difficult to solve the problems of COVID-19. It is still not clear how viruses penetrate into the blood. In bronchioles, dendritic cells were not identified at the EM level. The resolution of immunofluorescence microscopy is not high, and cryo-sections have not yet been used. Importantly, dendritic cells are not found in alveoli. Molecular mapping, immunofluorescence, and immune-electron microscopy are necessary for the specification of the above issues related to the interaction between SARS-CoV-2 and cells. Thus, in spite of a huge number of publications on SARS-CoV-2, there remain many unclear questions within this field. They should be additionally examined from the point of view of intracellular transport.

PMC10002984

Kira V. Derkach,Maxim A. Gureev,Anastasia A. Babushkina,Vladimir N. Mikhaylov,Irina O. Zakharova,Andrey A. Bakhtyukov,Viktor N. Sorokoumov,Alexander S. Novikov,Mikhail Krasavin,Alexander O. Shpakov,Irina A. Balova

Dual PTP1B/TC-PTP Inhibitors: Biological Evaluation of 3-(Hydroxymethyl)cinnoline-4(1H)-Ones

24-02-2023

cinnolines,phosphatase inhibitors,obesity,T-cell tyrosine phosphatase,tyrosine phosphatase 1B,insulin,leptin

Dual inhibitors of protein phosphotyrosine phosphatase 1B (PTP1B)/T-cell protein phosphotyrosine phosphatase (TC-PTP) based on the 3-(hydroxymethyl)-4-oxo-1,4-dihydrocinnoline scaffold have been identified. Their dual affinity to both enzymes has been thoroughly corroborated by in silico modeling experiments. The compounds have been profiled in vivo for their effects on body weight and food intake in obese rats. Likewise, the effects of the compounds on glucose tolerance, insulin resistance, as well as insulin and leptin levels, have been evaluated. In addition, the effects on PTP1B, TC-PTP, and Src homology region 2 domain-containing phosphatase-1 (SHP1), as well as the insulin and leptin receptors gene expressions, have been assessed. In obese male Wistar rats, a five-day administration of all studied compounds led to a decrease in body weight and food intake, improved glucose tolerance, attenuated hyperinsulinemia, hyperleptinemia and insulin resistance, and also compensatory increased expression of the PTP1B and TC-PTP genes in the liver. The highest activity was demonstrated by 6-Chloro-3-(hydroxymethyl)cinnolin-4(1H)-one (compound 3) and 6-Bromo-3-(hydroxymethyl)cinnolin-4(1H)-one (compound 4) with mixed PTP1B/TC-PTP inhibitory activity. Taken together, these data shed light on the pharmacological implications of PTP1B/TC-PTP dual inhibition, and on the promise of using mixed PTP1B/TC-PTP inhibitors to correct metabolic disorders.

Dual PTP1B/TC-PTP Inhibitors: Biological Evaluation of 3-(Hydroxymethyl)cinnoline-4(1H)-Ones Dual inhibitors of protein phosphotyrosine phosphatase 1B (PTP1B)/T-cell protein phosphotyrosine phosphatase (TC-PTP) based on the 3-(hydroxymethyl)-4-oxo-1,4-dihydrocinnoline scaffold have been identified. Their dual affinity to both enzymes has been thoroughly corroborated by in silico modeling experiments. The compounds have been profiled in vivo for their effects on body weight and food intake in obese rats. Likewise, the effects of the compounds on glucose tolerance, insulin resistance, as well as insulin and leptin levels, have been evaluated. In addition, the effects on PTP1B, TC-PTP, and Src homology region 2 domain-containing phosphatase-1 (SHP1), as well as the insulin and leptin receptors gene expressions, have been assessed. In obese male Wistar rats, a five-day administration of all studied compounds led to a decrease in body weight and food intake, improved glucose tolerance, attenuated hyperinsulinemia, hyperleptinemia and insulin resistance, and also compensatory increased expression of the PTP1B and TC-PTP genes in the liver. The highest activity was demonstrated by 6-Chloro-3-(hydroxymethyl)cinnolin-4(1H)-one (compound 3) and 6-Bromo-3-(hydroxymethyl)cinnolin-4(1H)-one (compound 4) with mixed PTP1B/TC-PTP inhibitory activity. Taken together, these data shed light on the pharmacological implications of PTP1B/TC-PTP dual inhibition, and on the promise of using mixed PTP1B/TC-PTP inhibitors to correct metabolic disorders. Protein phosphotyrosine phosphatase 1B (PTP1B) is a negative regulator of metabolic pathways activated by insulin (which is produced by pancreatic beta cells) and by adipokine leptin (which is produced by adipose tissue) [1,2]. In response to insulin stimulation, PTP1B dephosphorylates the active phosphorylated forms of the insulin receptor and insulin receptor substrate proteins-1 and -2 (IRS-1, IRS-2) [3,4]. Under leptin stimulation, the enzyme dephosphorylates the leptin-activated non-receptor Janus kinase 2 (JAK2) and IRS1/2-proteins, the key components of leptin signaling [2,5]. Suppression of PTP1B phosphatase activity abolishes its inhibitory effect on insulin and leptin signaling. In obesity, type 2 diabetes mellitus (T2DM), and metabolic syndrome, the insulin and leptin signaling pathways are attenuated as a result of long-term exposure to hyperinsulinemia and hyperleptinemia; thus, the use of PTP1B inhibitors may become one of the approaches to restore them and increase tissue sensitivity to insulin and leptin [1,6]. PTP1B can be inhibited by small molecules targeting either the catalytic or the allosteric site of the enzyme. However, inhibitors aimed at the allosteric site are expected to exert more specific inhibition because the allosteric site of PTP1B, unlike its catalytic site, is more distinct from the allosteric sites of other PTP1B-related phosphatases, such as the T-cell protein phosphotyrosine phosphatase (TC-PTP) and endothelial Src homology region 2 domain-containing phosphatase-1 (SHP1) [1,6,7]. TC-PTP is also capable of attenuating the insulin and leptin signaling pathways by dephosphorylating their receptor and post-receptor components [8,9]. TC-PTP inhibitors, similarly to PTP1B inhibitors, can also improve glucose homeostasis and prevent obesity in metabolic syndrome and T2DM [10]. Previously, selective PTP1B phosphatase inhibitors have been developed [11,12,13,14], which had little effect on TC-PTP activity. The therapeutic potential of such inhibitors may not be fully justified. Inhibition of PTP1B alone can lead to undesirable toxic effects, which have been observed in previous in vivo experiments [15] and, similarly, can cause a compensatory increase in the activity of other phosphatases, primarily TC-PTP, which can functionally replace PTP1B [16,17,18,19]. Consequently, currently, there are no approved PTP1B inhibitors [20], despite the high demand for the effective treatment of the diseases associated with insulin and leptin resistance (T2DM, metabolic syndrome, and obesity). Accordingly, a paradigm shift might be needed to create such inhibitors, which would act on both PTP1B and TC-PTP, though not necessarily with high potency. The aim of the present work is to identify small molecule inhibitors that would potentially be able to suppress the functional activity of both tyrosine phosphatases, PTP1B and TC-PTP, and thereby affect the metabolic and hormonal parameters in rats with diet-induced obesity. As a lead structure in our quest for dual PTP1B/TC-PTP inhibitors, we relied on the earlier reported compound PI4 (ethyl 3-(hydroxymethyl)-4-oxo-1,4-dihydrocinnoline-6-carboxylate), a 4-oxo-1,4-dihydrocinnoline derivative, that demonstrated an inhibitory activity towards PTP1B, and exerted a stimulating effect on components of the insulin and leptin signaling pathways in rat hypothalamic neurons, including the serine/threonine protein kinase Akt and transcription factor STAT3 (signal transducer and activator of transcription 3) [21]. In addition, PI4 reduced the body and fat weights in diet-induced obese rats, suppressed their food intake, improved metabolic parameters, and increased their sensitivity to insulin and leptin [22]. In this study, we hypothesized that by exploring an expanded set of 3-(hydroxymethyl)-4-oxo-1,4-dihydrocinnoline analogs 1–4 (Figure 1), we might not only obtain yet another set of PTP1B inhibitors but could potentially identify dual inhibitors of PTP1B/TC-PTP, which are sought after in the context of metabolic disease treatments (vide supra). Compounds 1–4 were obtained, as described previously [23]. Compounds 1–4 displayed dose-dependent inhibition of both phosphatases, PTP1B and TC-PTP, as expressed in the IC50 values (Table 1) calculated from the respective dose-response curves (Figure 2). In each case, the range from 0.1 to 80 μM of the tested compound was studied. As can be seen from Table 1, compounds 1 and 2 showed a ~5–7-fold higher selectivity for PTP1B compared to that for TC-PTP, and in the case of compound 2, the differences were significant (p = 0.001). In the case of compounds 3 and 4, the IC50 values for PTP1B and TC-PTP were comparable, indicating their close selectivity for both enzymes. In the case of compound 3, the IC50 value for TC-PTP was significantly lower than the IC50 values for TC-PTP inhibition by compounds 1 and 2 (p = 0.01 and p < 0.0001, respectively), although they did not differ significantly from that of compound 4 (p = 0.12), which indicates a more pronounced TC-PTP inhibitory effect of compound 3 as compared to compounds 1 and 2. In the case of PTP1B, no significant differences in the IC50 values were found between all the studied compounds. The obtained IC50 values for compounds 1–4 were close to the IC50 values for a number of natural tyrosine phosphatase inhibitors and their semisynthetic derivatives [24,25,26,27], which may indicate a similar dose dependence to their inhibitory effect on the activity of PTP1B and TC-PTP. At the same time, compounds 1–4 had higher IC50 values in comparison with those for some recently developed synthetic phosphatase inhibitors, yet they were inferior to them in their binding affinity to the allosteric sites of these enzymes [18,19]. Based on the results of the in vitro experiments and our earlier data on the pharmacodynamics of compound PI4 [21,22], we studied the anorexigenic effect of compounds 1–4 and their influence on glucose homeostasis, as well as insulin and leptin resistance, in rats with diet-induced obesity. The five-day treatment of obese male rats with all the studied compounds (1 and 2 at a dose of 7 mg/kg/day, and 3 and 4 at doses of 8 and 10 mg/kg/day, respectively) led to a decrease in the body weight and food consumption. This indicates a pronounced anorexigenic effect of compounds 1–4. The highest effect was demonstrated by compounds 3 and 4, which reduced the body weight in obese rats by 22.2 ± 4.5 and 22.6 ± 4.0 g, respectively, (p < 0.05 as compared to untreated obese animals) and reduced the consumption of dry standard food by 46% and 39%, respectively (Figure 3). Compounds 1–4 had no significant effect on glucose levels, although, of the most active compounds (3 and 4), compound 4 improved the glucose sensitivity, previously reduced in obesity, as shown by the glucose tolerance test. This was indicated by the values of the glucose levels 120 min after glucose load, which were reduced by 20% and 17% in the groups treated with compounds 3 and 4, respectively, in comparison with the untreated obese animals, as well as the values of AUC0-120 for the curves “glucose concentration (mM)”—time (minutes)”. The AUC0-120 values in the groups treated with compounds 3 and 4 were reduced by 24% and 20%, respectively, as compared with the untreated animals (p < 0.05 as compared to the Ob group) (Figure 4). The levels of Insulin and leptin were elevated in obese rats, indicating the development of insulin and leptin resistance. Measurement of the levels of insulin and leptin in the blood of animals, before and after the treatments with compounds 1–4, showed that the compounds caused a decrease in the levels of these hormones (except for the insulin level in the Ob + 2 group), which indicates an increase in the sensitivity to insulin and leptin. The inhibiting effect on insulin and leptin levels exerted by compounds 3 and 4 was more pronounced compared to compounds 1 and 2. For the purpose of normalization, insulin sensitivity was indicated by the index of insulin resistance (IR), calculated as the product of the blood concentrations of glucose and insulin. In the group treated with compound 3, the insulin resistance index was significantly reduced compared to the Ob group, yet did not differ from that in the control animals (Table 2). Based on the in vitro IC50 values for PTP1B and TC-PTP inhibition by compounds 1–4, and on their ability to increase insulin sensitivity and reduce hyperleptinemia, established in the in vivo experiments, we studied the effect of these compounds on the expression of the genes encoding PTP1B and TC-PTP, as well as for insulin and leptin receptors, in the livers of obese rats. Along with this, we studied the expression of cytoplasmic tyrosine phosphatase SHP1, the catalytic site of which differs from those of PTP1B and TC-PTP [28]. The treatments with all the studied compounds led to an overall increase in the expression of the PTP1B and TCPTP genes in the liver. However, a significant difference to the Ob group was shown only for the groups treated with compounds 3 and 4, and, in the case of the TCPTP gene, for the group treated with compound 1. Compounds 3 and 4 did not affect the expression of the Shp1 gene, which encodes the protein tyrosine phosphatase SHP1, while compounds 1 and 2 increased the expression of the Shp1 gene, and the differences from the control were significant. These data suggest that the unsubstituted and fluoro-substituted analogs, 1 and 2, are likely to also inhibit phosphatase SHP1. Compounds 3 and 4 caused a slight decrease in the expression of the genes encoding the insulin and leptin receptors, but the difference with the Ob group was not significant. This tendency, albeit rather weak, could be due to an increase in the sensitivity of hepatocytes to insulin and leptin (Figure 5). The evaluation of the specific biological activity of compounds 1–4 showed their capability to interact with PTP1B and TC-PTP. Based on the gene expression data of phosphatases in the liver, there are reasons to believe that compounds 1 and 2 are also potentially able to interact with the SHP1 phosphatase, which has a catalytic site different from that of other closely related phosphatases, PTP1B and TC-PTP. It is necessary to establish the causes of this phenomenon to reduce the spectrum of side interactions. As a first step, we studied the active sites of the phosphatases PTP1B, TC-PTP, and SHP1. The amino acids that form the catalytic sites of the enzymes are shown in Figure 6 and are highlighted in blue. As can be seen from Figure 6, some identical amino acid residues are not included in the catalytic site formation. The main reason is the difference in the protein loop conformations and the presence of secondary structure elements. The TC-PTP enzyme is less structured in the domain between Arg114 and Cys123 (unstructured loop). This domain in PTP1B (Arg114–Cys123) and SHP-1 (Arg352–Cys361) is more rigid due to the β-sheet secondary structure element presence (Figure 7A). An unstructured loop in the case of TC-PTP can be useful for studies into ligand-induced conformational changes. The second domain, very different in the studied phosphatases, is located between the following residues: Thr180–Pro187 (PTP1b), Thr179–Pro186 (TC-PTP), and Ser416–Pro423 (SHP-1) (Figure 7B). Primarily, in the PTP1b and TC-PTP structures, this domain is identical by sequence (TWPDFGVP), but in the SHP-1 phosphatase, it is different (SWPDHGVP). The main ligand-interacting sequences «WPD» and «GVP» are conserved, although the phenylalanine residue is changed to histidine and the threonine residue is replaced by serine. The substitution of phenylalanine for histidine provides a decrease in the efficiency of the hydrophobic interactions and an increase in the efficiency of polar interactions (also pH-dependent), in this part of the active site of the enzymes. If we compare the geometry of the TC-PTP and PTP1B loops, we will identify significant differences in their positions. However, their sequences remain the same. The key differences, here, are hidden in the different rotamer states of the Phe–Asp pair. Another difference lies in the amino acid properties forming the active site cavity. Here, we can observe the difference in the interacting amino acids profile: SHP1 is less hydrophobic and more polar with the addition of a histidine residue. The homology degree in these segments of PTP1B and TC-PTP is also much higher (Figure 8). Molecular docking results and the binding free energies of compounds 1–4 are shown in Table 3. Studied compounds bind stably within the active site of all the observed phosphatases. With regard to PTP1B, compounds 1–4 can be considered site-specific ligands, because the ligand efficiency (LE) value (Table 3) is superior to that of the structure of the reference compound. In contrast to the used reference compound, the active inhibitor co-crystallized with PTP1B (pdb model 1Q1M, ligand structure, Figure 9). At the same time, a binding mode for the studied structures 1–4 also reproduces interactions specific to the reference compound (see Figure 9, PTP1B inhibitor showed in PDB model 1Q1M). When switching to the alternative targets of TC-PTP and SHP1, we observe a decrease in the active site specificity. At the same time, in the case of SHP1, the compounds also change the binding area (which remains within the active site). Compounds 1 and 2 retain high levels of site-specificity towards SHP1 (Table 3—highlighted by orange). Conversely, compounds 3 and 4 show a potential capability to selectively interact with PTP1B and TC-PTP (Table 3—highlighted by green). More clearly, the specificity of the observed targets is corroborated by the free energy value (ΔG). Such significant differences in comparison to the docking results, in theory, may indicate a significant solvent role in the binding process (the MM-GBSA method considers this, implicitly). The binding selectivity to PTP1B and TC-PTP for compounds 3 and 4 agrees with our experimental data. Ligand interaction diagrams analysis, presented in Figure 9, shows that compounds 1–4 interact mainly within the amino acids: Asp181, Arg221, Phe182, Cys215, and Ala217, in the same manner as the reference compound. Thus, compounds 1–4 mimic the key lipophilic and polar contacts, from which PTP1B site-specificity is achieved. The diagrams of the ligand–protein (enzyme) interactions with TC-PTP were similarly analyzed. Studying the protein–ligand interactions of compounds 1–4 with TC-PTP showed that the interaction profile for these compounds is almost identical. A distinctive feature is the weakening of the network of lipophilic ligand–enzyme contacts in the cavity of the active site. Moreover, unlike PTP1B, a pi–cation interaction with Arg222 is realized (Figure 10). In the TC-PTP structure, it is more accessible for any subsequent interaction. Ligand interaction diagrams of compounds 1–4 with SHP1 (Figure 11) showed that these compounds are more than capable of interacting with the enzyme, to form a stable protein–ligand complex. However, the binding region is strongly shifted towards Tyr276, relative to the binding site. Both PTP1B and TC-PTP contain the residues Tyr46 and Tyr48, which have a similar arrangement in each phosphatase molecule. In regard to the reference structure of the PTP1B ligand (Figure 9), then, Tyr46 interacts with the lipophilic fluorophenyl part of the molecule, sometimes forming a pi–stacking interaction. Compounds 3 and 4 are distinguished by a lower intensity of lipophilic contacts with SHP1 and by the absence of the pi–stacking interaction with Tyr276 (Figure 11). Our in vitro data indicate that all 4-oxo-1,4-dihydrocinnoline derivatives 1–4, which are structural analogs of the previously studied compound PI4 [21,22], are inhibitors of the PTP1B and TC-PTP tyrosine phosphatases. At the same time, they differ in selectivity for these tyrosine phosphatases since compounds 1 and 2 were found to be more selective towards PTP1B, while compounds 3 and 4 had no significant differences in selectivity for either phosphatase. In addition, compound 3 was far more effective as an inhibitor of TC-PTP than compounds 1 and 2 (Table 1). These observations are supported by the molecular docking results. As noted above, unlike compounds 1 and 2, compounds 3 and 4, according to the results of the in vitro experiments, are similar in their ability to inhibit the PTP1B and TC-PTP phosphatases. Notably, the inhibitory effect for PTP1B, as judged by the IC50 values, did not fully correlate with the performance of the compounds in the in vivo experiments. Thus, the IC50 value for compound 1 was the lowest among all the derivatives studied and was 2.5 times inferior to that for compound 4. At the same time, the anorexigenic effect of compound 1 was less pronounced compared to compounds 3 and 4. Importantly, the effects of compounds 3 and 4 on the food intake and metabolic parameters in obese rats are similar, while, according to the in vitro experiments, the effectiveness of compound 3 as an inhibitor of TC-PTP is more pronounced. It can be assumed that the similar affinity of compounds 3 and 4, with respect to both phosphatases PTP1B and TC-PTP, is important for the metabolic effects of these inhibitors. This distinguishes compounds 3 and 4 from compounds 1 and 2, which are more selective for PTP1B. The PTP1B and TC-PTP phosphatases, being negative regulators of insulin and leptin signaling, are involved in the development of insulin and leptin resistance and mediate an increase in appetite, and the accumulation of excess adipose tissue in metabolic disorders [1,6,8,9,10]. At the same time, there are a number of common downstream targets for PTP1B and TCPTP, which makes them at least partly interchangeable. For instance, both phosphatases dephosphorylate the hormone-activated phosphorylated forms of the leptin and insulin receptors, as well as the non-receptor-associated JAK2-tyrosine kinase associated with the leptin receptor [6,10]. However, there are also significant differences in the intracellular targets of the PTP1B and TCPTP phosphatases. The PTP1B dephosphorylates the IRS1/2 proteins that couple the insulin receptor to downstream SH2 domain-containing proteins [3,6], while the TCPTP dephosphorylates the STAT3 transcription factor, which is activated via the leptin receptor and controls the expression of STAT3-dependent genes [10]. The fact that compound 3, which is the most active with respect to TC-PTP, significantly reduces leptin levels is likely due to the fact that phosphatase TC-PTP is even more involved in the regulation of leptin signaling than in the regulation of insulin signaling [10]. Our results on the high efficiency of the dual inhibitors of the PTP1B and TCPTP phosphatases are supported by numerous studies, whereby a pronounced anorexigenic effect of low-selective inhibitors of PTP1B and TC-PTP was identified, although this phenomenon remains poorly understood. Celastrol, a naturally occurring pentacyclic triterpene, when administered to mice, reduced the activity of both phosphatases in the hypothalamic arcuate nucleus, through an allosteric mechanism, significantly reducing their food intake and body weights. The anorexigenic effects of Celastrol are mainly due to the activation of leptin signaling in hypothalamic neurons [29]. Simultaneous knockout of the PTP1B and TC-PTP genes in the hypothalamus of obese mice, as well as the combined administration of the PTP1B inhibitor and the glucocorticoid hormone antagonist RU486, which attenuates TC-PTP expression, suppressed food intake, normalized body weight and adipose tissue, improved glucose tolerance, alongside insulin and leptin sensitivity [9]. At the same time, inhibiting the two phosphatases separately was significantly less effective. Thus, simultaneous, and similarly effective inhibition of both PTP1B and TC-PTP, which we have shown for 4-oxo-1,4-dihydrocinnolines 1–4, primarily for compounds 3 and 4, does not allow for the compensatory switching of the mechanisms, from one phosphatase to another, in the inhibition of leptin and insulin signaling. However, one cannot exclude the involvement in these compensatory mechanisms of additional phosphatases, which are less specific in their targeting of the insulin and leptin receptors and their downstream signaling proteins. Pharmacological or genetic suppression of PTP1B and TC-PTP activity can trigger a number of compensatory mechanisms, which weaken the effects of the inhibitors of these enzymes. Among them, are changes in gene expression of both phosphatases and the components of the insulin and leptin signaling cascade. In the liver, we studied the expression of the genes that encode PTP1B, TC-PTP, and SHP1, as well as genes encoding insulin and leptin receptors. It was shown that in the liver of rats treated with compounds 3 and 4, the expressions of the PTP1B and TC-PTP genes were significantly increased, while the expression of the Shp1 gene did not change. In the case of compounds 1 and 2, which are more specific to PTP1B, there was a trend towards an increase in the PTP1B and TC-PTP gene expressions, yet there was a significant increase in the Shp1 gene expression. An increase in the expression of the SHP1 phosphatase, in obese rats with impaired glucose tolerance, is consistent with its negative role in the regulation of feeding behaviors and glucose homeostasis [30]. Thus, it was found that in mice with diet-induced obesity, the expression of SHP1 is increased [31], and inhibition or knockout of this enzyme prevents the development of metabolic disorders [30,32]. Thus, there is reason to believe that this phosphatase may be involved in the mechanisms through which insulin and leptin signaling is weakened. Our data on the expression of the SHP1 gene, however, seem somewhat unexpected and require further study. Based on these data, it can be concluded that inhibitors with comparable selectivity towards the PTP1B and TC-PTP phosphatases (compounds 3 and 4) have little effect on the expression of SHP1, while inhibitors predominantly selective for PTP1B (compounds 1 and 2), increase it, and this effect does not depend on the IC50 values. Compounds 1–4 were synthesized, as described previously [23]. The measurement of the activity of the phosphatases PTP1B and TC-PTP and their inhibition was carried out using 6,8-difluoro-4methylumbelliferyl phosphate (DiFMUP), as previously described [33]. The stock solution of recombinant human PTP1B protein (#ab51277, Abcam, Cambridge, UK), at a concentration of 1 µg/µL, was prepared in 25 mM Tris–HCl (pH 7.5), 20% glycerol, 2 mM β-mercaptoethanol, 1 mm EDTA, and 1 mM DTT, and stored at −20 °C. Active human recombinant TC-PTP protein was purchased from Sigma-Aldrich (#SRP0218, Saint Louis, MO, USA) as the aqueous buffer solution at a concentration of 2.9 mg/mL, and aliquots were stored at −80 °C. The fluorogenic substrate DiFMUP (#D6567, Molecular Probes, Thermo Fisher Scientific, Waltham, MA, USA) was dissolved at a concentration of 10 mM in N,N-dimethylformamide and stored in aliquots at −20 °C. The 6,8-difluoro-7-hydroxy-4-methylcoumarin (DiFMU, #D6566, Molecular Probes, Thermo Fisher Scientific, Waltham, MA, USA) was used as a reference fluorescent standard. For the IC50 determination, the assay was carried out in black flat bottom 96-well plates using a reaction volume of 100 µL. The phosphatases (PTP1B or TC-PTP) were preincubated with the tested compounds (0.1–80 µM) in 50 mM HEPES (pH 6.9), 100 mM NaCl, 1 mM EDTA, 2 mM DTT, 0.1 mg/mL BSA for 5 min at 37 °C. The following concentrations of the compounds were studied: 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 40, and 80 μM. The reactions were initiated by the addition of the fluorogenic substrate DiFMUP and diluted in the assay buffer. Progress curves for hydrolysis reaction were obtained with 25 µM of DiFMUP for 80 ng/mL PTP1B, and 35 µM of DiFMUP for 80 ng/mL TC-PTP. Fluorescence excitation of hydrolyzed DiFMUP and the fluorescent standard DiFMU was monitored at 355 nm and emission was detected at 460 nm for 6–10 min at 30 s intervals in a Fluoroskan Ascent FL microplate reader (Thermo Electron Corporation, Vantaa, Finland). Initial velocities of the reactions were used to calculate the IC50 values using GraphPad Prism. The male Wistar rats (at the start of the experiment the age of the animals was 2-months, and at the end of the experiment their age was 6-months) were obtained from the Rappolovo animal facility (Russia). The animals were housed in plastic cages, five animals in each, with a normal light–dark cycle (12 h/12 h), a temperature of 22 ± 3 °C, and free access to food and water. All experiments were approved by the Institutional Animal Care and Use Committee at the Sechenov Institute of Evolutionary Physiology and Biochemistry (St. Petersburg, Russia) (protocol No 02/02-2020, 19 February 2020) and according to The Guide for the Care and Use of Laboratory Animals and the European Communities Council Directive of 1986 (86/609/EEC). All efforts were made to minimize animal suffering and reduce the number of experimental animals. The obesity model was induced at 16-weeks (starting at two months of age) using a high-fat diet. Control animals received standard laboratory chow pellets. The high-fat diet included supplements of 5–7 g of a fat mixture containing 52.4% pork lard, 41.7% curd, 5% liver, 0.5% L-methionine, 0.2% baker’s yeast, and 0.2% sodium chloride [34]. After 16-weeks on a high-fat diet, the animals with increased body weight, glucose intolerance, and hyperinsulinemia, and hyperleptinemia were selected for further experiments. The glucose intolerance was estimated according to the results of the glucose tolerance test (GTT). In the GTT, 120 min after glucose loading, the blood glucose levels in obese rats were above 7 mM, and the AUC0-120 values for the curve “glucose concentration (mM)–time (minutes)” were above 30%, as compared to the average AUC0-120 values in the control group. Further, six groups were formed: control (Con, n = 10), obesity (Ob, n = 10), obese rats with five-day treatment with compounds 1 (Ob + 1, n = 5), 2 (Ob + 2, n = 5), 3 (Ob + 3, n = 10), and 4 (Ob + 4, n = 10). All compounds were administered in DMSO (300 µL) at a daily dose of 7 mg/kg (1 and 2), 8 mg/kg (3), and 10 mg/kg (4) (i.p.), based on the results of the preliminary experiments. The used doses of compounds 1–4, in terms of the number of moles of each compound per kg of animal body weight, were equivalent. Control and obese rats received DMSO in the same volumes (300 µL), instead of the tested compounds. During the five days of the experiment, all animals were transferred to standard food and had free access to food and drinking water. Five animals each from the control group and the groups with obesity and treated with the most active compounds 3 and 4 were selected for the study of glucose tolerance using the GTT. The test was carried out on the morning of the next day after the last (fifth) injection of the compounds or DMSO, after a 10 h fast. The rest of the animals (n = 5 in each group) were anesthetized and decapitated on the last day of the experiment. The blood and liver samples were taken to measure blood glucose and hormone levels and gene expression in the liver. The glucose levels in the blood obtained from the tail vein were measured using a glucometer (Life Scan Johnson & Johnson, Denmark) and the test strips “One Touch Ultra” (USA). The levels of insulin and leptin in rat serum were estimated with the “Rat Insulin ELISA” (Mercodia AB, Uppsala, Sweden) and “ELISA for Leptin, Rat” (Cloud-Clone Corporation, Houston, TX, USA) kits. The GTT was carried out using a single injection of glucose (2 g/kg, i.p.) after 10 h of fasting, as described earlier [34]. The blood glucose levels were measured before (0 min) and 15, 30, 60, and 120 min after the glucose load. The total RNA was isolated from the liver samples of rats using the “ExtractRNA Reagent” (Evrogen, Moscow, Russia), and the samples containing 1 μg of RNA were transcribed to cDNA using the random oligodeoxynucleotide primers and the “MMLV RT kit” (Evrogen, Russia). The amplification procedure was carried out in the mixture containing 10 ng of reverse transcribed product, 0.4 μM of the forward and reverse primers, and the “qPCRmix-HS SYBR + LowROX kit” (Evrogen, Russia). The amplified signals were detected using the “Applied Biosystems® 7500 Real-Time PCR System” (Life Technologies, Carlsbad, CA, USA, Thermo Fisher Scientific Inc., USA). The primers that were used to assess the expression of genes encoding the phosphatase PTP1B, TC-PTP, and SHP1 and the insulin and leptin receptors are presented in Table 4. The obtained data were calculated with the delta–delta Ct method and expressed as a fold expression, relative to the corresponding control [35]. The expression of the gene encoding 18S RNA was used as an endogenous control. The data on food intake, body weight, and biochemical parameters in rats, as well as the PCR data, were analyzed using the IBM SPSS Statistics 22 software (“IBM”, Armonk, NY, USA), and the results are presented as mean ± standard error of the mean (M ± SEM). All differences are considered significant at p < 0.05. The calculation of the IC50 values of the studied inhibitors for the initial velocities of enzymatic reactions (PTP1B, TC-PTP) was carried out using the nonlinear regression analysis with GraphPad Prism 8 (“GraphPad Software, Inc.”, Boston, MA, USA). The statistical analysis was carried out using the Wilcoxon test for pairwise comparison and Dunn’s test for multiple comparisons. Observed protein structures were taken from the RCSB Protein Data Bank database [36]. PDB IDs: 1Q1M (PTP1b), 1L8K (TC-PTP), 4GRZ (SHP1). All proteins (enzymes) were preprocessed before the calculations using the protein prep wizard tool from Schrodinger suite 2021-4 [37]. During preprocessing, the following errors were fixed: missing amino acid sidechains, incorrect protonation states, missing hydrogens, incorrect bond orders, bond angles, bond length, and torsion angles. Solvent molecules were removed from all protein structure models. The three-dimensional structure of the compounds was generated using the LigPrep module with the computation of possible ionization states, tautomers, and stereoisomers at the physiological pH (7.4) All manipulations with the protein structures and small molecules were performed in the OPLS4 forcefield. All protein models (PTP1B, TC-PTP, and SHP1) were superimposed with the use of the protein to PTP1B structure, using the protein alignment tool (PTP1B was used as the reference). The active site was defined by positioning the reference ligand, which was present in the PTP1B model (PDB id: 1Q1M). The grid box was placed in accordance with the centroid of the workspace ligand structure. The grid box side size was 12 Å (in accordance with ligand size and the addition of the non-bonded interactions distance). The scaling factor was 1.0; the partial charge cutoff was 0.25, without the excluded volumes. The reference structure and the other studied compounds were docked in the PTP1B, TC-PTP, and SHP1 active sites. The Glide program [38] included in Schrodinger Suite was used for the docking. For each ligand, 15 docking solutions in standard precision (SP) mode were generated, without the use of constraints. Best-fitting binding pose was selected by comparing ligand–protein interactions with those for the reference ligand (see Figure 9). For each docked structure a ligand interaction diagram was generated, describing the protein–ligand contacts and types. Gibbs free energy was calculated with the use of the MM–GBSA method [39], including the implicit solvent model. This method considers the influence of the solvent and analyzes the free energy components, such as the energy increments of the strained contacts, solvation energy, and the ligand-induced conformational changes in protein amino acids surrounding the active site that interact with the ligand. For calculations, the best protein–ligand complexes obtained by docking were used. The VSGB solvation model was used along with the OPLS4 forcefield. Protein flexibility was allowed at a distance of 6 Å from the ligand. The calculations were performed with the use of the Prime module [40] from Schrodinger Suite 2021-4. We have studied the inhibitory effects of a small series of 4-oxo-1,4-dihydrocinnolines 1–4 in vitro, which exhibited dual inhibitory profiles towards two phosphatases, PTP1B and TC-PTP, which are both involved in insulin and leptin signaling. While two compounds (1 and 2) demonstrated different selectivity for the studied tyrosine phosphatases, PTP1B and TC-PTP, the selectivity of compounds 3 and 4 for these phosphatases was comparable. The affinity of the compounds to both phosphatases was corroborated by in silico modeling experiments. In obese rats, compounds 3 and 4 restored metabolic and hormonal parameters to a greater extent than compounds 1 and 2, which were more selective for PTP1B than TC-PTP. Thus, the development of phosphatase inhibitors with similar selectivity for PTP1B and TC-PTP may become a promising direction for the development of drugs for the correction of hyperphagia and obesity and the treatment of metabolic disorders, such as type 2 diabetes mellitus and metabolic syndromes.

PMC10002989

36824011

Kang He,Taiwei Wang,Xuemiao Huang,Zhaoyun Yang,Zeyu Wang,Shuang Zhang,Xin Sui,Junjie Jiang,Lijing Zhao

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma

23-02-2023

bioinformatics,nomogram,PPP1R14B,prognosis,uterine corpus endometrial carcinoma

Abstract Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein‐coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE databases. Then, PPP1R14B expression in UCEC was investigated by gene differential analysis and single gene correlation analysis. In addition, we performed gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis, and Kaplan–Meier survival analysis to predict the potential function of PPP1R14B and its role in the prognosis of UCEC patients. Then, a tool for predicting the prognosis of UCEC, namely, a nomogram model, was constructed. PPP1R14B expression was higher in UCEC tumour tissues than in normal tissues. The results revealed that PPP1R14B expression was indeed closely associated with tumour development. The results of Kaplan–Meier plotter data indicated that patients with high PPP1R14b expression had poorer overall survival, disease‐specific survival, and progression‐free interval than those with low expression. A nomogram based on the results of multifactor Cox regression was generated. PPP1R14B is a key player in UCEC progression, is associated with a range of adverse outcomes, and can serve as a prognostic marker in the clinic.

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein‐coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE databases. Then, PPP1R14B expression in UCEC was investigated by gene differential analysis and single gene correlation analysis. In addition, we performed gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis, and Kaplan–Meier survival analysis to predict the potential function of PPP1R14B and its role in the prognosis of UCEC patients. Then, a tool for predicting the prognosis of UCEC, namely, a nomogram model, was constructed. PPP1R14B expression was higher in UCEC tumour tissues than in normal tissues. The results revealed that PPP1R14B expression was indeed closely associated with tumour development. The results of Kaplan–Meier plotter data indicated that patients with high PPP1R14b expression had poorer overall survival, disease‐specific survival, and progression‐free interval than those with low expression. A nomogram based on the results of multifactor Cox regression was generated. PPP1R14B is a key player in UCEC progression, is associated with a range of adverse outcomes, and can serve as a prognostic marker in the clinic. Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies in the female genital tract, with over 200,000 new cases diagnosed worldwide each year. , In recent years, the morbidity and mortality of UCEC have been increasing over time due to the increase in life expectancy of the population and the overall prevalence of obesity and metabolic syndrome, and the age of onset has been decreasing, posing a serious threat to women's health and lives. , , Although we have made great progress in the treatment of UCEC in recent years, there is still a dearth of viable therapeutic options for advanced recurrent UCEC. As a result, discovering and identifying new compounds that may be used as prognostic biomarkers and therapeutic targets in the treatment of UCEC is critical. The PPP1R14B gene, also known as PLCB3N, SOM172, or PNG, is the protein‐encoding gene located on chromosome region 11q13 close to the human phosphatidylinositol‐specific phospholipase Cβ3 gene (PLCB3). The PPP1R14B protein is capable of inhibiting protein phosphatase 1 (PP1) as well as different PP1 holoenzymes. , PP1, a widespread Ser‐/Thr‐specific phosphatase in organisms, plays a key role in numerous biological processes, such as RNA splicing, protein synthesis, control of cell cycle progression, promotion of apoptosis, and glycogen metabolism. , , These biological processes are critical in the development of tumorigenesis and influence numerous functions, such as tumour growth, invasion, and metastasis. Studies have shown that PP1 cannot only inhibit the mitosis of tumour cells but also promote cell apoptosis when the cells are damaged beyond repair. Upregulation of PPP1R14B inhibits the expression of protein phosphatase 1 (PP1) and inhibits the function of PP1 to regulate cell growth and the cell cycle and promote apoptosis by inhibiting the myosin, glycogen‐related holoenzyme, and monomeric catalytic subunits of PP1. These effects may further lead to the proliferation, metastasis, and invasion of tumour cells. A previous study found that PPP1R14B was significantly overexpressed in ovarian clear cell carcinoma (OCCC) and endometriosis. Another study found that the mRNA expression of PPP1R14B was significantly higher in the plasma of patients with prostate cancer. A recent study also showed that PPP1R14B was highly expressed in tumour tissues, and its high expression predicted a shorter survival time for patients. To date, although one study has demonstrated the role of high expression of PPP1R14B in pancancer, no results have revealed the specific mechanism of PPP1R14B in UCEC, and its function in the development of UCEC remains unclear. This study was based on the analysis of online data without relevant experimental verification. Using the cervical cancer HeLa cell line and endometrial cancer HEC‐1‐A cell line, Xiang Nan et al. demonstrated that PPP1R14B knockdown could inhibit the activation of the Akt signalling pathway, thereby inhibiting cell proliferation and promoting cell death, but this study did not reveal a correlation of PPP1R14B with the clinical characteristics of tumours. In this paper, we further verified the differential expression of the PPP1R14B gene in UCEC by mining the latest RNAseq data of UCEC in the TCGA database and verified its expression independently using the GEO database and Human Protein Atlas (HPA) database. In addition, 105 UCEC clinical samples were collected to further verify the expression of PPP1R14B in tumours and adjacent tissues, and the results of bioinformatics analysis were verified by experiments. Regarding the specific function of PPP1R14B in UCEC development and occurrence, protein–protein interaction (PPI) networks, gene essentiality (GO) terminology analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, gene set enrichment analysis (GSEA), single‐sample gene set enrichment analysis (ssGSEA), and Kaplan–Meier survival analysis were used to predict PPP1R14B's role in UCEC patient prognosis. On the basis of a previous study, , the clinical characteristics of 105 clinical samples were used for correlation analysis, and we found that PPP1R14B expression was significantly correlated with FIGO grade and differentiation degree. Finally, we constructed a nomogram plot as a tool for clinicians to predict the prognosis of UCEC patients and help clinicians develop more suitable treatment plans for UCEC patients. The differential RNAseq expression data of PPP1R14B in pancancer were obtained from UCSC XENA (https://xenabrowser.net/datapages/) in the TPM format of the TCGA and GTEx processed uniformly by the Toil process. The differential RNAseq expression data of PPP1R14B in unpaired and paired samples were in level 3 HTSeq‐FPKM format from the TCGA (https://portal.gdc.cancer.gov/) UCEC project. FPKM (Fragments Per Kilobase per Million) format RNAseq data were converted to TPM (transcripts per million reads) format and log2 transformed. All final analyses were performed using data in TPM format. The differential analysis data for PPP1R14B in dataset GSE17025 , were downloaded from the GEO database using the GEOquery package (version 2.54.1). These data were obtained by removing probes corresponding to multiple molecules, and when probes corresponding to the same molecule were encountered, only the probe with the largest signal value was retained, and then the data were normalized again by the normalize Between Arrays function of the limma package (version 3.42.2). All statistical analyses and visualizations were performed using R (version 3.6.3). The protocol of this retrospective study was approved by the Ethics Committee of the School of Nursing of Jilin University (Changchun, China) and was consistent with the principles of the Declaration of Helsinki. All enrolled patients were informed and agreed to participate in the present study and gave written informed consent. The paraffin‐embedded specimens of a total of 105 patients, all female, with UCEC who were diagnosed between 1 January 2019 and 31 May 2019 were collected from The Second Hospital of Jilin University (Changchun, China). The inclusion criteria were as follows: The first surgery was performed at the Second Hospital of Jilin University, and the pathological diagnosis was UCEC. The exclusion criteria were as follows: diagnosis of other malignant tumours; intrauterine device (IUD) and/or hormone therapy were used within 6 months before surgery. Ten specimens from UCEC patients of fresh‐frozen tumours and adjacent noncancerous tissue were collected between May 2021 and June 2022. Baseline patient characteristics and pathological data, including age, menopause status, differentiation degree, and FIGO stage, were extracted from the database of The Second Hospital of Jilin University. Proteins were extracted from fresh‐frozen tissues followed by protein quantitation with a Coomassie Plus (Bradford) Assay Kit (Thermo Scientific, Cat#23236). Western blot analysis was conducted under standard procedures as previously described. The primary antibodies were PPP1R14B (Proteintech, Cat#18476‐1‐AP; Dilution, 1:500) and GAPDH (Proteintech, Cat#10494‐1‐AP; Dilution, 1:5000). The secondary antibody was HRP‐conjugated goat anti‐rabbit (Proteintech, Cat#SA00001‐2; Dilution, 1:20,000). Immunohistochemical (IHC) staining assays were performed as previously described. Briefly, the paraffin‐embedded tissues were cut into 4 μm thick slides. After deparaffinization and rehydration, antigen retrieval was performed with each slide. Then, slides were blocked with 5% serum and incubated with primary antibodies against PPP1R14B (Servicebio, Cat#GB113534; Dilution, 1:2000) overnight at 4°C. The following procedure was performed: incubation with secondary antibodies, signal detection with DAB chromogen solution, counterstaining with haematoxylin, dehydration, and sealing with neutral gum. Finally, the slides were imaged using an Olympus optical microscope (BX51). The evaluation criteria were based on staining intensity and the proportion of positive tumour cells as previously described. For staining intensity: 0 (no colour), 1 (light yellow), 2 (yellow brown), and 3 (brown). For the proportion of positive tumour cells: 0 (<5%), 1 (5%–25%), 2 (26%–50%), 3 (51%–75%), and 4 (>75%). The scoring was evaluated by two independent pathologists who were blinded to the patients' UCEC status. The expression profiles of PPP1R14B across cancers were analysed for differences using the Mann–Whitney U test (Wilcoxon rank sum test). The Shapiro–Wilk normality test was used to test the normality of the PPP1R14B expression data in paired samples, unpaired samples, and GSE17025, and the independent samples t test was used to analyse the differences in the data in unpaired samples. The paired samples t test was used to analyse the differences in the data in paired samples, and the Mann–Whitney U test (Wilcoxon rank sum test) was used for analysis of variance of data in GSE17025. The results of all the above analyses were visualized using ggplot2 (version 3.3.3) and were considered statistically significant when p < 0.05. Immunohistochemical staining images of PPP1R14B in UCEC and normal tissue sections were downloaded using the HPA database (https://www.proteinatlas.org/), where these sections were stained using the same antibodies and experimental methods. Single‐gene differential analysis of RNAseq data in level 3 HTSeq‐Counts format from the UCEC (endometrial cancer) project of TCGA was performed using the DESeq2 package (version 1.26.0). Single‐gene correlation analysis was performed on expression profile data in TPM format using the STAT package (version 3.6.3). The target molecule in the above analysis was PPP1R14B. Volcano plots were drawn using the results of single‐gene differential analysis, setting a threshold of |log2(FC)| > 1 and p.adj <0.05. These differentially expressed genes were entered into the STRING database, and protein–protein interaction (PPI) of differentially expressed genes was determined using Cytoscape software network analysis. Then, the HUB genes were identified using the MCODE plugin. Finally, using the results of single‐gene correlation analysis, the results were sorted by |Pearson value| in descending order, the genes whose correlations were in the top 50 were extracted, and the single‐gene coexpression heatmap of PPP1R14B was drawn using these genes and the HUB gene. Volcano plots and coexpression heatmaps were both generated by ggplot2 (version 3.3.3). By using the clusterProfiler package (version 3.14.3), GO, KEGG, and GSEA functional enrichment analyses were performed on the results of single‐gene differential analysis. Gene ID conversion was performed using the org.Hs.eg.db package (version 3.10.0), and the Z score was calculated using the GOplot package (version 1.0.2), which scores the relevance of PPP1R14B to the enrichment pathway. The reference gene set used for the GSEA was c2.cgp.v7.2.symbols.gmt (Curated), and the results were significantly enriched if they met the conditions of false discovery rate (FDR) < 0.25 and p.adjust < 0.05. The visualization of all the above analysis results was performed using ggplot2 (version 3.3.3). The relative infiltration levels of 24 immune cells were analysed using the GSVA package (version 1.34.0). ssGSEA was performed for the algorithm of immune infiltration, and the chosen correlation analysis method was Spearman. Markers for 24 immune cells were obtained from an Immunity study. Afterwards, the samples were divided into low and high expression groups according to the expression of PPP1R14B, the enrichment scores of various immune cell infiltrates in the different subgroups were calculated, and the analysis was performed using the GSVA package (version 1.34.0). Finally, the correlation between immune cell infiltration and PPP1R14B expression was visualized by analysing immune cells with statistically significant relative infiltration (p < 0.001), and PPP1R14B gene expression data were used to draw chord diagrams. Statistical analysis and visualization were performed using the circlize package (version 0.4.12). The survival data of UCEC patients were statistically analysed using the survival package (version 3.2‐10), and the results were visualized using the survminer package (version 0.4.9) to plot UCEC patients' overall survival (OS), disease‐specific survival (DSS), and progression‐free interval (PFI) of Kaplan–Meier survival curves. We then performed a subgroup analysis of Kaplan–Meier survival curves in UCEC patients for clinicopathological factors such as age, presence of diabetes, and menopause status. We then used these clinicopathological factors to calculate their correlation with PPP1R14B expression and visualized the calculated results using ggplot2 (version 3.3.3). ROC analysis of the data was performed using the pROC package (version 1.17.0.1) to determine the accuracy of PPP1R14B for prognostic prediction. Finally, univariate and multivariate Cox regression analyses were performed again using the survival package (version 3.2‐10) for different clinicopathological factors and PPP1R14B expression, and the median was used to determine the critical value of PPP1R14B expression. The results were visualized by forest plots. Based on the results of the Cox regression analysis, a nomogram prognostic prediction model was constructed using the rms package (version 6.2‐0) and the survival package (version 3.2‐10), and a calibration plot was drawn to check the accuracy of the rainfall prediction. All prognostic data for the above survival analysis were obtained from a paper in Cell. Data are expressed as the mean ± standard deviation (mean ± SD). The difference in the expression of PPP1R14B in UCEC tumour tissues and adjacent tissues was analysed by Student's t test. One‐way analysis of variance (anova) was used for comparisons between multiple groups. The association between the expression of PPP1R14B and the clinical data of UCEC patients was analysed by Mann–Whitney U test analysis. The statistical graph was completed using GraphPad Prism 8, and p < 0.05 was regarded as statistically significant. The results of differential expression analysis of PPP1R14B across carcinomas are shown in Figure 1A. In adrenocortical carcinoma (ACC, T = 77, N = 128), acute myeloid leukaemia (LAML, T = 173, N = 70), and skin cutaneous melanoma (SKCM, T = 469, N = 813), the expression of PPP1R14B was lower than that in normal tissues, and the differences were statistically significant (p < 0.05). In bladder urothelial carcinoma (BLCA, T = 407, N = 28), breast invasive carcinoma (BRCA, T = 1099, N = 292), cervical squamous cell carcinoma, and endocervical adenocarcinoma (CESC, T = 306, N = 13), the cholangiocarcinoma (CHOL, T = 36, N = 9), colon adenocarcinoma (COAD, T = 290, N = 349), Neoplasm Diffuse Large B‐cell Lymphoma (DLBC, T = 47, N = 444), oesophageal carcinoma (ESCA, T = 182, N = 666), glioblastoma multiforme (GBM, T = 166, N = 1157), head and neck squamous cell carcinoma (HNSC, T = 520, N = 44), kidney chromophobe (KICH, T = 66, N = 53), kidney renal clear cell carcinoma (KIRC, T = 531, N = 100), kidney renal papillary cell carcinoma (KIRP, T = 289, N = 60), brain lower grade glioma (LGG, T = 523, N = 1152), liver hepatocellular carcinoma (LIHC, T = 371, N = 160), lung adenocarcinoma (LUAD, T = 515, N = 347), lung squamous cell carcinoma (LUSC, T = 498, N = 338), ovarian serous cystadenocarcinoma (OV, T = 427, N = 88), pancreatic adenocarcinoma (PAAD, T = 179, N = 171), prostate adenocarcinoma (PRAD, T = 496, N = 152), rectum adenocarcinoma (READ, T = 93, N = 318), stomach adenocarcinoma (STAD, T = 414, N = 210), testicular germ cell tumours (TGCT, T = 154, N = 165), thyroid carcinoma (THCA, T = 512, N = 338), thymoma (THYM, T = 119, N = 446), uterine corpus endometrial carcinoma (UCEC, T = 181, N = 101), and uterine carcinosarcoma (UCS, T = 57, N = 78), the expression of PPP1R14B was higher than that of normal tissues, and the difference was statistically significant (p < 0.05). As shown in Figure 1B, in pancancer pairs, the expression of PPP1R14B in BLCA (T = 19, N = 19), BRCA (T = 112, N = 112), CHOL (T = 9, N = 9), COAD (T = 26, N = 26), ESCA (T = 13, N = 13), HNSC (T = 43, N = 43), KICH (T = 25, N = 25), KIRC (T = 72, N = 72), KIRP (T = 32, N = 32), LIHC (T = 50, N = 50), LUAD (T = 58, N = 58), LUSC (T = 50, N = 50), PAAD (T = 4, N = 4), PRAD (T = 52, N = 52), READ (T = 6, N = 6), STAD (T = 33, N = 33), THCA (T = 59, N = 59), and UCEC (T = 7, N = 7) was higher than that in the adjacent tissue, and the difference was statistically significant (p < 0.05). In both paired and unpaired samples of UCEC, the expression of PPP1R14B was significantly different compared with that in normal samples, and the results are shown in Figure 1C,D. We then used the GSE17025 dataset from the GEO database to verify the results in the TCGA database, and the results are shown in Figure 1E; the results were still significantly different. Finally, we analysed the difference in the protein expression levels of PPP1R14B in UCEC tissues and normal tissues using the HPA online database, and their immunohistochemical (IHC) images are shown in Figure 1F–I. IHC images of normal endometrium are presented in Figure 1F, while IHC images are presented in Figure 1G–I of endometrial adenocarcinoma tissue from an 80‐year‐old woman, a 50‐year‐old woman, and a 72‐year‐old woman, respectively. The expression of PPP1R14B was not detected in normal tissues, but high expression of PPP1R14B was detected in tumour tissues. Single gene differential analysis of PPP1R14B was performed in UCEC, and the results are shown in Figure 2A. A total of 687 genes satisfied the threshold of |log2(FC)| > 1 and p.adj < 0.05, and under this threshold, the number of genes with high expression (positive log2FC) was 161, and the number of genes with low expression (negative log2FC) was 526. We then constructed a PPI network using these 687 differentially expressed genes, and the results are shown in Figure 2B. The closer the genes are to the centre of the interaction network graph, the more connections they have with other genes. Then, using the MCODE plugin, we identified 15 HUB genes, namely, KRTAP26‐1, KRTAP9‐8, KRTAP13‐2, KRTAP7‐1, KRTAP3‐2, KRTAP11‐1, KRTAP29‐1, KRTAP9‐4, KRTAP2‐3, KRTAP9‐3, KRTAP KRT73, KRT82, KRTAP12‐2, KRTAP6‐3, and KRTAP2‐2. The PPI network of HUB genes is shown in Figure 2C. These hub genes were all keratin‐associated proteins or keratins, and based on these genes, we drew their gene coexpression heatmap with PPP1R14B, as shown in Figure 2D. Finally, we performed single gene correlation analysis of PPP14R14B and selected the top 50 most strongly correlated genes to draw a correlation heatmap with PPP1R14B, and the results are shown in Figure 2E. GO, KEGG, and GSEA enrichment analyses were performed using the results of single‐gene differential analysis, and the results are shown in Figure 3. Figure 3A,C and Table 1 show the results of GO analysis, which revealed that PPP1R14B is functionally related to epidermal cell differentiation, endopeptidase activity regulation, blood microparticles, and hormone activity. Figure 3B,D and Table 1 show the results of KEGG analysis, which revealed that PPP1R14B was associated with neuroactive ligand–receptor interaction, retinol metabolism, chemical carcinogenesis, tyrosine metabolism, steroid hormone biosynthesis, oestrogen signalling pathway, etc. The Z score reflects the correlation of PPP1R14B with these pathways to some extent. A negative Z score indicates a negative correlation, and a positive Z score indicates a positive correlation. Figure 3E,F show the enrichment and grading results of GSEA, which suggested that there was significant enrichment in kinsey targets of ewsr1 flii fusion up, hsiao liver specific genes, benporath es 1, vart kshv infection angiogenic markers up, sabates colorectal adenoma up, heller hdac targets silenced by methylation up, and other genes related to tumorigenesis, invasion, and angiogenesis, suggesting that PPP1R14B was indeed closely related to cancer. To determine the effect of PPP1R14B expression on the tumour microenvironment, immune infiltration analysis was performed using the ssGSEA method. The correlation between immune cell enrichment and PPP1R14B expression levels in UCEC tissues was calculated using Spearman correlation analysis. The results are shown in Figure 4B. The expression of PPP1R14B was positively correlated with the level of infiltration of four immune cells, namely, aDCs, CD8 T cells, Th1 cells, and Th2 cells. The expression of PPP1R14B was negatively correlated with the level of infiltration of nine immune cells, namely, eosinophils, iDCs, mast cells, neutrophils NK CD56bright cells, NK cells, Tcm, Tem, and Th17 cells. Next, we divided the expression profile data into high and low expression groups according to the expression level of PPP1R14B to identify the changes in the level of immune cell infiltration in the different groups. The results, which are shown in Figure 4A, indicate that in CD8 T cells, Th1 cells, and Th2 cells, the level of infiltration in the low expression group was significantly lower than that in the high expression group. In eosinophils, iDCs, mast cells, neutrophils, NK CD56bright cells, NK cells, Tcm cells, Tems, and Th17 cells, the infiltration level of the low expression group was significantly higher than that of the high expression group, and this result is consistent with the results shown in Figure 4B. Finally, we used the expression values of PPP1R14B with the enrichment scores of the six immune cells with significant correlation to produce chord plots to visualize the correlation between them, and the results are shown in Figure 4C. First, we divided the expression profile data into high and low expression groups according to the expression of PPP1R14B and analysed the overall survival (OS), disease‐specific survival (DSS), and progression‐free interval (PFI) of UCEC patients in the different groups. The results showed that the groups with high expression of PPP1R14B all exhibited shorter survival times, as shown in Figure 5A–C. We then grouped the clinicopathological factors to analyse whether the OS of UCEC patients would be significantly different in the different subgroups. We found that among patients older than 60 years, among patients with menopause status in peri and post, patients with diabetes, patients with primary therapy outcome of PD, SD, or PR, patients with clinical stage II, stage III, or stage IV, patients with less than 50% tumour invasion, patients with histologic type endometrioid, patients with histologic grade G3 level, and patients who did not receive radiation therapy, the group with high expression of PPP1R14 showed shorter survival time (Figure 5D–L). These results suggested that high expression of PPP1R14B was associated with poor prognosis and was closely related to tumour development. Furthermore, these findings indicated that high expression of PPP1R14B is a risk factor for patients. To further verify that high expression of PPP1R14B is associated with poor prognosis and is closely related to tumour development, we compared the expression levels of PPP1R14B in patients from different groups with distinct clinicopathological factors, and the results are shown in Figure 6A–J. A clinical baseline information table was constructed based on the expression level of PPP1R14B, as shown in Table 2. The expression levels of PPP1R14B in patients with different clinical stages or different histological types, etc., were significantly different from those in control patients, which suggested that the expression of PPP1R14B may be associated with tumorigenesis and can be used as a marker for tumour diagnosis. Then, we found a significant difference in PPP1R14B expression between patients with endometrioid and serous histological types of tumours, suggesting that PPP1R14B is indeed associated with poor prognosis. The expression of PPP1R14B also differed between patients with primary therapy outcomes of PD and CR, suggesting that its expression may also be associated with disease progression. The expression levels of PPP1R14B also differed among patients with different levels of tumour invasion, suggesting that the level of tumour invasion may also be correlated with the expression of PPP1R14. Finally, we constructed a ROC curve to verify the accuracy of PPP1R14B expression in predicting prognosis, and the results are shown in Figure 6K. The predictive ability of the variable PPP1R14B was somewhat accurate in predicting the prognostic outcome of tumour patients versus normal patients (AUC = 0.955, CI = 0.930–0.981). To construct an easy‐to‐use nomogram graph as a tool for clinicians to judge prognosis, we first performed univariate and multivariate COX regression analyses using different clinicopathological factors with PPP1R14B expression values to find independent prognostic factors for UCEC patients. The results are shown in Figure 7 and reveal that high expression of PPP1R14B is an independent prognostic risk factor for UCEC patients. The nomogram we constructed is shown in Figure 8A, and the factors used for prediction included clinical stage, histologic grade, histological type, primary therapy outcome, tumour invasion, and radiation therapy with the expression of PPP1R14B. To verify the accuracy of this prediction tool to predict prognosis, we constructed a calibration plot, as shown in Figure 8B, with a concordance index (C index) of 0.83, indicating a moderate accuracy of predictive ability, and the calibration plot was very close to the diagonal, which indicated good calibration performance. Next, we evaluated the expression of PPP1R14B in 10 UCEC tumour tissues and 10 adjacent tissues by Western blot analysis. As shown in Figure 9 A and B, the expression of PPP1R14B was higher in UCEC tumour tissues than in adjacent tissues. Additionally, the results of IHC staining confirmed the upregulated expression of PPP1R14B in low‐grade UCEC (Figure 9B–D). All clinical data, including age, menopause status, pathological grade, and FIGO stage, are summarized in Table 3. After Mann–Whitney U test analysis, pathological grade and FIGO stage were determined to be related to the level of PPP1R14B expression. UCEC patients with low pathological grade (p < 0.05) or high FIGO stage (p < 0.05) showed higher expression of PPP1R14B. Uterine corpus endometrial carcinoma is one of the most common gynaecological malignancies. In recent years, the incidence and related mortality of UCEC has been increasing year by year, and a trend toward younger age‐of‐onset has also emerged. Epidemiological results showed that 6.5% of patients with UCEC were younger than 45 years of age, and nearly 70% of them were diagnosed before first pregnancy. How to develop personalized treatment programs to preserve fertility, reduce mortality, and improve life quality will be the focus and theme of more research in the future. Therefore, further exploration of more molecular biomarkers is of great importance to detect the occurrence and prognosis of UCEC and develop more reasonable treatment plans. In this study, UCEC expression profile data from the TCGA and GEO databases were used to screen differentially expressed genes between UCEC and normal tissues. PPP1R14B expression in UCEC was higher than that in normal tissues, suggesting that PPP1R14B may be involved in the occurrence and development of tumours. Similar to this study, Mingxia Deng et al. found that PPP1R14B in pancancer was a type of diagnostic molecular marker associated with immune infiltration. To further predict the molecular mechanism by which PPP1R14B promotes the occurrence and development of endometrial cancer, single‐gene differential analysis and correlation analysis were performed, and a PPI protein interaction network was constructed. Fifteen HUB genes most related to PPP1R14B expression and 50 genes closely related to PPP1R14B expression were found to predict the function of the PPP1R14B gene. Among them, keratin‐related proteins and keratin‐PPP1R14B functions were particularly closely related to PPP1R14B expression. Keratin‐associated proteins (KRTAPs) comprise a large multigene family of proteins thought to be responsible for the bundling of keratin intermediate filaments. Keratin (KRT) is a cytoskeletal protein of epithelial cells that is involved in the regulation of apoptosis tolerance, growth, and migration of tumour cells and is closely related to tumorigenesis. Some keratin is increased in the serum of tumour patients or highly expressed in tumour tissues, which is widely used in the diagnosis of tumours clinically. Keratin expression is negatively correlated with the prognosis of tumour patients and can be used as a prognostic marker. , , , In addition, keratin 82 (KRT82) mutations have been shown to be prevalent in gastric, colorectal, and endometrial cancers. , Keratin‐associated protein 6–3 (KRTAP6‐3) mutations have been found in patients with aggressive brain tumours. Therefore, we hypothesized that PPP1R14B may play a role in promoting endometrial cancer by promoting the function of keratin‐related proteins and keratin. In addition, among the genes closely associated with PPP1R14B expression, UBE2S, JPT1, and PTTG1 were associated with abnormal expression of endometrial cancer desiccations, proliferation, migration, methylation, and prediction of response to metformin therapy. , , , Our study suggested that the high expression of PPP1R14B may be related to gene mutation and tumour proliferation, invasion, and metastasis in UCEC patients. To further clarify the possible molecular mechanism by which PPP1R14B promotes tumour development, GO analysis, KEGG analysis, and GSEA were performed. The results showed that PPP1R14B was negatively associated with intermediate filament‐related pathways, and intermediate filaments could inhibit UCEC metastasis and invasion. , In addition, hormone activity and oestrogen signalling pathways were found to be enriched. Given that endometrial cancer formation is associated with dysplasia caused by oestrogen overstimulation, this result suggests that involvement in this process may also be one of the mechanisms by which PPP1R14B promotes endometrial cancer development. In addition, the enrichment of retinol metabolism and tyrosine metabolism has been observed, and retinol and its derivatives can effectively delay or prevent precancerous lesions and induce tumour cell differentiation and apoptosis. Abnormal tyrosine metabolism also plays a very important role in the occurrence and development of tumours. GSEA results showed that PPP1R14B was closely related to H3K27me3, PRC2, and other epigenetic genes, which are closely related to the stem cell characteristics of tumour cells. In many poorly differentiated tumours, the stem cell phenotype is often very obvious. These results suggest that PPP1R14B may contribute to UCEC tumour cells showing stem cell characteristics, which are closely related to tumour differentiation and proliferation. , , Further experimental studies are needed to confirm the underlying mechanism of high expression of these pathways in PPP1R14B, leading to poor prognosis in UCEC patients. The correlation between PPP1R14B expression and 24 types of immune cells in UCEC patients was also analysed. The results showed that PPP1R14B expression was negatively correlated with eosinophils, iDCs, mast cells, neutrophils, and other immune cells. Immune cell infiltration can improve the poor prognosis of patients, and low concentrations of infiltrating immune cells can lead to immune escape of cancer cells, resulting in poor prognosis. , In addition, the results of immune infiltration showed that the degree of Th2 cell infiltration was significantly positively correlated with the expression of PPP1R14B. The transition from Th1/Th2 balance to Th2 dominance is a crucial factor in tumour progression, and Th2 cells are not conducive to the antitumour effect of cellular immunity. Restoring the balance between Th1 and Th2 cells is of great significance in the treatment of tumours. , All these results indicate that upregulation of PPP1R14B expression can inhibit the antitumour immune response in UCEC patients. To investigate the role of PPP1R14B in predicting the prognosis of patients, we used the TCGA database to analyse the relationship between PPP1R14B expression and clinicopathological features. The expression of PPP1R14B was significantly correlated with histological grade, histological type and tumour invasion. Furthermore, 105 clinical samples were collected, Western blotting and immunohistochemistry were employed to detect the expression of PPP1R14B in UCEC tissues, and the relationships between PPP1R14B and clinical characteristics were analysed. The results showed that PPP1R14B was correlated with FIGO grade and pathological grade (p < 0.05). This was consistent with the results of bioinformatics analysis, indicating that high expression of PPP1R14B may indicate poor prognosis of tumour patients. In the following survival analysis, the OS, PFI, and DSS of patients with high PPP1R14B expression were significantly shortened compared with those with low PPP1R14B expression. At the same time, the multivariate Cox regression results were used to construct the nomogram plot as a prediction tool for clinical prognosis, and the accuracy of the model was analysed. As seen from the calibration plot, the actual OS values at 1 year, 3 years, and 5 years were in good agreement with the predicted values. Therefore, the nomogram constructed in this study may become a new and valuable prognostic prediction method. A large number of previous studies have demonstrated the role of other protein‐coding RNAs and non‐coding RNAs in predicting the occurrence and prognosis of endometrial cancer. L1CAM has been shown to be a promising molecular marker for predicting prognosis in a high‐risk “no specific molecular profile” (NSMP) subgroup of patients with UCEC. Meanwhile, abnormal expression of non‐coding RNAs such as CCAT2, DLEU1, PVT1, LINC01170, MEG3, and FER1L4 in UCEC has also been proven to be related to the occurrence, development, and prognosis of UCEC. These non‐coding RNAs could also be used as prognostic molecular markers to guide the risk stratification of UCEC patients. These studies suggest the value and feasibility of PPP1R14B as a potential molecular marker in the diagnosis and prognosis assessment of UCEC. The high expression of PPP1R14B in UCEC predicts the poor prognosis of patients, which can help medical workers to screen out patients suitable for the treatment of fertility function preservation, expect the risk of recurrence of patients with UCEC after treatment, determine which patients need further follow‐up and treatment, develop individualized precise treatment programs, and provide new targets for targeted therapy or immune checkpoint inhibitor therapy in patients with recurrence or metastasis of UCEC. In conclusion, high expression of PPP1R14B can inhibit the antitumour immune response in UCEC patients and participate in various biological processes, such as tumorigenesis, metastasis, and invasion. Therefore, it may become an independent prognostic risk factor that can be used as a diagnostic and prognostic marker in clinical practice to help doctors make more reasonable treatment plans for patients. However, there was a large difference between the number of normal samples and the number of tumour samples in this study, and further studies with large sample sizes are needed in the future. In addition, the results obtained in this study need more experiments, such as animal experiments and cell experiments, to further verify the mechanism of PPP1R14B in promoting UCEC. Since this study is a retrospective study based on the existing RNA sequencing data in TCGA and GEO databases, prospective studies are needed in the future to reduce the bias caused by retrospective studies. Kang He: Data curation (equal); writing – original draft (equal). Taiwei Wang: Investigation (equal); writing – original draft (equal). Xuemiao Huang: Writing – review and editing (equal). Zhaoyun Yang: Writing – original draft (equal). Zeyu Wang: Writing – original draft (equal). Shuang Zhang: Data curation (equal); investigation (equal). Xin Sui: Data curation (equal); formal analysis (equal). Junjie Jiang: Conceptualization (equal); supervision (equal). Lijing Zhao: Conceptualization (equal); supervision (equal). This study was supported by a grant from the Jilin Provincial Department of Science and Technology project (grant number: 20210204200YY). The authors declare that they have no competing interests.

PMC10002992

Dorina Lauritano,Filiberto Mastrangelo,Cristian D’Ovidio,Gianpaolo Ronconi,Alessandro Caraffa,Carla E. Gallenga,Ilias Frydas,Spyros K. Kritas,Matteo Trimarchi,Francesco Carinci,Pio Conti

Activation of Mast Cells by Neuropeptides: The Role of Pro-Inflammatory and Anti-Inflammatory Cytokines

02-03-2023

mast cell,inflammation,neuropeptide,cytokines,immunity,tumor,allergy

Mast cells (MCs) are tissue cells that are derived from bone marrow stem cells that contribute to allergic reactions, inflammatory diseases, innate and adaptive immunity, autoimmunity, and mental disorders. MCs located near the meninges communicate with microglia through the production of mediators such as histamine and tryptase, but also through the secretion of IL-1, IL-6 and TNF, which can create pathological effects in the brain. Preformed chemical mediators of inflammation and tumor necrosis factor (TNF) are rapidly released from the granules of MCs, the only immune cells capable of storing the cytokine TNF, although it can also be produced later through mRNA. The role of MCs in nervous system diseases has been extensively studied and reported in the scientific literature; it is of great clinical interest. However, many of the published articles concern studies on animals (mainly rats or mice) and not on humans. MCs are known to interact with neuropeptides that mediate endothelial cell activation, resulting in central nervous system (CNS) inflammatory disorders. In the brain, MCs interact with neurons causing neuronal excitation with the production of neuropeptides and the release of inflammatory mediators such as cytokines and chemokines. This article explores the current understanding of MC activation by neuropeptide substance P (SP), corticotropin-releasing hormone (CRH), and neurotensin, and the role of pro-inflammatory cytokines, suggesting a therapeutic effect of the anti-inflammatory cytokines IL-37 and IL-38.

Activation of Mast Cells by Neuropeptides: The Role of Pro-Inflammatory and Anti-Inflammatory Cytokines Mast cells (MCs) are tissue cells that are derived from bone marrow stem cells that contribute to allergic reactions, inflammatory diseases, innate and adaptive immunity, autoimmunity, and mental disorders. MCs located near the meninges communicate with microglia through the production of mediators such as histamine and tryptase, but also through the secretion of IL-1, IL-6 and TNF, which can create pathological effects in the brain. Preformed chemical mediators of inflammation and tumor necrosis factor (TNF) are rapidly released from the granules of MCs, the only immune cells capable of storing the cytokine TNF, although it can also be produced later through mRNA. The role of MCs in nervous system diseases has been extensively studied and reported in the scientific literature; it is of great clinical interest. However, many of the published articles concern studies on animals (mainly rats or mice) and not on humans. MCs are known to interact with neuropeptides that mediate endothelial cell activation, resulting in central nervous system (CNS) inflammatory disorders. In the brain, MCs interact with neurons causing neuronal excitation with the production of neuropeptides and the release of inflammatory mediators such as cytokines and chemokines. This article explores the current understanding of MC activation by neuropeptide substance P (SP), corticotropin-releasing hormone (CRH), and neurotensin, and the role of pro-inflammatory cytokines, suggesting a therapeutic effect of the anti-inflammatory cytokines IL-37 and IL-38. Mast cells (MCs) derive from bone marrow progenitors and after maturation, they migrate into the tissues where they carry out various biological responses, including innate and acquired immunity [1]. In addition, MCs are immune cells involved in a number of disorders including inflammatory, autoimmune, and allergic diseases [2]. The maturation of MCs has been reported to occur in the presence of stem cell factor (SCF), IL-3, IL-4, and IL-9, in vitro and in vivo [3]. MCs are ubiquitous in the human body but are predominantly localized in perivascular tissue, and in the central nervous system (CNS) are located in corticotropin-releasing hormone (CRH)-positive nerve endings [4]. The meninges also possess MCs that can be activated by insults such as stress and toxins, via vascular permeability, an effect that does not occur in MC-deficient rodents [5]. The anti-inflammatory cytokines have provided good results both in vitro and in rodents, generating new therapeutic hopes. However, at the moment, there is no data on clinical treatments in humans, therefore the dosage, efficacy, lifetime and side effects of these cytokines are unknown and further studies are needed to clarify this. The therapeutic targets of MCs are diverse, including antigens such as mutated KIT variants, which have shown promise and are still being studied, but satisfactory studies concerning the inhibition of pro-inflammatory cytokines have not yet been reported. The goal of this article is to discuss the current status of knowledge on MC and neuropeptide interactions and the role of pro-inflammatory and anti-inflammatory cytokines. Human MCs were first described by Paul Ehrlich, and approximately 100 years ago Gilchrist observed that there was an increase in the number of MCs near the blood vessels. In 1910, Henry Dale, and later, in 1924, Thomas Lewis confirmed these results and reported that MCs released histamine causing wheal reactions and inflammation. In the last ten years, the exponential increase in the number of articles published on MCs testifies to the interest of researchers on this fascinating immune cell. MCs are myeloid lineage cells originating from the bone marrow cells CD34+/CD117+/CD13+ that mature into tissue under the stimulation of growth factors such as SCF. MCs are classic cells of allergic diseases, but they can also mediate angiogenesis, acute and chronic inflammation, autoimmune disorders, tissue repair, neurological diseases, and tumors. The generation, survival and development of MCs depends on the c-kit receptor which binds SCF by exerting the biological response [6]. c-kit/CD117 is a proto-oncogene transmembrane tyrosine kinase receptor that has been immunolocalized in various cells including MCs. CD117 is a 145-Kd glycoprotein that is the product of the kit-gene, and SCF is the c-kit ligand, named MC growth factor, which promotes autophosphorylation of the c-kit receptor, which mediates signal transduction, critical for the survival of MCs [7]. Moreover, CD117 can be instrumental in the diagnosis of some tumors, such as gastrointestinal ones where MCs are abundant [8]. Experiments in mice have shown that c-kit is encoded at the mouse locus where it affects immature germ cells [9]. However, for ethical and practical reasons, there is not much research on human MCs in vivo and the most significant results on this issue have been obtained from research on rodents. In fact, the biological effects of MCs are studied in MC deficient mice, such as KitW-f/KitW-f, KitW/KitW-v or KitW-sh/KitW-sh, which possess a c-kit receptor dysfunction [10]. MCs express various surface receptors that allow them to respond to stimuli such as IL-3, SCF, neuropeptides, and others [11]. Activation of MCs with various compounds triggers the increase in intracellular calcium concentration and plays a key role in various inflammatory diseases, including neurological disorders. The activation of MCs can follow the synthesis of cytokines and chemokines which occurs a few hours after the antigenic stimulus. There are various markers of MCs; among these, we have tryptases, which increase by approximately 10 times after activation of CD63. Bacterial products such as lipopolysaccharide (LPS) (a potent macrophage stimulator) also activate MCs, demonstrating that these cells have anti-bacterial functions [12]. The classical high specific activation of MCs occurs through the antigenic reaction with the IgE antibody bound on the cellular high-affinity IgE Fc receptor (FcεRI) [13]. This interaction occurs at high affinity (1 × 1010 M−1), provoking the aggregation of receptors and eliciting an intracellular biological response [14]. FcεRI is composed of four subunits called alpha, beta and two gammas, responsible for initiating the biological cascade that leads to the generation of proteins that mediate the inflammatory and allergic responses [15]. The beta subunit leads to the amplification of the antigen reaction with the IgE antibody, while the alpha subunit binds IgE and activates the MC [16]. The biochemical cascade of reactions, leading to the transcription and activation of inflammatory cytokines, thus begins with the activation of the FcεRI and the phosphorylation of tyrosine kinases (Src, Syk and Tec family) [17]. Next, the 76 kDa SH2-containing leukocyte protein (SLP-76), the non-T cell activation linker (NTAL), and the phospholipase Cγ (PLCγ) (which regulates calcium in the cell) contribute to recruit protein kinase C (PKC) [18]. The phospholipid PI-4,5-P2 membrane is subsequently hydrolyzed, as well as soluble inositol 1,4,5-triphosphate (IP3), and therefore, diacylglycerol (DAG) is formed [19]. Other signaling reactions include mitogen-activated protein kinase (MAPK), extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 that lead to the transcription and production of inflammatory cytokines [20,21] (Figure 1a). Literature data on electron microscopy of MCs is increasing significantly as this method, compared with the light microscope, allows to better identify and judge the quality of endo-cellular particles, allowing improved cell morphology and biological study of this interesting immune cell. In Figure 1b,c, MCs are shown magnified with light and electron microscopy, respectively. MCs are recruited into the inflammatory microenvironment by several chemoattractants, including TNF, which is also produced by MCs. Several chemokines such as CCR2, CCR3, CXCR2, CXCR3, and CXCR4 activate MC receptors that are important for inflammatory cell recruitment. The main cytokine receptors expressed by MCs are IL-1, TNF, IL-3, IL-4, IL-5, IL-6, IL-9, IL-13, INFγ and others, which are also involved in cellular development and inflammation. Furthermore, the activation of MC-phospholipases leads to the generation of arachidonic acid inflammatory products, such as prostaglandin D2 (PGD2), leukotrienes LTC4, LCD4, and LTE4. PGD2 is an unstable prostaglandin detected as 11β-PGF2α, a more stable compound, that is related to systemic inflammation at non-physiological concentration in peripheral blood [22,23]. Therefore, in the brain, PGD2 mediates inflammation and pain, while LTC4, LCD4, and LTE4 are slow reacting substances of anaphylaxis (SRS-A) involved in asthma and other inflammatory diseases [24,25]. For example, leukotriene E4 is produced by MCs and increases in mastocytosis, fueling inflammation. In fact, the inhibitor of this leukotriene is used in treatment of asthma and shortness of breath [26]. After the MCs have been activated, they degranulate and release the inflammatory mediators stored in their granules in seconds (rapid release) [27]. However, most of the production of the potent inflammatory cytokine tumor necrosis factor (TNF) results from the induction of the corresponding mRNA upon MC activation (late secretion) [28]. Cytokines such as IL-5, IL-6, IL-31 and IL-33, and the chemokines CCL2, CCL5 and CXCL8, are synthesized by MCs through mRNA after activation [29] (Table 1). Injury in the brain can stimulate pro-IL-1 which is cleaved by caspase-1 to form mature IL-1, which binds its receptor IL-1R in the cell membrane and activates gene expression pathways (Figure 2). The secretion of IL-1 and TNF in the brain induces fever which is produced in the hypothalamus [30]. The mechanism of the production of fever is not yet fully understood; however, the antigen which can be a neuropeptide and other pyrogens (IL-1, TNF, IL-6, etc.) activates MCs with the production of IL-1 [31,32]. This cytokine acts on the anterior hypothalamus to generate prostaglandin E2 (PGE2), which stimulates the vasomotor center with the heat and fever production [33]. MCs secrete neuropeptides CRH and Substance P (SP), which activate microglia in the brain to generate IL-1 and the chemokines CXCL8 [34]. In fact, MCs cross-talk with microglia by releasing histamine and tryptases which induce the secretion of pro-inflammatory cytokines in MCs [35]. IL-6 (also called “myokine”) is involved in fever and is mostly secreted by T lymphocytes, macrophages, and MCs. It stimulates the immune response by binding to its receptor gp130, increasing intracellular calcium and causing a transduction cascade that leads to the activation of the signal transcription factor signal transducer and activator of transcription 3 (STAT3) and MAPK [36]. IL-6 can be secreted by macrophages and MCs in response to specific microbial molecules called pathogen-associated molecular patterns (PAMPs), which bind a group of important receptors of the innate immune system, the pattern recognition receptors (PRRs), to which the Toll-like receptors (TLRs) belong [37]. Furthermore, IL-6 initiates PGE2 synthesis in the hypothalamus, thereby causing an increase in body temperature and mediating systemic inflammation [38]. The relationship between MC-mediated allergic diseases and some neurological pathologies is demonstrated by the higher frequency of allergies and elevated IgE in children with CNS disorders [39]. Recent studies exploring the effect of neuropeptides during inflammatory diseases reported that they can stimulate immune cells including MCs to produce pro-inflammatory cytokines that can aggravate the inflammatory clinical picture. In this paper, the study of cytokine inhibition with IL-37 or IL-38, suppressors of IL-1, may result in a new strategy against acute and chronic diseases induced by increased levels of neuropeptides, including substance P, CRH, and neurotensin. Therefore, it is necessary to add more information to the current literature on neuropeptide-induced inflammation and describe new therapeutic strategies, since many inflammatory neurological diseases are incurable. SP, discovered in 1931 by Von Euler, was characterized in 1970 by Leeman and Chang. It is a highly conserved neuropeptide, isolated from the rat brain, that is mainly secreted by neurons and is involved in nociception, hypotension, muscle contraction, and inflammation [40]. The pro-inflammatory effect of SP, acting through its specific neurokinin-1 (NK-1), was confirmed in a large number of studies [41,42,43]. SP is a member of the tachykinin peptide hormone family, located on human chromosome 7 and encoded by the TAC1 gene [44,45]. SP activates MCs through specific receptors without degranulation and causes the infiltration of granulocytes through the synthesis of some cytokines such as TNF and IL-8 [46]. In addition, the neuropeptide nerve growth factor (NGF) and NT can activate MCs and participate in inflammatory processes [47]. In fact, activation of MCs, in some neuronal diseases, leads to the activation of NK1 receptors following an increase in vascular permeability [48] (Table 2). SP stimulation can cause focal inflammation in the hypothalamus and amygdala, with pathological symptoms in several neurological diseases [49]. Neuropeptides such as SP, CRH, and NT may have a synergistic inflammatory action through the activation of cytokines [50]. Therefore, SP is an important neuropeptide and neuromodulatory compound involved in neurogenic inflammation [51]. It is an activator of several immune cells, including macrophages and MCs, causing pro-inflammatory compounds including interleukins, chemokines and growth factors [31,52]. In the brain, SP is involved in the process of pain reception through the stimulation of the trigeminal nerve. In in vitro studies, SP can activate MCs to secrete pro-inflammatory mediators such as cytokines, chemokines, arachidonic acid products and proteases. All these compounds participate in the local and systemic inflammatory response [53,54]. In addition, SP induces vascular endothelial growth factor (VEGF) and IL-33 in a dose-dependent manner in MCs and acts synergistically with them in inflammatory responses [41,55]. The cytokine IL-33, also called “alarmin”, is generated and secreted by MCs and increases the ability of the SP to stimulate MCs to release VEGF, TNF, and IL-1 [56]. This effect of SP on VEGF and TNF production demonstrates a crosstalk between neuropeptides and pro-inflammatory cytokines [55,57]. Moreover, human MCs stimulated with SP and anti-IgE produce IL-33 which increases the release of IL-31, a cytokine involved in atopic dermatitis (AD) and transmitting itch diseases involving the CNS [58]. This demonstrates that SP is a potent pro-inflammatory neuropeptide that can activate and contribute to the secretion of certain pro-inflammatory cytokines [59]. In fact, serum elevations of SP and its analogue hemokine-1, along with serum levels of the cytokines TNF and IL-6, have been detected in inflammatory diseases including fibromyalgia [60]. Additionally, in mouse models, it has been observed that SP stimulates angiogenesis through the proliferation of endothelial cells, causing neurogenesis and peripheral inflammation [61]. SP performs its biological action by binding to tachykinin NK1 receptors located on the membrane of vascular endothelial cells, inducing inflammation, vascular permeability and edema [62]. SP mediates pain through the trigeminal nerve and activates MCs to produce inflammatory mediators including leukotrienes and prostaglandins [63]. In some neurological and psychiatric disorders such as depression, bipolar mood disorder and anxiety, where MCs are in contact with SP positive nerves, an increase in SP, TNF and VEGF is observed [64]. However, some neuropeptides, such as epinephrine, a neurotransmitter beta-receptor agonist, are capable of inhibiting TNF, histamine, and PGD2 released by activated MCs, an effect that impedes some diseases including asthma [65]. As early as 1948, Harris reported that the hypothalamus is an important connecting organ between the nervous and endocrine systems [66]. Information is generated directly from the nuclei of the hypothalamus to the Locus Coureuleus, the main center for the release of norepinephrine, and from here, an efferent pathway starts that proceeds directly to the adrenal medulla causing the release of catecholamines, including adrenaline, norepinephrine, and dopamine [67,68]. Catecholamines can interact with pro-inflammatory cytokines secreted after cognitive (stress) or non-cognitive (microorganisms) stimuli [69]. Circulating cytokines reach the CNS and bind to their receptors, exerting an inflammatory effect [70]. CRH acts through two receptors, corticotropin-releasing hormone receptor (CRHR)-1 [71] and CRHR-2 [72] which is subdivided into CRHR-2α and CRHR-2β [73]. In 1981, Vale et al. isolated and characterized CRH from the sheep hypothalamus. It is a very similar peptide to the human one and is widely expressed in the brain [74]. The hypothalamus secretes CRH, allowing the pituitary gland to release adreno-corticotrophic hormone (ACTH) which, at the level of the cortex of the adrenal glands, will allow the release of cortisol, an anti-inflammatory marker [75,76]. Cortisol and catecholamines produced by the adrenal gland act at an anti-inflammatory level by inhibiting pro-inflammatory cytokines such as IL-1, TNF and IL-6 [77]. The parvocellular neurons of the paraventricular nucleus are the major source of CRH in rats and humans [78]. This hormone is secreted and then transported to the anterior part of the pituitary gland [79]. In humans, CRH can also be found outside the CNS, such as in the adrenal medulla, stomach, placenta, pancreas, duodenum, and in some tumors [80]. The administration of CRH in vivo causes an elevation of ACTH and cortisol in plasma, with side effects depending on the administered dose [81]. Thus, CRH is secreted by the hypothalamus after antigen stimulation and activates the hypothalamic–pituitary–adrenal (HPA) axis, but it can also be released from nerves outside the CNS and produced by immune cells including MCs [82]. Immune cells such as MCs and other cells are interconnected to the CNS through the production of cytokines influencing the physiological behavior of the body [83]. CRH secretion increases during stress and may lead to hypercortisolism. Moreover, CRH can promote MC maturation and induces neurogenic inflammation [84]. In fact, the histamine produced by MCs increases CRH both at the protein level and by inducing mRNA [29,85]. MCs can produce and be activated by neuropeptides which include SP, CRH, NGF and neurotensin (NT), an effect that can be altered by cytokines [86] (Table 3). Some CNS diseases can lead to an increase in the expression of CRH-1 receptor in MCs [87], with an elevation of CRH levels and the generation of neurological disorders. In some neurological disorders, there may be an increase in MCs expressing the CRH-1 receptor with induction of inflammation [88,89]. The secretion of IL-1 and IL-6 by MCs also causes stimulation of the CRH that can further stimulate the release of VEGF [90] and PGE2α [91]. In 1973, Susan Leeman (today a leading researcher in our group) isolated NT for the first time. NT is a 13 amino acid peptide which plays the role of neuromodulator and neurotransmitter in the CNS [92]. There are four cell receptors that bind NT: NTSR 1, NTSR2 and the type 1 receptors Sortilin 1 (Sort 1) and SorLA [93]. The NTSR1, with high neuron affinity, and the NTSR2, with low activity, were discovered first and therefore they are the most studied [94]. NTSR1 is expressed more in neurons, while NTSR2 is poorly expressed, but these data still need to be confirmed [95]. NT regulates the digestive tract and cardiovascular system and is a mediator of neurological responses such as pain, psychosis, temperature regulation, sensitivity to ethanol, analgesia, etc. [96]. Some studies show that NT can act as an antipsychotic-induced dopamine against schizophrenia without modifying NTS1 receptors [97]. It has also been observed that low levels of NT in the thalamus lead to a stimulation of greater alcohol consumption [98]. NT is mostly found in the brain and gut where it becomes involved with inflammatory processes [99]. It induces hormone secretion from the anterior pituitary gland and when it is administered in mice, causes side effects such as antinociception and hypothermia [100]. NT secreted under stress acts synergistically with CRH to stimulate MCs, resulting in increased vascular permeability, generation of VEGF, and disruption of the blood–brain barrier (BBB) [101]. This tridecapeptide which impacts the brain and other organs is fundamental in some inflammatory processes [102]. In addition, NT induces the expression of CRHR-1 and CRH protein which stimulates MCs in allergic diseases [103]. In an interesting article, we reported that NT stimulates the gene expression and release of IL-1β and CXCL8 from cultured human microglia, underlining that the NT is a proinflammatory peptide [104] and therefore confirming that NT plays an important role in inflammation. Immune cells such as lymphocyte macrophages and MCs are activated by NT with secretion of inflammatory cytokines and B cell immunoglobulin production, an effect that emphasizes the crosstalk of NT with the immune system [105]. At the cellular level, NT increases calcium levels and the production of nitric acid, a pentavalent nitrogen oxyacid, with strong oxidizing power. NT is therefore a brain neurotransmitter that interacts with MCs, both in innate and acquired immunity, and has a synergistic action with CRH on the stimulation of MCs, activating a neuro-immune mechanism [106]. These effects, which play a stress-mediating role, were observed in vivo in rodents [107,108]. In fact, NT and CRH released in the brain mediate CNS-related inflammatory disorders, such as stress, psoriasis, and AD, where MCs play a crucial role [109]. MC activation by neurotransmitters can lead to the release of histamine and increases vascular permeability with the generation of headache [110]. There are several neuropeptides that can activate cerebral MCs that can produce pathological phenomena. For example, SP is capable of inducing itch due to the interaction of SP with neurokinin-1 receptor (NK1R) on neurons. NT binding its receptor NTR1 of the MC, stimulates the production of cytokines and chemokines through the activation of RAS, a signaling protein associated with the cell membrane, with phosphorylation of the Raf gene family which activates MEK 1/2 and ERK ½, which promote the transcription factor AP-1 in the nucleus and, consequently, the production of cytokines/chemokines [111,112] (Figure 3). Stress-induced NT can mediate neurogenic inflammation in SP-enhanced mice, causing activation and degranulation of MCs via the NK-1 receptor which induces, in turn, the upregulation of SCF or IL-4, important for proliferation of the MCs [113]. In conclusion, NT in the brain causes the activation and proliferation of microglia with brain inflammation, disruption of the blood–brain and the intestinal barrier, along with MC activation and the generation of pro-inflammatory cytokines with neuronal damage [114]. In the late 1970s, IL-1α and IL-1β were shown to be pro-inflammatory cytokines that we now know can drive inflammation of Th1 and Th17 cells [115]. Inflammatory neuropeptides stimulate IL-1 and other cytokines in the brain. For example, NT stimulates gene expression and secretion of IL-1β and the chemokine CXCL8 in cultured microglia [116]. The IL-1 family includes IL-1α, IL-1β, and other inflammatory cytokines such as IL-18, IL-33, IL-36a, IL-36b, and IL-36γ [117]. Later, other cytokines were discovered, but with anti-inflammatory activity, such as IL-1Ra, IL-37, and later IL-38 and the anti-receptor IL-36Ra. IL-37 is a member of the IL-1 family and is a human anti-inflammatory cytokine, which suppresses innate immunity, modulates acquired immunity, and functions in mice [118]. Five isoform splice variants (“a to e”) of IL-37 have been reported, of which “b” is the most studied. IL-37 is expressed in the nucleus as IL-1 and IL-33, but in contrast to these last two cytokines, IL-37 has anti-inflammatory power, dumping the innate immunity [119]. Activation of the TLR in macrophages leads to the production and secretion of the IL-37 precursor (pro-IL37), which is cleaved by caspase-1 to form mature IL-37. Some IL-37 is transferred into the nucleus, while another part, together with pro-IL-37, is transferred out of the cell, and all are biologically active [120]. In addition, it appears that extracellular proteases may influence pro-IL-37 to become more active. Once generated, IL-37 binds to the IL-18 receptor alpha chain (IL-18Rα), exercising the down-regulation of inflammation [121]. Human monocytes treated with various stimuli such as IL-1 or bacterial LPS are known to produce abundant pro-inflammatory cytokines, an effect enhanced in genetically IL-37 deficient monocytes [122]. These data suggest that IL-37 controls the generation of pro-inflammatory cytokines of the IL-1 family. Indeed, in experimental models such as rheumatoid arthritis, where mice are treated with human IL-37, inflammation is inhibited [123]. The IL-37 gene has only been identified in human cells, but not in mouse cells. However, accurate and sophisticated studies have allowed the generation of transgenic mice expressing human IL-37 (IL-37tg), allowing to better understand the functions and role of this cytokine in the inflammatory process [124]. In these studies, IL-37 confirmed its inflammation-suppressing power even in clinical experimental models [125]. In fact, in mice with inflammatory diseases, such as asthma or ulcerative colitis, treatment with IL-37 improved their pathological condition [126]. IL-37 not only suppresses inflammation and innate immunity, but also plays a regulatory role in acquired immunity by acting on the inhibition of antigen-stimulated T lymphocytes [127]. Thus, IL-37 is produced to protect the body’s tissues against pro-inflammatory stimuli [128]. A number of human cells, including immune cells (such as monocytes, macrophages, B cells, dendritic cells, etc.) express IL-37. Upon stimulation, immune cells treated with IL-37 in vitro produce less IL-1β, IL-6, and TNF [129]. In addition, the migration of inflammatory cells is also inhibited by IL-37, an effect that confirms its anti-inflammatory power. However, the inhibitory mechanisms of IL-37 still need to be clarified, although some authors have hypothesized that IL-37 inhibits mammalian target of rapamycin (mTOR) [130]. IL-37 is generated as a protective, anti-inflammatory effect in the CNS in patients with ischemic stroke and other inflammatory diseases [131]. Therefore, the inhibition of IL-1 family proinflammatory cytokines requires the IL-1 family decoy receptor (IL-1R8) [120]. In our recent studies, we reported that IL-37 plays a fundamental role in autism spectrum disorder where it enhances and inhibits NT secretion and gene expression of IL-1 and CXCL8 in microglia [104]. However, the mechanism of action of IL-37 is still unclear even though it is thought that the anti-inflammatory molecule SMAD family member 3 (SMAD3) of the cytokine TGF is involved in the nucleus [127,132]. In light of these studies, we can certainly say that IL-37 opens up therapeutic hope for acute and chronic inflammatory diseases, including autoimmune disorders [133]. IL-1 is the endogenous pyrogen mediator of fever, with activating effects on CNS neurons and therefore is crucial in neurophysiological functions [134]. Increased IL-1 in the brain may result in a number of biological effects, including the elevation of inflammatory mediators and the inhibition of gamma-aminobutyric acid (GABA) receptor responses and calcium fluxes [135]. The IL-1 family member genes include pro-inflammatory and anti-inflammatory molecules (Figure 4). The last two cytokines discovered, IL-37 and IL-38, are anti-inflammatory and are located on chromosome 2. IL-38 is thought to be an ancestral gene intended to counteract the pro-inflammatory effects of IL-1 [136]. In humans, IL-38 is detected in several organs such as the tonsils, skin, fetal liver, heart, and placenta, but in future studies, it will certainly be detected in many other organs [137]. The anti-inflammatory effect of IL-38 is homologous with two anti-receptors, IL-36Ra (approximately 40%) and IL-1Ra (approximately 40%), sharing the anti-inflammatory effect [138]. To be active, IL-38 must be processed, but at the moment, the protease(s) responsible for the generation of its mature form are unknown. IL-38 has similar anti-inflammatory potency to IL-37 and IL-36Ra, and works best at low concentrations, while at higher concentrations it may have opposite effects [139]. In vitro studies demonstrated that IL-38 is capable of inhibiting TNF and IL-1 in LPS stimulated THP-1 cells. Moreover, it has been shown that IL-38 used in the truncated form is capable of inhibiting TNF and IL-1 in LPS stimulated THP-1 cells, whereas when IL-38 is used at full length, it can have a stimulatory effect, especially on IL-6. In certain fungal infections, such as Candida albicans, IL-38 suppresses TH17 lymphocytes and inhibits IL-17A, a pro-inflammatory cytokine that is produced in certain immune reactions [140]. The same effect occurred after treatment with IL-36Ra and IL-1Ra [141]. IL-17 comprises six subgroups ranging from IL-17A to IL-17F, and among these, the most studied cytokine is IL-17A [142]. Immune cells and glial cells of the CNS express IL-17A receptors which, once activated, can mediate inflammatory brain disorders [143]. IL-17 generated by γδ T lymphocytes is a cytokine with pro-inflammatory potential that can act synergistically on astrocytes with other cytokines such as TNF, causing the secretion of CXCL1 which recruits neutrophils to the inflammatory site [144]. In addition, in some cases, IL-17 expression may be due to bacterial infections or parasitic infestations which can activate TLR2. In these pathological conditions, treatment with IL-38 could have a therapeutic role [145]. Therefore, it is deduced that the activation of IL-17 in the CNS is very important in inflammatory pathologies [146]. However, in many inflammatory brain disorders where IL-17 is involved, the mechanism of action or whether IL-17 directly causes inflammation is not clear yet, and therefore future studies are needed to clarify this dilemma [147]. In light of the results that have been published so far, IL-38 has been shown to play a regulatory role in rheumatic diseases such as rheumatoid arthritis and psoriasis, which are IL-1-mediated diseases [148]. Since neuropeptides such as CRH, SP, and others can activate microglia leading to secretion of the proinflammatory cytokines IL-1β, IL-6 and TNF [60], it is pertinent to suppose that inhibiting IL-1 by IL-38 can have a therapeutic effect in inflammatory disorders mediated by IL-1 pro-inflammatory members [138]. A future use of anti-inflammatory cytokines could replace or be administered in combination with the use of corticosteroids, which in suppressing inflammation cause serious side effects such as immunosuppression. In this article, we investigated the role of the neuropeptide substance P, CRH, and neurotensin in cytokine MC activation. We reported that these neuropeptides stimulate IL-1, IL-6, and TNF. The inhibition of IL-1 by IL-37 or IL-38 could create new therapeutic possibilities and is a new concept that has not yet been reported in the literature for MCs. MCs, along with macrophages, lymphocytes, endothelial cells, and others, are inflammatory cells that produce IL-1. This cytokine induces other pro-inflammatory cytokines, such as TNF, and possesses an autocrine action by stimulating itself. This effect triggers a cytokine storm with a drastic inflammatory response. Inhibiting IL-1 with IL-37 or IL-38 could be a new therapeutic strategy. However, IL-37 and IL-38 have only been used in research and are not yet available for treatment. Therefore, before using these inhibitory cytokines, certain points need to be clarified such as the concentrations to be used in humans, possible side effects, immunosuppression, and perishability with in vivo treatment.

PMC10002996

Yin Ping Wong,Geok Chin Tan,T. Yee Khong

SARS-CoV-2 Transplacental Transmission: A Rare Occurrence? An Overview of the Protective Role of the Placenta

25-02-2023

COVID-19,maternal–fetal interface,pregnancy,SARS-CoV-2,transplacental,vertical transmission

The outbreak of the coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global public health crisis, causing substantial concern especially to the pregnant population. Pregnant women infected with SARS-CoV-2 are at greater risk of devastating pregnancy complications such as premature delivery and stillbirth. Irrespective of the emerging reported cases of neonatal COVID-19, reassuringly, confirmatory evidence of vertical transmission is still lacking. The protective role of the placenta in limiting in utero spread of virus to the developing fetus is intriguing. The short- and long-term impact of maternal COVID-19 infection in the newborn remains an unresolved question. In this review, we explore the recent evidence of SARS-CoV-2 vertical transmission, cell-entry pathways, placental responses towards SARS-CoV-2 infection, and its potential effects on the offspring. We further discuss how the placenta serves as a defensive front against SARS-CoV-2 by exerting various cellular and molecular defense pathways. A better understanding of the placental barrier, immune defense, and modulation strategies involved in restricting transplacental transmission may provide valuable insights for future development of antiviral and immunomodulatory therapies to improve pregnancy outcomes.

SARS-CoV-2 Transplacental Transmission: A Rare Occurrence? An Overview of the Protective Role of the Placenta The outbreak of the coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global public health crisis, causing substantial concern especially to the pregnant population. Pregnant women infected with SARS-CoV-2 are at greater risk of devastating pregnancy complications such as premature delivery and stillbirth. Irrespective of the emerging reported cases of neonatal COVID-19, reassuringly, confirmatory evidence of vertical transmission is still lacking. The protective role of the placenta in limiting in utero spread of virus to the developing fetus is intriguing. The short- and long-term impact of maternal COVID-19 infection in the newborn remains an unresolved question. In this review, we explore the recent evidence of SARS-CoV-2 vertical transmission, cell-entry pathways, placental responses towards SARS-CoV-2 infection, and its potential effects on the offspring. We further discuss how the placenta serves as a defensive front against SARS-CoV-2 by exerting various cellular and molecular defense pathways. A better understanding of the placental barrier, immune defense, and modulation strategies involved in restricting transplacental transmission may provide valuable insights for future development of antiviral and immunomodulatory therapies to improve pregnancy outcomes. Coronavirus disease 2019 (COVID-19), a viral respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization (WHO) on 11 March 2020 [1]. As of 19 January 2023, there have been 663,248,631 confirmed cases of COVID-19, including 6,709,387 deaths worldwide [2]. Accumulating evidence supports that the SARS-CoV-2 virus is not merely a respiratory virus per se but can potentially affect other organ systems including the placenta. The notion of pregnancy as an altered state of immune suppression is well documented. Questions have been raised in regard to the safety and impact of SARS-CoV-2 infection on both the mothers and their unborn babies. Pregnant mothers infected with SARS-CoV-2 may be asymptomatic or symptomatic. Those who are symptomatic appear to be at a higher risk for developing severe sequelae of COVID-19 such as an increasing need for mechanical ventilation, ventilatory support, and death, compared with reproductive age-matched nonpregnant females [3]. Emerging evidence has shown that the severity of COVID-19 disease in pregnancy is associated with maternal comorbidities including gestational hypertension, diabetes mellitus, obesity, and advanced maternal age [3,4]. Like certain viral infections in pregnancies, pregnant women infected with SARS-CoV-2 are at greater risk of pregnancy complications such as premature birth and possibly cesarean delivery, which is likely related to severe maternal illness [3]. Irrespective of the emerging reported cases of neonatal COVID-19, reassuringly, vertical transmission is rare [5,6]. The majority of the neonates born to COVID-19-positive mothers were spared from getting infected, despite the SARS-CoV-2 spike protein being detected in the placental villi. Congenital viral syndromes following maternal COVID-19 infection have not yet been reported thus far [7]. A successful pregnancy is dependent on a healthy and functioning placenta. The protective role of the placenta in limiting in utero spread of the virus to the developing fetus is intriguing. In this review, we explore recent evidence of transplacental SARS-CoV-2 viral transmission, transmission mechanics, and placental responses toward SARS-CoV-2 infection. A mechanistic description of the placental development, maternal–fetal placental interface, and innate mechanisms employed by the placenta which serves as a defensive front against SARS-CoV-2 by exerting various cellular and molecular defense pathways are also discussed. Vertical transmission, also known as maternal-to-child transmission of SARS-CoV-2 can theoretically occur in different moments, either in utero (transplacental/congenital), intrapartum, or in the early postnatal period [8]. In utero transmission can occur transplacentally through the hematogenous route, or more rarely the ascending route from a colonized maternal genital tract. Maternal systemic viral infection may result in viremia, potentially cross the maternal–placental interface to gain access to the fetal vessels and cause infection. Unequivocal diagnosis of SARS-CoV-2 transplacental/congenital infection requires the detection of viral RNAs in the placenta tissues, fetal tissues, umbilical cord blood, and amniotic fluid [8,9] by nucleic acid amplification tests. Where a reverse-transcriptase polymerase chain reaction (RT-PCR) test to quantify viral RNA is not readily available, immunohistochemistry or an in situ hybridization technique to detect viral nucleocapsid (N) and spike (S) proteins or electron microscopy in the placental tissue may be used. In utero transmission of respiratory viruses, including SARS-CoV-2, in general are considered to be infrequent (estimated 7.7–21%) [10], except for only a few reported in utero transmission cases by the influenza virus [5,6,11]. A few studies have successfully demonstrated SARS-CoV-2 placental infection by immunohistochemistry, in situ hybridization, RT-PCR, and transmission electron microscopy techniques [12,13,14,15]. SARS-CoV-2 viral proteins, RNA, and particles were detected mostly in the syncytiotrophoblasts. Infection of other placental compartments including the decidua, cytotrophoblasts, and maternal and fetal vascular endothelial cells were also previously reported [10,12,15]. Accurate estimation of SARS-CoV-2 placental infections, however, is challenging due to the lack of standardized diagnostic criteria and consistent data collection, such as duration of maternal COVID-19 infection and viral loads [14]. Viremia due to SARS-CoV-2, although rare, appears to be associated with disease severity. Intriguingly, high SARS-CoV-2 viral load was detected in the maternal blood and the placenta from an asymptomatic mother [16]. Larger scale studies are needed to draw a definite conclusion on this issue. Intrapartum transmission occurs during delivery and childbirth. Shedding of SARS-CoV-2 viral RNA in the feces and vaginal secretions of infected individuals, although rare, does occur. Fecal and blood contamination of the vaginal canal during the birth process could potentially expose the neonates’ oro/nasopharynx to the pathogen [17]. Nonetheless, several reports also highlighted that there was insufficient evidence to support that cesarean section was better than vaginal delivery in preventing intrapartum transmission [18,19]. Likewise, SARS-CoV-2 can be transmitted during the postpartum period through breastfeeding, direct contact to infected formites, and exposure to respiratory or other infectious maternal secretions. Data are conflicting on whether SARS-CoV-2 is present in the breast milk of infected mothers [20]; this requires further investigations. A recent published systematic review by Musa et al., (2021) on 69 systematic reviews reported on 54,413 pregnancies infected with SARS-CoV-2 resulting in more than 30,840 neonates delivered by the infected mothers [21]. Of these, over 800 neonates were tested positive for throat swab SARS-CoV-2 RT-PCR, indicating the plausibility of SARS-CoV-2 vertical transmission from COVID-19-infected mothers. Moreover, the elevated SARS-CoV-2 IgM levels in the neonates could further support the likelihood of in utero transmission [22,23], but this is also contentious [24]. Raschetti et al., (2020) revealed in their systematic review and meta-analysis that as high as 70% of mother-to-child transmission of SARS-CoV-2 during pregnancy were likely via environmental exposure (postpartum transmission). Of the 9% confirmed vertically transmitted cases, reassuringly, only 5.7% and 3.3% were transmitted via transplacental route and intrapartum, respectively [25]. Similarly, Allotey et al., (2022) in their recent systematic review revealed that less than 2% of the babies born to mothers with SARS-CoV-2 infection tested positive for this virus via RT-PCR; the rates were even lower (1%) when restricted to babies with in utero or intrapartum exposure to the virus. The authors also reported the severity of maternal COVID-19 infection appeared to be correlated with SARS-CoV-2 positivity in the offspring [26]. Other than humans, a myriad of animal species, including dogs, cats, otters, gorillas, deer, hamsters, mink, and ferrets have been demonstrated to be susceptible to SARS-CoV-2 via natural and/or experimental infections [27]. Except for a recent report on SARS-CoV-2 experimental infection in five adult pregnant white deer with 12 fetuses, SARS-CoV-2 in pregnant animal models are generally lacking. In this report, one of the two principal SARS-CoV-2-inoculated pregnant white deer was euthanized at an acute stage of infection (day 4), and two of her three fetuses were positive for SARS-CoV-2 RNA in at least one tissue organ. Interestingly, none of the fetuses (n = 9) collected on day 18 post COVID-19 infection had detectable levels of SARS-CoV-2 RNA, although half of the fetuses were non-viable [28]. Viruses are obligate intracellular parasites that depend solely on hosts for survival and generate new infectious particles. Of the myriad viruses that infect human beings, only a handful can cross the placental barrier, where the resulting infections can cause fetal growth restriction, preterm delivery, or birth defects. These viruses include rubella virus, herpes simplex virus, human cytomegalovirus, Zika virus, and possibly the SARS-CoV-2 virus. Transmission of virus from the mother to her fetus in utero can occur either via maternal circulation or by ascending from the lower genital tract [29]. Maternal viremia is a prerequisite for maternal–fetal transmission by transplacental route. From maternal circulation, these pathogens can be transmitted to placental trophoblasts from infected maternal blood macrophages/vascular endothelium or through paracellular routes to fetal capillaries [30,31]. The underlying mechanisms of how these viruses can circumvent the placental defense barrier and get to the fetus has been a puzzle. Generally, viruses need to stay within the target cell in order to survive. The exact mechanism of how SARS-CoV-2 transplacental transmission occurs however is still poorly understood. Generally, there are two main mechanisms employed by the viruses in order to gain entry into the host cell: (i) through direct fusion with the cell plasma membrane via attachment to the host cell-surface receptors or (ii) through an internalization process into endosomes and further release into the cytoplasm [32]. The tropism of viruses for the decidua and placenta depends largely on the expression of specific viral entry receptors in these tissues as well as on the maternal immune response. Consequently, infection can result in disease outcomes ranging from no effect to pregnancy loss by miscarriage or to fetal infection with subsequent congenital viral syndromes [33]. The presence of specific receptors on the plasma membrane of placental trophoblasts is a prerequisite for the entry of many viruses. It is worth noting that SARS-CoV-2 virus infects the uterine vasculature, and spreads to extravillous trophoblasts. Spike glycoprotein of SARS-CoV-2 virus interacts with the host cell surface receptor—angiotensin converting enzyme 2 (hACE2) through the receptor–binding domain. This is followed by conformational changes (priming and activation) of the spike protein by host cell proteases (such as furin, cathepsins, and transmembrane serine protease (TMPRSS-2 and -4)), to allow fusion with the host cell membrane and subsequent entry into the cytoplasm [34]. Although ACE2 receptor and TMPRSS2 are identified in placental trophoblasts, there are conflicting data with regards to the extent of their co-expression in the same cell types and whether there is differential expression by gestational age [35]. Huang et al., (2022) in their single cell RNA sequence (scRNA-Seq) analysis revealed that ACE2 receptor was similarly expressed between the lungs and the placenta, whereas TMPRSS2 was almost absent in the placenta across different stages of pregnancy. ACE2 and TMPRSS2 co-expression was seen in very few placental trophoblastic cells [36]. This was further supported by the analysis of the Human Protein Atlas, Genome-based Tissue Expression, and FANTOM5 CAGE datasets which concluded that first trimester placental tissues expressed abundance of ACE2 protein despite low mRNA levels [37]. A recent study investigated the gene expression alteration in term placentas from COVID-19 pregnant women compared to uninfected women [38]. Through robust transcriptomic analysis (microarray and scRNA-Seq) and in silico predictions of viral–host protein–protein interactions, studies revealed that almost all villous trophoblast cells, placental and trophectoderm cells express high levels of the potential non-canonical cell-entry mediators such as human dipeptidylpeptidase-4 (DPP4), cathepsin-L (CTSL) and CD147 [39,40] throughout pregnancy, and may serve as candidate binding targets of the SARS-CoV-2 spike protein. First trimester ACE2+ placental trophoblast cells and second trimester ACE2+ extravillous trophoblasts were reported to co-express CD147 and CTSL [41]. A sc-RNA expression map identified a list of 28 SARS-CoV-2 and coronavirus-associated receptors and factors (SCARFs) that may facilitate or restrict SARS-CoV-2 entry into host cells. A small population of cytotrophoblasts were found to co-express ACE2 with TMPRSS2, CD147, and/or DPP4 but exhibit very low level of interferon-induced transmembrane protein (IFITM1-3) and lymphocyte antigen 6E (LY6E) restriction factors, which could predispose a subset of the trophoblast cells to SARS-CoV-2 infection. This is consistent with the current opinion that vertical transmission from infected mother to fetus is plausible but probably rare [42]. In addition, neurolipin 1 (NRP1) is also a recently discovered alternative receptor for SARS-CoV-2 viral entry in the placenta [43]. Changes in DAAM1 and PAICS gene expressions in the human placenta that encode for proteins predicted to potentially interact with SARS-CoV-2 viral proteins during pregnancy were also identified [40]. Leucine-rich repeat-containing protein 15 (LRRC15) is a novel toll-like receptor-related cell surface receptor recently discovered in the placenta, skin, lymphatics, and tissue fibroblasts. It is believed it could control viral load with antiviral and antifibrotic abilities. Unlike the ACE2 receptor, it does not act as an entry receptor for SARS-CoV-2. Mechanistically, it binds and sequesters SARS-CoV-2 virus away from ACE+ cells, and helps to suppress infection [44]. Notably, a previous study identified LRRC15 as one of the 10 genes that was upregulated in early onset severe preeclampsia compared to the control group [45]. Via infecting the maternal immune cells, SARS-CoV-2 virions could infiltrate the placenta and transmit the virus to the fetal cells (cell-to-cell transmission) [34]. Transcytosis is another proposed mechanism to gain access to trophoblasts, as has been shown for human immunodeficiency virus (HIV) [46]. It involves movement of molecules between two cellular compartments or environments. Egloff et al., (2020) proposed that primary trophoblasts were able to transcytose opsonized or free infectious SARS-CoV-2 viral particles in an endosome-dependent manner [47]. It was also proposed that alterations in the maternal–fetal barrier due to any insults such as inflammation and ischemia could allow transmigration of SARS-CoV-2 virions throughout the placenta into the fetal environment [48]. Additional clinical and experimental studies, however, are needed to confirm these mechanisms. Following successful infection, viruses may hsve a negative impact on pregnancy outcomes through various proposed pathogenic processes, which include modulation of regulated cell death (by apoptosis, necroptosis, pyroptosis, and novel ferroptosis) and induce excessive inflammatory and repair responses. Ferroptosis, a unique form of non-apoptotic, regulated lipotoxic cell death, has been recently implicated as a culprit for multiorgan damage in COVID-19-infected individuals. It is characterized by disproportionate iron-dependent hydroxy-peroxidation of polyunsaturated fatty acid (PUFA)-containing phospholipids in the cell membranes and a depletion of lipid peroxidation repair capacity [49]. Invading SARS-CoV-2 virus may cause cytotoxic effects to the host cells. Influx of iron following SARS-CoV-2 resulted in iron overload in the infected host cells. Iron oxidizes lipids in the Fenton reaction, a hallmark of ferroptosis which generates massive lipid reactive oxygen species (ROS) causing cell membrane damage. Apoptosis can be induced via the extrinsic death receptor pathway and intrinsic mitochondrial pathways. Apoptotic cell death plays a critical role in host defense by effectively limiting viral expansion [50]. SARS-CoV-2-encoded accessory proteins, including ORF3a and ORF7b, can trigger apoptosis in cells by caspase-8 activation independent of BCL-2 expression (via the extrinsic apoptotic pathway) in the lung epithelial cells [51]. This process of apoptosis has been observed in other cell types including the placenta. Parcial et al., (2022) recently revealed that apoptotic-related changes were apparent in SARS-CoV-2-infected syncytiotrophoblasts and cytotrophoblasts ultrastructurally [52]. As a corollary, placental integrity and function can be compromised, instigating obstetric complications like preterm birth, pre-eclampsia, and fetal growth restriction [49]. Pathological alteration in the placenta following maternal COVID-19 infection may be attributed to the direct and indirect impact of the SARS-CoV-2 virus on the placenta. No one histopathological signature was identified in the placentas of SARS-CoV-2-infected pregnancies [53]. Apoptosis of the infected syncytiotrophoblast is recently proposed to be associated with localized SARS-CoV-2 placentitis, that is manifested histologically by a triad of trophoblast cell death, histiocyte-predominant intervillous inflammatory infiltrates, and variable perivillous fibrin deposition [54]. Fibrin deposition is a repair mechanism [55] and, when excessive, can declare as massive perivillous fibrin deposition, whereas an excessive inflammatory response can result in massive chronic intervillositis (chronic histiocytic intervillositis) [13,56]. Accumulating data suggest that SARS-CoV-2 placentitis was associated with an elevated risk of vertical transmission and adverse pregnancy outcomes [57,58,59]. COVID-19 infection may also result in maternal hypoxia leading to reduction in placental blood flow, which could be manifested indirectly in placentas as maternal vascular malperfusion (MVM). MVM features, including accelerated villous maturation, distal villous hypoplasia, villous infarction, and decidual arteriopathy were reported in SARS-CoV-2-infected placentas [13,56,60,61]. Other histopathological patterns that have been previously described in the setting of SARS-CoV-2 maternal infection include fetal vascular malperfusion and inflammatory reaction patterns such as chronic villitis, chronic deciduitis, and acute and chronic chorioamnionitis [13,56,60,61]. Notably, up to 18% of these pregnancies did not show any placental abnormalities [61]. Placental histomorphological alteration in relation to different variants of SARS-CoV-2, immunization status, timing of infection to delivery, and the rate of vertical transmission may be an area of research interest awaiting to be explored further. The placenta is the first and the largest chimeric organ that develops from the blastocyst following conception, made of both the fetal and maternal tissues. Its main functions are to nurture and provide nutrients to support the development of the conceptus, besides serving as physical and functional barriers against intruding pathogens and protection from maternal immune rejection to the semi-allogenic fetus [62]. Understanding the unique architecture and function of the placenta will provide a framework to address the key physical and immunomodulatory defense pathways employed by the placenta against SARS-CoV-2 transplacental infection. The human placenta originates from the trophectoderm, the outermost layer of the blastocyst [62]. Following implantation of the embryo into the maternal endometrium (decidua), the trophectoderm differentiates into the first trophoblast lineages: early mononuclear cytotrophoblasts and the highly invasive primitive syncytium at day 8 post-conception. The latter further expands and invades into the maternal decidua, forming an expanding syncytiotrophoblastic mass. At day 9 post-conception, a system of confluent vacuoles (lacunae) appears within the syncytiotrophoblastic mass. Uteroplacental circulation is established with the formation of blood-filled lacunae following the breaching of syncytiotrophoblasts into maternal uterine capillaries at around day 12 [63]. Morphogenesis of placental chorionic villi commences at around day 10 post-conception. Rows of actively proliferating cell columns consisting of mononuclear cytotrophoblasts break through the expanding syncytiotrophoblastic mass forming primary chorionic villi [64,65]. Primary villi are transformed into secondary and subsequently tertiary villi upon migration of extraembryonic mesodermal cells forming the villous core which are then vascularized. These villi are covered by a non-proliferative and multinucleated syncytiotrophoblasts that are generated by cellular fusion of the inner progenitor villous cytotrophoblast layer. As the pregnancy advances, cytotrophoblast cells become more sparse within the placental villi. The syncytiotrophoblasts form the only continuous epithelial layer of the chorionic villi, separating the maternal intervillous space and the fetal capillary endothelium which constitute the key interface between the mother and her fetus [66]. Notably, the human placenta is a hemochorial tissue in which the villous syncytiotrophoblast layer is in direct contact with the maternal blood; the syncytiotrophoblasts, therefore, serve as the foremost barrier against hematogenous spread of infectious pathogens [67]. Besides formation of floating villi, at day 15 post-conception, columns of proliferating cytotrophoblasts continue to expand and differentiate into extravillous trophoblast (EVT). These cells migrate from the villous tips, invade into the base of the implantation site, and anchor the placenta to the maternal decidua [68]. In addition, they invade into the wall of uterine spiral arteries resulting in vascular remodeling and subsequent transformation of these vessels into wide, low resistance conduits [69]. The placental (fetal) vasculature continues to undergo extensive expansion within the villous mesenchyme as a result of branching vasculogenesis in the late first and second trimester. As it expands, the fetal capillaries of the terminal villous core bulge against thin attenuated syncytiotrophoblasts forming vasculosyncytial membranes towards the end of pregnancy, to decrease maternal–fetal diffusion distance and thereby maximizing oxygen delivery, nutrient transport, and waste exchange with the fetus [70,71]. Failure of these processes at any stage of development could lead to placental insufficiency, compromising fetal growth and development [72,73,74,75]. The core of the chorionic villi contains several different cell types, such as Hofbauer cells (fetal macrophages), fetal endothelial cells, fibroblasts, and mesenchymal stem cells. The Hofbauer cells are found as early as day 18 post-conception and remain until term [76,77]. These innate immune cells together with fetal endothelial cells act as additional barriers to infection, which must be traversed prior to reaching fetal circulation. The maternal–fetal interface is the direct point of contact between the mother and her fetus and governs the fetal development, regulates the maternal immune system, and safeguards the fetus from pathogens [29]. It is composed of both the maternal and fetal tissues and consists of multiple cell types. The maternal side consists of decidual stromal cells, and a wide range of decidual immune cells such as natural killer (NK) cells, macrophages, T and B lymphocytes, and dendritic cells. Decidual NK cells (70%) and macrophages (20%) are the major immune cell population at the maternal–fetal interface. As well as being engaged in immunosurveillance, decidual NK cells are mainly responsible for immune tolerance to the fetus, uterine spiral artery remodeling, and EVT cell invasion [78]. The fetal side is made of placental chorionic villus, formed by a mesenchymal core containing fetal blood vessels and Hofbauer cells, surrounded by inner villous cytotrophoblasts and outer multinucleated syncytiotrophoblasts, an epithelial covering that is in direct contact with maternal circulation [29]. Hofbauer cells can be found in villous stroma as early as three weeks post conception and are present in all stages of gestation. They are presumed to play diverse roles: they not only serve as immune cells, but are also involved in promoting and regulating placental morphogenesis and angiogenesis [79]. In addition, the paucity of toll-like receptors (TLRs) on syncytiotrophoblast confers extra syncytial resistance to infection. TLRs are the key player in activating the innate immune system that recognizes pathogen-associated immunostimulants, including peptidoglycan and lipopolysaccharide. Interestingly, TLRs are temporally expressed throughout the pregnancy. The syncytiotrophoblast layer is negative for both TLR-2 and TLR-4 in the first trimester placenta, in contrast to term placenta where TLR-2 and TLR-4 are highly expressed [80]. The lack of TLR expression by syncytiotrophoblast in early pregnancy allows placental tissues to respond only to a microbe that has penetrated through this outer layer; in other words, a pathogen can only pose a threat to the fetus if the TLR-negative syncytiotrophoblast layer is breached. On the contrary, the large apical surface of syncytiotrophoblast (12–14 m2) at term increases the probability of recognizing hostile microorganisms in maternal blood through TLRs [81]. The intrinsic defense of the placenta is entrenched in its unique microarchitecture. The outermost syncytiotrophoblast cells form a fused multinucleated cell layer, lacking intercellular gap junctions that can be exploited by microorganisms through intercellular unions [82]. Syncytiotrophoblast has an unusually enriched actin cytoskeletal network that contributes to its elasticity. This cytoskeletal organization helps create a shielding brush border on its apical surface that may impede pathogen adhesion, and at the same time resists physical deformations essential for pathogen invasion [66,83,84]. Additionally, caveolins play a vital role in endocytosis and transcytosis allowing entry of some viruses into host cells. They then trigger the caveolin-1 protein system, initiate inflammatory reaction by triggering the release of cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) through the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), leading to cell damage. Due to the low or near absence of caveolin expression in syncytiotrophoblasts, it may interfere with the success of viral transmission, including SARS-CoV-2 virus [82]. The role of trophoblast basement membrane that separates cytotrophoblasts from the villous stromal core cannot be overemphasized, as it represents an additional physical barrier to hinder effective transmission of microorganisms. The placenta secretes antimicrobial components that target a wide range of viruses. Interferons (IFNs) are key cytokines involved in innate host defense against pathogens, particularly RNA viruses, DNA viruses, intracellular bacteria, and parasites [85]. There are three types of IFNs namely type I IFNs (including IFN-α, β, ε, τ, and δ), type II IFN (IFN-γ) and type III IFNs (IFN-λ1, λ2, λ3, and λ4). While type I IFNs function in a broad systemic manner, type III IFNs control infection locally restricted to barrier surfaces including the maternal–fetal interface, blood-brain barrier, gastrointestinal, and respiratory epithelial surfaces. Growing evidence suggests that type III IFNs are powerful placental gestational-age dependent antiviral proteins [86,87]. Unlike in other barrier cell types, type III IFNs are constitutively released from human trophoblasts in the absence of viral infections, without the need to undergo canonical pattern-recognition receptor (PRR)-mediated innate immune signaling pathways. Bayer et al., (2016) discovered that primary human trophoblast cells isolated from full term placentas protect placental and non-placental cells from Zika virus infection through the release of type III IFN, which functions in a paracrine and autocrine manner [88]. Likewise in murine pregnancy, placentas lacking functional type III IFN signaling demonstrated a higher rate of Zika virus vertical transmission and were associated with fetal demise and/or congenital malformations [89]. Pregnant women contracted with SARS-CoV-2 were found to have high type III IFN cytokine levels, and levels significantly increased with disease severity. It is postulated that the high level of type III IFN could be one of the possible mechanisms protecting the fetus against SARS-CoV-2 transplacental infection, although this warrants further study [90]. Similar to IFNs, NF-κB is a transcription factor that regulates inflammatory response by controlling genes that (1) are involved in the recruitment, activation, and differentiation of innate immune cells and inflammatory T cells; (2) participate in inflammasome activation; and (3) encode cytokines including interleukin 1β (IL-1β), IL-6, and tumor necrosis factor α (TNF-α) and chemokines such as IL-8, C–C motif chemokine ligand 2 (CCL2), and C–X–C motif chemokine 10 (CXCL10) [91]. NF-kB is tightly regulated in pregnancy as it plays a role in the onset of labor. Suppression of NF-κB in T cells throughout pregnancy is critical to maintain a favorable cytokine environment that is essential for the success of a pregnancy. NF-κB is downregulated in the first trimester decidua that may contribute to the immunosuppressive state during pregnancy. [92]. NF-κB has been shown to be elevated in a dose-dependent manner in response to SARS-CoV-2 viral infection. It has a pivotal role in cytokine storm syndrome, which is linked to a greater severity in COVID-19-related symptoms and could potentially serve as an attractive target in COVID-19 therapeutics [93]. Inflammatory response is a double-edged sword. These responses are crucial for protecting the developing fetus from pathogen intrusion, but at the same time, inappropriate or dysregulated expression of pro-inflammatory cytokines and IFNs can seriously disrupt placental and fetal development, leading to birth defects and pregnancy complications [90]. Placental trophoblasts produce and release high levels of exosomes. Exosomes are regarded as small cargo vehicles that serve to transfer nucleic acids, proteins, lipids, and other biomolecules to maternal, fetal, or placental cells. Exosomes are enriched in microRNAs (miRNAs). MiRNAs are small endogenous non-coding, single-stranded RNA that post-transcriptionally regulate the expression of a variety of target genes. MiRNAs are approximately 22 nucleotides in length and possess a longer half-life and stability that is 10 times stronger than mRNAs. They govern gene expression by mRNA degradation or by translational repression, depending upon their 3′-untranslated region (UTR) complementarity [94,95]. They serve as critical regulators in various cellular biological processes including cell proliferation, differentiation, angiogenesis, immune cell development, and apoptosis [96]. By far, more than 2000 mature miRNAs have been discovered in the human genome, among which over 600 miRNAs are identified in the human placenta [97]. A high proportion of placental-derived miRNAs originate from a large miRNA cluster located on chromosome 19 (termed chromosome 19 miRNA cluster (C19MC). C19MC contains 56 highly homologous miRNA genes within a 100 kb genomic region, and is exclusively expressed in human trophoblasts, embryonic stem cells, and some cancer cells [98]. Placental-derived miRNAs are released into the maternal circulation through encapsulation into the exosomes, and transfer their contents into other cells, mediating tri-directional communication between the mother, the placenta, and her fetus. Studies identified at least three members of the C19MC family (miR517-3p, miR516b-5p, miR512-3p) that exhibit potent antiviral properties against RNA and DNA viruses [99]. These trophoblast-derived exosomes and C19MC-associated miRNAs attenuate viral replication by robustly inducing autophagy, conferring viral resistance to nonplacental recipient cells in autocrine and paracrine manners [99]. In addition to the C19MC family, using a bioinformatic approach, Khan et al., (2020) identified three other host miRNAs (miR-17-5p, miR-20b-5p, and miR-323a-5p) that could target SARS-CoV-2. However, the authors acknowledged that the virus may mutate; hence, the host miRNAs may change according to the new binding sites. Furthermore, the possibility of host genomic variations may also alter the miRNA binding sites [100]. Taken together, these suggest that the miRNAs might vary in different individuals depending on host genome and types of SARS-CoV-2 variants. Interestingly, RNA viruses can create their own miRNAs which may modulate host response to the virus, by facilitating viral replication, and modulating cytokines. A study of 15 SARS-CoV-2 infected pregnant women compared to six control uninfected pregnant women identified two groups of miRNAs that were upregulated in the blood and placenta, that is, (1) seven antiviral miRNAs (miR-21, miR-23b, miR-28, miR-29a, miR-29c, miR-98, miR-326) and (2) six immunomodulatory miRNAs (miR-17, miR-92, miR-146, miR-150, miR-155, miR-223) [101]. They found that the miR-29 family has the largest number of interaction sites with SARS-CoV-2 transcripts. Notably, miR-21 was also found to be upregulated in the placentas of preeclampsia patients [102]; this is similar to the histological findings of hypertensive-like changes of the placenta in SARS-CoV-2 infected pregnant women [13]. In the case of SARS-CoV-2 virus, recent studies have suggested five plausible mechanisms employed by the host miRNAs to tune down SARS-CoV-2 infection. These include (1) binding of host cell miRNA to viral genome by translational repression or mRNA degradation and modulating viral replication; (2) regulation of host innate and adaptive immune response via modulating anti-inflammatory cytokine genes (IL-10 and TGF-1β); (3) downregulation of the expression of proinflammatory cytokine genes (IL-1β, IL-6, and TNF-α); (4) posttranscriptional regulation of the expression of ACE2 receptor and TMPRSS2; (5) interfering with SARS-CoV-2 cell entry by downregulation of ACE2 receptor and TMPRSS2 gene expression; and (6) SARS-CoV-2-derived RNA transcripts acting as competitive endogenous RNAs that may attenuate host cell miRNA expression [103,104]. Comprehensive reviews on the role of host miRNAs against SARS-CoV-2 infection were previously published [103,104]. Further investigations will provide more evidence on the antiviral properties of miRNAs and may help to create a new avenue for SARS-CoV-2 therapeutic targets which could potentially serve as an antiviral medication alternative. Figure 1 summarizes the plausible infective pathways of SARS-CoV-2 virus into fetal circulation and various placental defense mechanisms to combat the viral infection. As previously mentioned, SARS-CoV-2 entry results in placental ACE2 downregulation, which may be heightened during severe infection. Downregulation of ACE2 may lead to dysregulation of the renin–angiotensin system (RAS), resulting in elevated maternal blood pressure and dysfunctional placental vascularization. This may lead to comorbidities associated with infection in pregnancy, such as preeclampsia [105]. Mendoza et al., (2020) revealed that pregnancies with severe COVID-19 can develop clinical manifestations similar to pre-eclampsia and could be distinguishable from actual pre-eclampsia by biomarker level assessment, including serum soluble fms-like tyrosine kinase and placental growth factor [106]. This is consistent with another study from Sweden that pregnant women with COVID-19 had a higher prevalence of pre-eclampsia [107], especially those with severe COVID-19 [105]. Studies have also revealed that COVID-19 in pregnancy is associated with increased risk of preterm labor and stillbirth, especially those in the active phase of the disease or when infections occurred in the first or second trimester [108,109,110]. The preterm birth rate among COVID-19-affected pregnancies was 11.8% compared with 8.7% among those without COVID-19. Pregnancies with comorbidities and a superimposed COVID-19 infection increased the risk of preterm labor [111]. For instance, pregnancies complicated with hypertension, diabetes mellitus, and/or obesity along with a COVID-19 infection had a 160% greater risk of very preterm delivery and a 100% elevated risk of preterm delivery compared to those without comorbidities or COVID-19 infection [111]. Also, severe COVID-19-affected pregnancies were reported to have a higher incidence of spontaneous or iatrogenic preterm deliveries and preterm rupture of membranes [108]. Extreme prematurity is associated with increased mortality in the early to mid-adulthood. Many survivors may suffer from lifetime health problems, including neuropsychiatric impairment such as learning disabilities and visual and hearing problems [112]. DeSisto et al., (2021) revealed that in U.S., the stillbirth rate had increased from 0.59% (pre-pandemic stillbirth rate) [113] to 0.98% (COVID-19 affected pregnancies during pre-Delta period) and 2.70% (during the Delta period) [114]. Accumulating data suggested that impaired placental function, manifested histologically as placentitis, is a plausible mechanism of stillbirth in these cases [5,58,115]. While some studies revealed that SARS-CoV-2 infection during pregnancy was not associated with fetal growth restriction regardless of the timing of infection [13,116,117,118], lower birth weight was observed in COVID-19-infected pregnancies [105], especially when infection occurred in early pregnancy [119]. Placental fetal vascular malperfusion may be attributed to suboptimal fetal growth, especially in severe COVID-19 infection [120]. Uncomplicated deliveries and favorable neonatal outcomes were largely reported by researchers detailing first trimester COVID-19 maternal infections [121,122]. Emerging early follow-up studies reported that SARS-CoV-2 infection during pregnancy was associated with adverse neurodevelopmental outcomes in the offspring [123,124,125]. When compared with the pre-pandemic cohort, infants in the pandemic cohort were more likely to suffer from communication impairment, without significant differences in other domains such as gross motor, fine motor, and problem-solving skills [123]. Infants with exposure to SARS-CoV-2 in utero were at risk of fine motor impairment compared to those without [123]. Ayed et al., (2022) reported that only 10% of infants born to mothers with SARS-CoV-2 during pregnancies showed developmental delays. Compared to infants born to mothers who had COVID-19 infection during the third trimester, the risk of developmental delays among infants was higher in those born to mothers who had SARS-CoV-2 infection during their first and second trimesters [125]. Increased serum levels of IL-6 especially during the severe course of maternal SARS-CoV-2 infection may alter offspring’s salience network and be responsible for the subsequent cognitive impairment in the newborns, such as autism spectrum disorder, schizophrenia, and cerebral palsy [126]. Nonetheless, a definitive connection between SARS-CoV-2 exposure in utero and impaired neurodevelopment in the offspring is yet to be fully established, requiring studies with longer follow-up periods. Ethical regulations evolving around human placental research have caused significant delay in the development of effective therapies for maternal–fetal infection. Exact mechanisms of how vertical transmission occurs in novel emerging viruses such as SARS-CoV-2 and how host–pathogen interactions in the placenta niche remain as major unresolved questions. Questions like why some but not other maternal infections result in congenital defects, what are the cellular targets of virus in the placenta, and what are the precise molecular mechanisms of viral-mediated host cell damage remain unanswered. For instance, further investigations to generate more consistent data with regards to the expression level and period of ACE2 and TMPRSS2 in the placenta in relation to different gestational ages are required. Our knowledge of LRRC15, a recently discovered potential novel biomarker that could determine SARS-CoV-2 disease severity, in the placenta and how it affects the maternal–fetal barrier in pregnancy is still limited, requiring more studies. Preeclampsia-like features that are seen in SARS-CoV-2-affected pregnancies are intriguing, with many studies demonstrating the viral affinity towards ACE2 receptor, placental histomorphological changes similar to preeclampsia, and upregulation of miRNA associated with preeclampsia in SARS-CoV-2-affected pregnancies; clear evidence of this association is still lacking. The question of whether SARS-CoV-2 can cause preeclampsia remains a mystery. Additionally, the evolutionary processes involved in the emergence of new SARS-CoV-2 viral variants that potentially result in severe illnesses in pregnancy need to be further explored. Last but not least, miRNAs, either encoded by host cells or by a viral genome, play a vital role in regulating host–cell gene expression and manipulating the cellular environment in the context of host–viral interactions. A comprehensive analysis of host and viral miRNAs and their target is warranted to provide valuable insights into the complex mechanisms underlying miRNA-mediated host–SARS-CoV-2 viral interactions during the COVID-19 pathogenesis. Future studies could address whether SARS-CoV-2 viral miRNAs have modulated the host (human) genome to enable a favorable intracellular milieu. With the advancement of next generation sequencing and artificial intelligence-powered bioinformatics, we foresee a rapid expansion in our knowledge on host–placental–viral miRNA interaction in near future, where personalized therapy could be based. A better understanding of the placental barrier, immune defense, and modulation strategies involved in restricting transplacental transmission of SARS-CoV-2 and other emerging pathogens may provide valuable insights for future development of antiviral and immunomodulatory therapies to improve pregnancy outcomes.

PMC10002997

Joshua Seifert,Yingfu Chen,Wenzel Schöning,Knut Mai,Frank Tacke,Joachim Spranger,Josef Köhrle,Eva Katrin Wirth

Hepatic Energy Metabolism under the Local Control of the Thyroid Hormone System

02-03-2023

T3,T4,NAFLD,energy metabolism,deiodinase,cholesterol,lipid metabolism

The energy homeostasis of the organism is orchestrated by a complex interplay of energy substrate shuttling, breakdown, storage, and distribution. Many of these processes are interconnected via the liver. Thyroid hormones (TH) are well known to provide signals for the regulation of energy homeostasis through direct gene regulation via their nuclear receptors acting as transcription factors. In this comprehensive review, we summarize the effects of nutritional intervention like fasting and diets on the TH system. In parallel, we detail direct effects of TH in liver metabolic pathways with regards to glucose, lipid, and cholesterol metabolism. This overview on hepatic effects of TH provides the basis for understanding the complex regulatory network and its translational potential with regards to currently discussed treatment options of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) involving TH mimetics.

Hepatic Energy Metabolism under the Local Control of the Thyroid Hormone System The energy homeostasis of the organism is orchestrated by a complex interplay of energy substrate shuttling, breakdown, storage, and distribution. Many of these processes are interconnected via the liver. Thyroid hormones (TH) are well known to provide signals for the regulation of energy homeostasis through direct gene regulation via their nuclear receptors acting as transcription factors. In this comprehensive review, we summarize the effects of nutritional intervention like fasting and diets on the TH system. In parallel, we detail direct effects of TH in liver metabolic pathways with regards to glucose, lipid, and cholesterol metabolism. This overview on hepatic effects of TH provides the basis for understanding the complex regulatory network and its translational potential with regards to currently discussed treatment options of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) involving TH mimetics. Thyroid hormones (THs) are well known for their important regulatory functions during development and growth. Further early descriptions of TH actions point to the role of THs supporting homeostasis in metabolic pathways through enhancing and diminishing energy consumption from different dietary sources like carbohydrates and lipids. In addition, effects of THs in mitochondrial biogenesis and activation have been described in various models and species. TH concentrations, mainly those of thyroxine (T4) and 3,3’,5’-triiodothyronine (T3), are assessed and accounted for mainly in the circulation where they are distributed throughout an organism. Their production and release from the thyroid gland is regulated via feedforward and feedback mechanisms within the hypothalamus-pituitary-thyroid (HPT) axis. Circulating concentrations of THs often reflect the production and release of THs mainly from the thyroid gland. However, TH actions are executed on a local tissue level within cells of the organism through direct binding to TH receptors (TRs), TRα and TRβ, acting as nuclear transcription factors (type 1 signaling) or by type 3 signaling activating signaling cascades (for example, phosphatidylinositol 3-kinase/PI3K) [1]. TR modulated gene expression in hepatocytes is mediated via TRβ, which also mediates TH signals in the HPT axis, while, for example, heart rate and brain development are mainly steered via TRα. The process of pre-receptor control determining the local TH availability within each cell is mediated by the uptake of THs into cells through transmembrane transporters and via local activation and inactivation through deiodinases (Dio). The eminent role of TH transmembrane transporters became obvious with the discovery of human mutations in the most specific TH transmembrane transporter, the monocarboxylate transporter (MCT) 8. These lead to the Allan-Herndon-Dudley syndrome, which is characterized by psycho-motor retardation along with high T3 and low T4 serum concentrations in patients [2,3]. MCT8 is expressed in a variety of tissues, including the brain, kidneys, and liver. In patients with mutations in MCT8 and mouse models with Mct8 deficiency, despite the loss of Mct8 function, the liver can take up the high circulating T3 concentrations and presents a local hyperthyroid status. This indicates the presence of further TH transmembrane transporters in the liver. Transmembrane transporters that can take up THs are, for example, L-type amino acid transporters, Oatps, Mct10, and the sodium-taurocholate transporter Ntcp, which is highly expressed in the liver (since Ntcp is a major bile acid transporter). Therefore, the liver is obviously exposed to alterations in circulating TH concentrations. Concentrations of TH in the liver are not only mediated by the uptake of circulating TH but also by local activation and inactivation through Dios. Dios are a group of selenoproteins that are responsible for the local activation and inactivation of TH metabolites via deiodination (removal of one iodide) within cells. The three different Dios are capable of reductively removing iodide from different positions within the TH molecules (for a detailed review, see [4]). While Dio2 activity is functionally relevant in the liver during development [5], the adult liver of rodents and humans displays high Dio1 activity. Dio1 activity is regulated by the presence of T3. However, Dio1 itself is involved in the activation of T4 to T3. On the other hand, it locally inactivates TH, while especially TH sulfates are substrates with high affinity [6]. Injuries to the liver, inflammation, and fasting conditions can lead to the induction of Dio3. While Dio1 is expressed in hepatocytes, up to date, it is still not known in which cells of the liver this induction takes place. While liver deiodinases regulate local availability, they also contribute to changes in circulating TH concentrations with varying contributions between different species. Additionally, the liver has a major impact on transport and stabilization of circulating TH concentrations by secreting the plasma distribution proteins albumin (binding 10–15% of T4 and 10% of T3), transthyretin (TTR, binding 10–15% of T4 and 10% of T3), and thyroxin binding globulin (TBG, binding 70% of both T4 and T3), which steady the equilibrium of free-to-total TH. The majority of THs are carried by TBG due to their much higher affinity, although TTR and albumin are much more abundant in plasma. While regulation of energy homeostasis in an organism is achieved by the complex interplay between different energy storing and metabolizing organs like brown and white adipose tissue, muscle, and liver, local TH action differentially affects these processes within cells of an organ. Different cell types of the same organ can even have distinct responses to local TH availability, while circulating concentrations of THs are the same throughout the organism. An example can be given through differential local T3 availability in skeletal muscle cells. Upon muscle injury, Dio3 is induced in satellite cells which promote muscle regeneration, while its inactivation leads to satellite cell apoptosis, hampering regeneration [7]. Further evaluation on a single-cell basis led to the identification of specific muscle cell subsets with differential expression and regulation of Dio2 and Dio3 upon injury and regeneration [8]. Therefore, the evaluation of local TH availability and action within an organ remains crucial. With regards to different liver cell types, the expression of Dio1, as well as TRβ, has been described many times. However, expressions of transmembrane transporters for TH, Dios, and TRs remain elusive for Kupffer and hepatic stellate cells, which also play major roles in the development of NAFLD and NASH. In the adult organism, THs systemically regulate the energy metabolism in oxidative tissues most noticeably, so more energy-rich compounds must be supplied or mobilized from storage sites for energy production. Therefore, it is not surprising that the liver is a target organ of endocrine signaling of the TH axis, complementing the peripheral TH action. On the other hand, the liver itself is an active player in modulating TH concentrations locally and systemically by providing or removing active TH from circulation. In particular, local hepatic T3 availability orchestrates carbohydrate, lipid, cholesterol, and bile acid biogenesis at the level of gene expression, translation, and enzyme function, together with other hormones, signaling molecules, and transcription factors of nutritional regulation. In this review, we will evaluate and summarize data from animal models and cell culture systems with regards to the impact of THs exerted on liver physiology and metabolism. To delineate between data generated in animals vs. human cell culture systems, genes and proteins of animal origin are written with only the first letter capitalized, while human genes and proteins are written in all uppercase letters. Genes are depicted in italics. Nomenclature of human and mouse genes is in accordance with HGNC and MGI. In some cases, we included data derived from human studies to either illustrate known similarities or differences between the different systems needed for the mechanistic understanding of treatment possibilities in humans. Consequences of supplying or restricting different nutrients on regulation of TH system-related genes and proteins in the liver will be discussed. In addition, we will also focus on the regulation of genes and enzymes by THs that are involved in carbohydrate, lipid, and bile acid metabolism in the liver. Fasting influences the regulation of the hypothalamus-pituitary-thyroid (HPT) axis in various species. These physiological alterations in TH synthesis, metabolism, and action might be needed to preserve energy due to a low nutrient supply shutting down stimulatory effects of THs on energy consumption in various tissues. During fasting, a gradual decrease of serum T3 and T4 concentrations is observed, while thyroid-stimulating hormone (TSH) concentrations remain unaltered. These alterations are linked to rapidly decreased activity of hepatic Dio already observed in rat models undergoing fasting and refeeding before the individual contributions of the three Dio isoenzymes to systemic and local TH provision are distinguished [9,10] (for a recent review, see Russo et al. [11]). The data are summarized in Table 1 and Table 2. According to van der Wal et al. [15], fasting resulted in a decrease of serum T3 concentrations after 12 h and serum T4 concentrations after 48 h in rats, whilst serum TSH remained constant. Lower serum concentrations of T3 and T4 (some even undetectable) were also reported upon 48-h fasting in mice [13,14] and in rats [18]. Similarly, 36-h fasting also led to decreased serum T3 and T4 concentrations in male rats [16,17] (Table 1), while three weeks of food restriction (50% of their individual baseline 24 h intake) led to a decrease only in T4 but not in T3 [17] (Table 2). Additionally, Visser et al. [21] also described that three-day fasting caused a decrease in serum T3 and T4 concentrations in both male and female rats, while TSH concentrations only decreased in male rats. Three-week food restriction (one-third of normal food intake) led to significantly lower serum T4, T3, and TSH concentrations in both male and female rats. Similar data on T4 have also been reported by Giacco et al. [20]. In a more recent study from 2020 [14], in accordance with previously reported data, 24-h fasting caused a remarkable decline in serum T4 and T3 concentrations in 12-week-old male mice. Moreover, fasting also affects binding of TH to plasma distribution proteins. Young et al. reported that T4 bound to Tbg and albumin increased during four-day and seven-day fasting in lean rats, while T4 bound to Ttr (designated as thyroxine-binding prealbumin, TBPA) was reduced. In obese rats, Tbg-bound T4 constantly increased up to 28 days already from day 4 upon fasting, whilst Ttr bound T4 steadily dropped and albumin bound T4 remained unaffected [22]. The fasting-induced generation of serum Tbg may account for these alterations. Moreover, serum Ttr decreased significantly during fasting, proportionally to the duration (one-, two-, and three-day fasting) in rats, accompanied by a decreased T4-bound fraction [23]. Fasting for 48 h caused a lower T3 generation rate from T4 in rat liver homogenate, indicating reduced Dio1 activity [18]. In the rat liver, T3 was lower in both 36-h fasting and three-week food restriction, whilst T4 diminished only with three-week food restriction (50% of their individual baseline 24-h intake) [17]. In mice, hepatic T4 decreased during 16- and 36-h fasting and T3 decreased upon 28- and 36-h fasting [12]. In agreement with these results, upon 24-h fasting, mice showed a decrease in hepatic T4 and T3 concentrations [14]. In male rats, hepatic TH contents were unaffected after 36-h fasting according to de Vries et al. [16]. The expression of hepatic TRs was not affected during fasting and food restriction, while the expression of TH responsive genes fatty acid synthase (Fasn) and Spot14 was lower during fasting [17]. In addition, van der Wal et al. [15] showed that decreased serum T3 led to increased low-density lipoprotein (Ldl) cholesterol from 24 h onwards, associated with a lower liver Ldl receptor mRNA (Ldlr). Serum triglyceride (TG) content decreased, while serum free fatty acid (FFA) concentrations increased. Timing of fasting-induced alterations in TH availability therefore differs between species. The clearance of THs plays a major role in regulating the energy metabolism in a state of hunger, which is possibly responsible for the drop in TH concentrations. There are three major pathways of TH metabolism in the liver that are involved in this clearance of TH upon fasting: deiodination, sulfation, and glucuronidation. Deiodination contributes to the modification of TH bioactivity and availability locally via deiodinases [24,25,26]. There are two different isoforms, Dio1 and Dio3, which are capable of inactivating TH. Although Dio1 is believed to be the major source of circulating T3 in humans, the enzyme displays high affinity towards reverse T3 (rT3; 3,3′,5′-triiodo-L-thyronine) and sulfate conjugates of TH [19]. It is evident that hepatic Dio1 activity is significantly lower in both male and female rats after three-day fasting, as well as after three weeks of food restriction (one-third of normal food intake) [21]. In mice, a fasted liver showed a decrease in Dio1 activity compared with a liver in a fed state [12]. In contrast, Dio3 mRNA expression and activity was higher during 36-h fasting and three-week food restriction (50% of their individual baseline 24-h intake), while Dio1 activity remained unchanged despite a lower mRNA expression in mice [16,17]. Thus, the fasting duration and the extent of food restriction play a role in the regulation of local TH concentrations in the liver. To elucidate how and which deiodinases have effects on the TH concentration in both circulation and in the liver, different knockout mice of deiodinases were examined. Despite the alterations in Dio3 expression and Dio1 activity upon fasting described by de Vries et al. [16,17], Galton et al. [12] pointed out that hepatic Dio3 activity was undetectable upon 30-h fasting in WT mice but showed minimal activity in Dio1/Dio2 double KO (D1/D2KO) mice. In accordance with above-mentioned data, serum T4 and T3 also decreased upon 30-h fasting in WT, D1KO, D2KO, and D1/D2KO mice, while TSH remained unchanged. Although D3KO showed a lower baseline of T4 and T3 than WT, 30-h fasting still caused a decline in serum T4 and T3 for D3KO as well as for WT mice. Upon fasting, rT3 is increased in D1KO and D1/D2KO mice, likely resulting from elevated Dio3 activity. Furthermore, [125I] labeled TH were used as Dio substrates in vivo to sensitively monitor their function during fasting. Mice were injected with either [125I] T4, [125I] T3, or [125I] rT3 on the same day of fasting. As a result, fasted WT mice showed a higher distribution of [125I] T3 in liver (and other tissues) than fed mice. In a fasted state, hepatic [125I] T3, [125I] rT3, and [125I] T4 were generally higher than in a fed state in WT and D1/D2KO mice, which also had increased Dio3 activity indicating alterations in uptake, efflux, and/or metabolism of THs. Taken together, fasting-induced systemic TH changes were not dependent on Dio1 or Dio2 but rather on Dio3 and sequestration of T4 and T3 in tissues but not excretion. Sulfation and glucuronidation are responsible for marking TH for degradation and enterohepatic recycling, and remarkable substrate preferences for the individual TH metabolites were observed for various members of the enzyme families catalyzing these conjugation reactions [19,27,28]. Sulfate conjugation may lead to the inactivation of TH by Dio1 [29] or reversible inactivation during fetal development or when TH sulfates are cleaved and liberate unconjugated TH during microbiota-dependent enterohepatic recycling [30,31,32] or cleavage by sulfatases expressed in many tissues [33,34,35]. Glucuronidation of iodothyronine facilitates its biliary and urinary excretion (reversible) [36]. Sulfotransferases (Sults) and UDP- glucuronyltransferases (Ugts) are enzymes performing sulfation and glucuronidation. Phenol sulfotransferases, which can make sulfate conjugates out of TH, belong to the Sult1 family, including Sult1a1, 1a2, 1a3, 1b1, and 1c2 [33,34,37,38]. Most UGTs involved in TH degradation are members of the Ugt1a and Ugt2b families [36,39]. It has been reported that hepatic expression of Sultn, Sult1a1, Sult2a1, and Ugt1a1 increased during fasting in mice [40,41]. Reported as bilirubin UGT [21], Ugt1a1 showed higher activity in rats upon both three-day fasting and three weeks of food restriction to one-third of normal food intake. Sult1b1 expression upon fasting and Sult1c1 expression with food restriction were lower in rats [17]. Fasting for 36 h induced gene expression of Ugt1a1, Sult1a1, and Sult1d1 in mice, associated with an upregulation of the constitutive androstane receptor (Car) mRNA expression [16], and 24-h fasting induced similar effects [14]. Car is an upstream regulator of Sult and Ugt expression and a key target of nutrients, nutritional xenobiotics, and drugs interfering with hepatic metabolism both during regular nutrition and steatosis-induced alterations [42]. Nr1l3 (Car) expression was upregulated during 36 h of fasting, whose serval target genes showed an upregulation during fasting to increase TH metabolism [14]. Similar induction of conjugating enzymes was achieved by Car agonist TCPOBOP, while these induced changes were absent in Car-KO mice, which showed similar TH concentrations in fed states compared with WT mice [40]. Car-/- female mice resembled WT mice upon 24-h fasting in TH concentration with lower basal and fasting-induced hepatic T3 concentrations, and they showed an attenuated induction of Ugt1a1, Sult1a1, and Sult1d1. Interestingly, Car-/- mice showed an elevated Dio3 expression and activity compared with WT mice, but the fasting-induced upregulation of Dio3 was absent [14]. Apart from direct effects on hepatic genes related to TH metabolism and conjugation, fasting and altered leptin secretion from white adipocytes also impacted on hypothalamic neuronal circuits regulated by neuropeptide Y (Npy) and melanocortin 4 receptor (Mc4r). Such central hypothalamic inputs are also required for adaptive hepatic responses of T4 metabolizing pathways during fasting [41]. Apart from the local hepatic changes of TH, the uptake into and efflux of TH from the liver may play an important role in regulating systemic and local TH concentrations [43]. Evidently, 48 h of fasting led to decreased uptake of T3 and T4 into the liver, presumably due to depletion of ATP in a perfused rat liver, accompanied by diminished T3 glucuronidation [33,43]. Notably, Mct10 expression was higher during fasting in male rats, while expression of Mct8 remained unchanged during fasting and food restriction [17]. In mice, mRNA expression of hepatic TH transporter Mct10 was enhanced, whilst Mct8 expression decreased [14], similar to data obtained from rats fasting for three days [20]. In addition, 48-h fasting increased hepatic Ntcp mRNA expression, and 72-h fasting significantly enhanced Ntcp protein expression in the liver of rats [44]. Whether fasting-related altered expression of hepatic TH transporter transcripts is similarly reflected in changes of protein content and function, subsequently resulting in variation of the net import or export of TH, remains to be clarified. Sirt1 is a nuclear deacetylase that is activated upon binding with ligand-bound TRß1, leading to downstream modulation of activities of various gluconeogenic transcription factors/modulators. Cordeiro et al. [13] reported that decreased TH concentrations during fasting resulted in the upregulation of Sirt1 protein and its activity via TRβ, which has beneficial effects upon 48-h fasting, for instance, on life-span extension. Glucose metabolism also plays an important role during nutrient restriction. Studies pointed out that hepatocytes regulated glucose metabolism via the hepatic cAMP/PKA/CREB pathway possibly involving Tsh receptors (Tshrs) [45,46,47]. Studies with cell-type specific knockouts of Tshr in hepatocytes and white adipocytes have been conducted [48,49]. So far, observations reported on the role of TSH and Tshr activation for hepatocyte metabolic function are mainly based on the hepatocyte-specific TshrKO mouse model of one research group [47] and need to be independently confirmed. Diet-induced obesity has become increasingly prevalent worldwide in association with additional comorbidities such as diabetes, hyperlipidemia, and cardiovascular disease. Obesity is recognized as a major risk factor for non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). The imbalance between energy intake, storage, and expenditure plays a pivotal role in diet-induced obesity. TH are key modulators on energy metabolism, regulating both glucose and lipid metabolism. However, there is little data on the systemic and local regulation of TH during different diets (Table 3). Gonzalez-Ramos et al. [50] reported that six weeks of a high-fat diet (HFD) (10.2% hydrogenated coconut fat and 0.75% cholesterol) did not alter serum T3 and T4 concentrations in WT and Nod1-/- mice. However, three and six months of HFD with excessive iodine intake (15% lard, 10% yolk powder, and 79% standard laboratory powder chow; with 1200 μg/L iodine in the form of potassium iodate (KIO3) in the drinking water) led to increases of serum T3 and T4 concentrations and a decrease in TSH concentration [51]. In the LoCoTAct consortium and in our lab, we found that HFD induced Dio1 mRNA expression and activity already after four weeks, and this remained elevated for up to 18 weeks induced by HFD [52]. In accordance with these findings, induction of Dio1 mRNA expression and activity was observed in mice fed with a western diet (D12079B; Research Diets), supplemented with 15% weight/volume fructose in drinking water for eight or 16 weeks [53]. However, Han et al. [51] pointed out that only six months of HFD caused elevated hepatic Dio1 activity, while one month of HFD did not show any influence on TH concentrations or Dio1 activity. According to Gonzalez-Ramos et al. [50], although hepatic Dio1 activity was unaffected by HFD, Nod1-/- mice showed significantly lower Dio1 activity independent of diet. Based on a liver transcriptome analysis [54], only 106 hepatic genes were differently regulated in male mice on a HFD by treatment with the thyromimetic TH metabolite 3,5-T2 (2.5µg/g bw; HFD: 60 kJ% fat; 9% soybean oil, 90% lard, four weeks), while 221 genes responded in mice fed normal chow (ND: 10 kJ% fat, 55% soybean oil, 44% lard). Among these, 56 genes were differently regulated in HFD mice. Strikingly, 12 genes (Cyp1a2, Cyp39a1, Cyp46a1, Cyp51, Cyp2d9, Ces1(f,g) and 2a, Sult1b1, Slc13a3, Slc39a4, Gpx6) involved in xenobiotic metabolism and detoxification were differentially expressed only in HFD mice. Elevated Cyp39a1 expression and reduced Cyp46a1 expression exclusively in HFD mice indicated that 3,5-T2 affected genes involved in bile acid synthesis in obese mice. Treatment with 3,5-T2 altered TH responsive gene expression such as upregulation of Dio1 and downregulation of Serpina7 (Tbg) for both HFD and a regular diet. In addition to factors that regulate the TH concentrations, expression of genes involved in lipid metabolism is altered in HFD mice. Wu et al. reported that C57BL/6 male mice fed with HFD (45% fat, 35% carbohydrate, 20% protein; 12 weeks) and db/db male mice showed upregulation of thyroid hormone-inducible hepatic protein (Thrsp) expression [55]. Thrsp, similar to the initially discovered rat S14 protein expressed in liver and adipocytes, has been used as a lipogenesis marker and endpoint of T3 action, as it rapidly responds to nutritional changes and is regulated by TH but also by steroids and other hormonal factors [56]. In db/db mice, silencing of the hepatic Thrsp gene led to reduced hepatic TG content and attenuated liver steatosis, while hepatic Thrsp overexpression in C57Bl/6 mice led to increased hepatic TG and cholesterol content, as well as upregulation of lipogenesis genes such as sterol regulatory binding proteins (Srebp) Srebf1, Fasn and Acc, associated with elevated enzyme activity. Fatty acid uptake decreased, and fatty acid oxidation increased, due to enhanced expression of peroxisome proliferator-activated receptor α (Ppara), acyl-CoA oxidase, and peroxisomal ketothiolase. Remarkably, treatment with TO901317 (5 mg/kg/day), a LXR agonist, led to upregulation of hepatic Thrsp expression, mediated by LXRα but not LXRβ [55]. According to Jornayvaz et al., TRα-0/0 mice fed with HFD (three weeks, 54.8% fat, 24% carbohydrate, 21.2% protein, energy density 4.8 Kcal/g) showed a reduction in hepatic lipid intermediates, triglyceride and DAG, as well as a decrease in expression of hepatic lipogenic genes, Srebf1, and its downstream targets, Acc1 and Fasn. Expression of genes involved in lipid oxidation like Fgf21, carnitine palmitoyltransferase 1, acyl-CoA oxidase, and 70-kDa peroxisomal membrane protein mRNA levels was similar to WT [57]. It Is also worth mentioning that the liver is a sexually dimorphic organ [58]. Smati et al. pointed out that male mice are more susceptible to NAFLD. Male mice fed with a high-fat diet for 15 weeks (D12492, Research Diets) showed the highest lipid accumulation, and male mice fed with a western diet for 15 weeks (WD, TD.88137, Envigo) displayed the most severe inflammation/fibrosis. It is possible that the development of the disease may take much longer in females. Nevertheless, transcriptome analysis for different dietary challenges (HFD, Choline deficient-HFD (CDHFD, D05010402, Research Diets), WD and WD with glucose (18.9 g/L) and fructose (23.1 g/L) in drinking water) revealed that hepatocyte Ppara serves as a sexually dimorphic factor in mouse liver [59]. Dio1, which is altered by dietary interventions, underlies together with other selenoproteins sexual dimorphism in mouse kidneys and livers [60]. Circulating as well as local TH concentrations in an organism can be regulated by nutritional conditions. However, local TH also directly affect the regulation of metabolic pathways in the liver. To further elucidate mechanisms of direct canonical and non-canonical TR-mediated TH signaling in energy metabolism, a comprehensive overview of major energy pathways is presented. Since TH signaling is not always an effector in gene regulation, but a master regulator, we also introduce other selected cascades with their signal molecules and transcription factor activation in detail. Carbohydrate metabolism in the liver comprises the major energy generating pathways in the body. In this context, TH regulate basal global energy turnover and reciprocally glucose supply from stores or by recycling of energy-rich compounds in the liver. Especially during hyperthyroidism, high T3 concentrations affect glucose utilization in the whole body. One reason for the basally increased cellular energy consumption is the T3-dependent increased membrane potential, built up via Na/K-ATPases, as demonstrated in rat and hepatic rat liver cell lines [61], and by Ca2+ resequestration via Serca in mouse myocytes [62]. The glucose transporter family (Glut) supplies the raised demand for intracellular glucose in a T3-regulated manner. Weinstein et al. reported that induced hyperthyroidism in rats increased the Glut2 transcript and protein levels in the liver [63]. The liver stores glycogen as an energy reserve for extrahepatic tissues. It accumulates glucose after food intake in excess nutrient situations and releases it when blood glucose levels threaten to drop due to peripheral utilization [64]. Glucose consumption in muscle and adipose tissue is controlled locally by factors like T3 availability. Therefore, this part focuses on the component of the regulated tissue-specific T3 concentration that largely influences carbohydrate metabolism in the liver by providing energy substrates. Intracellular deiodination of T4 to T3 mediated by Dio2 is a noteworthy element of local TH availability. While Dio2 expression and activity in the liver is only found during early development with Dio1 being the main deiodinase for local conversion of TH, in muscle and adipose tissue, this conversion is achieved by Dio2. The rapid ubiquitination of Dio2 indicates how dynamically T3 concentration can be regulated in a tissue-specific manner and at the cellular level [65]. Salvatore et al. demonstrated by northern blotting and enzyme activity assays of human skeletal muscle biopsies that DIO2 is not only expressed but also active in skeletal muscle [66]. T3 can control glucose uptake via Glut4 expression in muscle since the rat Glut4 promoter shows binding affinity for TRs, as shown in the electrophoretic mobility shift assay. Glut4 gene expression is increased in vivo after T3 administration in rats, as well as functional Glut4 transporter expression, so basal and insulin-stimulated glucose uptake are increased [67,68,69]. Thus, local Dio2 activity has a non-negligible role in insulin-stimulated glucose disposal in the muscle. Dio2 possesses a cAMP-inducible promoter, leading to a Dio2 expression increment after dibutyryl-cAMP treatment in rat astrocytes [70]. Moreover, bile acids can bind the G-protein coupled receptor Tgr5 that produces cAMP, which increases Dio2 expression in mice in brown adipocytes and skeletal myocytes; thus, more available T3 increases cellular energy expenditure and protects against insulin resistance in BAT and muscle [71]. The ß3-adrenergic signaling due to cAMP signaling is crucial for Dio2 expression during thermogenesis in brown adipose tissue [71]. T3 stimulates hepatic gluconeogenesis in rats already at the level of the hypothalamic paraventricular nucleus. T3-induced sympathetic excitation influences the liver’s endogenous glucose production independently of circulating glucoregulatory hormone concentrations. This was demonstrated by subjecting rats to bilateral T3 microdialysis in the PVN, and as a result, endogenous glucose production and plasma glucose levels increased. The effect was absent when the rats underwent selective hepatic sympathectomy [72], indicating the mediating role of the sympathetic nervous system. Local thyrotoxicosis in muscles during hyperthyroidism leads to proteolysis of muscle protein [73], with hepatic nitrogen excretion via the Cahill cycle. In this process, free ammonium is stored in alanine and transported to the liver where it undergoes deamination by alanine-aminotransferase. The resulting pyruvate is subsequently available for gluconeogenesis [74]. Gluconeogenesis is TH regulated by three rate-limiting enzymes, which provide phosphoenolpyruvate (via PCK1), control pyruvate formation (via PFK4), and the formation of D-glucose (via G6PC). T3 induces the activation of various gluconeogenic transcription factors/modulators such as FOXO1, PGC1α, ERRα, and PPAR via Sirt1 [75]. These transcription factors amplify the transcription of TH target genes, demonstrated for PCK1, pyruvate dehydrogenase kinase isoform 4 (PDK4), and G6pc [76,77]. It has been shown with Sirt1 knockdown in rat livers that absent signal amplification decreases hepatic glucose production [78]. Although insulin sensitivity and disposal in skeletal muscle increases during hyperthyroidism, glucose intolerance and elevated plasma glucose concentrations have been reported in patients with Graves’ disease or non-insulin-dependent diabetes during experimental hyperthyroidism [79,80,81]. T3 signaling may trigger preferential anaerobic glycolysis, causing tissues to produce lactate rather than oxidatively degrade glucose. Pyruvate and lactate thus serve as substrates for endogenous glucose production in the liver and prevent glycogen stores from being excessively depleted by increased cellular energy expenditure [82]. However, an excessive availability of T3 overrides this protective mechanism. Battarbee et al. treated rats with 100 µg/g b.w. L-T4 and reported reduced hepatic glycogen stores, caused by T3-driven increased G6Pase activity in the hyperthyroid state [83]. The thyrotoxic enhanced enzyme activity might explain the observation by Burton et al. in 1957 when livers of rats fed 0.1% L-T4 depleted glycogen despite perfusion with high glucose concentrations in contrast to the euthyroid control group, although they had fewer glycogen stores at the start of the perfusion [84]. The thyroid state significantly affects various stages of lipid metabolism, including hepatic de novo lipogenesis. Energy consumption in the hyperthyroid organism outweighs anabolic processes over time and clears FA from the liver. Lipid metabolism in the body begins with uptake of FA from nutrition or its release from adipose tissue by lipases and circulation in the blood [85]. This chapter outlines TH regulation at the levels of FA uptake, the precursor supply from other energy metabolic pathways such as glycolysis for de novo biogenesis, and the coordination of mitochondrial FA breakdown. The expression of FA transporters in hepatocytes, such as FA translocase (Fat/Cd36), FA binding proteins (Fabpl), and FA transporter proteins (Fatp), regulate the influx of free FA into the liver. PPARs cooperate with TH-responsive genes for mobilization, degradation, and oxidation of lipids [86]. Wierzbicki et al. demonstrated the regulatory role of Ppara in the expression of Fat/Cd36 by determining the transporter expression levels and the FA saturation status of lipids in rat liver [87]. Knock-down of FA transport protein Fatp5 in mice after diet-induced non-alcoholic fatty liver disease (NAFLD) by HFD remarkably reduced FA uptake in the liver and reversed the NAFLD status in terms of TH content and lipid droplet formation [88]. There is certainly an influence of THs on FA uptake, while the exact mechanism needs to be further elucidated. Klieverik et al. showed that TG-derived radio-labeled FA uptake in oxidative tissue in rats increases during hyperthyroidism and decreases in BAT, whereas hypothyroidism elevates FA uptake in WAT [89]. Fabpl expression in the liver increases in hypothyroid rats upon T3 administration at the transcriptional and functional levels [90,91]. In addition to uptake of FA from serum, the liver can also build FA itself for energy storage or synthesis of complex lipids. Malic enzyme (Me) forms the bridge to add energy-rich carbon compounds from glycolysis to the assembly of FA, catalyzing pyruvate to acetyl-CoA metabolism with simultaneous regeneration of one NADH equivalent. Petty et al. demonstrated in promoter studies with COS-7 cells that T3 induces Me1 expression via a TRE [92]. As another source for de novo lipogenesis (DNL), acetyl-CoA carboxylases (ACC) provide the conversion of acetyl-CoA from the citrate cycle to malonyl-CoA, the substrate for the assembly of long-chain amino acids. The Acc1 isoform is present primarily in liver and adipose tissue of rats to form the substrate reservoir for the synthesis of longer-chain FA, whereas the expression of Acc2 in oxidative tissue such as heart and skeletal muscle has a regulatory function in rats [93]. Interestingly, human RNA pools from skeletal muscle, heart, and liver, as well as skeletal muscle biopsies revealed that ACC2 expression predominates in both lipogenic and oxidative tissues [94,95]. In chick embryo hepatocytes, the promoter of Acc1 can bind different transcription factor complexes depending on T3 availability and thus contributes to basal expression via LXR-RXR control, whereas administration of TH could increase Acc1 expression 7-fold [96] (Figure 1, part 11). Blennemann et al. presented, in northern blot analysis, hepatic Acc upregulation in hyperthyroid rats compared to hypothyroid rats [97], while data from hyperthyroid mice in comparison to euthyroid mice revealed less Acca, as well as its phosphorylated form, on the protein level [98]. Spot14 facilitates gene regulation in de novo lipogenesis. Spot14 is located in a chromosomal region associated with obesity, which phenotypically reflects the abnormal lipogenesis of Spot14-null mice [99]. The distance from TRE to transcription start (−2700) is enlarged compared to the usual T3-regulated genes. Studies of Campbell et al. using primary rat hepatocytes revealed that both TH and carbohydrate signaling enhanced Spot14 expression. They proposed that the coregulating carbohydrate response element might be causal for the unexpected distance [100]. Contrary to general upregulation of the lipogenic pathway, TH negatively regulates steroyl-CoA desaturase 1 (Scd1), which is positively coregulated by Srebf1, whereas TH signaling plays the dominant role. Scd1 transforms saturated to monounsaturated fatty acids critical for complex lipid assembly of phospholipids, TG, cholesterol esters, and alkyldiacylglycerols. Experiments in HepG2 cells with co-transfection of TRß1 and RXR revealed a negative TRE in human SCD1 [101] accounting for the downregulation via THs. Fasn generates the assembly of malonyl-CoA and acetyl-CoA to longer-chained FA such as palmitate or stearate in the presence of NADPH in the liver. Radenne et al. reported, in HepG2 cells, an increase in FASN protein expression after T3 treatment between 10 nM and 1.6 µM, which could be further increased by the additional administration of 100-nM insulin. The synergistic effect of 1.6-µM T3 and 100-nM insulin was confirmed in chicken embryo hepatocytes by a much stronger Fasn enzyme activity compared to the administration of the individual hormones. Using CAT-reporter and electrophoretic mobility shift assay, a TRE was confirmed in the goose Fasn 5’ UTR [102]. Furthermore, there is evidence for a non-canonical T3 action targeting the TRE by activating a PI3-kinase-ERK1/2-MAPK-dependent pathway [102]. Hönes et al. focused on the non-canonical influence of TRß on fatty acid synthesis in vivo using mouse models in which either the DNA-binding domain (TRßGS) or the domain involved in activation of PI3K were mutated (TRß147F), as well as in TRß KO (TRß-/-) mice. After a single administration of T3 at 7 ng/g BW, comparable TG levels were reported in the WT and TRßGS, whereas the TRß-/- and TRß147F exhibited similarly increased hepatic TG. This observation was explained by increased protein levels of Fasn in the livers of animals without non-canonical TRß signaling (TRß-/- and TRß147F), whereas FASN activity in HepG2 cells was strongly reduced after treatment with T3 and PI3-kinase inhibitor LY-290042 or MEK1/2 inhibitor PD-98059 [102,103]. Besides direct enzymatic activity regulation to assemble FA, TH also activate lipogenic transcription factors. CHREBP, SREBF1, and LXL are noteworthy key regulators that further mediate the action of TH in the liver. Mendoza et al. demonstrated in wild-type mice that the Chrebpa protein levels were positively influenced during hyperthyroidism while downregulated in a hypothyroid state. In NCoR1-KO and NCoR1/TRß1 double knock-out mice, which provide models for altered TH action through KO of the nuclear receptor corepressor 1 (Ncor1) that directly interacts with TRs [104,105], there was no change in Chrebpa according to TH status. The positive regulation of T3-regulated genes of DNL such as Acaca, Acacb, Fasn, and Me1 was absent in liver-specific Chrebp-KOs compared with wild types. Concentrations of two endpoint markers reflecting thyroid-state-dependent regulation (acetate for DNL and palmitate for FAO) were unaffected in the Chrebp-KO model, further highlighting the necessity of Chrebp for hepatic lipid metabolism. However, Chrebp-KO showed decreased hepatic TG concentrations during hyperthyroidism and increased concentrations in a hypothyroid situation, compared to WT. The authors proposed as an underlying mechanism that the increased hepatic TG content in the Chrebp-KO model in hypothyroidism is related to decreased export of VLDL from the liver, whereas in the hyperthyroid animals, the decreased FAO results from lowered availability of substrates and cofactors from DNL [106]. Downstream of the previously described TRß1-specific activation of Sirt1, the master regulator of lipogenesis, Pgc1a is activated. Sirt1 coregulates TH-signaling specific TRß1-regulated gene sets and thus mainly influences FAO, e.g., via carnitine-palmitoyltransferase-1a (Cpt1a) and Pdk4 expression [75,77]. Based on a ChIP assay in rat hepatocytes, Thakran et al. proposed that via TR mediation, Sirt1 associates with the Cpt1a promoter to activate Pgc1a, which further activates Ppara (Figure 1, part 11). A PPAR response element (PPRE) in the first intron of Cpt1a is known to form the completion in the cascade from TH-mediated signal transduction to gene expression [107]. T3-induced Ppara signaling further leads to the expression of Fgf21, another transcription factor with essential effects on energy provision in the liver and adipose tissue in mice [108]. Fgf21 contributes to the enhancement of the mitochondrial oxidative function by activating the Ampk-Sirt1-Pgc1a-dependent pathway in adipocytes of the 3T3-L1 murine cell line and increasing total energy expenditure while decreasing hepatic TG content via downregulation of lipogenic gene expression in diet-induced obese mice [109,110]. Autophagy is a self-digestion process that primarily recycles cellular fuel stores in lysosomes to generate amino acids, glucose, and FA [111]. Sinha et al. demonstrated that activated TR-mediated TH signaling increases autophagic flux in HepG2 cells after transfection with TRA1. Qualitative and quantitative protein-level analysis of autophagosome marker LC3-II indicated an increased autophagy activation. Likewise, they observed enhanced autophagy in hepatic cell lines AML-12, Hep3B, and Huh7 cells after administration of 1 µM T3 for 72 h. Furthermore, they elucidated the coupling of substrate-providing lipophagy to ß-oxidation. Phagophore membrane elongation in autophagic vesicles depends on ATG5, and siRNA-induced ATG5 knock-down prevented a T3-driven increase in lipophagy in HepG2 and in mice to decreased ß-oxidation interpreted by reduced endpoint marker ß-hydroxybutyrate [112]. In the lysosome, lysosomal acid lipase (Lal) hydrolyzes TG and cholesterol. Coates et al. were the first to report that TH status controls Lal/cholesteryl ester hydrolase activity in rats. T3 administration of either 2 µg/g BW for four days or high single administration of 10 µg/g BW in euthyroid animals increased Lal enzyme activity compared to control animals. Accordingly, thyroidectomized animals exhibited a decreased Lal activity after four weeks [113]. Furthermore, direct TH signaling or transduction through transcription factor Foxo1 activated by deacetylation of Sirt1 affected the expression of protein determinants for autophagic processes [114], such as ULK1, Pink1, DAPK2, betatrophin, and LC3 [112,115,116,117,118]. TH-dependent modulation of the master transcription factor EB activity for lysosomal biogenesis and autophagy or the signaling cascade via PGC1A-CAMKK2-AMPK to inhibit mTOR signaling and activate autophagy by ULK1 phosphorylation expanded the picture of complex TH-induced lipophagy regulation [111,115]. The released FA are metabolized mainly in the mitochondrion to be supplied to the citric acid cycle for energy production or thermogenesis in BAT [119]. The peroxisome activates long-chain FA, where they are converted to membrane-permeable acyl-CoA [120]. Undoubtedly, there is an influence of TH on peroxisome activity, without an elucidated mechanism yet [85]. The transport of activated FA into the mitochondrial matrix is processed by CPT1α whereas shorter-chain FAs pass freely through the membrane [121]. Malonyl-CoA as the precursor of DNL downregulates FAO with a substrate-sensing mechanism by sterical hindrance of CPT1α [85]. Hyperthyroidism decreases intrahepatic malonyl-CoA levels. An electrophoretic mobility shift assay using hepatic rat nuclear extract and promoter analysis via luciferase readout led to the identification of a TRE and further transcription factor recognition sequences in the CPT1A promoter, consistent with the complex CPT1A regulation described above [122]. The aforementioned PGC1α controls a mitochondrial signal axis and resembles the connection between TH signaling and mitochondrial homeostasis. In parallel to a number of directly regulated targets, the physiological response is mainly directed by transcription factors such as NRF1, NRF2, and coactivators [123]. Direct TH-regulated target genes necessary for ß-oxidation of FA in the mitochondrion include medium-chain acyl-CoA dehydrogenase (Mcad, identified in vivo in rats) [124], Pdk4 (promotor analysis of rat gene) [76], and mitochondrial uncoupling protein 2 (Ucp2) (T3 treatment of thyroidectomized mice) [125] and hyperthyroid patients (gene expression analysis on fat tissue biopsies) [126]. There is evidence that the two TR isoforms preferentially regulate different lipid metabolic pathways. Fozzatti et al. observed in TRßPV mice that lipid turnover decreased, whereas the lipid content of the liver increased. In contrast, they described a decrease in lipogenic gene expression and changes in liver mass in TRαPV mice [127]. Lipid metabolism takes place in the liver, which also synthesizes and recycles cholesterol. The sterol cholesterol is crucial for cell integrity and provides the precursor of steroid hormones, bile acids, and vitamin D (Figure 1, part 12). Srebps represent an interface between TH signaling, on the one hand, and cholesterol/lipid homeostasis, as well as intracellular cholesterol sensing, on the other. These transcription factors are directly dependent on TH signaling and enhance or extend the effects of T3, which could be demonstrated by Shin et al. [128]. The isoform mainly involved in cholesterologenesis, SREPB2, was shown to be positively regulated by T3 in human hepatic cell lines [129]. The β-hydroxy-β-methylglutaryl-CoA (HMG-CoA) reductase marks the rate-limiting step in the formation of cholesterol in the liver (Figure 1, part 8). THs primarily regulate HMG-CoA reductase, besides estrogen, glucagon, insulin, and glucocorticoids [130,131]. In hypophysectomized rats, T3 steers the HMG-CoA reductase activity positively [131]. While a study using kidney hamster cell cultures (BHK) showed no direct effect of T3 on expression levels, T3 does stabilize HMG-CoA reductase mRNA [132]. Nevertheless, T3 controls Srebp2 expression and thus influences HMG-CoA reductase gene regulation via their upstream regulatory elements [130]. After synthesis, loading onto lipoproteins solubilizes cholesterol so that it can be secreted from the liver to circulate in the periphery. One way to eliminate excess cholesterol from the circulation is the T3-dependent LDL endocytosis with LDLR (Figure 1, part 6). In thyroidectomized mice, oral T3 administration (10 to 50 nmol/kg/day) for seven days could recover the Ldl serum concentrations compared to sham-operated controls. With higher T3 dosing (up to 330 nmol/kg/day), overcompensation of Ldl decrease was observed [133]. The Ldlr promoter in the rat hepatoma cell line H4IIE contains two functional independent TREs, of which the US-TRE at −612 exhibits increased TRß1 binding affinity. Therefore, regulation via T3 is the determinant independent of the described regulation via the sterol response element [134,135] and indicates liver-specific TR isoform signaling. The serine protease PCSK9 impairs receptor recycling and thus the uptake of LDL-bound cholesterol into the liver by facilitating lysosomal degradation. PCSK9 antibodies have already been successfully used to treat sequelae of hypercholesterolemia [136] (Figure 1, part 7). A comparative study between hyperthyroid patients versus euthyroid patients treated with liver-selective TH-analog KB2115 emphasized the effect of TH on cholesterol metabolism. Bonde et al. reported that hyperthyroidism and treatment with KB2115 reduced plasma concentrations of PCSK9, lipoprotein cholesterol, apolipoproteins B and AI, and lipoprotein(a) [137]. In line with this, two human studies showed a positive correlation between PCSK9 and TSH and a negative correlation with free T3/free T4 [138,139]. SREPBs form the direct link between TH action and PCSK9 expression, although there is no evidence for a TRE, yet. The identified regulatory sequences of PCSK9 in HepG2 cells consist of a sterol response element (SRE) and, with higher regulatory capacity, a binding site for hepatocyte nuclear factor 1 (HNF1) [140]. Worth noting is that the effect of TSH (mainly mediated via SREPB2) might have a steering capacity on PCSK9 expression in humans and HepG2 cells [141]. Cholesterol 7a-hydroxylation is the rate-limiting step to convert LDL-bound cholesterol to bile acids. Thus, it protects against hypercholesterolemia and its sequela, such as atherosclerosis, and bile acids provide a vehicle for dietary absorption in the intestine and serve as signaling molecules [142]. The role of TH in cholesterol degradation is already evident in subclinical hypothyroid patients, who exhibit significantly elevated serum total cholesterol and decreased bile acid concentrations [143,144]. Ldlr knock-out mice treated with TRß-specific thyromimetics GC-1 and KB2115 demonstrated a dramatic decrease in total cholesterol, particularly LDL bound, after ten days. Lindemann et al. also reported a remarkable increase in Cyp7a1 transcripts and serum levels of C4, a marker of bile acid synthesis and a physiological indicator of Cyp7a1 activity [145,146]. TH steer the CYP7A1 expression in HepG2 cells with physiological TR levels via the regulatory element (N1) [147] (Figure 1, part 9). A heterodimer structure consisting of the two semi-transporter ATP-binding cassette subfamily G, member 5 (ABCG5) and ABCG8, is responsible for the transport of formed bile acid and sterols across the canalicular membrane of hepatocytes into the gallbladder [148] (Figure 1, part 10). However, ABCG5/8 are also present in the apical membrane of enterocytes, where they mediate transintestinal cholesterol excretion (TICE) [149]. In the study of intestinal absorption of cholesterol in hypophysectomized mice, administration of TH did not normalize Abcg5/8 expression in the small intestine but strongly upregulated it in the liver [150]. Excess cholesterol after conversion to cholesteryl ester can be transported from the periphery back to the liver by high-density lipoproteins (HDL). This process contributes to the natural cholesterol cycle and prevents manifestation of hypercholesterolemia provoked by excessive fat intake from food and cholesterol circulation in the body via VLDL and LDL. The formation of atheromatous plaques in the arteries would be promoted without reverse cholesterol transport (RCT) back to the liver and would have fatal effects on the cardio- and cerebrovascular systems. RCT initially requires a cholesterol efflux pump in peripheral cells. ABCA1 encodes the cholesterol efflux regulatory protein (CERP) and therefore resembles the shuttle for excess cholesterol. The importance of CERP in reverse cholesterol transport is reflected by the various regulators that control its expression and activity (Figure 1, part 1). Among these regulators are metabolites and signal molecules such as fatty acids, glucose, bilirubin, and adiponectin, which act via the nuclear receptors LXRs, TRs, RXRs, and PPARs [151,152,153,154,155]. Comparative promoter analysis in HEK293 cells overexpressing LXR and TR showed that both receptors bind a classical TH response element (TRE) in the ABCA1 promoter, with LXR leading to upregulation and TR to downregulation of ABCA1 expression [154] (Figure 1, part 11). ApoAI forms the major component of HDL secreted by the liver. Studies in rats showed that administration of TH has a positive rapid regulatory effect on Apoa1 transcription and increases mRNA stability [156] (Figure 1, part 2). When studied in human cell lines, promoter analysis in Huh7 cells demonstrated positive regulation [157], and the increased transcripts in HepG2 cells were presumably mainly related to increased mRNA stability [158], in a similar way to the aforementioned T3 regulation on HMG-CoA reductase. In humans, however, the TH-dependent regulation of HDL is less clear than in previous animal or cell culture models of mechanistic elucidation. In patients, HDL regulation, as well as HDL particle size and the ability to bind cholesterol esters, appear to depend on the severity of TH dysregulation [159]. Trends are toward normal to high HDL in overt, normal to low in subclinical hypothyroidism, and normal to low HDL in both subclinical and overt hyperthyroidism [160,161,162]. There are additional Apoa1 expression regulators described that act via transcription factors such as Foxa3 and epigenetic locus control with long non-coding RNA, which may explain the indistinct correlation between TH status and lipoprotein composition [163,164]. Hepatic lipase (HL) catalyzes the conversion of lipoprotein fractions from HDL via very-low-density lipoproteins (VLDL) and intermediate-low-density proteins (ILP) to low-density lipoproteins (LDL). Cholesteryl ester transport proteins (CETP) are pore forming, and they shuttle the neutral lipids cholesteryl esters and TG between lipoprotein fractions into the hydrophobic core [165] (Figure 1, part 4). HL and CETP are positively TH regulated and influence the lipoprotein composition in plasma [166]. These direct regulations via THs might be the underlying cause for increases in TG concentrations in hypothyroid individuals having low HL activity (Figure 1, part 5). Treatments with L-T4 can increase HL activity and lower TG concentrations in the circulation [167,168,169]. The uptake of the HDL-bound cholesterol ester into the liver is supported by the transporter scavenger receptor beta 1 (Srb1) (Figure 1, part 3). To date, only data on regulation are available from pharmacological studies in mice. After administration with thyromimetics GC-1 or T-0681, an increase of Srb1 at the protein level could be detected [170,171]. Nutritional influences like diets and fasting impact both the systemic and the local hepatic TH system, resulting in alterations of local TH concentrations and subsequent modulation of gene expression in all pathways. With the wealth of data presented in this comprehensive overview, species- and sex-specific differences with regards to these regulations are obvious and reveal open questions. Much data has been compiled from rat models, which differ from those in mice, e.g., with regards to the extent of reduction in circulating TH concentrations upon fasting time or details of the regulation of the TH axis. Underlying molecular mechanisms fully describing the (re)distribution and enzymatic cascades involved in the clearly present reduction of circulating TH concentrations in all species remain partially elusive. Future research needs to document alterations in the liver TH system by associating different disease stages with cell-type-specific regulations of TH action, for example, for NAFLD, NASH, and diabetes models with or without local inflammation. This would provide underlying evidence for further translational insights for the possible usage and mechanism of TH mimetics that are currently in clinical trials [172,173]. While TH mimetics have been under evaluation as drugs for altering energy metabolism for many years, early substances that activated both TRα and TRß failed clinical trials due to adverse reactions. Recently, TRß-isoform-selective drugs (eliminating TRα-related adverse effects) like Resmetirom have been evaluated for the treatment of NAFLD/NASH in phase 3 clinical trials with effective reductions of hepatic and serum lipids and triglycerides. Details on thyromimetics in the context of NAFLD/NASH can be found in our recent review [172]. Nonetheless, based on the central role of local TH actions for intermediary, energy, and structural metabolism in various tissues, it is promising to therapeutically leverage the beneficial actions of THs in a tissue- and cell-type-specific manner for the treatment of metabolic disorders, including NAFLD, dyslipidemia, and obesity, as well as type 2 diabetes.

PMC10002998

Morena Scotece,Mari Hämäläinen,Tiina Leppänen,Katriina Vuolteenaho,Eeva Moilanen

MKP-1 Deficiency Exacerbates Skin Fibrosis in a Mouse Model of Scleroderma

28-02-2023

scleroderma,fibrosis,inflammation,cytokines,cell signaling,MKP-1,DUSP1

Scleroderma is a chronic fibrotic disease, where proinflammatory and profibrotic events precede collagen accumulation. MKP-1 [mitogen-activated protein kinase (MAPK) phosphatase-1] downregulates inflammatory MAPK pathways suppressing inflammation. MKP-1 also supports Th1 polarization, which could shift Th1/Th2 balance away from profibrotic Th2 profile prevalent in scleroderma. In the present study, we investigated the potential protective role of MKP-1 in scleroderma. We utilized bleomycin-induced dermal fibrosis model as a well-characterized experimental model of scleroderma. Dermal fibrosis and collagen deposition as well as the expression of inflammatory and profibrotic mediators were analyzed in the skin samples. Bleomycin-induced dermal thickness and lipodystrophy were increased in MKP-1-deficient mice. MKP-1 deficiency enhanced collagen accumulation and increased expression of collagens, 1A1 and 3A1, in the dermis. Bleomycin-treated skin from MKP-1-deficient mice also showed enhanced expression of inflammatory and profibrotic factors IL-6, TGF-β1, fibronectin-1 and YKL-40, and chemokines MCP-1, MIP-1α and MIP-2, as compared to wild-type mice. The results show, for the first time, that MKP-1 protects from bleomycin-induced dermal fibrosis, suggesting that MKP-1 favorably modifies inflammation and fibrotic processes that drive the pathogenesis of scleroderma. Compounds enhancing the expression or activity of MKP-1 could thus prevent fibrotic processes in scleroderma and possess potential as a novel immunomodulative drug.

MKP-1 Deficiency Exacerbates Skin Fibrosis in a Mouse Model of Scleroderma Scleroderma is a chronic fibrotic disease, where proinflammatory and profibrotic events precede collagen accumulation. MKP-1 [mitogen-activated protein kinase (MAPK) phosphatase-1] downregulates inflammatory MAPK pathways suppressing inflammation. MKP-1 also supports Th1 polarization, which could shift Th1/Th2 balance away from profibrotic Th2 profile prevalent in scleroderma. In the present study, we investigated the potential protective role of MKP-1 in scleroderma. We utilized bleomycin-induced dermal fibrosis model as a well-characterized experimental model of scleroderma. Dermal fibrosis and collagen deposition as well as the expression of inflammatory and profibrotic mediators were analyzed in the skin samples. Bleomycin-induced dermal thickness and lipodystrophy were increased in MKP-1-deficient mice. MKP-1 deficiency enhanced collagen accumulation and increased expression of collagens, 1A1 and 3A1, in the dermis. Bleomycin-treated skin from MKP-1-deficient mice also showed enhanced expression of inflammatory and profibrotic factors IL-6, TGF-β1, fibronectin-1 and YKL-40, and chemokines MCP-1, MIP-1α and MIP-2, as compared to wild-type mice. The results show, for the first time, that MKP-1 protects from bleomycin-induced dermal fibrosis, suggesting that MKP-1 favorably modifies inflammation and fibrotic processes that drive the pathogenesis of scleroderma. Compounds enhancing the expression or activity of MKP-1 could thus prevent fibrotic processes in scleroderma and possess potential as a novel immunomodulative drug. Systemic sclerosis (SSc) is a chronic fibrosing autoimmune disease affecting skin and internal organs. Scleroderma is a skin manifestation of this disease, and it is typified by fibrotic changes resulting in thickening and hardening of skin. Although its etiology remains unknown, the early SSc is characterized by a combination of vasculopathy, autoimmunity and inflammation [1,2]. Activated fibroblasts produce excessive amounts of extracellular matrix (ECM) components, collagen and glycoproteins like fibronectin, which are accumulated in different organs causing variable disease subtypes [3,4]. Currently, there is no disease-modifying drug treatment for SSc. Treatment of organ-specific complications (renal crisis, pulmonary arterial hypertension and some other SSc organ manifestations) has improved survival, but SSc still has the highest cause-specific mortality of any of the rheumatic diseases, and especially patients with diffuse cutaneous systemic disease have a poor prognosis [1,2,5]. Imbalanced inflammation and activated dendritic cells play an important role in triggering fibrosis in SSc [1,2]. Type I interferon (IFN) signature, T helper (Th) 2 and alternative macrophage (M2-type) activation are characteristic features of inflammation preceding collagen accumulation [2]. Several lines of evidence suggest inflammatory cells as important sources of profibrotic mediators interleukin-6 (IL-6), transforming growth factor (TGF)-β1, fibronectin, YKL-40 and chemokines that initiate fibrotic processes through the activation of fibroblasts [6,7,8,9]. One of the feasible approaches is to target these key mediators or inflammatory signaling pathways that are involved in the pathogenesis of the disease [1,2,9]. Mitogen-activated protein kinase phosphatase-1 (MKP-1, also known as dual-specificity phosphatase 1, DUSP1), is a nuclear-localized phosphatase present in most cell types and tissues. MKP-1 is a negative feedback regulator of mitogen-activated protein kinase (MAPK) signaling pathways Erk1/2, p38, and c-Jun NH2-terminal kinase (JNK) that regulate many cellular responses such as growth, differentiation, mitosis and inflammatory response [10,11]. In vitro and in vivo studies have shown that MKP-1 is an important regulator of innate and adaptive immune responses and inflammation [12,13,14,15]. MKP-1 deficiency leads to a more severe disease in experimental arthritis and psoriasis [16,17]. Importantly, MKP-1 supports Th1 polarization by inducing interleukin-12 (IL-12) expression through interferon regulatory factor 1 (IRF1), which could be important in preventing Th2-supported fibrotic processes and development of scleroderma [18,19]. All these findings open an interesting possibility that MKP-1 could have a protective role in fibrosing diseases such as scleroderma and that hypothesis was approached in the present study. There is no perfect mouse model able to summarize every facet of scleroderma, but bleomycin-induced dermal fibrosis is a well-characterized experimental model used to evaluate the potential role of genes or treatments in the early inflammatory phase and/or in the subsequent fibrosis process typical for scleroderma [20]. We decided to investigate the potential protective role of MKP-1 in the pathogenesis of scleroderma by using the bleomycin-induced dermal fibrosis model in wild-type and MKP-1-deficient mice. To begin to assess whether MKP-1 might play a role in scleroderma-like skin fibrosis, dermal thickness was evaluated in wild-type and MKP-1-deficient mice following local bleomycin injections. As shown in Figure 1, bleomycin treatment increased dermal thickness in wild-type mice, and it was even further increased in MKP-1-deficient mice (Figure 1A,C). We weighed standard size full-thickness skin samples (6 mm in diameter) and observed that genetic deletion of MKP-1 also resulted in significantly more increased skin weight in bleomycin-treated mice compared to wild-type mice (Figure 1B). In addition, the subcutaneous fat layer was decreased in bleomycin-injected skin from both genotypes, and an interaction between the genotype and bleomycin was seen suggesting a more pronounced effect in the MKP-1-deficient mice (Figure 1A,D). To probe whether bleomycin-induced increased dermal thickness in MKP-1-deficient mice corresponds with increased extracellular matrix deposition (ECM), we investigated the collagen content and collagen expression in the dermal skin samples from wild-type and MKP-1-deficient mice following bleomycin injections. For direct visualization of collagen and histological assessment of collagen deposition, Masson’s trichrome stain was utilized. Both wild-type and MKP-1-deficient mice responded to bleomycin treatment with an increase in collagen content in the skin. Bleomycin injections in MKP-1-deficient mice resulted in a significantly higher collagen accumulation in dermis compared to the wild-type mice (Figure 2A,B). Next, we studied the expression of collagens 1A1 and 3A1 by qRT-PCR in skin samples from wild-type and MKP-1-deficient mice following bleomycin injections. As shown in Figure 2, bleomycin treatment increased dermal collagen 1A1 and collagen 3A1 expression in both wild-type and MKP-1-deficient mice, and the collagen expression levels were significantly higher in MKP-1-deficient mice (Figure 2C,D). After having detected that fibrosis was increased in bleomycin-treated skin from MKP-1-deficient mice, we investigated the expression of fibrogenesis mediators interleukin-6 (IL-6), transforming growth factor-β1 (TGF-β1) and fibronectin-1. We observed an increase in these mediators in bleomycin-treated skin more pronouncedly in MKP-1-deficient than in wild-type mice (Figure 3A–C). YKL-40, also named chitinase-3-like protein-1 (Chi3L1), has been shown to be associated with inflammatory processes and increased fibrotic activity. Accordingly, YKL-40 expression was found to be upregulated in bleomycin-treated skin from both wild-type and MKP-1-deficient mice compared to control skin. Interestingly, the bleomycin-enhanced YKL-40 expression was higher in the skin samples from MKP-1-deficient mice than in those from wild-type mice (Figure 3D). However, no difference was found in connective tissue growth factor (CTGF), platelet-derived growth factor subunit B (PDGFB), or vascular endothelial growth factor A (VEGFA) expression between wild-type and MKP-1-deficient mice skin treated with bleomycin (Figure 3E–G). Chemokines together with cytokines contribute to the development of fibrosis through the recruitment of collagen producing myofibroblasts and other important effectors cells to the site of injury. We analyzed the expression of three important chemokines implicated in the fibrotic process: monocyte chemoattractant protein-1 (MCP-1), macrophage inflammatory protein-1 alpha (MIP-1α) and macrophage inflammatory protein-2 (MIP-2). Bleomycin treatment induced increased chemokine expression in both wild-type and MKP-1-deficient mice, but the response was higher in MKP-1-deficient mice (Figure 4). Our results show, for the first time, that MKP-1-deficient mice treated with bleomycin present a significant increase in the dermal thickness and lipodystrophy as well as in the gene expression of inflammatory and profibrotic factors as compared to wild-type mice. The present findings support our hypothesis that MKP-1 has a protective role in the fibrotic response induced by bleomycin and known to mimic scleroderma. Understanding the pathogenesis of scleroderma, and especially its early features, is essential to discover novel drug targets to treat scleroderma and fibrosis. Bleomycin-induced dermal fibrosis is considered as an accurate experimental model for the study of scleroderma [20]. It reproduces the early stages of the disease characterized by vasculopathy, autoimmunity and inflammation with subsequently increased production and accumulation of collagen and other ECM components into the dermis and replacement of the adipose layer by fibrotic tissue (lipodystrophy). The accumulation of the collagen and other ECM proteins lead to increased skin thickness and fibrosis [21]. Accordingly, we observed that bleomycin treatment resulted in a significant increase in dermal collagen content in wild-type mice. The findings on protective role of MKP-1 in this process were supported by the results, where MKP-1-deficient mice had higher collagen deposition and increased expression of collagens 1A1 and 3A1 and fibronectin-1 in dermis as compared to wild-type animals. Accumulating evidence indicates that inflammatory response is necessarily preceding fibrogenesis [1,2]. Several studies have reported a high number of infiltrating activated macrophages and lymphocytes in the skin of patients with scleroderma [22,23]. These inflammatory cells are key producers of a variety of profibrotic cytokines, such as TGF-β and IL-6. TGF-β is a potent inducer of ECM production and a key factor in fibrogenesis in different fibrosing diseases [21,22], and IL-6 is an important regulator of fibroblasts activation [22,24]. Therefore, we measured TGF-β and IL-6 expression in the skin from wild-type and MKP-1-deficient mice treated with bleomycin. Interestingly, MKP-1 deletion resulted in an increase in the expression of both cytokines, supporting a role for this nuclear phosphatase in the pathogenesis of the bleomycin-induced dermal fibrosis. We also analyzed the expression of YKL-40, a chitinase-3-like protein-1 (Chi3L1), that is upregulated in many pathological and inflammatory conditions [25,26,27,28] and associated with increased fibrotic activity [7,29,30]. YKL-40 may also actively promote fibrosis as it induces apoptosis of classically activated M1 macrophages, but not alternatively activated M2 macrophages, which are known to possess profibrotic properties [31,32]. Here, we demonstrated that YKL-40 expression was regulated by MKP-1 as the levels were enhanced in the skin from bleomycin-treated mice with MKP-1 genetic deletion when compared with wild-type counterparts. Chemokines are leukocyte chemoattractant that cooperate with profibrotic cytokines in the development of fibrosis by recruiting collagen-producing myofibroblasts, macrophages and other key effector cells to sites of tissue injury. A large number of chemokines are involved in the mechanism of fibrogenesis, but the CC- and CXC-chemokine families have exhibited important regulatory roles [33]. CCL-2/MCP-1, CCL-3/MIP-1α and CXCL2/MIP-2 are examples of chemokines identified as profibrotic mediators [34,35]. Accordingly, we showed here that chemokines MIP-1α, MIP-2 and MCP-1 were increased in response to bleomycin treatment and importantly, the expression of these chemokines was strongly upregulated in MKP-1-deficient mice compared to wild-type counterparts. This finding further supports the protective role for MKP-1 in controlling migration of profibrotic inflammatory cells to the site. Moreover, we did not detect significant differences in control groups between wild-type and MKP-1-deficient mice, suggesting that MKP-1 deficiency increases fibrogenesis only after an appropriate trigger. Considering the present findings on the protective role of MKP-1 in an experimentally induced scleroderma, it is of interest that MKP-1 has been shown to increase IL-12 production [18,19]. IL-12 promotes Th1 response, which is thought to prevent from Th2 type response typical for the development of scleroderma [2,18,19]. Interestingly, increased circulating IL-12 concentrations have been reported in patients with scleroderma, particularly in the healing phase of the disease [36]. In addition, cases of scleroderma such as morphea skin lesions have been reported in psoriasis patients using ustekinumab, an antagonist of IL-12 and IL-23 [37,38]. However, further studies are needed to understand the detailed mechanisms how MPK-1 downregulates the pathogenesis of scleroderma. In the light of the present results, drugs inducing MKP-1 could have antifibrotic effects in scleroderma and fibrosis. Drugs known to induce MKP-1 include antirheumatic gold compounds, aurothiomalate and auranofin [39], phosphodiesterase (PDE)4 inhibitor rolipram [15,40], β2-agonists [41,42] and glucocorticoids (GCs) [11,15,43,44,45]. GCs are used as a part of the drug treatment in SSc-related diffuse cutaneous disease, interstitial lung disease, and inflammatory arthritis, although their efficacy is limited and the risk of renal adverse effects restrains their use in SSc patients [46]. Potential beneficial effect of GCs on SSc via increased MKP-1 expression may be complicated by their widespread effect on the expression of hundreds of genes involved, e.g., in extracellular matrix organization and cell metabolism [47]. cGMP is an intracellular signaling molecule that has been reported to increase MKP-1 expression [48], and cellular cGMP levels are regulated by the activity of the enzymes guanylate cyclase (GC) and by phosphodiesterase 5 (PDE5). The current findings on the role of MKP-1 in bleomycin-induced fibrosis also shed light on the hitherto unknown mechanisms of the antifibrotic effects of cGMP-enhancers, namely the sGC stimulator riociguat and PDE5 inhibitors, recommended currently to the treatment of SSc-related disease subtypes [46]. To our knowledge, MKP-1 has not been investigated in patients with scleroderma, and this is the first study in an experimental model of the disease. A limitation of the applicability of the current findings to the clinical disease lies in the potential differences in the pathogenesis of the bleomycin model and the actual human disease. Furthermore, the detailed mechanisms how MKP-1 downregulates or retards the pathogenesis of scleroderma remains to be investigated. Although MKP-1 has not directly been studies in scleroderma, it is of interest that inhibitors of the MAP kinases p38 and JNK were reported to have antifibrotic effects in human SSc fibroblasts [49,50]. Furthermore, Ihn et al. also reported a constitutive phosphorylation and activation of p38 in SSc patient-derived fibroblasts. Considering that MKP-1 dephosphorylates and thereby inactivates MAP kinases p38 and JNK, those findings are in line with our results supporting their significance and applicability in SSc patients. Intriguingly, MKP-1 has also been identified as a primary candidate in a meta-analysis combining microarray data from patients with systemic sclerosis and chronic graft-versus-host disease—two diseases with common fibrotic skin and internal organ involvement [51]. Our present findings together with the cited data in the literature strongly encourage researchers to continue to investigate the potential role of MKP-1 as a factor and drug target in SSc. In conclusion, we have demonstrated for the first time that MKP-1 deficiency in mice promotes skin fibrosis by augmenting profibrotic and proinflammatory factors, suggesting a potential protective role of MKP-1 in fibrosing diseases. At the moment, the treatment modalities for scleroderma and other fibrosing diseases are limited. The present study introduces MKP-1 as a potential new treatment target for scleroderma and compounds able to increase the expression/activity of MKP-1 as potential new drugs for the treatment of fibrosing pathologies. MKP-1-deficient male C57BL/6 mice and corresponding wild-type controls were used in the bleomycin-induced model of scleroderma. The MKP-1-deficient mice were originally generated at Bristol-Myers Squibb Pharmaceutical Research Institute (Princeton, NJ, USA) [52]. Mice were bred under standard conditions (12h:12h light: dark cycle, +22 ± 1 °C temperature, 50–60% humidity), and water and food were constantly available ad libitum. Experimental procedures were performed according to the legislation on the protection of animals used for scientific purposes (Directive 2010/63/EU), and the license for the experiment was approved by National Animal Experiment Board (ESAVI/10109/04.10.07/2015). Bleomycin (Cayman Chemical, Ann Arbor, MI, USA) was dissolved in sterile phosphate-buffered saline (PBS) and diluted to 0.5 mg/mL. The upper dorsa of mice were shaved, and a square (about 1.5 cm2) was drawn with a marker. Sevoflurane inhalation was used to anesthetize mice, and 100 μL of bleomycin was administered by using a 27-gauge needle into the shaved area rotating injection sites, every other day for 4 weeks. On the day following the last injection, CO2 was used to euthanize the mice, and punch biopsies of 6 mm diameter were taken from the injected skin. Two skin biopsy specimens were weighed and fixed in 10% formalin and used for histological analyses. One specimen was stored in RNAlater solution (Invitrogen, Life technologies, Carlsbad, CA, USA) and processed for RNA extraction. Lesioned skin samples were obtained from age-matched male MKP-1-deficient and wild-type mice (n = 6) injected with bleomycin. Control skin was collected from MKP-1-deficient and wild-type mice (n = 8) that did not receive bleomycin treatment. The skin specimens were fixed in 10% formalin, embedded in paraffin, cut in 6 μm sections, and mounted on slide. Hematoxylin and Eosin (HE; Histolab Products AB, Göteborg, Sweden) or Masson’s trichrome (Sigma-Aldrich Chemical Company, St. Louis, MO, USA) were used to stain slides. Dermal and adipose tissue thickness (μm) were measured in HE-stained sections at six randomly selected locations in each section using the Image J program. Collagen accumulation (% of total area) was measured in Masson’s-stained sections by Image J program as previously described [53]. RNA from skin samples was extracted using the GenElute Mammalian Total RNA Miniprep Kit (Sigma-Aldrich Chemical Company, St. Louis, MO, USA), according to the manufacturer’s instructions. Total RNA was reverse-transcribed to cDNA using Maxima First Strand cDNA Synthesis Kit for RT-qPCR (Thermo Fisher Scientific, Waltham, MA, USA). After the transcription reaction, the cDNA obtained was subjected to PCR using TaqMan Universal PCR Master Mix and ABI PRISM 7500 Sequence detection system (Applied Biosystems). The primer and probe sequences and concentrations were optimized according to the manufacturer’s guidelines in TaqMan Universal PCR Master Mix Protocol part number 4304449 revision C and were 5′-GCATGGCCTTCCGTGTTC-3′ (mouse glyceraldehyde-3-phosphate dehydrogenase (GAPDH) forward primer, 300 nM), 5′-GATGTCATCATACTTGGCAGGTTT-3′ (mouse GAPDH reverse primer, 300 nM), 5′-TCGTGGATCTGACGTGCCGCC-3′ (mouse GAPDH probe, 150 nM, containing 6-FAM as 5′-reporter dye and TAMRA as 3′-quencher) and 5′-TCGGAGGCTTAATTACACATGTTC-3′ (mouse interleukin-6 (IL-6) forward primer, 900 nM), 5′-CAAGTGCATCATCGTTGTTCATAC-3′ (mouse IL-6 reverse primer, 300 nM), 5′-CAGAATTGCCATTGCACAACTCTTTTCTCA-3′ (mouse IL-6 probe, 200 nM, containing 6-FAM as 5′-reporter dye and TAMRA as 3′-quencher). Primers and probes were purchased from Metabion (Martinsried, Germany). TaqMan Gene Expression assays for mouse COL1A1 (Mm00801666_g1), mouse COL3A1 (Mm01254476_m1), mouse TGF-β1 (Mm01178820_m1), mouse fibronectin-1 (Mm01256744_m1), mouse CTGF (Mm01192933_g1), mouse PDGFB (Mm00440677_m1), mouse VEGFA (Mm01281449_m1), mouse MCP-1 (Mm00441242_m1), mouse MIP-1α (Mm99999057_m1), mouse MIP-2 (Mm00436450_m1) and mouse YKL-40 (Mm00801477_m1) were obtained from Thermo Fisher Scientific, Waltham, MA, USA. The PCR cycling parameters were as follows: incubation at 50 °C for 2 min, incubation at 95 °C for 10 min, and thereafter 40 cycles of denaturation at 95 °C for 15 s and annealing and extension at 60 °C for 1 min. The mRNA levels were normalized against the housekeeping gene GAPDH mRNA levels and quantified using the ΔΔCt method. The results are presented as the mean + standard error of the mean (SEM). Two-way analysis of variance ANOVA followed by Tukey’s multiple comparison test was used. p values less than 0.05 were considered significant. Data were analyzed using the Prism computerized package (Graph Pad Software, San Diego, CA, USA).

PMC10003002

Sungmi Jeon,Miyeon Jeon,Sanga Choi,Seongkyeong Yoo,Soohyun Park,Mingyu Lee,Iljin Kim

Hypoxia in Skin Cancer: Molecular Basis and Clinical Implications

23-02-2023

skin cancer,hypoxia,hypoxia-inducible factor,cancer reconstruction

Skin cancer is one of the most prevalent cancers in the Caucasian population. In the United States, it is estimated that at least one in five people will develop skin cancer in their lifetime, leading to significant morbidity and a healthcare burden. Skin cancer mainly arises from cells in the epidermal layer of the skin, where oxygen is scarce. There are three main types of skin cancer: malignant melanoma, basal cell carcinoma, and squamous cell carcinoma. Accumulating evidence has revealed a critical role for hypoxia in the development and progression of these dermatologic malignancies. In this review, we discuss the role of hypoxia in treating and reconstructing skin cancers. We will summarize the molecular basis of hypoxia signaling pathways in relation to the major genetic variations of skin cancer.

Hypoxia in Skin Cancer: Molecular Basis and Clinical Implications Skin cancer is one of the most prevalent cancers in the Caucasian population. In the United States, it is estimated that at least one in five people will develop skin cancer in their lifetime, leading to significant morbidity and a healthcare burden. Skin cancer mainly arises from cells in the epidermal layer of the skin, where oxygen is scarce. There are three main types of skin cancer: malignant melanoma, basal cell carcinoma, and squamous cell carcinoma. Accumulating evidence has revealed a critical role for hypoxia in the development and progression of these dermatologic malignancies. In this review, we discuss the role of hypoxia in treating and reconstructing skin cancers. We will summarize the molecular basis of hypoxia signaling pathways in relation to the major genetic variations of skin cancer. Intratumoral hypoxia is a common feature of solid malignancies, including skin cancer. Cellular responses to low oxygen tension promote cancer progression by inducing biological processes involved in cancer cell survival, such as angiogenesis and glycolysis. Skin cancer most often arises from cells in the epidermal layer of the skin, which are relatively deprived of oxygen [1]. In this review, we describe the roles of hypoxia and hypoxia signaling molecules in skin cancer cells. The well-established hypoxia-inducible factor (HIF) pathway plays a central role in the hypoxic response of skin cancer cells. In addition, the major genetic alterations of skin cancer and their association with hypoxia signaling are discussed. Furthermore, we summarize the effects of hypoxia on the reconstruction of skin defects after surgical tumor resection. Human skin consists of three main layers: the epidermis, dermis, and hypodermis. The epidermis is the outermost layer of the skin that protects the body from foreign substances. The dermis is located below the epidermis and is primarily composed of fibrous connective tissue supporting the skin’s overall structure. It is the thickest layer of skin and contains various dermal appendages, such as hair follicles, sweat glands, and sebaceous glands. The hypodermis (or subcutaneous layer) is the lowermost layer of skin, which primarily consists of loose connective tissue and is a major site for fat storage [2]. The dermal layer of the skin is well oxygenated, while the epidermis is moderately hypoxic. This is because the dermis receives oxygen directly from numerous blood vessels, whereas oxygen delivery to the epidermis occurs inefficiently via the dermal blood vessels or atmospheric oxygenation of the skin surface. As a result, some skin appendages have a moderate-to-severe hypoxic environment [3] (Figure 1). Although many studies have measured the partial pressure of oxygen (pO2) in animal skin, only a few studies have measured it in human skin. The oxygen tension recorded by microelectrodes in the epidermis and dermal papillae of human nail fold skin ranges from 5–25% of the atmospheric value [4]. EF5, a 2-nitroimidazole compound, is a widely used hypoxia marker that selectively binds to cells at low oxygen concentrations [5]. One study that evaluated tissue oxygenation using EF5 values reported physiologic pO2 (76 mmHg) in the dermis, physiologic-to-moderate hypoxia (3.8–76 mmHg) in the epidermis, and modest-to-severe hypoxia (0.76–19 mmHg) in hair follicles and sebaceous glands [1]. Skin cancer commonly originates from epidermal cells and later infiltrates deep into the dermis and subcutaneous layers. Three main types of epidermal cells develop into skin cancer: basal cells, squamous cells, and melanocytes. Basal cells lie at the base of the epidermis and gradually rise to the skin’s surface to flatten and become squamous cells, covering the upper part of the epidermis. Melanocytes reside in the basal layer of the epidermis and produce the brown pigment melanin. Melanin protects deeper layers of the skin from DNA damage by blocking ultraviolet (UV) rays. Skin cancer most often results from the abnormal growth of basal cells, squamous cells, or melanocytes [6,7]. Melanoma, which arises from melanocytes, is the most aggressive type of skin cancer worldwide [8,9,10]. Non-melanoma cancers usually refer to basal and squamous cell carcinomas. Nonetheless, there exists rare forms of skin cancer, such as Kaposi’s sarcoma, Merkel cell carcinoma, sebaceous gland carcinoma, and dermatofibrosarcoma protuberans [11]. Hypoxia is a critical feature that promotes the onset and progression of solid cancers [12]. Precancerous skin cells exposed to hypoxic conditions are prone to malignant transformation. In addition, as the tumor mass increases, the oxygen consumption by actively proliferating cells increases, and the oxygen supply decreases owing to insufficient blood vessels, resulting in an imbalance between the oxygen supply and demand. This activates the signaling pathways that promote tumor cell survival and disease progression [13,14]. The mechanism of cells adapting to changes in ambient oxygen tension has been described in detail from the 1990s to 2000s. HIF was discovered in 1995 as a transcription factor that binds to the 3′ enhancer element of erythropoietin (EPO) gene [15]. HIF consists of alpha and beta subunits encoded by various genes [16]. HIF-α contains an oxygen-sensitive degradation (ODD) domain targeted by the von Hippel–Lindau protein (VHL) for proteasomal degradation [17,18,19,20]. This degradation occurs only in the presence of molecular oxygen. Prolyl hydroxylases (PHD1-3) use oxygen to attach hydroxyl groups to two conserved proline residues within the ODD domain of HIF-α [21,22,23]. At normal oxygen concentrations, the hydroxylated form of HIF-α is recognized and degraded by VHL. In contrast, this process does not occur under hypoxic conditions, and stabilized HIF-α relocates to the nucleus. HIF-α forms a dimer with HIF-β (also known as aryl hydrocarbon receptor nuclear translocator, ARNT), which is constitutively expressed in the nucleus and activates the transcription of target genes containing hypoxic response element (HRE) sequences [24]. The transcriptional activity of HIF is regulated by the hydroxylation of an asparagine residue in the C-terminal transactivation domain (CTAD). Factor-inhibiting HIF (FIH), an oxygen-sensitive asparaginyl hydroxylase, prevents HIF from binding to CBP/P300, which are cofactors required for transcriptional activity [25,26]. Three HIF family members are currently known: HIF-1α, HIF-2α, and HIF-3α. Although HIF-1α and HIF-2α share common target genes, each has unique target genes and is known to play independent roles in different cancer types [27,28]. HIF-3α has several variants, with some acting as transcription factors and others as negative regulators of HIF-1/2α [29]. The HIF transcription factors are overexpressed in many solid cancers, including skin cancer, and are linked with a poor patient prognosis [30,31,32]. A sufficient oxygen supply from blood vessels to the skin is restricted to the dermis and subcutaneous layer, and the hypoxic microenvironment of the epidermis can lead to the activation of HIF and other hypoxia pathways [1,33,34,35,36]. The following sections discuss the molecular and cellular mechanisms associated with hypoxia for each type of skin cancer. Melanomas usually develop in the skin (cutaneous melanomas), but can also occur in the eye (ocular melanomas) and the tissues lining the internal surface of body organs (mucosal melanomas). Cutaneous melanomas account for more than 90% of all melanoma cases in the United States and the majority (75%) of skin cancer-related deaths [37,38]. It is characterized by distinct genetic alterations resulting from mutations that are predominantly induced by UV radiation. Prolonged sun exposure is the most important risk factor for melanomas, and people with pale skin are more susceptible than others. UV radiation causes DNA damage in the epidermis and transforms the melanocytes into melanomas. Sporadic mutations cause melanomas in approximately 90% of patients. A large fraction of melanoma mutations are UV-induced cytosine-to-thymine transitions at dipyrimidine sites [39]. The most commonly mutated driver genes in cutaneous melanomas are the proto-oncogene B-Raf (BRAF) (~45–50%), Ras GTPase (RAS) (~30%), and neurofibromin 1 (NF1) (~10–15%). These mutations usually occur during the early stages of tumor development. A cutaneous melanoma lacking the above three mutations is classified as a triple wildtype (~10–15%) [40,41,42]. Other recurrently mutated genes in cutaneous melanomas include the proto-oncogene c-Kit (KIT), telomerase reverse transcriptase (TERT), Rac family small GTPase 1 (Rac1), phosphatase and tensin homolog (PTEN), and tumor protein p53 (TP53) [42,43,44]. Hereditary melanomas are uncommon, and only ~10% of melanoma patients have an underlying familial predisposition. Germline mutations in the cyclin-dependent kinase inhibitor 2A (CDKN2A) gene are the most frequent, accounting for approximately 20–40% of familial cases [45]. Although CDKN2A was first identified in 1994, followed by cyclin-dependent kinase 4 (CDK4) in 1996, most familial melanoma genes were only discovered after 2010 when next-generation sequencing technologies were introduced [46,47,48,49]. However, although CDKN2A mutations exist in up to 40% of high-density families, mutations in other inheritable genes have been found in less than 1% of familial melanomas. Microphthalmia-associated transcription factor (MITF) has been reported to be a susceptible gene in melanoma families and the general population [49]. A schematic diagram of the signaling pathways involved in melanomagenesis and its progression under hypoxia is shown in Figure 2. Some of these alterations in melanomas change the mitochondrial metabolism, leading to tumor progression and resistance to targeted therapies [50]. It is known that hypoxic cancer cells increase glycolysis and decrease oxidative phosphorylation compared to normal cells. However, recent studies have shown that oxidative phosphorylation can be enhanced in certain cancers, such as BRAF-mutant or high-peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) melanomas. It has been shown that the expression levels of oxidative phosphorylation-related proteins are increased in patients with BRAF-mutant skin cancer that is resistant to BRAF inhibitors [51,52,53,54]. Oxidative phosphorylation also plays an important role in metastasis because mitochondrial activity is higher in metastatic cancer than in primary cancer [55,56]. Mitochondrial metabolism can stimulate cancer cell proliferation by altering the activity of transcription factors such as HIF-1α, c-Fos, and c-Jun [57]. Several drugs that inhibit oxidative phosphorylation could potentially be used to target specific melanoma subtypes [51]. Photodynamic therapy (PDT) can cause chemical damage to cancer cells by generating reactive oxygen species (ROS) in the presence of sufficient oxygen. Certain nanomedicine-based therapeutics are being tested as a combination modality to reverse tumor hypoxia and improve PDT efficacy [58,59,60]. BRAF encodes the serine/threonine protein kinase B-Raf, which plays a vital role in the mitogen-activated protein kinase (MAPK) pathway. The MAPK pathway, initiated by the binding of extracellular factors to receptor tyrosine kinases (RTKs) in the plasma membrane, regulates various cellular processes involved in melanoma development. RTKs then activate Ras GTPases, which sequentially activate effector proteins such as BRAF and phosphoinositide 3-kinase (PI3K) [61]. Most (~90%) BRAF mutations observed in melanomas are V600E mutations, with the second most frequent mutation being V600K (~5%). BRAF-activating mutations cause constitutive enzyme activation and resistance to the negative feedback regulation [62]. In BRAF V600E-positive melanocytes and melanoma cells, the HIF-1α and VEGF levels were elevated, possibly due to the downregulation of VHL expression by BRAF mutations [63]. Similarly, increased VEGF expression has been observed in patients with papillary thyroid carcinomas (PTCs) with the BRAF V600E mutation [64]. It is likely that HIF-1α regulation by BRAF is not limited to melanomas and is equally present in other cancers with BRAF mutations. The BRAF V600E mutation, at least in part, induces angiogenesis through HIF-1α/VEGF, and the treatment of SK-MEL-28 melanoma cells with the BRAF inhibitor PLX4720 reduces VEGF expression and secretion. In an SK-MEL-28 mouse xenograft model, PLX4720 could successfully abolish tumor hypoxia and necrosis by normalizing tumor vasculature [65]. PHD2, which destabilizes HIF-1α, is downregulated in melanomas. In a transgenic mouse created with the Cre–Lox system, the depletion of Phd2 and the ectopic expression of Braf V600E in melanocytes led to melanoma formation. Metastasis to the regional lymph nodes and survival rates were dramatically reduced in these mice. In melanoma tissues, the loss of Phd2 increases HIF-1/2α protein levels and target gene expression. Moreover, the protein kinase B/mammalian target of rapamycin (AKT/mTOR) pathway is activated in part through HIFs, and the pharmacological inhibition of mTOR with rapamycin inhibits melanoma growth in mice [66]. In clinical trials, the BRAF inhibitor vemurafenib (PLX4032) showed promising treatment responses in metastatic melanoma patients with the BRAF V600E mutation [67,68]. However, hypoxia may confer resistance to vemurafenib by activating the hepatocyte growth factor/mesenchymal–epithelial transition factor (HGF/c-Met) pathway in melanoma cells. HIF-1α can induce the expression of HGF and c-Met in various cancer cells [69,70,71]. In melanoma spheroids with hypoxic cores, a concomitant treatment with MSC2156119J, a specific c-Met inhibitor, and vemurafenib reduced the resistance of the melanoma cells to vemurafenib [72]. These studies suggest that blocking BRAF-related pathways may be an effective strategy for treating malignant melanomas in a hypoxic microenvironment. A cDNA microarray analysis of BRAF V600E-positive A2058 melanoma cells cultured under hypoxic conditions showed a differential expression of genes related to the cell cycle and apoptosis [73]. Further studies are needed to elucidate the molecular basis of hypoxia-induced cancer progression in BRAF-mutant melanomas. The Ras family of GTPases is an upstream regulator of BRAF. They are small GTP-binding molecules near the plasma membrane that receive signals from membrane-bound RTKs such as c-Kit. RTKs convert Ras proteins from an inactive GDP-bound to an active GTP-bound form. Conversely, NF1 encodes neurofibromin 1, which promotes GTP hydrolysis and the inactivation of Ras proteins [74]. The oncogenic RAS genes in melanoma cells include NRAS, KRAS, and HRAS. However, mutations in NRAS (~30%), but not KRAS (3%) or HRAS (2%), are common in melanomas. NRAS mutations mainly occur in Q61 and result in the ablation of GTPase activity, leading to the constitutive activation of the protein. Similarly, loss-of-function mutations in NF1 can lead to the sustained activation of Ras proteins [75]. In NRAS-driven melanomas, the overexpression of growth factor receptor-binding protein 2-associated protein 2 (GAB2) has been reported to enhance tumor formation and angiogenesis in vivo. GAB2, in concert with mutant NRAS, promotes angiogenesis by stabilizing HIF-1α at the post-transcriptional level and upregulating VEGF expression under hypoxia-mimicking conditions. In a xenograft mouse model, an intraperitoneal injection of bevacizumab, a humanized anti-VEGF monoclonal antibody, reduced tumor growth [76]. Although the c-Kit mutation is known to activate the PI3K/AKT pathway in melanocytes preferentially, it also strongly activates the Ras/Raf/MEK/ERK cascade under hypoxic conditions. In Melan-a mouse melanocytes, the co-expression of mutant c-Kit and HIF-1α lacking the ODD domain successfully induces oncogenic transformation. The treatment of these cells with imatinib, a c-Kit inhibitor, inhibits the hypoxia-induced proliferation and transformation of melanocytes [77]. The hypoxic regulation of Ras pathway proteins has been reported to some extent in other cell types; however, studies on melanomas are still lacking [78,79,80,81,82]. Interestingly, HRAS and KIT were found to possess putative HRE sequences upstream of their transcriptional start sites [83]. Nonetheless, whether these genes are directly targeted for transcription by HIFs in melanocytes remains unclear. Recently, miRNome and proteome profiling of extracellular vesicles (EVs) isolated from BRAF- or NRAS-mutant melanoma cells cultured under hypoxia revealed distinct changes in several factors that could potentially be tested as biomarkers for melanoma progression. CDKN2A encodes two alternative splicing variants, the p16 inhibitor of CDK4 (p16INK4A) and the p14 alternate reading frame (p14ARF), transcribed from different first exons, 1α and 1β, respectively. p16INK4A inhibits CDK4 and CDK6, preventing S-phase entry and cell cycle progression. p14ARF stabilizes the tumor suppressor p53 by inhibiting mouse double minute 2 (MDM2)-dependent p53 degradation. Thus, both p16INK4A and p14ARF mutations found in melanoma patients are mostly loss-of-function mutations that result in cell growth and proliferation. Similarly, CDK4 mutations promote the G1 to S phase transition by preventing the p16INK4A-mediated inhibition of the CDK4 [45,49]. Recently, it has been shown that the concurrent inactivation of the p16INK4A and p14ARF pathways, along with the activation of the PI3K/AKT pathway, can induce melanocyte transformation. Interestingly, the AKT-mediated transformation of melanocytes occurs only in hypoxic environments. In CDKN2A-null mouse melanocytes, AKT cooperates with HIF-1α to induce in vitro melanocyte transformation and in vivo tumor growth. Furthermore, the inhibition of mTOR downstream of AKT with rapamycin significantly reduced HIF-1α activity and tumor growth [35,84]. In another study, PI3K/AKT and HIF-1α activated Notch1 signaling under hypoxia during melanoma development. The chemical and genetic inhibition of Notch1 suppressed tumor growth in a xenograft melanoma model [85]. Targeting the PI3K/AKT and HIF-1α pathways may be effective for treating melanoma patients with CDKN2A mutations. Genetic polymorphisms resulting in loss-of-function variants of the melanocortin 1 receptor (MC1R) gene are associated with an increased risk of melanomas. MC1R is a G protein-coupled receptor that recognizes α-melanocyte-stimulating hormone (α-MSH) as a ligand and induces MITF via cyclic adenosine monophosphate (cAMP) signaling [86]. MITF, a melanocyte lineage-specific transcription factor, was initially shown to play an important role in melanogenesis through the transcriptional activation of genes involved in melanocyte differentiation. Thus, by producing melanin, MITF protects skin cells from UV radiation-induced DNA damage. However, further studies have shown that MITF is somatically amplified in ~10% of primary cutaneous melanomas and plays a role in promoting the survival of melanoma cells [49,87]. MITF activates nearly 100 genes involved in cell differentiation, apoptosis, proliferation, migration, metabolism, and senescence [88]. Furthermore, cAMP-mediated MITF expression transcriptionally activates HIF-1α in B16-F10 melanoma cells. In addition, MITF upregulates HIF-1α to enhance melanoma cell survival by directly binding to the HIF-1α promoter [89]. Interestingly, in primary melanocytes and UACC62 melanoma cells, MITF expression has been shown to decrease under hypoxia in an HIF-1α-dependent manner. The basic helix–loop–helix family member E40 (BHLHE40, also known as DEC1), a target of HIF-1α, is recruited to the MITF promoter for the transcriptional repression of MITF under hypoxic conditions. This may be a negative feedback mechanism that attenuates oncogenic MITF signaling in melanomas. However, basal MITF expression remains high in the hypoxic tumor microenvironment because of the amplification of MITF itself or other alterations in its upstream regulators [88,90,91]. BCC arises from the excessive growth of basal cells in the stratified epithelium and is the most common type of skin cancer, representing approximately 75% of all skin cancers. The incidence of BCC is increasing by up to 10% per year, probably due to an increased life expectancy and UV exposure [92,93,94]. BCC mainly affects the head and neck (approximately 70–80%) but can also affect the trunk and extremities [95]. Basal cell nevus syndrome (BCNS, also known as Gorlin syndrome) is an autosomal dominant inherited disorder characterized by multiple BCCs, odontogenic keratocysts, skeletal abnormalities, calcified falx cerebri, plantar or palmar pits, and other clinical manifestations [96,97]. This genetic predisposition to BCC has led to the identification of protein patched homolog 1 (PTCH1) as a highly altered (~70%) gene in patients with BCC [98,99,100]. Loss-of-function mutations in PTCH1 activate the hedgehog (Hh) signaling pathway for BCC carcinogenesis. Similarly, mutations in other factors that activate the Hh pathway, such as gain-of-function mutations in the smoothened homolog (SMO), have been frequently found in BCC cases [101]. Accordingly, inhibitors of the Hh pathway, such as vismodegib and sonidegib, have been tested in clinical trials and approved for the treatment of advanced BCCs [102,103,104]. An immunohistochemical study showed that HIF-dependent hypoxia signals were activated in BCC and trichoepithelioma, a benign hair follicle tumor resembling BCC’s clinical and histological features. Representative HIF target genes, such as BCL2-interacting protein 3 (BNIP3), carbonic anhydrase IX (CAIX), glucose transporter 1 (GLUT1), and VEGF, were also found to be positively expressed in BCC tissues [105]. In another IHC study, HIF-1α was upregulated in human BCC samples compared to normal epidermal tissues [106]. In an analysis of histologically heterogeneous BCC patient samples, CAIX was highly expressed in more aggressive types (~60%) of BCC compared to low-risk types (~10%) and was associated with poor relapse-free survival. BCC subtypes with high recurrence rates include basosquamous, micronodular, morpheaform, and infiltrative [107]. In addition to these histopathological analyses, studies on the role of hypoxia in BCC pathogenesis are limited. In other cancers, hypoxia activates the Hh pathway via HIF-1α. For example, in pancreatic cancer, HIF-1α activates Hh signaling in a sonic hedgehog (Shh) ligand-dependent or -independent manner. The genetic or pharmacological inhibition of HIF-1α inhibits the activation of Hh signaling, suggesting the potential use of HIF inhibitors in treating BCC [108,109,110]. SCC is the second most common skin cancer with an increasing incidence. It arises from squamous cells lining the outermost layer of the skin. Non-invasive squamous cell carcinoma in situ, also known as Bowen’s disease, is an early form of skin cancer. Actinic keratosis is a well-known precursor of SCC. Bowen’s disease and actinic keratosis are considered easily manageable diseases; however, if left untreated, they can eventually progress to invasive SCC [111,112,113,114]. Actinic keratosis progresses to cancer at a rate of 0.025–16% per year, depending on the individual lesion [115,116]. In addition, UV radiation-induced mutations in TP53 are frequently found in patients with actinic keratosis and SCC and are considered an early event in SCC development. Hypoxia promotes the proliferation and abnormal differentiation of skin keratinocytes [117,118,119]. In a K14-HPV16 transgenic mouse model, HIF-1α and its downstream target genes were upregulated during epidermal carcinogenesis [120]. Furthermore, in a UV radiation-induced skin cancer model, an HIF-1α knockout in the epidermis reduced tumor formation and the oncogenic transformation of keratinocytes. Furthermore, the DNA repair ability increased upon UV irradiation in HIF-1α knockout mice compared to that in controls [121]. In keratinocytes, HIF-1α transcriptionally activated several factors related to the nucleotide excision repair (NER) pathway, such as xeroderma pigmentosum (XP) group proteins [122]. Indeed, a double knockout of HIF-1α and XPC resulted in the partial restoration of UV-induced tumor development in HIF-1α knockout mice. Moreover, in human skin, HIF-1α expression progressively increased during SCC carcinogenesis [121]. In an IHC analysis, HIF-1α and VEGF expressions were consistently higher in SCC than in normal skin or precancerous lesions. In addition, they were associated with an advanced histological grade [123]. Although HIF-1α is generally thought to promote cancer progression, conflicting findings have also been reported. In a transgenic mouse model, HIF-1α gain-of-function suppressed malignant development and the epithelial–mesenchymal transition in squamous cancers [124]. To utilize HIF inhibitors for the treatment of SCC, more preclinical experiments and detailed studies on molecular mechanisms are needed. Kaposi’s sarcoma-associated herpesvirus (KSHV) is an oncovirus that causes Kaposi’s sarcoma, a cancer that usually develops in the skin and mouth of immunocompromised individuals. A KSHV infection induces lytic viral replication by upregulating HIF-1α and HIF-2α [125,126,127]. KSHV upregulates HIF-2α in the endoplasmic reticulum (ER) to enhance the eukaryotic translation initiation factor 4E family member 2 (eIF4E2)-mediated translation of sarcomagenic proteins [126]. In addition, HIF-2α is known to play an essential role as a member of the hypoxia-regulated eIF4FH translation–initiation complex and its role as a transcription factor [128,129]. RNA sequencing of KSHV-infected cells revealed a 34% overlap in the gene expression signatures between KSHV infections and hypoxia [127]. Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with a high risk of metastasis. It usually appears as a painless nodule on the face, head, or neck in the elderly. Merkel cells are located in the basal epidermal layer and are connected to nerve endings involved in the light touch sensation [130]. In MCC tissue samples, HIF-1α is predominantly expressed at the invading edge of the tumor margin [131]. VEGF2 downstream of HIF was also correlated with MCC tumor size [132]. Consistently, another IHC analysis showed that VEGF-A (91%), VEGF-C (75%), and VEGF-R2 (88%) were highly expressed in MCC patients [133]. Therefore, VEGF-targeting bevacizumab has been proposed as a potential drug for MCC treatment [134]. After a surgical excision with a safety margin is performed to completely remove skin cancer, the resulting defect should be reconstructed, depending on its size, extent, and location. When primary closure is impossible, various reconstructive options, such as skin grafts and local or free flaps, exist. According to the reconstructive ladder principles, split or full-thickness skin grafts are considered simple to cover defects without bone, cartilage, or tendon exposure. Regarding functional and esthetic aspects, local flaps usually have a better tissue match than distant donor sites, with a skin color and texture similar to the defects resulting from cancer removal. A free microvascular tissue transfer should be performed if the defect is too large or complex. Regardless of the reconstruction method (repair with either grafts or flaps), tissue necrosis is one of the most common postoperative complications and may require secondary surgery. It is usually caused by insufficient blood perfusion or ischemia-reperfusion injury [135,136,137,138,139]. The ischemic and hypoxic necrosis of the implanted flaps resulting from an insufficient blood supply is a major problem in reconstructive surgery. In a rat pedicle flap model, preconditioning flaps by injecting a plasmid encoding HIF-1α improved tissue viability and reduced the necrotic area formation [140]. Similarly, in an ischemic mouse flap model, the systemic activation of HIF-1α with the prolyl hydroxylase inhibitor dimethyloxalylglycine (DMOG) increased flap survival by increasing angiogenesis and inhibiting cell apoptosis. HIF-1α protein levels and CD31-positive vessels increased in the skin flaps of DMOG-treated mice. Circulating VEGF and other HIF downstream angiogenic factors also increased in the DMOG group. In addition, the heterozygous deletion of HIF-1α in mice reduced the survival of ischemic skin flaps [141]. PHD2 depletion in keratinocytes stimulated wound healing in mouse skin [142]. Likewise, in murine diabetic skin ulcer models, the stabilization of HIF-1α with hydroxylase inhibitors or iron chelators promoted wound healing [143,144,145,146]. HIF-1α combined with basic fibroblast growth factor (bFGF) could improve random skin flap survival by increasing VEGF expression in rats [147]. The adenoviral delivery of VEGF increased the viable, non-necrotic surface area and blood perfusion in mouse skin flaps [148]. Rivastigmine, a cholinesterase inhibitor, enhanced angiogenesis in skin flaps by upregulating the HIF-1α and VEGF expression. In one such study, laser Doppler flowmetry and lead oxide/gelatin X-ray angiography were used to evaluate the increased perfusion of skin flaps after rivastigmine treatment [149]. Taken together, these studies suggest that HIF stabilizers may potentially inhibit the ischemic necrosis of the skin flaps. However, HIF stabilizers should be used with caution, as they may increase the risk of cancer recurrence [150]. Ischemia-reperfusion injury triggers the release of inflammatory cytokines and ROS. HIF-1α has an overall beneficial effect on flap survival through angiogenesis, but is also known to promote ROS damage and apoptosis during ischemia-reperfusion injury [151]. Several studies have shown that the ischemic preconditioning of flaps by brief periods of ischemia followed by reperfusion increases the success rate of flap surgery [152]. In addition, ischemic preconditioning induces adaptation of the flaps to the expected fluctuations in blood supply after transplantation. In a rat flap model, ischemic preconditioning lowered the necrosis rate and increased the skin flaps’ survival [153]. Furthermore, the injection of therapeutic stem cells or extracellular vesicles has shown protective effects against ischemia-reperfusion injury [154,155,156,157,158,159,160]. In addition, hypoxia-stimulated ADSCs increased the survival of ischemic rat skin flaps [161]. Therefore, using hypoxia-enhanced stem cells and extracellular vesicles could be an effective strategy to treat ischemia-reperfusion injury. Significant efforts have been made to develop inhibitors of the hypoxia pathway for cancer treatment. For example, the VEGF inhibitor bevacizumab has been approved for numerous cancers and has become one of the primary drugs for targeted cancer therapy [162]. In addition, several HIF inhibitors are undergoing phase II and phase III clinical trials [163]. Recently, the FDA approved the HIF-2α inhibitor belzutifan for treating certain cancers associated with von Hippel–Lindau disease, such as renal cell carcinoma, hemangioblastoma, and pancreatic neuroendocrine tumors [164]. However, HIF and VEGF inhibitors require more mechanistic and clinical studies for their application in skin cancer treatment. Conversely, several potential drugs that stabilize HIF, such as roxadustat, are in clinical trials for the treatment of chronic kidney disease-related anemia [165]. HIF stabilizers have the potential to be used for effective reconstruction after skin cancer removal; however, the risk of cancer recurrence must be considered. Recently developed, new techniques to reverse tumor hypoxia may be applicable to skin cancer. A treatment combining hypoxia-activated chemotherapy with PDT has potential for use in hypoxic tumors. PDT works by converting tissue oxygen into ROS, and this oxygen-dependent mechanism limits the efficacy of PDT in the hypoxic TME. In a recent study, the combination of the hypoxia-activated prodrug tirapazamine (TPZ) and near-infrared (NIR) light-induced PDT showed synergistic effects against CT26 murine colorectal cancer cells under hypoxic conditions [166]. The currently used immune checkpoint blockades (ICBs) are effective at treating various cancers, but have some limitations, in part because they are antibody-based therapeutics. For example, pembrolizumab, a monoclonal antibody against programmed cell death protein 1 (PD-1), cannot affect the cytoplasmic or nuclear distributed PD-L1 protein. A novel nanoparticle, IR-LND@Alb, that can selectively accumulate in mitochondria has been suggested as a novel strategy to reduce PD-L1 expression. IR-LND@Alb inhibits PD-L1 and mitochondria complexes to reduce endogenous oxygen consumption, thereby alleviating tumor hypoxia. The reversion of hypoxia helps improve the efficacy of various tumor therapies [167]. BSA-MHI148@SRF nanoparticles have been shown to enhance PDT efficacy by inducing tumor reoxygenation [168]. Similarly, MB@Bu@MnO2 nanoparticles reverse tumor hypoxia to reactivate immunotherapy [169]. Engineered microalgae capable of photosynthesis can treat cancer cells that are resistant to radiation and phototherapy by increasing local oxygen levels in the hypoxic TME [170]. Conversely, certain drugs can be used based on their hypoxia-dependent cytotoxic effects. Perfluorocarbon nanoparticles can boost the effect of hypoxia-based agents (HBAs) by sustaining the hypoxic TME [171]. In conclusion, a comprehensive understanding of hypoxia biology is needed to accelerate the development of new therapies for patients with skin cancer.

PMC10003004

Muhit Rana,Nimet Yildirim,Nancy E. Ward,Stephanie P. Vega,Michael J. Heffernan,Avni A. Argun

Highly Specific Detection of Oxytocin in Saliva

02-03-2023

oxytocin,aptamer,peptide detection,electrochemical,sensor,saliva

Oxytocin is a peptide neurophysin hormone made up of nine amino acids and is used in induction of one in four births worldwide (more than 13 percent in the United States). Herein, we have developed an antibody alternative aptamer-based electrochemical assay for real-time and point-of-care detection of oxytocin in non-invasive saliva samples. This assay approach is rapid, highly sensitive, specific, and cost-effective. Our aptamer-based electrochemical assay can detect as little as 1 pg/mL of oxytocin in less than 2 min in commercially available pooled saliva samples. Additionally, we did not observe any false positive or false negative signals. This electrochemical assay has the potential to be utilized as a point-of-care monitor for rapid and real-time oxytocin detection in various biological samples such as saliva, blood, and hair extracts.

Highly Specific Detection of Oxytocin in Saliva Oxytocin is a peptide neurophysin hormone made up of nine amino acids and is used in induction of one in four births worldwide (more than 13 percent in the United States). Herein, we have developed an antibody alternative aptamer-based electrochemical assay for real-time and point-of-care detection of oxytocin in non-invasive saliva samples. This assay approach is rapid, highly sensitive, specific, and cost-effective. Our aptamer-based electrochemical assay can detect as little as 1 pg/mL of oxytocin in less than 2 min in commercially available pooled saliva samples. Additionally, we did not observe any false positive or false negative signals. This electrochemical assay has the potential to be utilized as a point-of-care monitor for rapid and real-time oxytocin detection in various biological samples such as saliva, blood, and hair extracts. Oxytocin (OT) is a neuropeptide hormone best known for its role in the facilitation of childbirth through the induction of myometrial smooth muscle contractions [1,2]. It also plays an essential role in the later stages of life, affecting various health conditions and complex social behaviors. These include affiliation, sexual behavior, social recognition, social bonding, parturition, lactation, appetite regulation, aggression, depression, obesity, and social deficit of autism spectrum disorder (ASD) [3,4,5,6,7]. Recent scientific evidence indicates that dysfunction of the oxytocin system could be the underlying cause for the pathogenesis of insulin resistance and dyslipidemia and contribute to weight gain in some genetic obesity conditions such as the Prader–Willi syndrome (PWS). The circulating peripheral oxytocin levels were reported to be higher in children with PWS as compared to their healthy siblings; in contrast, the oxytocin levels were lower in individuals with anorexia [5,8,9,10,11,12,13,14,15]. Oxytocin is also involved in regulation of metabolic energy and linked to late-onset obesity in an oxytocin receptor-deficient mice model [12]. Therefore, monitoring oxytocin levels could play a therapeutic role in management of obesity and diabetes. Besides, it has been suggested that oxytocin, known to promote mother-infant bonds, may be implicated in the social deficit of autism [6]. The researchers recently reported that oxytocin levels were significantly lower in individuals with ASD as compared to control subjects [16,17,18]. Some features of ASD have also been linked to disturbance of the oxytocin system in the body [19,20,21]. Exogenous administration of oxytocin has improved various outcomes associated with social responsiveness, including eye contact, emotion recognition, social cognition, and neural circuitry associated with social awareness [17,18,22]. OT is of particular interest in the study of childbearing women, as it has a role in the onset and course of labor and breastfeeding. One in four births worldwide (more than 13 percent in the United States) is induced with oxytocin [23]. Exogenous administration of oxytocin is critical in a clinical setting for induction and augmentation of labor as well as management of postpartum uterine atony/hemorrhage [24,25,26,27,28]. When oxytocin levels are high, strong contractions occur that reduce the chance of bleeding or postpartum hemorrhage. A double-blinded clinical trial on 200 participants showed oxytocin’s role in reducing blood loss during cesarean delivery and the investigators reported that oxytocin infusion is an appropriate regimen [29,30]. Another clinical study by the Cohen Group showed that obese patients required more oxytocin than lean women during the first stage of successful labor induction, indicating that the current clinical practice can benefit from dosage optimization [31]. Oxytocin levels also have great significance during the perinatal period. For example, endogenous oxytocin is a potential biomarker for the prediction of the type of labor and risk assessment of premature labor. Perinatal screening after the 32nd week of pregnancy can help predict premature labor in high-risk pregnancies [32]. Increased levels of circulating peripheral oxytocin levels are linked to postpartum breastmilk production as well as a decrease in the frequency of migraine headaches over the course of pregnancy [33,34,35]. Additionally, a group of physicians and researchers from Northwestern and Indiana University conducted multi-centered clinical research on 66 pregnant women and reported that elevated oxytocin levels during pregnancy may signal postpartum depression (PPD) [36]. Oxytocin also plays a critical role as a neurotransmitter. It mediates the brain’s dynamic function and various complex social behaviors, including affiliation, sexual behavior, social recognition, and aggression. Oxytocin is secreted in the hypothalamus along with a similarly structured nonapeptide called vasopressin. Due to the similar structure of these two neuropeptides, they often compete to bind with existing antibodies, resulting in poor specificity for current immunoassays. Currently, two existing immunoassays (radioimmunoassay-RIA and enzyme immunoassay-EIA) are insufficient for sensitive and specific detection of oxytocin. This problem can be resolved with mass spectrometry combined with liquid chromatography (LC/MS); however, micro dialysis of the sample and lengthy retention times make this method unsuitable for practical oxytocin monitoring. Despite being one of the most widely utilized drugs in obstetrics, there is currently no instrument capable of point-of-care (POC) detection of oxytocin. While its pharmacokinetics has been extensively studied for both intravascular (IV) and intranasal (IN) administration, its dose-effect response has been poorly understood. The research studies, as well as the clinical significance of perinatal oxytocin, suggest that accurate and real-time measurement of peripheral oxytocin levels may help develop pharmacokinetic models to facilitate a better understanding of the effects of oxytocin and optimize oxytocin use. [37,38] Therefore, it would be extremely valuable for researchers and medical professionals to have a simple and practical assay that would accurately determine the peripheral levels of oxytocin in pregnant women and guide clinical plans for oxytocin administration. Clinical researchers could also benefit from the development of such a tool to aid in quantifying peripheral oxytocin levels toward a better understanding of the long-term effects of exogenous oxytocin on mother and child. The biological levels of oxytocin in bodily fluids such as saliva are very low. The physiological level of peripheral oxytocin is only on the order of 1–300 pg/mL, making it difficult to detect it with high specificity using the current immunoassay-based methods. These antibody-based methods also suffer from significant cross-reactivity by arginine vasopressin, another similar neuropeptide hormone [39,40,41]. Other laboratory-based methods, such as LC-MS/MS, exist but they require complex instrumentation and sample processing steps, increasing the cost and turnaround times. As illustrated in Figure 1, we have developed an aptamer-based electrochemical assay that enables the measurement of oxytocin in minimally invasive biological samples (e.g., commercially available pooled saliva samples) with high sensitivity and specificity while lowering the detection limits to pg/mL levels. Upon running a rapid (<2 min) electrochemical algorithm, the oxytocin content is quantified. This study demonstrates the electrochemical oxytocin detection in both lab samples and exogenously enriched saliva samples with a limit of detection (LOD) of 1 pg/mL. Table 1 shows the comparative performance of our electrochemical sensor assay with other available technologies, including the commercially available ELISA kit. Aptamers are synthetic, single-stranded DNA or RNA oligonucleotides with very high affinity, selectivity, and specificity to low molecular weight molecules, macromolecules such as proteins, and even whole cells [46]. Aptamers have been generated with binding constants (Kd) to their targets that are in the nanomolar range, comparable to antibody-antigen values. Commonly used bioreceptors (enzymes and antibodies) are mostly unavailable for small peptide targets, especially for short-chain peptides, making aptamers excellent candidates for bimolecular recognition due to the small size of nucleic acids and their versatile in vitro development and synthesis for any targeted peptide. In comparison to antibodies and enzymes, aptamers are also less prone to degradation and denaturation. Aptamer development has traditionally been via an iterative process called systematic evolution of ligands by exponential enrichment (SELEX); however, this approach has limited aptamer development studies for new targets to academic laboratories or specialized companies. The emergence of oxytocin aptamer as “Raptamers” from Raptamer Discovery Group has been a game changer in this field to allow efficient aptamer development for a wide range of targets. We have employed this non-SELEX strategy in our study to develop the first aptamer specific to the oxytocin molecule. In contrast to SELEX, the Raptamer strategy employs a bead-based library as the basis for the rapid selection of affinity agents for targeted biomarkers with standard laboratory practices. The Raptamer selection process has the advantage of using a single round of PCR amplification; this is in contrast to the multiple rounds of PCR in SELEX which can lead to PCR bias in the aptamer selection. In addition, Raptamer library beads incorporate proprietary modified nucleotides in the random region; these modified bases provide a more functionally diverse composition for enhancement of interactions with target molecules. In our study to develop an oxytocin aptamer, the combinatorial library (typically ~10 × 10−7 members) was initially mixed with magnetic particles functionalized (tagged) with oxytocin molecule. Isolation from magnetic separation provided the first stage selection of library beads, and the putative Raptamers were released and subjected to a secondary pull-down to remove ‘false-positive’ candidates. The true Raptamers were identified using next-generation sequencing (NGS) methods and the comparison of the amount of each sequence after pull-down to its initial presence in the solution pool. The most abundant sequences were then synthesized with the appropriate oligonucleotide modifications and end modifications such as biotinylation. After the initial bead assay and the NGS stage, eight putative Raptamer sequences for oxytocin were obtained. All of the eight putative Raptamers were biotinylated, immobilized on streptavidin-coated carbon screen-printed electrodes (SPE), and characterized for oxytocin binding using both electrochemical impedance and direct electrochemical oxidation as demonstrated in Figure 1. Oxytocin was initially introduced to the Raptamer-modified SPEs (a-SPE) in controlled buffer solutions and incubated for durations varying between 1 and 10 min. After a brief rinsing step, aptamer-bound oxytocin resulted in impedance changes on the surface of the electrode (Figure A1) and the magnitude of this change was used to rank the affinity of each Raptamer as shown in Table 2 and Figure A2. This initial Raptamer validation step allowed us to rapidly down select four Raptamers for further characterization using an electrochemical oxidation method (utilizing the electrochemically active tyrosine group in oxytocin) and an optical particle aggregation method (using wavelengths shifts of functionalized gold nanoparticles). All the measurements were recorded as Nyquist plots in a 0.1 M PBS buffer solution containing 5 mM [Fe(CN)6]3/4 redox pair (1:1 M ratio). The electrochemical impedance spectroscopy (EIS) spectra were conducted over a frequency range from 10 kHz to 0.1 Hz using an AC voltage with amplitude of 10 mV, superimposed on a DC potential of 0.15 V vs. Ag/AgCl. Affinity levels of each oxytocin aptamer (Raptamer) to oxytocin is denoted as “-” for no affinity, “+” for weak affinity and “++” for strong affinity as shown in Table 2. We performed an independent validation of one of the candidates Raptamers, and then we have developed a robust, non-electrochemical procedure in house to validate the performance of this Raptamer. We utilized a well-established gold nanoparticle colorimetric assay, which proved to be an independent confirmation of aptamer binding. Our detection strategy [47] along with the spectroscopic information to characterize and validate each Raptamer is demonstrated in Figure 2. Briefly, citrate-reduced gold nanoparticles (AuNP) possess negative charges and their strong inter-particle electrostatic repulsive forces make them retain a characteristic red color in the solution. Upon mixing, the aptamer adsorbs on negatively charged AuNP and protects the nanoparticle against positively charged salt (Na+)-induced aggregation with its negative phosphate backbone. Conversely, when target biomarker (oxytocin) is introduced, the adsorbed aptamer desorbs from AuNP surface and strongly binds to the target, leaving AuNP unprotected in the solution. In presence of ~150 mM NaCl, the remaining AuNP negative charge is easily neutralized with Na+, leading to a loss in electrostatic repulsion. As a result, the inter-particles distance reduces and a salt-induced aggregation takes place and leads to a plasmon effect reflecting in color transition (red to purple to clear) in less than a minute [48,49,50]. In fact, the gold nanoparticles surface plasmon resonance peak (OD520) is reduced and the peak is shifted to a longer wavelength region (OD700) with increasing amount of Na+ ions. This simple mechanism allowed us to discriminate aptamer functionality in complex biological matrices like saliva based on the quantitative information obtained using UV-Vis spectroscopy for cross-validation. With the colorimetric assay, we performed sensitivity and specificity analysis of Raptamer gOT-1B. Figure 2 and Figure A3 with inset demonstrates a dose-dependent linear correlation between the absorbance reading (OD520) and various oxytocin levels. As expected, a more drastic color change was observed when higher dosing of OT was introduced in buffer. According to the absorbance reading at 520 nm wavelength, a calibration curve was obtained with a coefficient of determination (R2 value) of over 0.98 after linear regression. These findings prove that Raptamer gOT-1B (one of the putative aptamers) is capable of distinguishing different levels of oxytocin target. In this gold nanoparticle aptamer assay, when oxytocin was exogenously exposed to Raptamer-bound nanoparticles, a signal reduction at OD520 confirmed the binding event as shown in Figure 3. When a cocktail of oxytocin and vasopressin was tested exogenously, the absorbance reading showed nearly no difference compared to the result when only oxytocin was present. It is crucial to distinguish oxytocin from vasopressin since the two molecules differ only by two peptide residues while both contain the signal-generating tyrosine in their structures [1]. In this case, the absence of any false positive or false negative detection verified the specificity of the chosen aptamer. The specificity demonstrated by our novel technology offers a distinct advantage over commercially available immunoassays such as EIA or RIA [41]. A reduction in absorption was also observed when additional oxytocin was added endogenously, confirming the proper function of aptamer in real saliva environment. At this point, we have successfully validated the functionality of the Raptamer candidate gOT-1B identified previously for oxytocin detection both exogenously in buffer and endogenously in saliva. With the selected and validated Raptamer, we continued to develop an electrochemical assay for oxytocin detection. As highlighted in Figure 4, oxytocin aptamer gOT-1bB produced sufficient and distinguishable signals when binding with exogenously expressed oxytocin. The sensitivity analysis showed a dose-dependent response curve as demonstrated in Figure 4 (right panel). We obtained a calibration curve to correlate the electrochemical signal with oxytocin concentrations in reaction buffer environment. As Figure 5 shows, when oxytocin was exogenously administrated in saliva, the aptamer on the carbon SPE surface bound specifically to oxytocin, and the tyrosine residue of the peptide produced a peak current as signal readout as shown in Figure 4. Such peak current (readout signal) was only observed when exogenously oxytocin was introduced into test samples both in buffer and control saliva environment [51,52]. On the other hand, adding vasopressin to saliva did not produce any signals, confirming that oxytocin was the only target. In this study, we successfully established an electrochemical sensor and a technology platform for future development of a rapid and accurate instrument capable of measuring oxytocin level in peripheral body fluids at point-of-care. This novel technology utilizes Raptamer-modified disposable carbon electrodes to achieve preeminent sensitivity of 1 pg/mL, which is on the order of laboratory-based technologies such as LC-MS and more sensitive than the commercially available Enzo Oxytocin ELISA Kit [41]. Cross-validated by electrochemical impedance spectroscopy and a nanoparticle colorimetric assay, we confirmed that this electrochemical detection method is also highly specific to oxytocin (1 µg/mL) with 100× specificity over vasopressin (>100 µg/mL) as shown in Figure 5. While the current commercially available immunoassays such as RIA and EIA often fail to distinguish vasopressin and oxytocin, our approach is able to capture the structural difference of these two similar molecules. Invitrogen’s Ultrapure DNase-free, RNase-free DEPC treated water (catalog # 4387937) was used in all studies. 10X PBS, NaCl, MgCl2, and all other reagents were purchased from Sigma-Aldrich, St. Louis, MO 63103, USA. Oxytocin peptide (ab120186) is purchased from Abcam Inc. Cambridge, MA 02139, USA. To avoid any DNase contamination, DNA Away (DNA Surface Decontaminant) was purchased from Thermo Scientific and used before performing any experiment. Streptavidin screen-printed carbon electrodes (Catalog# Dropsens DRP-STR110) were purchased from Metrohm USA Inc., Riverview, FL, USA. The USB-powered potentiostat (Model number: EmStat3+, Potential range ±3 V or ±4 V, and current ranges 1 nA to 10 mA or 100 mA) was obtained from PalmSens BV, Houten, Netherlands. A Raptamer (formerly X-Aptamer) Selection Kit was purchased from Raptamer Discovery Group, Houston, TX (RDG; formerly AM Biotechnologies; Houston, TX). This kit employs a proprietary bead-based library, containing modified DNA nucleotides within the random region, as the basis for the rapid selection of affinity agents for several targets in parallel using standard laboratory tools. All commercial de-identified pooled saliva samples were obtained from BioIVT (Westbury, NY, USA) and tested at a BSL-2 lab facility. For the primary Raptamer selection, a non-SELEX bead-based selection approach was utilized. In this selection, a bead-based DNA oligonucleotide library was mixed with oxytocin-coated magnetic particles and incubated for 90 min at room temperature. The library beads containing oligonucleotides that bound to oxytocin were isolated via magnetic separation. The isolated library beads were resuspended in 1N NaOH and incubated at 65 °C for 30 min to cleave the oligonucleotides from the beads. The cleaved oligonucleotides were then subjected to a secondary pull-down selection to remove ‘false-positive’ binders and to enrich the pool for Raptamers with high affinity to oxytocin. Following PCR amplification of the enriched and control pools and next-generation sequencing (PrimBio Research Institute, Garnet Valley, PA, USA), the candidate oxytocin Raptamers were identified by a proprietary analysis method (Raptamer Discovery Group, LLC, Houston, TX, USA). This method identifies the sequences enriched in the primary target pool compared to the control(s), which consist of any negative target controls and the magnetic particle (not containing target) control. These enriched oxytocin candidate Raptamers were then synthesized with the appropriate modified nucleotides included in the sequences. Gold nanoparticles (AuNPs) were synthesized using the standard citrate reduction method. This nano-plasmonic test was designed according to the published articles [49,53,54,55]. Briefly, 2 mL of 50 mM HAuCl4 was added into 98 mL of boiling DI water in an Erlenmeyer flask. Then 10 mL of 38.8 mM sodium citrate was added, and the mixture was stirred until the color turned wine-red. The synthesized homogenous gold nanoparticles were characterized using UV-Vis spectroscopy and stored at 4 °C. All aptamers were reconstituted in 1× PBS, 2 mM MgCl2, pH 7.4, and targets were resuspended in 1 × PBS. All oxytocin aptamers were pre-heated at 95 °C for 5 min to remove any dimerization before utilizing in any experiment. For aptamer validation, 1 µL of 10 µM aptamer is added to 98 μL of 11 nM AuNPs (~13 nm size) to a final volume of 99 µL and incubated at room temperature (RT) for 5 min. After 5 min, 1 µL of 10 µM target (OT) is added to the 99 μL of pre-incubated Aptamer/AuNP solution for a final volume of 100 μL, resulting in final aptamer and target concentrations of 100 nM. After an additional 15–20 min of incubation at RT, 3 µL of 1 M of NaCl is added to 100 µL of the nanoparticle solution to a final concentration of ~30 mM Na+. After the addition of NaCl, the color transition was observed within 1 min or less and recorded with a photograph. In the presence of salt addition, when the aptamer binds to the specific target, it desorbs from the gold nanoparticle surface, leaving gold nanoparticles unprotected and easily neutralized by Na+ and showing a color changed from red to purple. Similarly, if the aptamer does not bind to its target, the gold nanoparticle’s color will be unchanged upon salt (Na+) addition. The resulting nanoparticle assembly’s change in the optical density (OD) at 520/700 nm (Abs 520/700) was used to plot the aggregation rate and degree. The UV-Vis spectrum of each sample was measured in 96 well plates using BioTek microplate reader (Gen5 microplate data collection and analysis software, BioTek Science Company, Winooski, VT). Control experiments were performed in the absence of target (only Aptamer + AuNP + adjusted reaction buffer, 1 × PBS, 2 mM mgCl2, pH 7.4). We utilized a similar procedure for detecting and validating all eight-oxytocin candidate Raptamers in buffer and saliva samples. In the previous study, the change in OD ratio at 520/700 nm of the resulting nanoprobe complex assembly was used to determine the limit of detection (3 σ/slope) where σ is the standard deviation of controls while slope is obtained by linearly fitting the calibration curve [53,54]. The limit of detection (LOD) is calculated, followed by the 3-sigma rule. The equation is, LOD =3.3 × standard deviation of the regression line (σ) /Slope(S). A 3σ-rule is widely used to determine the signal-to-noise ratio for estimating the detection limit [54,55,56,57,58,59]. For sensitivity measurement, studies were also performed using various amounts (0, 10, 40, 70, 100, 140 ng/mL) of target OT in 100 μL of solution and, color changes were recorded with in 1 min after incubation with ~30 mM NaCl. Control experiments were performed in the absence of target OT. We performed similar procedure to detect oxytocin in Saliva where we spiked various amounts of target in presence of fixed aptamer concentration. The OD value at 520/700 nm and the pictures of the nanoparticle suspensions were recorded. All experiments were performed in triplicate (n = 3) using 96 well plates. For specificity measurements, individual OT Raptamers with their target and/or non-target analyte with a ratio of Raptamer: target = 1.4:1 (for buffer/Saliva) and evaluated to verify its false positive and false negative binding performance. The change in OD value at 520/700 nm was measured and plotted. For electrochemical sensitivity measurement, various concentrations (1 pg/mL to 100 pg/mL) of target oxytocin were tested, and a dose-dependent calibration curve with improved sensitivity (R2 = 0.9921) is observed from saliva samples. The assay’s specificity and cross-reactivity is evaluated in presence of non-target (Vasopressin) with saliva samples. A complex cocktail mixture of non-target peptide was prepared to show that the assay can detect only the targeted oxytocin in vitro PBS buffer as well as in exogenously enriched commercial saliva samples. The unprocessed (no anticoagulant/filtration, storage condition at −20 °C or colder) human saliva samples (de-identified, pooled samples sourced from BioIVT) were utilized to demonstrate the assay preclinical utility. Prior testing, 70 µL of 400 nM oxytocin aptamer in 1× PBS 2 mM MgCl2 is loaded on s-SPEs (prior washed with 1× PBS) for at least 10 min, then 70 µL (35 µL saliva + 35 µL of 1× PBS, 2 mM MgCl2) loaded on oxytocin aptamer immobilized streptavidin (s)-SPEs. Detection time is less than 5 s. The electrochemical Square Wave Voltammetry (SWV) parameters are: Current: 1 mA; T equilibration: 0 s; E begin: 0.0 V; E end: 1.5 V; E step: 0.005 V; Amplitude: 0.05 V; Frequency: 15.0 Hz.

PMC10003005

Nabilah Zulkefli,Che Nur Mazadillina Che Zahari,Nor Hafiza Sayuti,Ammar Akram Kamarudin,Norazalina Saad,Hamizah Shahirah Hamezah,Hamidun Bunawan,Syarul Nataqain Baharum,Ahmed Mediani,Qamar Uddin Ahmed,Ahmad Fahmi Harun Ismail,Murni Nazira Sarian

Flavonoids as Potential Wound-Healing Molecules: Emphasis on Pathways Perspective

27-02-2023

wound healing,flavonoids,pathways,signaling,scar,natural products

Wounds are considered to be a serious problem that affects the healthcare sector in many countries, primarily due to diabetes and obesity. Wounds become worse because of unhealthy lifestyles and habits. Wound healing is a complicated physiological process that is essential for restoring the epithelial barrier after an injury. Numerous studies have reported that flavonoids possess wound-healing properties due to their well-acclaimed anti-inflammatory, angiogenesis, re-epithelialization, and antioxidant effects. They have been shown to be able to act on the wound-healing process via expression of biomarkers respective to the pathways that mainly include Wnt/β-catenin, Hippo, Transforming Growth Factor-beta (TGF-β), Hedgehog, c-Jun N-Terminal Kinase (JNK), NF-E2-related factor 2/antioxidant responsive element (Nrf2/ARE), Nuclear Factor Kappa B (NF-κB), MAPK/ERK, Ras/Raf/MEK/ERK, phosphatidylinositol 3-kinase (PI3K)/Akt, Nitric oxide (NO) pathways, etc. Hence, we have compiled existing evidence on the manipulation of flavonoids towards achieving skin wound healing, together with current limitations and future perspectives in support of these polyphenolic compounds as safe wound-healing agents, in this review.

Flavonoids as Potential Wound-Healing Molecules: Emphasis on Pathways Perspective Wounds are considered to be a serious problem that affects the healthcare sector in many countries, primarily due to diabetes and obesity. Wounds become worse because of unhealthy lifestyles and habits. Wound healing is a complicated physiological process that is essential for restoring the epithelial barrier after an injury. Numerous studies have reported that flavonoids possess wound-healing properties due to their well-acclaimed anti-inflammatory, angiogenesis, re-epithelialization, and antioxidant effects. They have been shown to be able to act on the wound-healing process via expression of biomarkers respective to the pathways that mainly include Wnt/β-catenin, Hippo, Transforming Growth Factor-beta (TGF-β), Hedgehog, c-Jun N-Terminal Kinase (JNK), NF-E2-related factor 2/antioxidant responsive element (Nrf2/ARE), Nuclear Factor Kappa B (NF-κB), MAPK/ERK, Ras/Raf/MEK/ERK, phosphatidylinositol 3-kinase (PI3K)/Akt, Nitric oxide (NO) pathways, etc. Hence, we have compiled existing evidence on the manipulation of flavonoids towards achieving skin wound healing, together with current limitations and future perspectives in support of these polyphenolic compounds as safe wound-healing agents, in this review. The skin is the largest organ in the human body in terms of surface area. It protects internal tissues from mechanical damage, microbial infection, UV light, and extreme temperatures [1]. A wound is an injury to the integument or underlying structures; it is the visible outcome of individual cell death or damage, which may or may not result in a loss of skin integrity, impairing the tissue’s physiological function. When the natural structure and function of the skin are damaged, injuries occur [2]. When an injury occurs on the skin, there are complex interactions involving different cell types, cytokines, mediators, and the vascular system as parts of a natural physiological reaction that occur in wound healing. Wounds are classified as either acute or chronic based on the root causes and effects of each. An acute wound is on in which there is a quick loss of skin integrity, which is frequently due to trauma or surgery. Any surgical wound that heals by primary intention is considered an acute wound, as is any traumatic or surgical wound that heals by secondary intention. An acute wound is anticipated to proceed through the stages of typical healing, leading to the wound’s closure. Although a chronic wound is a wound that does not heal in a timely and orderly manner, resulting in anatomic and functional integrity loss. A chronic wound is “frozen” in the inflammatory phase for longer than the typical estimated healing time (4 weeks) and does not heal or react to treatment. This pathologic inflammation results from a delayed, ineffective, or disorganized healing process. Both intrinsic and extrinsic variables, such as drugs, poor diet, comorbidities, or incorrect dressing options, can cause a wound to take longer to recover [3]. To further comprehend chronic wounds, the three types of these injuries include pressure ulcers, diabetic ulcers, and vascular ulcers (such as venous and arterial ulcers). Each of these wounds has some commonalities, such as persistent infections, prolonged or severe inflammation, the development of drug-resistant microbial biofilms, and the incapacity of dermal and/or epidermal cells to react to reparative stimuli [4]. It is understood that pressure ulcers can develop over pressure points, such as on the heel of a bedridden patient or on the side of the foot from wearing tight shoes. Conventionally, any ulcer in a diabetic patient is interpreted as a diabetic ulcer. However, vascular reflux is most likely the cause of ulcers that have developed at the ankle, calf, or pretibial sites [5]. As for an acute wound, it is a skin injury that occurs suddenly rather than gradually. It heals at the normal wound-healing rate, which is predictable and expected. Acute wounds can occur anywhere on the body and range in severity from minor scratches to deep wounds that damage blood vessels, nerves, and muscles [6]. According to various research reports and data published by Mission Regional Medical Center in 2020, it was estimated that around 6.7 million people in the world were suffering from chronic wounds. The global chronic wound care market is projected to grow from USD 12.36 billion in 2022 to USD 19.52 billion by 2029, at a CAGR of 6.7% in the forecast period [7]. On a slightly different note, treatment for wounds that cause scarring is as crucial as chronic wounds. This is due to the immense numbers of patients, which is estimated to be around 100 million patients per year in the developed world, that were affected by scars from 55 million elective surgeries and 25 million trauma-related surgeries [8]. The hunt for the best wound-healing treatment has long been a goal of research on wound-healing therapy including surgical, non-surgical, and drug treatments. With an emphasis on wound-healing drugs, commonly used drugs are non-steroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen, warfarin, colchicine, aspirin, (antiplatelets), prednisolone (corticosteroids), heparin (anticoagulants), nicotine, cocaine, and adrenaline (vasoconstrictors). However, there are some drawbacks from these drugs; for example, vasoconstrictors cause tissue hypoxia by adversely affecting the microcirculation, leading to impaired wound healing. Vasoconstrictors such as nicotine, cocaine, adrenaline (epinephrine), and ergotamine should be avoided in patients with acute, surgical, or chronic wounds [9]. In the early 19th century, nicotine and cocaine were both used medicinally, but cocaine was outlawed in the US in 1914 due to its hallucinogenic properties. Additionally, nicotine has been highlighted as a potential contributor to pharmaceutical overreliance [10,11]. In 1808, ergotamine was widely used to precipitate childbirth and to control post-partum hemorrhage due to its remarkable uterotonic and vasoconstrictor effects [12]. The European Medicines Agency’s Committee for Medicinal Products for Human Use (CHMP) has suggested prohibiting the use of medications that include ergot derivatives. Because the hazards outweigh the benefits in these indications, these medications should no longer be used to treat a variety of illnesses involving blood circulation issues. Therefore, natural-product-based treatments have been naturally explored for their ability to serve the optimum effects of wound healing to patients accordingly. Flavonoids, which are prominently known for their wound-healing properties, have recently been reported to be implemented in numerous formulations, topical ointments, and dressings for wound healing [13,14]. To date, flavonoids for wound healing have been thoroughly discussed and reported through various pathways such as Wnt/β-catenin, Hippo, TGF-β, Hedgehog, JNK, (Nrf2/ARE, NF-κB, MAPK/ERK, Ras/Raf/MEK/ERK, PI3K/Akt, NO, etc. [15]. Thus, this review sets out to establish knowledge and thoroughly discuss the flavonoids and their underlying mechanisms in wound-healing treatments. Wound healing is a multi-phased process that occurs when the normal anatomical structure and function of skin tissues are disrupted. Inflammation, granulation, wound shrinking, collagen creation, epithelial closure, and scar formation are all part of the process. The smoothness of these phases promotes wound healing and restores the skin’s previously compromised anatomical condition and function [16]. Wound healing is a four-phase process that involves a complicated series of reactions and interactions between cells and mediators; these phases are hemostasis, inflammation (0–3 days), proliferation (3–24 days), and maturity (24 to 365 days). Figure 1 depicts the physiological wound-healing phases. These phases and their physiological functions must occur in the correct order, at a specified moment, and at an optimal intensity for a specific length. In the first phase (bleeding and hemostasis), hemostasis occurs immediately after bleeding and reduces blood flow by constricting blood vessels to stop bleeding following vascular injury. The phenomenon that subsequently occurs is the aggregation of platelets, degranulation, and the production of fibrin, which is also known as thrombus. However, in the second phase (inflammation), the events are the release of cytokines, growth factors, infiltration of lymphocytes, neutrophils, monocytes, and their differentiation into macrophages in the area, causing hemostasis and acute inflammation in the area of a wound. The third phase is proliferation; the occurrences are increases in the keratinocyte, fibroblast, and endothelial and extracellular matrix (ECM) production; re-epithelialization; angiogenesis; collagen synthesis; and leukocyte migration and proliferation in the wound area. The last phase serves for remodeling and maturity in that the stretching and pulling forces interact with the scar tissue. Meanwhile, vascular maturation, regression, and collagen remodeling occur, thus helping collagen regain the normal alignment needed [17]. In more detail, the initial phase of hemostasis begins with vascular constriction and fibrin clot formation shortly after injury. Pro-inflammatory cytokines and growth factors such as transforming growth factor (TGF), platelet-derived growth factor (PDGF), fibroblast growth factor (FGF), and epidermal growth factor are released by the clot and surrounding wound tissue (EGF). After the bleeding has been stopped, inflammatory cells migrate into the wound (chemotaxis) and initiate the inflammatory phase, which is marked by the successive infiltration of neutrophils, macrophages, and lymphocytes [18]. Neutrophils are important for clearing invading microorganisms and cellular debris from wounds, but they also produce chemicals such as proteases and reactive oxygen species (ROS), which can cause extra bystander damage. Meanwhile, macrophages are involved in wound healing in a variety of ways. Macrophages release cytokines in the early stages of a wound, which increase the inflammatory response by attracting and activating extra leukocytes. Macrophages are also responsible for generating and removing apoptotic cells (such as neutrophils), allowing inflammation to be resolved. As macrophages remove apoptotic cells, they undergo a phenotypic shift to a reparative state, which encourages keratinocytes, fibroblasts, and angiogenesis to aid tissue regeneration. In this way, macrophages facilitate the transition to the proliferative phase [19]. The proliferative phase is characterized by epithelial proliferation and migration across the provisional matrix within the wound, and it usually follows and overlaps with the inflammatory phase (re-epithelialization). The most significant cell types found in the reparative dermis are fibroblasts and endothelial cells, which support capillary expansion, collagen synthesis, and the formation of granulation tissue at the site of damage. Fibroblasts in the wound bed create collagen, glycosaminoglycans, and proteoglycans, all of which are important components of the extracellular matrix (ECM). Wound healing reaches the ultimate remodeling phase after vigorous proliferation and ECM synthesis, which can continue for years. During this phase, many of the newly formed capillaries regress, and the wound’s vascular density returns to normal. One of the most important aspects of the remodeling phase is ECM remodeling to resemble normal tissue architecture. The wound physically shrinks during the healing process, which is thought to be mediated by contractile fibroblasts (myofibroblasts) that develop in the injury [18,20]. Wound healing is a burden and a cost to a country’s healthcare system, potentially arising because of diabetic ulcers or accidents, as opposed to cuts that occur on a routine basis. According to reports, more than 13 million people worldwide experience chronic wounds each year, and the number of patients affected is steadily growing as the world’s population ages [21]. Chronic wounds of the lower leg are notoriously difficult to heal, resulting in decreased patient satisfaction, increased morbidity and mortality, and a significant rise in healthcare costs [22]. The situation worsened during the coronavirus (COVID-19) pandemic, which wreaked havoc on worldwide healthcare, particularly wound care [23]. Furthermore, the wound-healing process might also slow down due to systemic factors such as poor sleep habits, poor nutrition, less exercise, and a high predilection for the use of alcohol, cigarettes, and other drugs. Aside from systemic factors, local factors, such as oxygenation, infection, foreign bodies, and venous sufficiency, might also cause wound-healing problems. All of these variables may contribute to the slowing of the healing process [17,24]. On a positive note, extensive studies have been conducted on exploring the potential of natural compounds with anti-inflammatory, antioxidant, anti-bacterial, and pro-collagen production capabilities as wound-healing agents. The presence of bioactive phytochemicals such as alkaloids, essential oils, flavonoids, tannins, saponins, and phenolic compounds in natural resources makes it possible to exploit all of their bioactive qualities [16]. Several studies employing medicinal plants have recently discussed the creation of new resources and technologies with the potential to heal a variety of acute and chronic wounds with minimum side effects, ease of administration, increased efficacy, and cheaper treatment costs for patients [25,26,27] Flavonoids are one of the most important and promising families of natural compounds for treating skin lesions [28,29]. Regrettably, the management of both acute and chronic wounds continues to be one of the most challenging healthcare issues in the world. Wounds of all forms, including burns, continue to be a major public health concern in both developing and industrialized countries [30]. Additionally, poor lifestyle practices and unhealthy choice of nutrition falters wound management. From a more positive perspective, nano dressing, negative pressure, medicinal plants, synthetic polymers, gene therapy, stem cells, growth factors, and functionalized silk biomaterials are some of the various wound-healing techniques that can help reduce the cost of wound care. Flavonoids, which are secondary metabolites present in several types of vegetables and fruits, are frequently reported in the literature as being responsible for numerous in vitro and in vivo biological activities, including the treatment of wounds [14]. Hence, this review aims to understand the effect of flavonoids on wound healing through previously reported pathways. The art of wound care has been practiced traditionally since time immemorial; however, given the current advances in recent knowledge, few drugs have improved wound healing. The search for an effective route of treatment with minimal side effects remains elusive due to the complexity of tissue restoration. Chronic and acute wounds are the most prevalent of all injuries, affecting people worldwide with no effective treatments. Despite substantial progress in wound care over the last few decades, vigorous breakthrough studies continue to search for innovative therapeutic techniques that target acute and chronic wound management [31]. Chronic wounds are commonly known as difficult-to-heal injuries with a physiological impairment of tissue restoration and typically do not improve according to the timely sequence of tissue repair [32]. All injuries are susceptible to becoming chronic wounds and are etiologically divided into four groups, i.e., pressure, diabetic, venous, and arterial ulcers. These wounds typically exude pus and odors, and applied dressings are always prominent. Microbial colonies such as Staphylococcus aureus and Pseudomonas aeruginosa often invade chronic wounds, forming biofilms and leading to critical infections as well as impacting the overall process of wound repair [33]. They secrete endo- and exotoxins while modulating several immune responses at the wound site, producing excessive proteases that could degrade the extracellular matrix and impede the overall process of wound healing [34,35]. On the other hand, acute wounds are associated with the external destruction of intact skin and are composed mainly of burns, cuts, and bites, as well as traumatic lacerations [36]. The treatment regime depends on the type, severity, and size of the wounds. Similar to chronic wounds, acute wounds are also susceptible to microbial infections, with an estimated microbial colonization of 5 to 26% [37]. Burn wound infections encompass more than half of mortalities per year, and a number of pathogenic microbes such as S. aureus, P. aeruginosa, and Escherichia coli, as well as coagulase-negative Staphylococci, have been identified in post-burn injuries [38]. Of all, there are no current effective treatments for both wounds in terms of side effects and cost effectiveness. Figure 2 illustrates the current treatment utilized for treating acute and chronic wounds. Thus, in this section, current treatments available in wound healing are thoroughly discussed. Wound dressing is typically used to cover a specific site of injury from microorganisms. It acts as an insulator by moisturizing the wound site and promoting tissue granulation and epithelialization [39]. The chief goal of wound dressing is to minimize the risk of pathogenic infections and to reduce scarring. Myriads of wound dressings, such as medicated, traditional, and modern dressings, have been developed, each promoting flexibility and oxygen exchange at the wound site. Table 1 highlights the distinct types of wound dressings, their functions, and their limitations. Antibiotics were first discovered in the early 19th century by Alexander Fleming and have been broadly utilized ever since to combat infections. A plethora of antibiotics, namely penicillin, streptomycin, tetracycline, and vancomycin, have been developed to treat specific pathogenic infections since their discovery. In wound healing, topical applications such as creams, pastes, gels, and lotions are desirable as treatment because they are more localized and provide better drug bioavailability. Topical antibiotics such as neomycin, povidone-iodine, and silver sulfur diazine are extensively prescribed for their effectiveness to prevent infections [49]. However, the prolonged use of topical and systemic antibiotics on recovered wounds has resulted in major antibiotic resistance worldwide [50]. Recent data reported that bacterial infections related to wound healing have been reaching rates of antibiotic resistance of almost 70%, which could cause the spreading of resistant strains [35]. In view of this, more than half a million deaths have been recorded annually, and deaths are forecasted to increase by 10 million per year by 2050 [51]. In addition, the use of topical antibiotics may also cause hypersensitivity and allergic reactions [52]. Alternatively, antiseptics such as octenidine hydrochloride, polyhexamethylene biguanide, and sodium hypochlorite are preferred by clinicians, as these medications have potent anti-microbial properties as well as anti-biofilm-forming activity [53]. Debridement is one of the common techniques used to treat acute wounds or injuries such as burns, as it allows wounds to advance from the inflammatory to the healing phase. It facilitates wound epithelialization and minimizes the risk of bacterial infections by removing necrotic tissues, senescent cells, and biofilms from the wound site. However, biofilm removal is a laborious process due to its adhesive properties at the wound site, and the bioavailability of specific antibiotics are usually very low [54]. In the case of deep tissue infection, i.e., that involving muscle or adipose layer, amputation is the best approach for sepsis prevention [55]. Nonetheless, the amputation approach does not resolve the risk of reinfection on patients who have diabetic foot ulcers, as they are still susceptible to a 40% mortality rate after amputation [56]. To date, no known approach has been identified for its successful wound-healing activity and its ability to initiate distinct molecular and cellular mechanisms in various types of wounds. Previously mentioned treatments not only have side effects but are also expensive. Hence, an alternative treatment with minimal side effects is warranted. In fact, recent studies have suggested that natural products could be used to treat wounds. A mixture of black seed oil and honey has been reported to promote wound healing without causing cellular toxicity [57]. Honey in gellan gum (GG) hydrogel containing virgin coconut oil (VCO) was shown to hasten the healing process of an injury [58]. Additionally, there is preliminary evidence that granulated sugar is an effective wound cleanser and is safe to use in patients with insulin-dependent diabetes [59]. Current trends have been focusing on herbal medicines for their low side effects as well as drug resistance in treating wound infections [55]. Herbal medicines and herbally derived substances have been used in folklore medicine since time immemorial as they exert multiple therapeutic benefits, for instance, anti-inflammatory and antioxidant activities and modulation of cell proliferation [60]. The therapeutic properties of herbal medicine are unique to the mixture of bioactive components. Among them, flavonoids are one of the promising key bioactive ingredients for wound-healing properties [15]. Their structure–activity relationship (SAR), i.e., the presence of a hydroxyl group is essential for various biological activities, for example, anti-bacterial, antioxidant, and anti-inflammatory activities [61,62]. The number of people with chronic wounds has been rising like a “silent epidemic” [63]. Chronic wounds account for 2–4% of the health expenditure in Western nations [64]. This has frequently led to inadequate planning and implementation of preventative, treatment, and management methods. Therefore, wound research is an important yet undervalued topic of study [22]. The ideal plan for wound management includes exploring ways to minimize economic strain while simultaneously reducing morbidity and mortality. Some chronic wounds take years or even decades to heal. Patients may experience extreme pain, major mental and physical discomfort, decreased mobility, and social isolation during this period [65]. Reduced mobility can impair a person’s ability to work, complete household chores, and care for one’s personal hygiene. Mobility limitations are one of the worst aspects of having a wound, according to patients, as these limitations can impede independence and quality of life. The loss of independence caused by functional deterioration and social isolation has a negative impact on overall health and wellbeing [66]. Chronic wounds place a significant financial strain on healthcare systems, in terms of both direct and indirect expenditures. The frequency of dressing changes, the length of hospital stays for treatment, the frequency of complications, and, in particular, the time spent on healthcare all contribute significantly to the expense of wound care [67]. It will be very helpful to create new, low-cost therapeutic and preventative technologies to meet the needs of a specific healthcare environment, especially in low- and middle-income nations in which a lack of access to affordable, high-quality healthcare is a grave problem. In addition, hospitals also need to have wound registries because they will serve as a trustworthy data collection tool. Wound registries can be utilized as continual quality-improvement tools or to standardize wound observation. These registries will aid in the development of wound care techniques required in healthcare facilities including hospitals and nursing homes [66]. Flavonoids are generally recognized as the most common bioactive compounds on the planet. Flavonoids are abundant in fruits and vegetables. Flavonoids are phenolic compounds that can be found in fruits, vegetables, herbs, cocoa, chocolate, tea, soy, red wine, and other plant food and beverage products. Flavonoids are composed of two aromatic rings (A and B rings) connected by a three-carbon chain to produce an oxygenated heterocyclic ring (C ring). Based on changes in the general structure of the C ring, functional groups on the rings, and the position at which the B ring is linked to the C ring, flavonoids can be classified into various classes such as flavones, flavonols, flavanols, flavanones, isoflavones, anthocyanins, and chalcones. Figure 3 represents the basic skeletal structure of flavonoids and their classes as well as the examples. Individual compounds within each category are distinguished by distinct hydroxylation and conjugation patterns [68,69,70]. Flavonoids are one of the most attractive and promising families of natural products for treating skin problems. The structure–activity connection (SAR) of flavonoids is one of the key elements that lead to this feature. The presence of hydroxyl groups in their chemical structure, particularly at positions 5, 7, 3, and 4, is critical for their antibacterial, antifibrotic, antioxidant, and anti-inflammatory effects due to their high hydroxylation levels [61]. Catechins (flavan-3-ol), which modulate wound healing, are one of the most widely studied flavonoids [71]. Some researchers hypothesized that flavonoids such as apigenin could help treat skin injuries by inhibiting fibroblast development, because wound healing was delayed due to insufficient or excessive fibroblast operation. Lutein is a prominent dietary flavonoid that can be found in a variety of medicinal plants, as well as ordinary vegetables and fruits. It has also been used as a wound healer in a variety of wound models [72]. Rutin (quercetin-3-O-rutinoside), which is found in many medicinal plants, has wound-healing properties [73]. Flavonoids protect body cells from oxidative damage, which can cause disease, and they have advantageous defensive actions. Flavonoids such as quercetin form o-quinones, which, upon treatment with a solvent containing water, restored the potent antioxidant activity of the quinone. For example, carnosol quinone is the antioxidation product of carnosol, which possesses a very weak antioxidant activity. Quinones are a class of toxicological intermediates that can cause a number of harmful consequences in vivo to cells, including acute immunotoxicity, cytotoxicity, and carcinogenesis. In contrast, quinones can provide cytoprotection by inducing detoxifying enzymes, anti-inflammatory actions, and altering the redox state. The methods by which quinones exert these actions can be rather complicated [74]. Many flavonoids have been characterized as potent reactive oxygen species (ROS) inhibitors, making them vital antioxidant food components. The influence of ROS on the oxidation of quercetin, kaempferol, morin, catechin, and naringenin was investigated. The reaction rates determined by spectrophotometry and oxygen consumption were drastically different. Quercetin possesses powerful antioxidant and anti-inflammatory effects, which support its potential use in wound healing. Additionally, quercetin can reduce both acute and chronic inflammatory stages. Reactive oxygen species and oxidative stress have only a minor role in the normal physiology of wound healing, but an excess of either can hinder healing. The use of antioxidants as most flavonoids is thought to speed up wound healing by reducing oxidative stress in the wound [74]. The list of potential flavonoids requires more research to promote more discovery. Hemostasis, inflammation, proliferation, and remodeling are the sequential steps of wound healing. Each of these phases is governed by distinct growth factors, mediators, immune cells, and metabolites within signaling pathways that promote wound-healing activity. Numerous in vitro and in vivo investigations have demonstrated that flavonoids possess wound-healing effects. To determine the efficacy of flavonoids in wound healing, it is customary to detect cell migration in a scratch assay using a cell line study in accordance with the proper dosage of the tested flavonoids. Typically, the reliability of the test is determined by comparing treated and untreated cells. The inability of cell line research to simulate the actual process of wound healing, which involves inflammation and the immune system, necessitates subsequent in vivo testing on an organism [75]. Table 2 summarizes the effect of flavonoid treatment in in vivo and in vitro testing. Previous research has demonstrated the efficacy of flavonoids in shortening the period of wound healing by influencing collagen breakdown and MMP-2 activity following 24-h therapy [76]. The wound-healing rate was increased by 51% after being treated with quercetin-3-oleate at its highest concentration of 1 μM, with slight TGF-β production and MMP-9 release [77]. Although the upregulation of TGF-β was significantly induced, the absence of MMP-9 in HaCaT cell cultures suggests that the wound-healing capacity of these cells may be governed by distinct signaling pathways. Several studies with various in vivo testing sources and methodologies have indicated delayed wound healing. This issue is currently a major concern for healthcare professionals and individuals globally [78]. Hesperidin, one of the flavone glycosides, was, therefore, tested for its effects on diabetic foot ulcers. Compared to the control mice, the rate of wound closure for a chronic diabetic foot ulcer was less than 21 days. In addition to accelerating angiogenesis by elevating the expression of VEGF-c, Ang-1/Tie-2, TGF-, and Smad-2/3 mRNA, a considerable increase in wound closure has been observed [79]. Angiogenesis is a crucial process that promotes the regeneration of new tissue and organ development while simultaneously supplying wounds with nutrients and new cells [80,81]. Additionally, the rate of epithelialization promoted by flavonoids is assisted by their other antimicrobial properties [82]. In addition, it is essential to evaluate wound closure as a role in wound-healing activity by examining the wound margins until they heal. Consequently, in another trial involving a hydrogel containing flavonoid glycoside, a reduction in wound area over a period of 4 to 16 days was observed [83]. This discovery was made in several mouse models using different medication formulations denoted as H1 (0.0020% w/w), H2 (0.0025% w/w), and H3 (0.0030% w/w), with H2 proving to be the most effective formulation for encouraging wound closure beginning on day 4. In accordance, the flavonoid has played a significant part in the restoration of bone abnormalities, which has become one of the obstacles of clinical therapy [84]. The investigation was evaluated on 44-week-old mice that were placed into groups of eight and administered varying amounts of flavonoids. The therapeutic activity was discovered to be directly related to the higher dosage, i.e., 100 mg/kg per day was found to be the optimal dosage which can provide successful treatment for bone defects. Flavonoid is capable of initiating osteoblast differentiation, hence promoting angiogenesis and indirectly reflecting the activity of proliferation. In features of the veterinary application, an extract with a high flavonoid content from Libidibia ferrea has been suggested to be commercialized because histologically, it displays substantial numbers of fibroblasts, newly created capillaries, and collagen fibers from a concentration of only 5% [85]. In a separate study, quercetin-loaded liposomal hydrogel was evaluated for its ability to stimulate cell proliferation both in vitro and in vivo [72]. The multiphase system was successfully formulated, and its in vivo test yielded considerable results. As compared to the control group, wound excision in rats treated with quercetin-loaded liposomes resulted in 52.26% more wound contractions within four days of treatment. The authors highlighted that the produced hydrogel’s combination of excellent hemocompatibility, intact mechanical strength, and low swelling ratio led to quick wound closure. Quercetin has also been reported to demonstrate the ability to reduce fibrosis and scar formation during wound healing, promote fibroblast cell proliferation, reduce immune cell infiltration, and trigger alterations in fibrosis-related signaling pathways [86]. Reportedly, diabetic people typically have healing difficulties. Researchers have published several studies evaluating a suitable source for accelerating wound healing in diabetics. In a previous study [87], the rate of wound healing in incisional and excisional wounds of diabetic rat models was investigated. The wound was treated for fourteen days with remarkable results. In diabetic rats with excisional wounds, the rate of healing was determined to be 92.12%. Reepithelization scores were measured via histological examination on the 7th and 14th days, and they were found to be greater than the control alongside other wound-healing characteristics including granulation, angiogenesis, and inflammation. The need for these characteristics to produce a meaningful influence on the wound defines the efficacy of a particular studied drug, which in this case appears to be kaempferol, a potent wound-healing agent. The skin microbiota consists of microorganisms that play a pivotal role against pathogens. As injury occurs, microorganisms such as commensal bacteria will colonize the wound and become pathogenic as they produce biofilms (Figure 4) [88]. Staphylococci families are among the first colonizers, as they are major inhabitants of our skin and mucous membranes [89]. Similar to any other injury, acute and chronic wounds are at risk of bacterial infections that could be life threatening and could cause multiple inflammations in our body systems [90]. Bacterial infections are one of the major contributing factors for delayed wound healing and are susceptible to new infections and treatment failures, as they accumulate excessive ROS. At a low level, ROS promotes angiogenesis, promoting blood perfusion at the affected area [90]. Nonetheless, excessive ROS is the causative agent that contributes to biofilm production which could prevent the transitional stage of the inflammatory process towards the proliferative phase [91]. Thus, the search for a safe anti-bacterial agent is warranted. Among all of the safe anti-bacterial agents, flavonoids have been evaluated for their anti-bacterial properties owing to their accessibility and non-toxic therapeutic use. Moreover, a growing interest in flavonoids and terpenes for their anti-bacterial properties has been reported [92]. Therefore, the therapeutic use of flavonoids as anti-bacterial agents on wound healing has been highlighted with examples (Table 3) in this section. Numerous studies have suggested that flavonoids have wound-healing abilities; hence, this section will address the various widely accepted, reported mechanisms in particular (Table 4). The Wnt/β-catenin signaling pathway is a pathway that is essential for embryological growth and renewal of mature tissue homeostasis. The Wnt/β-catenin pathway plays crucial roles in numerous wound-healing processes involving tissue remodeling and cell growth. Additionally, it plays a role in the expression of growth factors and stem cell activation and improves wound angiogenesis. In fact, there are numerous reports that the Wnt family is involved in biological processes such as cell proliferation, apoptosis, differentiation, and the maintenance of pluripotency in stem cells [111,112]. According to reports, the flavonoids that contributed towards wound healing were quercetin and berberin [98,113]. The Hippo pathway is an evolutionarily conserved signaling mechanism that holds important functions in tissue regeneration, immunological regulation, epithelial homeostasis, organ development, and wound healing. Many of these functions are carried out by the transcriptional effectors YAP and TAZ, which regulate the TEAD family of transcription factors to control gene expression [114]. According to previously published research, it has been found that there is an interaction between the YAP/TAZ (Hippo pathway) and TGF-1/Smad signaling pathways during the healing process, which suggests that the findings might have pleiotropic effects that affect collagen production, cell growth, and wound healing [115]. Despite that, there are hardly any reports on flavonoids’ beneficial effects on wound healing. The TGF-β signaling pathway controls a number of biological functions, such as cell division, proliferation, death, plasticity, and migration [116]. This pathway is associated with a variety of wound-healing processes, including inflammation, promotion of angiogenesis, boosting of fibroblast growth, collagen synthesis and deposition, and remodeling of the new extracellular matrix [117]. Hesperidin, quercetin, glycitin, naringin, and genistein are flavonoids that have been linked to the healing of wounds via this pathway [15]. The Hedgehog signaling route is a signaling pathway that provides embryonic cells with the information they need to differentiate properly. This pathway is vital for healthy embryonic development and is crucial for the maintenance, renewal, and regeneration of adult tissue [118]. The results from an investigation conducted by Le et al. (2008) [107] strongly suggested that Shh signaling is involved in the natural healing of regular, definite, full-thickness wounds [119], thus implying that this pathway has potential for wound healing. However, there are no flavonoids reported so far for wound healing through this pathway. Jun N-terminal kinase (JNK), also called stress-activated protein kinase (SAPK), is one of the three main members of the mitogen-activated protein kinase (MAPK) superfamily. The other two are extracellular signal-regulated kinase (ERK) and p38 MAP kinase [120]. A few studies have implicated the JNK pathway in the regulation of cell migration. Cell migration is required for wound healing. Cell migration can be separated into multi-step cyclic processes. The fundamental migratory cycle consists of the elongation of a protrusion, the creation of stable attachments along the protrusion’s leading edge, the translocation of the cell body forward, the release of adhesions, and the contraction of the cell’s rear. In general, the JNK pathway is a “death” signaling mechanism. It regulates the cell’s response to damaging extracellular stimuli such as inflammatory cytokines, UV-irradiation, and gamma-irradiation, among others. Under the influence of these noxious stimuli, DNA may undergo mutation or damage. In the situation in which DNA damage cannot be repaired promptly, the cell must be programmed to die (also known as apoptosis) to prevent further mutation or harm. In a wound-healing assay, JNK-inhibited cells had a lower migration rate than control cells after 12 h in the presence of basic fibroblast growth factor (bFGF) [121]. The JNK pathway is important for the healing of imaginal disc wounds, as it has been shown to be in other types of wounds in Drosophila, including embryonic dorsal closure, thoracic closure, and adult epithelial wounds [122]. The antioxidant and signaling characteristics of flavonoids have been linked to their physiological effects [123]. The green tea polyphenol (−)-epicatechin-3-gallate (ECG) effectively protects HaCaT keratinocytes from ultraviolet B (UVB)-induced damage. The keratinocytes are protected by ECG from oxidative stress caused by H2O2 and photodamage caused by UVB, likely through blocking the activation of the JNK signaling pathway [124]. Quercetin prevents apoptosis and increases cell viability by inhibiting oxidant-induced signaling in the JNK and p38 MAPK (mitogen-activated protein kinase) pathways [125]. Citrus flavonoids have been shown to increase pro-survival signaling molecules, such as Akt/protein kinase B and p38 mitogen-activated protein kinase, and prevent the expression of JNK, which induces apoptosis [123]. Enhancing cell survival requires the activation of ERK, Akt/PKB, PI3K, and PKC, whereas avoiding apoptosis requires the downregulation of P38 and JNK. Wound healing is promoted by nuclear factor erythroid 2-related factor 2 (Nrf2) and nuclear factor kappa B (NF-κB) transcription factors via their anti-inflammatory and antioxidant effects or via the immune system [126]. The primary regulator of intracellular redox homeostasis is (Nrf2), a redox sensitive transcription factor. It drives the expression of cytoprotective genes and boosts the generation of antioxidants that scavenge free radicals. In numerous pathophysiological diseases—including diabetes and its resulting conditions such as diabetic foot ulcers, chronic kidney disease, and diabetic nephropathy—activators of Nrf2 have been observed to reduce oxidative stress and improve the process of wound healing. Chronic wounds take longer to heal due to a number of different factors, including reactive oxygen species (ROS), systemic illness, trauma, immune suppression, ischemia, an imbalance of pro/anti-inflammatory cytokines, interleukins, leukotrienes, and complement factors at the wound site, and a lack of extracellular matrix proteins (ECM). Wound healing is promoted by Nrf2 and NF-κB transcription factors via their anti-inflammatory and antioxidant effects or via the immune system. In wound healing, Nfr2 and Nf-κB perform a key and reciprocal role. Nrf2 regulates repair-related inflammation and protects against excessive accumulation of ROS, whereas Nf-κB activates the innate immune response, cell proliferation, and cell migration and modulates the expression of matrix metalloproteinases, secretion, and stability of cytokines and growth factors for wound healing [126]. Through activation of Nrf2, bioactive compounds, both those that come from nature and those that are made in a lab, can help diabetic wounds heal in important ways [127]. The role of Nrf2 in the wound-healing process has been a focus of interest for therapeutic research. In the presence of severe tissue injury and ROS generation, Nrf2 prevents the activation of cytoprotective genes that leads to apoptosis of keratinocytes [128]. It is widely acknowledged that Nrf2 functions as a defense signal under oxidative stress and protects cells by decreasing ROS (Figure 5). It has been shown that some bioactive compounds reduce cellular stress and consequently accelerate cell proliferation, neovascularization, and healing of injured tissues by activating Nrf2 expression. During wound healing, the Nrf2 pathway protects against oxidative stress via the production of antioxidative enzymes [128]. Injuries to the nasal mucosa that persist after nasal trauma, septoplasty, turbinate treatment, functional endoscopic nasal surgery, and tumor removal can be treated with curcumin because curcumin significantly improves wound healing. Curcumin dramatically speeds up the healing process by reducing inflammation. In the early stages of wound healing, curcumin has an apoptotic effect [129,130]. Some of the flavonoids discussed in this review were capable of increasing levels of SOD, CAT, GSH, GST, and GPX, all of which point to an antioxidant effect, and they also helped the body’s natural healing process. NF-κB is a transcription factor that regulates protein kinases, regulates cell activation and proliferation directly, and enhances the expression of several pro-inflammatory genes in cells [131]. Flavonoids inhibited the expression of nuclear factor kappa B (NF-kB) and reduced the levels of inflammatory mediators such as prostaglandin E2 (PGE2), leukotriene B4 (LTB-4), interleukin 1 (IL-1), tumor necrosis factor (TNF-), interleukin 6 (IL-6), and interferon (IFN-) [88]. Supplementation with luteolin significantly reduced protein expressions of inflammatory factors such as matrix metalloproteinase (MMP)-9, tumor necrosis factor (TNF)-, interleukin (IL)-6, and IL1-. Additionally, luteolin downregulated nuclear factor (NF)-B while also inducing increases in anti-oxidative enzymes such as superoxide dismutase 1 (SOD1) and glutathione peroxidase (GSH-Px) [132]. Mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signaling is heavily involved in the regulation of cell migration and proliferation. Activation of the MAPK/ERK signaling pathway is a significant regulator of the migration of different cell types [133]. The MAPK pathways have long been acknowledged in the scientific literature for their roles in angiogenesis during wound healing [134]. Quercetin may be a bioactive substance that can help with the symptoms of atopic dermatitis. It has anti-inflammatory and antioxidant properties and speeds up wound healing through the ERK1/2 MAPK [135]. Vaccarin is a flavonoid glycoside with several biological roles. Vaccarin promotes wound healing and the proliferation of endothelial cells and fibroblasts at the wound site. A previous study showed that vaccarin can increase the expressions of p-Akt, p-Erk, and p-bFGFR to cause angiogenesis and speed up wound healing in vivo. The MAPK and PI3K/AKT signaling pathways are known to play a role in angiogenesis throughout wound healing [134]. The MAPK/ERK and PI3K/AKT signaling pathways control this process [136]. The PI3K/Akt signaling system controls cell proliferation, differentiation, and migration in addition to controlling angiogenesis and metabolism. Additionally, it may facilitate skin growth and homeostasis. It is well known that the PI3K/Akt pathway is intimately linked to the creation of an epidermal barrier, which is mostly dependent on the proliferation and differentiation of keratinocytes [137]. Focal Adhesion Kinase (FAK) and Src are two significant non-receptor tyrosine kinases that have been shown to play a role in the healing of wounds [138]. Initially, p38-MAPKs were referred to as the stress-activated protein kinases that are activated in cells in response to a variety of stimuli, including ultraviolet light, osmotic stress, inflammatory cytokines, changes in oxygen content, and protein synthesis inhibition [139]. Inhibitors of p38 MAPK have demonstrated anti-inflammatory properties, primarily by blocking the expression of inflammatory cytokines and controlling cellular trafficking in wounds [140]. It appears that controlling p38 MAPK activity is essential for wound healing. This apparent contradiction between normal and chronic wound healing linked to p38 MAPK shows that extracellular stress on the fibroblast potentially changes the signaling cross-talk that is linked to cell survival to increase pro-apoptotic processes [141]. Transforming growth factor beta (TGF-β) signaling is required for a variety of cell functions. Although many different growth factors have been investigated as potential contributors to wound healing, TGF-β is broadly accepted to have the most far-reaching effects. TGF-β plays an important role in wound healing because of its pleiotropic effects on cell proliferation and differentiation, extracellular matrix (ECM) formation, and immunological regulation. Therapeutic drugs that target the TGF-β signaling system have shown promise in enhancing wound healing and/or diminishing scarring in preclinical investigations [142]. Five growth factors, including epidermal growth factor (EGF), platelet-derived growth factor (bFGF), vascular endothelial growth factor (VEGF), and transforming growth factor-beta 1 (TGF-1), operate as the primary regulators of cell signaling in wound healing in humans. The compounds bFGF, VEGF, PDGF, and TGF-1 stimulate cellular responses that encourage angiogenesis, keratinocyte migration and proliferation, fibroblast migration and differentiation, and collagen production. VEGF expression is increased when curcumin promotes TGF-1 signaling pathways [80]. Hesperidin is a prominent flavonoid present in lemons, sweet oranges, and a variety of other fruits, vegetables, and polyherbal mixtures. Treatment with hesperidin speeds up angiogenesis and vasculogenesis by increasing the expression of VEGF-c, Ang-1/Tie-2, TGF-β, and Smad-2/3 mRNA to help diabetic foot ulcers heal faster [79]. In this section, eight clinical studies (Table 5) that were conducted on different flavonoids for their wound-healing properties have been taken into consideration. Prior to conducting clinical trials, it is crucial to conduct in vitro and in vivo pre-clinical research. Comparing the results of pre-clinical and clinical studies will assist a researcher in bolstering the proof of research conduct. Clinical results on chronic wounds must also be examined because these results have a long-term effect on patients’ lives. Nevertheless, there are still possibilities of generating irrelevant or uncorrelated data after conducting the clinical investigations due to the mechanisms of the human body, which most of the in vitro studies are incapable of depicting. Most flavonoid treatments for wound healing are used in conjunction with other substances that promote cell development. In a published investigation [143], the use of quercetin boosted the activity of keratinocyte proliferation. The work continued with clinical trials on 56 diabetes mellitus patients (28 men and 28 women), in which a nano-hydrogel containing quercetin and oleic acid was administered to foot skin wounds for eight months. Hyaluronic acid was used as the positive control for comparison. The combination therapy greatly outperformed the effect of the hyaluronic acid, suggesting the promising potential of quercetin as one of the flavonoid types in the management of wound healing. According to the study, quercetin effectively minimized skin lesions and improved tissue viscoelasticity and may have facilitated the treatment of chronic wounds. Modulating cytokines, growth factors, and protease were suggested to facilitate the treatment of chronic wounds while regenerating diabetic skin wounds [144]. Similarly, this capability was attributed to the exceptional antibacterial activity of quercetin. Patients also reported less discomfort and no new infections, both of which were confirmed by the trial. Neither was there any evidence of a local recurrence. The combination of micronized purified flavonoid fraction (MPFF) with compression treatment was another flavonoid treatment combination. MPFF is a combination of diosmin and flavonoids, and this combination is expressed as hesperidin. In lieu of treating chronic venous leg ulcers with medications or natural extracts alone, the study revealed a superior technique of wound management in venous ulcers [145]. This comprises the compression treatment that uses either a bandage or a stocking in conjunction with the application of medications or other treatment, which in this instance is the MPFF. In addition, the study suggested that effective wound management may not be able to expedite recovery but has the potential to avoid recurrence. Ultrasound-guided foam sclerotherapy, endovenous laser coagulation, and radiofrequency ablation were also highlighted as treatment options in the study. The combination of compression and oral treatment with MPFF substantially hastened the healing of venous leg ulcers in 723 individuals, according to previous findings [146]. After six months of clinical testing, it was determined that MPFF can easily surpass conventional therapy by 32% in terms of healing rate. This result implies that MPFF can protect microcirculation from damage caused by elevated ambulatory venous pressure [147]. However, the treatment of wound healing with flavonoid alone is also capable of producing considerable outcomes. For instance, in a clinical experiment involving oral wounds/mucosa treated with plant-derived quercetin cream, forty male volunteers participated. The trial assessed ulcer size and pain tolerance and made general enquiries regarding the flavor and application convenience of the quercetin cream. The study revealed that the cream was capable of producing wound closure in two to four days in 35% of cases [148]. This result was found to be comparable to a study that examined anthocyanin content in a different form of adhesive gel produced from Zea mays and Clitoria ternatea extracts on oral wounds [149]. Based on the results of a clinical trial involving 68 orthodontic patients between the ages of 18 and 25, it was shown that 7 days after the application of anthocyanin gel to their dental sores, wound repair was accelerated. The clinical trial outcome was consistent with animal testing and clinical studies in which anthocyanin gel was administered to oral wounds on 60 volunteers aged 18 to 60 [150]. Quantitatively, the wound size was decreased without corresponding changes in erythema. This is related to the process of re-epithelialization, which creates new tissues. It is admissible to conclude that a flavonoid-containing mucoadhesive gel can efficiently penetrate the oral mucosa of humans and, subsequently, accelerate wound healing by stimulating fibro-blast replication [151,152]. In other instances in which flavonoid compounds were used to treat wound healing, the flavonoid type was not specified. For instance, a study was conducted on propolis, which is the common term for a substance produced by honeybees and a well-known source of flavonoids. Thirty-three patients who had uncomplicated sacrococcygeal pilonidal sinus wound surgery were evaluated for the ability of propolis to promote wound healing (from the age of 18 to 45) [153]. The wounds of these patients who had undergone marsupialization surgery were treated with a 15% propolis water solution at each dressing change, and they were examined for 28 days. In contrast to the efficacy of flavonoids in propolis based on in vitro and in vivo pre-clinical studies reported in the literature, the investigators noticed that wound-healing activity was dramatically accelerated after 14 days of therapy. However, the findings did not rule out the potential that the result was also influenced by other variables, such as the dosage given to the lesion, the source of the propolis, and the solvent-extraction technique used [154]. No local infection complications or necrosis or allergy reactions were reported in the investigation. Another clinical trial on flavonoid-rich medicinal plants from Latin America has shed new light on the efficacy of flavonoids against persistent leg ulcers. The study was carried out with randomized, single-blind, and double-blind clinical investigations. In a single-blind study, the researcher knows about the treatment that the patients received but not vice versa. However, the double-blind method is a process in which both the researcher and the patient are uninformed of the treatments received or administered. Five medicinal plants from Latin America were compared for their wound-healing properties. Among the studied plants, Mimosa tenuiflora (Willd.) Poir demosntrated the strongest wound-healing activity by lowering ulcer size by 93% in the eighth week in a clinical study that involved less than 50 individuals with chronic venous leg ulcers and a one-year monitoring period. However, the study did not directly discuss the type of flavonoids [155]. It is difficult to conduct a clinical study observation on wound-healing activity in chronic venous leg ulcers because the therapy might significantly impact the patient’s life through a variety of symptoms that result in movement limitation, causing the majority of patients to discontinue treatment halfway. It has been demonstrated that the aerial parts of Achillea millefolium, which is popularly known as yarrow or the common yarrow plant, contain a high level of flavonoids [156]. Extraction of the flavonoids in the plant was followed by preclinical testing that revealed wound-healing and anti-inflammatory effects [157]. As part of the continuation of a double-blind clinical investigation, 140 primiparous women served as test subjects to examine wound-healing activity following epiosomy incision. At the seventh-, tenth-, and fourteenth-day intervals, several parameters, including redness, edema, and discharge, were used to measure the healing activity. It was concluded that the treatment could lessen pain, redness, and edema, but no significant differences were observed between the treatment and control groups. Flavonoids isolated from A. millefolium were discovered to have no effect on wound dehiscence and secretion. In light of the possibility that the active ingredient may work in a dose-dependent manner or synergistically with other classes of secondary metabolites present in the plant extract, it is necessary to conduct additional research into the topic to understand the wound-healing property of flavonoids better. In general, the positive findings on flavonoids as wound-healing agents are somewhat restricted, and the majority of advancements did not continue until phase 3 of clinical trials to further confirm the true role of plant-based flavonoids as wound-healing agents. This review provides a comprehensive assemblage of the utilization of flavonoids in the wound-healing process through diverse pathways. This serves as a foundation towards understanding and apprehending the mechanism of wound healing, thus facilitating the development of medicines to treat skin wounds. Because flavonoid has promising potential in wound repair in regard to this study, additional natural-based extracts must be understood and integrated with cutting-edge technology with the aid of other active ingredients. For example, a flavonoid-containing chitosan hydrogel was recommended for use in the treatment of wounds due to its positive effect on wound-healing induction and antioxidant activity in diabetic mice [158]. The enhanced production of anionic phenolic hydroxyl groups in chitosan fibers has been shown to greatly aid antioxidant and wound-healing activities [159]. Chitosan is extensively used as a medicine carrier due to its antimicrobial, biocompatible, biodegradable, and non-toxic properties [160]. In particular, a drug delivery system that utilizes natural-based treatments for wound healing can be enhanced by adding nanotechnology. Bio-nanomaterials derived from natural sources may be one of the most promising means of accelerating tissue repair. In a recent study on the efficacy of flavonoid, which was efficiently induced in bio-fabricated nano-biomaterials, flavonoid-loaded silver derived from the seed of the Madhuca longifolia plant was found to be effective [161]. Compared to flavonoid-loaded gold and bimetallic substances, flavonoid-loaded silver enhanced wound healing by up to 80.33%. In another recent study, chronic wounds treated with carbonized nanogel (copper sulfide nanoclusters) and quercetin exhibited fast healing of wounds. The discovered multifunctional nanogel can stimulate angiogenesis, epithelialization, and collagen synthesis to accelerate granulation tissue formation [162]. On the contrary, according to the literature, the majority of studies have not yet conducted in vivo testing or clinical trials. Similarly, not all conducted clinical studies have yielded consistent findings, and the majority of clinical trials did not even reach Phase 3. By focusing on a single primary source of flavonoids, more therapeutic investigations can be conducted. Likewise, more research confirming flavonoids’ efficacy in all therapeutic domains is recommended. The current study has the potential to introduce a novel concept to flavonoid discovery, highlighting the signaling pathways for future endeavors. This work provides future researchers with additional information on the limitations of flavonoid therapy for tissue regeneration. Thereby, the results of this study can serve as a starting point for future research to select the optimal signaling pathways that will result in the quickest rate of healing without scarring and will not activate unwanted (malignant) or negative pathways.

PMC10003010

Csilla Temesszentandrási-Ambrus,Gábor Nagy,Annamária Bui,Zsuzsanna Gáborik

A Unique In Vitro Assay to Investigate ABCB4 Transport Function

24-02-2023

ABCB4 inhibitors,MDR3,hepatotoxicity,drug-induced liver injury

ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates.

A Unique In Vitro Assay to Investigate ABCB4 Transport Function ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates. Multidrug resistance protein 3 (MDR3, ABCB4) is predominantly expressed in the canalicular membrane of hepatocytes. It has been predicted to be a floppase that translocates phosphatidylcholine (PC) from the inner to the outer leaflet of the membrane bilayer [1,2,3]. Translocated PCs are available for extraction by bile salts mixed micelles, and exert two essential functions in the bile: they protect the biliary tree from the detergent activity of bile salts [4,5], and maintain cholesterol solubility, preventing supersaturation with cholesterol [6]. In agreement with these proposed roles, ABCB4 mutations result in a broad spectrum of phenotypes ranging from progressive familial intrahepatic cholestasis type 3 (PFIC3) to ABCB4-related cholestatic liver disorders of varying manifestation and severity in adults [7]. Clinical studies revealed the strong association between ABCB4 gene mutations and low-phospholipid-associated cholelithiasis syndrome (LPAC), a rare type of gallstone disease [8,9]. Historically, ABCB4 was classified as multidrug resistance transport protein based on 76% identity and 86% similarity of its amino acid sequence to the highly promiscuous ABCB1 transporter [10]. In a recent publication on cryo-EM studies with chimeric transporters of ABCB1 and ABCB4, a shared overall transport mechanism has been proposed. It suggests that ABCB4 transports PC to the outer membrane leaflet by an alternative access mechanism with the entire phospholipid molecule entering and leaving a central translocation pathway, in contrast to mechanisms proposed for other phospholipid transporters [11]. However, the loss of ABCB4 function is not readily compensated by ABCB1 or by other mechanisms [12]. In mouse knockout studies Abcb1 is unable to compensate for loss of Abcb4 function, as these mice develop a liver disease that appears to be caused by the complete inability of the liver to secrete phospholipids into the bile [5]. In a similar fashion, stable transfectants of LLC-PK1 cells revealed that ABCB1 has broad specificity for phospholipids, but ABCB4 expressing cells exclusively released short chain phosphatidylcholine [13]. In contrast, ABCB4 can recognize and transport ABCB1 substrates, but its role in conferring drug resistance is still inconclusive. Although the transport rate was low for most ABCB1 substrates, Smith et al. demonstrated directional transport of digoxin, paclitaxel, vinblastine and ivermectin through ABCB4-transfected LLC-PK1 cells. Digoxin transport was inhibited by typical ABCB1 inhibitors such as verapamil, cyclosporin A or valspodar [5,13,14,15,16]. These results also suggest that ABCB4 is primarily a PC transporter that can translocate various typical ABCB1 substrates as well. Even though ABCB4 showed approximately 10-fold less ATPase activity than ABCB1, this activity is enough to confer multidrug resistance in chimera protein containing ABCB1 transmembrane domains [17]. The potential role of ABCB4 in multidrug resistance was indicated by increased ABCB4 transcript levels in paclitaxel-, doxorubicin-, and vincristine-resistant cell lines [18,19,20]. ABCB4 overexpression was also correlated with high-risk Wilms tumors [21]. Drug-induced liver injury (DILI) is a leading cause of drug development termination; therefore, its prediction in early stages is crucial [22,23]. Because of its role in the process of bile formation, inhibition of ABCB4 by drugs is believed to contribute to DILI and impact the hepatocellular/biliary toxicity of bile acids [24,25]. Drug-induced cholestasis (DIC), a frequent manifestation of DILI [26], is caused by alterations in the hepatobiliary disposition of bile acids, which in turn, is a result of direct injury to the bile ducts or inhibition of bile acid formation or transport [27,28]. Several drugs cause cholestasis by inhibiting canalicular efflux transporters [7,29]; however, there are significant differences in the relevance of biliary transporter inhibition in the development of DILI [30,31]. Inhibition of ABCB11 (Bile Salt Export Pump, BSEP) is a major risk factor in the development of cholestatic hepatotoxicity, though recent publications do not fully underscore this correlation [32,33]. To improve the predictive power, multidrug resistance proteins (MRPs) are included in screens with varying degrees of success [30,33,34]. In contrast to ABCB11, inhibition of ABCB4 in cholestatic diseases has received little attention to date. Impaired ABCB4-mediated biliary phospholipid secretion was shown to be involved in itraconazole-induced cholestasis, where biliary PC levels were markedly reduced, while biliary bile salt levels remained unchanged [24]. While studying antifungal agents, Mahdi et al. described the inhibitory effect of ketoconazole and posaconazole in LLC-PK1-ABCB4 cells [35]. In a primary hepatocyte assay, ABCB4-mediated PC transport was investigated using several structurally distinct cholestatic drugs [25]. In a similar study, Aleo et al. tested 125 drugs grouped by their DILI potential, and identified several drugs which are shared inhibitors of both ABCB4 and ABCB11 [36]. These results suggest that such inhibitors may exacerbate the cholestatic effect [35]. Although in vitro ABCB4 assays have been already reported, only a few addressed the role of ABCB4 in drug interactions [25,36]. Hence, compared with other drug transporters, ABCB4 has a small number of identified drug substrates and inhibitors. Therefore, we aimed to investigate ABCB4 activity and interaction with drugs independently of other transporters in an in vitro assay. Here, we developed an Abcb1 knockout (Abcb1KO) MDCKII-ABCB4 cell line, which shows a polarized morphology and completely lacks Abcb1 background activity but has ABCB4 activity. Using this cell line, the interaction of several hepatotoxic, anticancer as well as ABCB1 interactor drugs with ABCB4-mediated digoxin transport was investigated. We showed that this assay system is also well suited to identify potential drugs highly specific for ABCB4 by excluding overlapping specificity from Abcb1. An Abcb1 biallelic knockout MDCKII (Abcb1KO-MDCKII) cell clone was generated by GenScript (Leiden, the Netherlands) using the CRISPR/Cas9 system. To verify biallelic KO, the canine Abcb1-related properties of the Abcb1KO-MDCKII and MDCKII parental cells were characterized. The transcript levels of Abcb1 in the cell lines were analyzed by RT-qPCR (Figure S1a). The parental MDCKII and Abcb1KO-MDCKII cells were examined by FACS using a calcein AM assay. Compared with the MDCKII parental cells, the Abcb1KO-MDCKII cells exhibited a high fluorescent signal, corresponding to the lack of canine Abcb1 efflux activity (Figure S1b). To confirm the impact of endogenous canine Abcb1 on the efflux ratio (ER) on two prototypic Abcb1 substrates, bidirectional transport experiments with digoxin and talinolol (both 1 µM) were performed. In the MDCKII parental cells, apparent permeability (Papp) in the B-A direction was higher than in the A-B direction, with an average ER of 4.74 ± 0.15 for digoxin and 2.70 ± 0.57 for talinolol, indicating active transport by canine Abcb1. In contrast, digoxin and talinolol Papp were identical in both directions in Abcb1KO-MDCKII cells, with an ER close to unity (Figure 1a). The Abcb1 inhibitor valspodar decreased the efflux ratios of both digoxin and talinolol close to unity in the MDCKII parental cells, whereas in the Abcb1KO-MDCKII cells the ER remained unaffected. In a previous study, using this Abcb1KO-MDCKII cell line, we also confirmed that maraviroc has a strong affinity for endogenous canine Abcb1 in MDCKII cell lines, despite the lack of transport in the Abcb1KO-MDCKII cell line [37]. For the purpose of this study, we expressed the ABCB4 protein in this Abcb1KO-MDCKII cell line. Expression of human ABCB4 mRNA were determined in the Abcb1KO-MDCKII-Mock and Abcb1KO-MDCKII-ABCB4 cells by RT-qPCR (Figure S2). The ABCB4 mRNA level (determined by the formula 2−(ΔΔCT)) was approximately 6000-fold higher in the Abcb1KO-MDCKII-ABCB4 cells than in Abcb1KO-MDCKII-Mock cells. Canine Abcb1 mRNA could not be detected in any of the cell lines. Protein expression of human ABCB1 and ABCB4 were assessed by Western blot in the Abcb1KO-MDCKII-ABCB4, Abcb1KO-MDCKII-Mock and previously established Abcb1KO-MDCKII-ABCB1 cells (from now on referred as ABCB4, Mock and ABCB1 cells, respectively). Human ABCB1 protein was detected in the ABCB1 cells, but not in the ABCB4 cells, and ABCB4 was expressed only in the ABCB4 cell line. Neither ABCB1 nor ABCB4 was detectable in the Mock cells (Figure S3a,b). Since the substrate specificity of ABCB4 and ABCB1 was reported to be overlapping, we tested five known ABCB1 substrates (quinidine, prazosin, fexofenadine, digoxin, and ketoconazole at 1 µM final concentration) in bidirectional transport assays using ABCB1, Mock and ABCB4 cell lines (Figure 1b). While digoxin is a shared substrate for ABCB1 and ABCB4, it shows higher ER in the ABCB1-expressing cell line compared with ABCB4. The other compounds span a wide range of ERs (3.47 to 39) in the ABCB1-expressing cells. In contrast, quinidine and fexofenadine showed ER < 2 in the ABCB4 cells, which is a cut-off value for active efflux. In the case of prazosin, minor ABCB4-mediated directional transport was detected. Ketoconazole is an ABCB1 inhibitor [38] and an ABCB1 substrate [39]. Accordingly, an ER of 5.54 for ketoconazole was seen in the ABCB1 cell line. Under the experimental conditions of the present study, ketoconazole was also identified as an ABCB4 substrate (ER 2.78). The corresponding ERs in the control experiments using Mock cells were at, or very close to, unity. For further functional validation of the assay, digoxin was used as an ABCB4 probe substrate. ABCB4-mediated digoxin transport experiments were conducted as a time course by taking samples from both compartments at various time points (1, 2, 3, 4 and 6 h). During the 6-h incubation, digoxin transport was roughly linear. Therefore, taking samples at one fixed time point should suffice for Papp calculations, and the 3 h time point was chosen for this (Figure S4a). The transepithelial transport of digoxin was measured for 3 h using a range of initial concentrations (Figure S4b,c); however, because of the low aqueous solubility and potentially higher Km, the kinetic parameters of digoxin transport could not be determined. To investigate the predictive nature of the ABCB4 bidirectional assay in potential drug-ABCB4 interactions, inhibition studies were performed using 30 drugs with different DILI outcomes (18 Most-DILI concern, 9 Less-DILI concern and 3 No-DILI concern) from the U.S. Food and Drug Administration (FDA) Liver Toxicity Knowledge Base (LTKB). In addition, seven structurally diverse compounds were also tested in ABCB4 inhibition assays. The concentration-dependent effect of the selected compounds on ABCB4-mediated digoxin (1 µM) transport were determined. The known ABCB4 inhibitors itraconazole [24,25,35,40] and verapamil [16,25,36] showed potent inhibition of ABCB4 with estimated IC50 values of 0.17 and 0.39 µM, respectively. Ketoconazole (IC50 0.56 µM), ritonavir (IC50 0.73 µM), saquinavir (IC50 1.4 µM) and valspodar (IC50 0.15 µM) also inhibited ABCB4-mediated digoxin transport. As shown in Table 1, fluconazole, amiodarone, carbamazepine, minoxidil, furosemide and acetylsalicylic acid have no effect on ABCB4-mediated transport of digoxin. The results are in agreement with the previous studies on hepatocytes [25,36]. We also identified ivermectin as an ABCB4 inhibitor in our assay, which is not surprising since it was described earlier that ABCB4 can bind and transport ivermectin in LLC-PK1-ABCB4 cells [16]. We did not detect interaction with methotrexate in our assay, in contrast to previous data [36]. In the case of benzbromarone, we observed the opposite phenomenon compared with other reported inhibitors. Instead of an IC50 value of 0.4 µM [36], a significantly higher IC50 value (19.89 µM) was determined in the ABCB4 cells. Among drugs with Less-DILI-concern, the ABCB1 modulator amlodipine [41] showed a weak interaction with the ABCB4 protein. Fenofibrate, felodipine and pantoprazole showed no interaction with the ABCB4 transporter at the concentrations we tested, whereas carvedilol proved to be a potent inhibitor with an IC50 value of 0.70 µM. Known ABCB1-interacting compounds were also investigated on the ABCB4 cells. We found that valspodar [16] is a potent ABCB4 inhibitor as previously described, and zosuquidar, elacridar, mibefradil also elicited a strong concentration-dependent inhibitory effect. Quinidine, a weak ABCB4 substrate, potently inhibited ABCB4 function with an IC50 value of 1.09 µM. Prazosin also inhibited ABCB4 with an IC50 value of 16.12 µM. The tyrosine kinase inhibitors (TKIs) gefitinib, imatinib, sorafenib and erlotinib are classified as Most-DILI-concern drugs, and idelalisib can cause clinically apparent liver injury [42]. In our assay, the most potent ABCB4 inhibitors were gefitinib and imatinib (IC50 0.81 and 1.24 µM), whereas sorafenib and erlotinib showed less potent inhibition (IC50 4.42 and >5µM). Idelalisib did not inhibit ABCB4. We also identified antiviral agents (lopinavir, darunavir and asunaprevir) as ABCB4 inhibitors, which has not previously been described in the literature. Representative inhibition curves are shown in Figure S5. As a next step, we also tested whether the two most potent inhibitors in the group of TKIs are ABCB4 substrates. Gefitinib at a concentration of 0.5 µM showed directional transport with an ER higher than 2 (4.02 at 60 min, 2.54 at 120 min and 3.23 at 180 min) in the ABCB4 cell line. The corresponding ERs in the Mock cells were very close to unity (Figure 2a). ABCB4-mediated transport of gefitinib was inhibited by itraconazole (2 µM). These results indicate that gefitinib is an inhibitor and a substrate of human ABCB4. In contrast, the corresponding ERs in ABCB4 and Mock cells were below 2 for imatinib, suggesting that although imatinib inhibits the function of ABCB4, it is not a substrate for this transporter (Figure 2b). Finding an efficient non-hepatocyte based in vitro model to study interactions between chemical entities and ABCB4 is still challenging. A few ABCB4 non-hepatocyte-based cellular assays have been reported, including ABCB4-transfected LLC-PK1 and HEK293 cells [13,74,75]. However, a major disadvantage of these cell lines is that they retain the expression of endogenous transport proteins [76,77,78], which might functionally interfere with the introduced transporter of interest [79]. Previous studies support that cell lines with a genomic knockout of the endogenous transporters, e.g., canine Abcb1, are more sensitive and overall, more suitable for assays of an introduced transporter [80,81]. In the present study, we successfully developed a cell line, Abcb1KO-MDCKII-ABCB4, which lacks endogenous canine Abcb1 activity and expresses the human ABCB4 transporter. Thorough characterization of the cell line with digoxin, a shared substrate of both ABCB1 and ABCB4, resulted in an assay capable of detecting ABCB4 inhibitors and substrates in an easy-to-use format. This cell line was then utilized to test a versatile array of drugs as potential inhibitors and/or substrates of ABCB4. For these inhibition studies, 30 drugs with different DILI outcomes were chosen from the Liver Toxicity Knowledge Base of the FDA, and seven more, structurally diverse, compounds were added to this list. In line with the literature data, we have here confirmed the interactions of many of these drugs (itraconazole, verapamil, ketoconazole, ritonavir, saquinavir and valspodar) with the ABCB4 protein in bidirectional assays. When comparing our results with those presented by He et al. [25] and Aleo et al. [36], however, a few things are worth noting. First, the above-mentioned primary hepatocyte assays utilize labeled PC to test ABCB4-dependent transport inhibition. He et al. tested the inhibitory potency of structurally distinct cholestatic drugs (chlorpromazine, imipramine, itraconazole, haloperidol, ketoconazole, saquinavir, clotrimazole, ritonavir, and troglitazone) [25]. In the latter study 125 drugs, grouped by the severity of liver injury caused, were tested [36]. Our assay detected all interactions reported in these studies, with only one exception, and drugs that did not interact with the ABCB4 protein in hepatocytes did not interact in our system either. Of note is that the IC50 values for ABCB4 inhibition obtained in our study are much lower than those obtained in hepatocyte assays. The results suggest that our assay can detect potential ABCB4 interactors with higher sensitivity compared with primary hepatocyte assays. Possible explanations include the difference in the substrate used and/or transporter protein abundance. For a correct interpretation of MDCKII assay results, specific features of these cells need to be considered. For instance, the IC50 value of benzbromarone in our assay was much higher than in hepatocytes. Benzbromarone is metabolized by CYP2C9, and its toxic effect is believed to be mainly caused by its metabolites [82]. It can be speculated that the potent inhibitory effect observed in hepatocytes is partially caused by the metabolite. In general, in hepatocyte-based assays, both the parent drug and its metabolites may affect the assay readout [83], whereas in MDCKII cells, production of metabolites does not interfere with the effect of the parent drug. Another feature of the MDCKII bidirectional assay is that transcellular transport as well as intracellular accumulation might be limited by the diffusion rate across the basolateral membrane or depend on the presence of endogenous SLC transporters. Such an example is methotrexate, which did not show inhibition in our assay. However, methotrexate potently inhibited ABCB4 with an IC50 of 3.1 µM in a human primary hepatocyte assay [36]. Since methotrexate is a hydrophilic dicarboxylic acid and shows low Papp in MDCKII cells [84], it is hypothesized that its transport is limited by the diffusion rate and cannot accumulate intracellularly to exert its inhibitory effect. In contrast, OATP1B1 and OATP1B3 can substantially contribute to the intracellular accumulation of methotrexate in hepatocytes [55,85]. Our results show that several potent ABCB1 inhibitors, such as verapamil, ketoconazole, valspodar, zosuquidar, cyclosporin A and mibefradil, inhibit ABCB4 activity. TKIs, such as gefitinib, imatinib, sorafenib and erlotinib, are classified as Most-DILI-concern drugs and are well known ABCB1 interactors [67,86,87,88,89]. In our assay, we demonstrated for the first time that all four TKIs also inhibited the function of ABCB4, which might contribute to the DILI properties of these drugs. Additionally, we identified gefitinib as a substrate of ABCB4. To our best knowledge, this is the first demonstration of the interaction of these TKIs with ABCB4. Previous results suggest that several drugs are shared inhibitors of ABCB4 and ABCB11 transporters [36], supporting the earlier finding by Mahdi et al. that if a drug inhibits the function of both transporters, its cholestatic effect may increase [35]. These results imply that during drug development, combined drug–drug interaction tests, which include the transporters involved in hepatocellular bile acid homeostasis and bile formation (ABCB11, ABCB4 and ABCC2), may help to screen for drug candidates causing liver injury. However, the functional and clinical impacts of ABCB4 inhibition in the development of DILI require further investigation. Unlike hepatocyte-based assays, our ABCB4 cell line is suitable to identify even low affinity non-phospholipid substrates of ABCB4. This feature of our assay is put into context by recent studies that point to the importance of ABCB4 in non-hepatobiliary tumors. High levels of ABCB4 expression have been reported in different leukaemias, even without co-expression with ABCB1 [90]. In leukaemia cells, daunorubicin accumulation is dependent on transporter inhibition with Cyclosporin A [91], indicating that ABCB4 is able to remove ABCB1 substrates from cancer cells and may play an active role in drug resistance. In a similar pattern, ABCB4 mediated the efflux transport of doxorubicin in vitro and contributed to the acquired resistance of doxorubicin in breast cancer cells [92]. Previous reports showed that ABCB4 and ABCC1 overexpression correlates with high-risk and significantly shorter disease-free survival time in patients with Wilms tumors (WT). This suggests the role of ABCB4 and ABCC1 in drug resistance observed in WT treatment [21]. In conclusion, we report here a novel assay that specifically measures ABCB4 activity using an ABCB4-overexpressing canine Abcb1 knockout MDCKII cell line. In terms of inhibition of this transporter, the positive and negative hits obtained in hepatocytes were reproduced in our assay with even higher sensitivity. We propose that the Abcb1KO-MDCKII-ABCB4 bidirectional assay could be used to screen the potential of chemical entities to inhibit ABCB4 transport activity to improve DILI prediction or assist in elucidating the mechanism of DIC. This is a superior system for ABCB4 substrate identification to aid drug development. Non-radiolabeled chemicals were obtained from Merck/Sigma-Aldrich. Calcein AM was purchased from Invitrogen. All chemicals were of analytical grade. 3H-digoxin ([3H(G)], 23.8 Ci/mmol), 3H-prazosin ([7-methoxy-3H], 77.4 Ci/mmol) and Ultima Gold XR scintillation fluid were purchased from PerkinElmer (Waltham, MA, USA). 3H-quinidine ([9-3H], 20 Ci/mmol) and 3H-talinolol ([ring-3H(G)], 20 Ci/mmol) were purchased from American Radiolabeled Chemicals (St. Louis, MO, USA). 3H-fexofenadine ([3H], 4.9 Ci/mmol) was purchased from Moravek Biochemicals Inc. (Brea, CA, USA). The Tetro™ cDNA Synthesis Kit was purchased from Meridian Bioscience (London, UK). The Light Cycler® 480 SYBR Green 1 master kit was obtained from Roche Applied Science (Foster City, CA, USA). 4–15% precast polyacrylamide gel (Invitrogen, Carlsbad, CA, USA) and ProSieveTM QuadColorTM Protein Marker (4.6–300 kDa) were obtained from Lonza (Basel, Switzerland). Monoclonal human ABCB4 (P3II-26, sc-58221) primary antibody was purchased from Santa Cruz Biotechnology, Inc. (Dallas, TX, USA), and ABCB1 (C219) primary antibody was purchased from Enzo Life Sciences, Inc (Lausen, Switzerland). Secondary anti-mouse IgG antibody was obtained from ThermoFisher (# 62-6520). The BCA protein assay kit was obtained from Thermo Scientific (Rockford, IL, USA). Madin–Darby canine kidney II (MDCKII) wildtype cells were obtained from the European Collection of Authenticated Cell Cultures (ECACC catalogue no. 00062107). A MDCKII-Abcb1 biallelic KO (Abcb1KO-MDCKII) cell clone was generated by GenScript (Leiden, The Netherlands) using the CRISPR/Cas9 system to knockout the canine Abcb1 gene. To confirm gene editing, after clonal expansion of the cells, genomic DNA was extracted, and the target regions were amplified by PCR using primer pairs for the expected mutation sites. The genotype of this KO clone was determined by Sanger sequencing by GenScript. The phenotype was verified through transport assays using the ABCB1/Abcb1-specific substrates digoxin and talinolol. Sequence verified cDNA encoding human ABCB4 (NCBI Reference Sequence: NM_000443.3) was synthesized and cloned into pCDH-CMV-EF1-Puro using 5′ NheI and 3′ NotI by GenScript, and lentiviral particles were generated in HEK293FT cells (Invitrogen/ThermoFisher, Waltham, MA, USA). Transduced and antibiotic-selected Abcb1KO-MDCKII-ABCB4 cells were subjected to single cell cloning, and amplified clones were functionally tested for transporter-specific efflux activity. Four puromycin-resistant clones were isolated and tested for ABCB4 efflux activity using the known ABCB4 substrate digoxin [16] with a digoxin ER cut-off of two [93]. Based on this criterion and on ABCB4 mRNA and protein expression levels and cell culturing properties, the best clone was selected for continued validation and is hereafter referred to as the ABCB4 cell line. Empty vector transduced Abcb1KO-MDCKII-Mock cells were used as negative controls. Cell cultures were maintained in Dulbecco’s modified Eagle’s medium (DMEM), 4500 mg/L of glucose, supplemented with GlutaMaxTM, 10% v/v fetal bovine serum (FBS), 100 units/mL penicillin and 100 µg/mL streptomycin (all from Gibco/ThermoFisher) at 37 °C in 5% CO2 at 95% humidity. The medium was replaced three times per week. Cells were harvested using TrypLE™ Express (ThermoFisher) at 80 to 90% confluence and passaged or seeded. For transport experiments, cells were seeded on MillicellTM High pore density 0.4 μm PCF cell culture plate inserts (Millipore, Merck KGaA, Darmstadt, Germany) at a density of 2.27 × 105/cm2 and grown for 6 days at 37 °C in an atmosphere of 5% CO2 and 95% relative humidity. The culture medium was changed once, the day before the experiment. The cells were detached with TrypLE™ Express and washed with PBS once before use. The cells were suspended in 0.1 µM calcein AM diluted in DMEM without phenol red at a cell concentration of 1 × 106 cells/mL. The cells were incubated with calcein AM at 37 °C for 30 min, protected from light, and cells in suspension were intermittently agitated. The cells were kept on ice until the flow cytometry measurements. Cellular fluorescence reflecting the transport activity was measured by an Attune Nxt cytometer (Thermo Fisher Scientific, Waltham, MA, USA) equipped with a blue (488 nm) laser. The calcein signal was detected in the BL1 channel (emission filter: 530/30 nm). Analysis of the data was carried out by the Attune Nxt Cytometer Software v3.1.2 (Thermo Fisher). Stock solution of the compounds were prepared freshly in dimethyl sulfoxide (DMSO). Donor solutions were prepared by diluting test compounds in Hanks’ balanced salt solution (HBSS) at pH 7.4. Prior to the transport studies, the cell monolayers were washed twice with pre-warmed HBSS and pre-incubated for 15 min in HBSS. The test compounds were added in triplicate to either the apical or basolateral sides of the monolayers, and HBSS was added to the receiver wells to start the transport assay. The cells were incubated with the compounds for indicated times at 37 °C, and permeability was measured both in the apical-to-basolateral (A-B) and basolateral-to-apical (B-A) directions. The apical chamber had a final volume of 0.125 mL, while the basolateral chambers contained 0.25 mL. Samples (35 µL) were withdrawn from the receiver compartments at 1 h, 2 h, 3 h, 4 h and 6 h, and from the donor compartments at 0 and 6 h. Sample volumes withdrawn at each time point were replaced with a corresponding volume of pre-warmed HBSS to maintain constant volumes during each experiment. All sample concentrations were corrected for dilution with replacement buffer during sampling. In the inhibition studies, A-B and B-A permeabilities of digoxin (1 µM, traced with 0.17 µCi/mL 3H-digoxin) were investigated across ABCB4 cell monolayers in the absence or presence of increasing concentrations of putative inhibitors. Samples were collected at 3 h. To determine the amounts of radiolabeled substrates (including digoxin) transported, samples mixed with liquid scintillation cocktail were measured with a MicroBeta2 microplate counter (PerkinElmer). Samples from the receiver compartments as well as donor compartments and dosing solution were diluted as necessary and injected into LC-MS/MS. The compounds were separated on a Zorbax RRHD Eclipse Plus C18 3 × 50 mm, 1.8 µm column (Agilent) using water and acetonitrile including 0.1% formic acid (v/v) as mobile phases in gradient modes. The HPLC system was coupled to an AB Sciex 5500 QTRAP Triple quadrupole linear ion trap mass spectrometer using an electrospray interface (AB Sciex LLC, Framingham, MA, USA). The mass spectrometer was operated in multiple reaction monitoring mode. Data analysis was performed with Analyst software (AB Sciex LLC). The integrity of tight junction dynamics in cell monolayers was monitored before and after the transport studies by measuring the transepithelial electrical resistance (TEER) using a World Precision Instrument, Epithelial Voltohmmeter system (Sarasota, FL, USA). The approximate TEER values were 100–120 Ω·cm2. Lucifer Yellow as a paracellular permeability marker was used to check that the highest concentration of the putative inhibitors did not disturb the integrity of cell monolayers. In brief, HBSS containing the putative inhibitors and Lucifer yellow (40 µg/mL) was added to the apical chambers. Samples were collected from the basolateral chambers. Fluorescence of the dosing and receiver samples was measured at an excitation wavelength of 450 nm and an emission wavelength of 520 nm with FLUOstar OPTIMA Microplate Reader (BMG Labtech, Germany). Monolayers with Papp values < 2 × 10−6 cm/s were considered intact. Total RNA was extracted from cells using the TRIzol reagent according to the manufacturer’s instructions. Reverse transcription was performed using the Tetro kit, and TaqMan real-time qPCRs (assay ID Hs00240956_m1 for ABCB4) were performed (Invitrogen/ThermoFisher, Waltham, MA, USA). Canine Gapdh (Assay ID Cf04419463_gH) was used as an internal control. In each sample, ABCB4 mRNA was normalized to Gapdh mRNA. Relative gene expression data were given as the fold change (ΔΔCT). Each sample’s ABCB4 expression was first subtracted from its Gapdh expression to determine its ΔCT. The ΔCTMock was then subtracted from the ΔCTABCB4 to determine the ΔΔCT. The relative expression of ABCB4 was determined by the formula 2−(ΔΔCT). Confluent Mock and ABCB4 cells grown on filters were washed twice with ice-cold PBS and lysed on ice in M-PER Mammalian Protein Extraction Reagent (Thermo Fisher, Waltham, MA, USA) buffer containing freshly added protease inhibitors. The lysate was centrifuged at 13,000× g, 4 °C for 10 min and the supernatant was collected. The total protein content was determined using the PierceTM BCA Protein Assay Kit (Thermo Fisher, Waltham, MA, USA). The lysate was mixed with LDS loading buffer 3:1, and total protein (30 μg/lane) was loaded and separated on 4–15% SDS-PAGE gradient gels. The proteins were then transferred to a polyvinylidene fluoride (PVDF) membrane, blocked with 5% non-fat dry milk for nonspecific binding and probed with primary antibodies specific to human ABCB4 (1:1000) or human ABCB1 (1:1000), respectively, overnight. Following three 5-min washes with TBST (Tris buffered saline + 0.1% Tween 20), the blots were probed with secondary antibody in TBST (1:2000, anti-mouse IgG-HRP) at room temperature for 1 h. After the washing steps, the blots were visualized by ECL reagent (Pierce™ ECL Western Blotting Substrate, #32106) by a BioRad ChemiDoc imaging system (Bio-Rad Laboratories, Inc., Watford, UK). All the experimental conditions were run in triplicate wells and repeated in three biological replicates. The apparent permeability coefficient (Papp, expressed in 10−6 cm/s) was determined from the amount of compound transported per unit time according to the following equation: where ΔQ (pmol) is the amount of substrate translocated to the receiver compartment by the end of incubation, Δt (s) is the duration of incubation, A (cm2) is the filter surface area, and C0 (pmol/cm3) is the initial donor concentration of the substrate. Sink conditions were fulfilled. The mass balance (recovery) was defined as the sum of the test compound recovered from the receiver compartment and the test compound remaining in the donor compartment at the end of the experiment, divided by the initial donor amount. This was calculated according to: Recovery (%) = (CD(Fin)VD + CR(Fin)VR)100/(CD(0)VD), where CD and CR are the concentrations on the donor (D) and receiver (R) sides of the monolayer at the start (0) or end (Fin) of the experiment, and V is used for each of the respective volumes. In all experiments, the recovery for all tested substrates was >70% The efflux ratio (ER) was calculated as Papp, B-A/Papp, A-B. The ER of digoxin as a probe substrate was determined at all concentrations of the inhibitor and in the presence of the vehicle only. IC50 values were calculated from ER values by nonlinear regression analysis in GraphPad Prism 9 (GraphPad, La Jolla, CA, USA).

PMC10003012

Abir Khazaal,Seid Miad Zandavi,Andrei Smolnikov,Shadma Fatima,Fatemeh Vafaee

Pan-Cancer Analysis Reveals Functional Similarity of Three lncRNAs across Multiple Tumors

01-03-2023

long non-coding RNA,cancer,mRNA,pan-cancer analysis,functional analysis,gene ontology

Long non-coding RNAs (lncRNAs) are emerging as key regulators in many biological processes. The dysregulation of lncRNA expression has been associated with many diseases, including cancer. Mounting evidence suggests lncRNAs to be involved in cancer initiation, progression, and metastasis. Thus, understanding the functional implications of lncRNAs in tumorigenesis can aid in developing novel biomarkers and therapeutic targets. Rich cancer datasets, documenting genomic and transcriptomic alterations together with advancement in bioinformatics tools, have presented an opportunity to perform pan-cancer analyses across different cancer types. This study is aimed at conducting a pan-cancer analysis of lncRNAs by performing differential expression and functional analyses between tumor and non-neoplastic adjacent samples across eight cancer types. Among dysregulated lncRNAs, seven were shared across all cancer types. We focused on three lncRNAs, found to be consistently dysregulated among tumors. It has been observed that these three lncRNAs of interest are interacting with a wide range of genes across different tissues, yet enriching substantially similar biological processes, found to be implicated in cancer progression and proliferation.

Pan-Cancer Analysis Reveals Functional Similarity of Three lncRNAs across Multiple Tumors Long non-coding RNAs (lncRNAs) are emerging as key regulators in many biological processes. The dysregulation of lncRNA expression has been associated with many diseases, including cancer. Mounting evidence suggests lncRNAs to be involved in cancer initiation, progression, and metastasis. Thus, understanding the functional implications of lncRNAs in tumorigenesis can aid in developing novel biomarkers and therapeutic targets. Rich cancer datasets, documenting genomic and transcriptomic alterations together with advancement in bioinformatics tools, have presented an opportunity to perform pan-cancer analyses across different cancer types. This study is aimed at conducting a pan-cancer analysis of lncRNAs by performing differential expression and functional analyses between tumor and non-neoplastic adjacent samples across eight cancer types. Among dysregulated lncRNAs, seven were shared across all cancer types. We focused on three lncRNAs, found to be consistently dysregulated among tumors. It has been observed that these three lncRNAs of interest are interacting with a wide range of genes across different tissues, yet enriching substantially similar biological processes, found to be implicated in cancer progression and proliferation. Cancer is a complex disease that continues to be a health burden globally [1]. It is characterised by dynamic genomic alterations, including somatic mutations, epigenetic modifications, copy number variations, and changes in expression profiles [2,3,4]. The emergence of massively parallel sequencing technologies has enabled systematic documentation of the genetic changes in tumors and introduced the concept of the cancer genome [5,6,7]. Considered a landmark in cancer genomics, The Cancer Genome Atlas (TCGA) program has produced, to date, more than 2.5 PB of multi-layered omic data, along with clinical profiles for more than 11,000 patients across 33 cancer types [8,9,10]. TCGA has improved our understanding of cancer genomics, revolutionised cancer classification and identified therapeutic targets [8,11,12]. Although cancers have their own genetic identity with distinct, tissue-specific changes, many tumors share similar genetic alterations that disrupt common biological processes [13,14]. Emerging computational technologies and rich datasets present an opportunity to explore the differences and similarities of genetic and molecular changes across different tumor types using a set of techniques collectively referred to as pan-cancer analyses [14,15]. The importance of pan-cancer profiling lies in its ability to provide a comprehensive analysis of the genetic changes associated with multiple cancers. In addition, not only does it identify shared patterns that aid in the development of uniform treatments strategies, but also distinguishes those unique alterations and enhances personalised care [14]. With the decreasing cost of whole genome sequencing, there is a growing focus on performing pan-cancer analysis on non-coding regions of the genome. An increasing body of evidence suggests non-coding RNAs (ncRNAs) play an important role in biogenesis of cancer [16]. While some ncRNAs have been well studied, such as microRNAs [17], other types have been studied less extensively, including long ncRNAs (lncRNAs). LncRNAs are transcripts with a length greater than 200 nucleotides, exhibiting similar molecular characteristics to messenger RNAs (mRNAs) but lacking an appreciable potential to code for proteins [18,19]. Localised either in the nucleus or cytoplasm, lncRNAs form a complex network of interactions with DNA, RNA, and proteins [20]. Although it is still debatable whether the majority of lncRNAs are simply transcriptional noise, some have been found to be associated with important biological roles. For example, lncRNA XIST is known to initiate silencing of the inactive X chromosome during X inactivation [21,22]. More generally, studies have suggested lncRNAs as cis- and trans-acting regulators of gene expression via chromatin reprogramming [23,24]. They have also been implicated in post-transcriptional regulation, including mRNA translation [25], as well as cell differentiation and development [26]. Despite these findings, lncRNA functions remain poorly understood. LncRNAs are engaged in many cellular functions, and their dysregulation has been linked to diseases, including cancer [16,27]. Aberrant expression of lncRNAs has been identified in different tumors including brain, breast, and colon cancer [28,29]. Many lncRNAs have also been shown to be regulated by oncogenes and tumor suppressors, suggesting a role in oncogenesis [30]. Furthermore, functional studies have revealed validated cancer roles for more than hundred lncRNAs in tumors [31]. A wide range of cancer treatments are currently available [32,33]; chemotherapy, however, continues to be preferred despite its diminishing effectiveness when cancer has advanced or metastasised [33,34]. Poor prognosis is probably due to late diagnoses of cancer, together with tumors having acquired drug resistance, and continues to be a major challenge in treating malignancies [34]. It is thus important to search for new biomarkers for early diagnosis and therapeutic targets for more effective treatments. A plethora of evidence has revealed dysregulation of lncRNAs to be associated with cell proliferation, apoptosis, invasion and drug resistance, processes found implicated in the pathogenesis of cancer [35,36]. These findings put forward lncRNAs as potential biomarkers and therapy agents. At present, there is an increasing focus on identifying lncRNAs associated with tumorigenesis and elucidating their functional implications. Rich RNA-seq datasets are a promising tool for this purpose, but their use can be computationally challenging. To highlight the importance of lncRNA association with cancer and overcome these challenges, The Atlas of Noncoding RNAs in Cancer (TANRIC) was developed [37]. TANRIC is a free and interactive database which gives users access to genomic, proteomic, clinical and lncRNAs expression data of 8143 samples (tumorous and non-neoplastic) from TCGA and others. In order to characterise common, aberrantly expressed lncRNAs we performed a pan-cancer analysis on lncRNA expression profiles from a TCGA derived dataset using TANRIC platform. We hypothesise that those found to be implicated in different cancer types may exhibit similar functional implications across cancers. To assess this hypothesis, we sought to identify dysregulated lncRNAs across eight TCGA cancer types and explored commonality among different malignancies. We then investigated their functional implications, by performing functional analysis and exploiting the similarity of enriched biological processes. Previous pan-cancer studies have focused on somatic mutations of whole genomes [15], tumor microenvironments [38] as well as proteomic profiles [39]. Putative functions have been studied for onco-lncRNAs dysregulated in multiple cancers [40] without focusing on common consistently dysregulated lncRNAs or exploring the similarity of gene ontologies across different cancer types as performed in our study. In total, 9616 lncRNAs manifested significant differential expression across cancers (Table S1). Whilst similarity between pairs of cancers, represented by the Jaccard index, appears low (Figure S1), collectively the number of shared lncRNAs of one cancer type with the remaining types is quite high, with overlap ranging from ~80% to ~97% (Table S2). Of the large number of lncRNAs found to be overlapping among different cancer pairs, seven were observed to be differentially expressed in all cancer types (Table S3). Often the same lncRNA deemed upregulated in one cancer type can be found downregulated in another, or the other way around. Nonetheless, three lncRNAs were found to be consistently dysregulated across all cancers: ENSG00000235904 (RBMS3-AS3) (hereafter, “Antisense”) and ENSG00000261472 (Novel transcript) (hereafter, “Novel”) are both upregulated, and ENSG00000272455 (MRPL20-DT) (hereafter, “Divergent”) is downregulated (Table S4). We chose to focus in the present study on the three consistently dysregulated lncRNAs: Antisense, Novel and Divergent. Correlation analysis revealed in total, 3141 coding genes (|rs| ≥ 0.5 and p-value ≤ 0.01), with 2185 mRNAs found to be co-expressed with Antisense, 69 mRNAs with Novel and 1026 mRNAs with Divergent (Figure 1a,b). We found little overlap between correlated mRNAs across different cancers. It appears that for a given lncRNA, the group of co-expressed mRNAs is specific for each cancer type (Figure 1c). The full list of correlated mRNAs can be found in Table S5. After identifying and combining GO terms enriched by each lncRNA, additional filtering (FDR ≤ 0.05) resulted in the acquisition of three GO terms lists: Two lists of GO terms associated with Antisense and one list with Divergent, with no records linked with lncRNA Novel (Figure S2). In order to provide functional elucidation of the remaining lncRNAs of interest, we explored similarity between GO term pairs using NaviGO and GO pairwise similarity networks were created (RSS ≥ 0.05). Starting with GO list enriched by mRNAs positively correlated with Antisense, three clusters in the network of functionally similar GO terms were identified (Figure 2a). The first cluster contains GO terms predominantly involved in tissues and vessel morphogenesis, together with tissues and vasculature development (Figure 2b). The second cluster includes system and cellular processes such as actin-mediated cell contraction in addition to localisation and movement of cell and/or subcellular component (Figure 2c). Finally, GO terms in the third cluster found of extracellular matrix, structure organisation along with cell adhesion (Figure 2d). Network of mRNAs negatively correlated with Antisense, displayed GO terms appear to be mainly associated with ncRNA metabolic processes, particularly ribosomal RNA (rRNA), ribosome biogenesis, and ubiquitination (Figure 3). Lastly, mRNAs positively correlated with Divergent have enriched substantially similar GO terms, immersed with mRNA processing, splicing and metabolism, in addition to processes associated with cell cycle (Figure 4). Finally, when GO terms enriched by both lncRNAs were compared, high similarity was found between GO terms enriched by mRNAs negatively correlated with Antisense and those enriched by mRNAs positively correlated with Divergent (Figure S3). Interestingly, after further scrutinisation of the different networks, four GO terms were found to be shared between the two: DNA metabolic process, chromosome organisation, cell cycle and RNA processing (Figure 5). The identification of 9616 dysregulated lncRNAs suggests pervasive variation of lncRNA expression in cancers, consistent with previous studies [17,41]. Therefore, understanding functional implications of lncRNAs in malignancies is of high importance, as not only can this serve in developing diagnostic tools, but it can also lead to new treatment strategies. Upon exploring commonality of dysregulated lncRNAs, it was observed that tumors share a substantial number of genes (average overlap ~90%), suggesting that potentially the same lncRNAs could be associated with different tumors across different tissues. Whilst it has been suggested that lncRNAs are cancer specific, with tumors of different types and subtypes exhibiting different expression patterns [41,42], some evidence show otherwise. For instance, MALAT1 was suggested to be involved in multiple tumors; inhibition of the well-studied lncRNA was found to prevent lung cancer metastasis [43]. Conversely, a more recent study showed that knocking out MALAT1 actually promotes metastasis in breast cancer, suggesting its role as a metastasis suppressant [44]. Additionally, an oncogenic role has also been proposed for MALAT1 in colorectal carcinoma [45]. Nonetheless, we observed 2855 lncRNAs to be dysregulated uniquely in one cancer type, denoting some level of specificity. Intriguingly, three lncRNAs showed striking consistent dysregulation: ENSG00000235904, known as RBMS3-AS3 gene and ENSG00000261472, a novel transcript, both exhibited upregulation in all tumor samples whilst ENSG00000272455, known as MRPL20-DT gene, manifested downregulation. As with the majority of lncRNAs, little is known about the functional implication of RBMS3-AS3 or its association with tumors. According to lncATLAS [46], RBMS3-AS3 is found to be expressed mainly in the cytoplasm. Generally, cytoplasmic lncRNAs are believed, through formation of complexes with RNA binding proteins, to be involved in different mechanisms, such as mRNA translation and stability [47,48,49] and protein localisation [50,51]. With regard to cancer, RBMS3-AS3 has been proposed as a competing endogenous RNA (ceRNA), targeted by several miRNAs in breast cancer [52]. In addition, RBMS3-AS3 was shown to be serving as miRNA sponge, acting as a tumor suppressor in prostate cancer [53]. We explored TANRIC’s survival analysis for both of these cancer types and found the survival rate across patients to be higher in those who have lower expression of RBMS3-AS3 (Kaplan–Meier analysis and log-rank test, p-value < 0.05). Furthermore, both gastric and colorectal cancers exhibited dysregulation of RBMS3-AS3 and involvement in ceRNA network [54,55]. Taken together, RBMS3-AS3 seems to display aberrant expression patterns across tumors; further studies are required to investigate its function and potential involvement in cancer. Although this lncRNA was also found to be consistently upregulated across tumors, little is known about its association with cancer. ENSG00002614172 is small in size (<500 bp), and unlike RBMS3-AS3, no localisation information was found in lncATLAS [46]. Expression across tissues was almost negligible, with body fat having the highest value of only 1.7 TPM, according to the Genotype Tissue Expression project GTEX [56]. Lack of information on this transcript is possibly due to it being newly annotated, and most importantly minimally expressed across tissues. In the literature, we came across a breast cancer analysis where ENSG00000261472 was listed among other enriched lncRNAs [57]. However, to the best of our knowledge, no other studies have been published with reference to cancer. Concisely, ENSG00000261472 is a novel lncRNA whose cellular function is yet to be discovered. Similar to Novel, no localisation information was detected in lncATLAS for MRPL20-DT [46]. A recent study, however, found that MRPL20-DT promoter is consistently upregulated across 13 tumors [58]. Likewise, its upregulation amid other lncRNAs was reported in muscle invasive bladder cancer [59]. In contradiction, TANRIC’s survival analysis displayed better survival probability for those with higher expression of MRPL20-DT in bladder cancer (Kaplan–Meier analysis and log-rank test, p-value < 0.05), which comes in conformity with our results of it being downregulated in malignancy. In essence, MRPL20-DT role is still undetermined, but evidence suggest its possible association with cancer. Future research is needed to investigate its dysregulation in tumors and better understand the molecular mechanisms involved. Co-expressed mRNAs lists, classified between positively and negatively correlated, ranged in size across different cancers and different lncRNAs, proposing a wide and diverse network of gene interactions across tumors. In addition, the number of correlated mRNAs of a given lncRNA was dependent on the tissue type. For instance, 1428 mRNAs were positively correlated with Antisense in stomach cancer sample set, compared to only 353 and 30 mRNAs in prostate and breast cancer, respectively (Figure 1a), suggesting some level of tissue specificity, which comes in accordance with previous findings [60]. Although there is little intersect between malignancies, mRNAs were noted to be predominantly different (Figure 1c), suggesting that, despite the commonality of the three lncRNAs of interest, they appear to be interacting with different mRNAs in different tissues. Taken together, lncRNAs seem to manifest both tissue-specific and ubiquitous relations, interacting with a broad range of genes across tumors. GO enrichment analysis differentiated three GO term lists; no GO terms were found to be notably associated with Novel post-filtration, possibly because the number of correlated mRNAs was the lowest compared to Antisense and Divergent, hence, as a consequence no significant ontology enrichment was detected. The absence of GO terms is somewhat surprising but does not undermine the possible involvement of this lncRNA with tumors. It is worth noting that there is evidence of enrichment of Novel in breast cancer [57], in addition to the present study where consistent upregulation was outlined across all eight cancer types. These initial findings are promising; further studies would make a worthwhile contribution, to better understand the underlying mechanisms related to cancer. In order to understand the functional similarities of the two remaining lncRNAs, Antisense and Divergent, we identified three GO similarity networks. It is worth noting that the scoring scheme (RSS) we adopted in creating these networks showed minimal variation when compared with Resnik and Lin’s semantic similarity, another two widely used and known measures [61,62]. Whilst this increases our confidence with results presented here, a caveat with this approach is that network representation differs slightly based on the cut-off used with these scoring schemes. With that said, this is generally the case with many analyses and statistical tests which rely on arbitrary cut-off values, and in our analysis, cut-off value does not change the number or nature of biological processes involved, rather the way they are represented in a network. Three clusters can be identified in this network (Figure 2a). The first cluster comprised of biological processes linked to angiogenesis, blood vessel and tissue morphogenesis as well as vasculature development, all known to be critical for cancer growth (Figure 2b). For instance, it is well-established that angiogenesis is one of the hallmarks of cancer [3]; tumor cells recruit new blood vessels to allow for nutrients and oxygen delivery, as well to be able to metastasise to other tissues [63,64], and this also involves the development of new blood vessels and tissues. This is of importance as it implies that Antisense might be involved with pivotal mechanisms of tumorigenesis. Simultaneously, the second cluster encompassed GO terms of cell motility and migration along with actin filament-based processes (Figure 2c). These processes are also linked to those seen in the first cluster; taking cell motility for example, this is essential in allowing tumor cells to enter the vasculature, transport through blood vessels and invade other sites [65]. Moreover, networks of actin protein filaments form actin cytoskeleton, involved primarily in cell migration and motility in cancer, leading to metastasis [66,67]. Finally, the third cluster involved extracellular matrix and structure organisation together with cell adhesion, processes also associated with cancer progression (Figure 2d). Indeed, there has been a focus on understanding the dysregulation of the extracellular matrix in complex diseases such as cancer. Being the major component of the tumor ‘microenvironment’, it has been suggested to modulate cell behavior and influence adhesion and migration of cells [68,69]. Collectively, the GO terms presented in this network appear to be closely related, describing vital processes for the proliferation and progression of malignancies. The question remains though, whether Antisense is exerting a regulatory role in this network or is simply a by-pass product. Further investigation is required to understand its potential role. The smaller list of negatively correlated mRNAs with Antisense enriched important functions relating to ncRNA metabolic processes, particularly rRNA, ribosome biogenesis, and ubiquitination (Figure 3). Mounting evidence suggests that impaired ribosomal activity drives tumorigenesis [70,71]. Ribosome biogenesis is an important regulator of cellular activities, including cell growth and cell cycle progression [72,73]; an increase in rRNA processing is observed during G1 of interphase, in preparation for protein translation, whilst during mitosis, downregulation of ribosomal activity is needed to signal the ending of cell cycle. Uncontrolled cell proliferation, a common feature in cancer, is a consequence of impaired ribosomal activity. Furthermore, it is now believed that perturbation of ribosomal biogenesis is sufficient to lead to malignant transformation [74]. Another process found is ubiquitination (also known as ubiquitylation), a post-translational mechanism in which proteins are tagged by the conjugation of ubiquitin, for modification. Ubiquitin is a small regulatory protein that is highly conserved in eukaryotes, most commonly found to initiate proteins degradation, apart from also altering protein–protein interactions and modulating cellular processes such as cell cycle, apoptosis cell signaling and DNA repair [75,76]. It has been shown that cytoplasmic lncRNAs interfere with protein expression by either obstructing or promoting ubiquitination [77]. With a balanced ribosomal genesis for instance, tumor suppressor protein p53 is usually post-translationally downregulated through ubiquitination. However, studies have revealed that disruption of ribosomal biogenesis primarily causes activation of p53, and consequently disrupts its degradation through ubiquitination [70]. Hence, it comes as no surprise that these processes are interconnected, and their perturbation is associated with carcinogenesis. lncRNA Antisense, identified in this study, has been shown to be associated with a range of important biochemical processes, explicitly ubiquitination. Currently, novel strategies are being developed to target certain pathways in which ubiquitin is primarily involved, resulting in potentiation of drug efficacy, and overcoming multi drug resistance [78]. Finally, the network similar GO terms related with “Divergent” displayed processes, enriched in more than one cancer type, relating to mRNA processing, in particular, splicing pathways in addition to cell cycle regulation, specifically mitosis (Figure 4). Accounting primarily for protein diversity, splicing is a fundamental step of mRNA processing where the same coding gene can have different, even at times, opposing functional transcripts called isoforms. It has been revealed that aberrant splicing is linked with cancer, yielding cancer-specific isoforms favorable for tumor growth [79,80]. In addition, defective splicing also perturbs the cell cycle, which is also enriched in this network. Consistent with the literature, lncRNAs have been suggested to influence splicing in diseases such as cancer [81]. Moreover, new mechanism of cell death modulation has also been linked to lncRNA through interaction with protein factors, leading to apoptosis resistance [82]. However, the downfall of these findings is that the underlying mechanisms still remain largely unknown. Nonetheless, Divergent has been presented in this study to be consistently downregulated across tumors and seems to be associated with pivotal processes, involved in cancer growth and development; investigating its possible role in splicing events and cell growth may be of benefit. We reported four processes to be shared by both lncRNAs (Figure 5). Interestingly, these processes were found in the network of negatively correlated mRNAs with Antisense, reported to be upregulated, and that of positively correlated mRNAs with Divergent, found to be downregulated in cancers. Taken together, it appears that although these two lncRNAs are interacting with different sets of mRNAs across different cancers, and possibly through different mechanisms with one being upregulated and the other shown to be downregulated; they are both enriching substantially similar processes, found to be fundamental in cancer proliferation and progression. We were interested to evaluate if our findings are generalisable to other cancer types not included in the discovery phase of the three lncRNAs. Accordingly, we assessed the dysregulation of Antisense, Novel, and Divergent on independent TCGA and non-TCGA datasets obtained from TANRIC repository. These include the total of 1047 tumor samples and their related adjacent 218 non-neoplastic tissue samples across five cancer subtypes, four of which are sourced from TCGA including urothelial bladder carcinoma, BLCA (19 non-neoplastic and 252 tumor samples), kidney chromophobe, KICH (25 non-neoplastic and 66 tumor), kidney renal clear cell carcinoma, KIRC (67 non-neoplastic and 448 tumor), and cervical kidney renal papillary cell carcinoma, KIRP (30 non-neoplastic and 198 tumor samples), and one is a non-TCGA dataset collected in Seoul, South Korea comprising 77 non-neoplastic and 83 tumor samples of lung adenocarcinoma (LUAD_KOREA) [83]. We investigated the DE of the three lncRNAs of interest across each dataset. In addition to the t-test, we estimated p-values using a non-parametric test (i.e., the two-sample Wilcoxon test or the Mann–Whitney test) to mitigate the biases associated with the underlying assumptions of hypothesis tests. The p-values were adjusted for multiple hypothesis testing using the Bonferroni correction. In agreement with our results, we observed the three lncRNAs to be consistently dysregulated across all five cancer types, with adjusted p-value ≤ 0.01 (Figure 6 and Table S6). While the direction of dysregulation can be different in the validation datasets compared to the discovery datasets, the significance of DE (independent of the hypothesis test) supports the potential role of these lncRNAs across diverse cancer types and provides more evidence that lncRNAs identified in this study could serve in potentially developing new pan-cancer biomarkers or therapeutic agents. The foundational processes identified in this study, such as angiogenesis, underly all tumors regardless of tissue type. Understanding the role of lncRNAs in enriching these perturbations is thus very important and can be advantageous, particularly when malignant cells spread to other tissues, leading to current treatment strategies in becoming somewhat ineffective. A possible future direction would be to use other computational approaches and databases to decipher putative functions of lncRNAs. For instance, taking an integrative approach considering transcriptomic and epigenomic data (e.g., methylation profile [84]), or genomic changes such as copy number alterations (CNAs) [85]. In addition, using UCSC genome browser [86], we could also examine the genomic location of lncRNAs along with co-expressed coding genes in order to explore cis and trans-relationships, which can be an initial step in discovering potential regulatory roles. Further analysis of the dysregulation of the identified lncRNAs can also be performed across other datasets, allowing further evidence to be provided for their dysregulation across other cancer types. Moreover, we have focused in the present study on commonly dysregulated lncRNAs, the complimentary future approach could be to explore lncRNAs that are specific to each cancer type/subtype, with the aim of investigating cancer-specific functions, which can also be of benefit. We used TANRIC to access expression data of lncRNAs of 3326 tumor samples and their related adjacent 416 non-neoplastic tissue samples for eight cancer subtypes as categorised in TCGA. Included were 105 non-neoplastic and 837 tumor samples of breast invasive carcinoma (BRCA), 58 non-neoplastic and 488 tumor samples of lung adenocarcinoma (LUAD); 17 non-neoplastic and 220 tumor samples of lung squamous cell carcinoma (LUSC); 52 non-neoplastic and 374 tumor samples of prostate adenocarcinoma (PRAD); 59 non-neoplastic and 497 tumor samples of thyroid carcinoma (THCA); 33 non-neoplastic and 285 tumor samples of stomach adenocarcinoma (STAD), 50 non-neoplastic and 200 tumor samples of liver hepatocellular carcinoma (LIHC); and 42 non-neoplastic and 425 tumor samples of head and neck squamous cell carcinoma (HNSC). An overview of the workflow of this study is shown in Figure S4. We carried out differential expression analysis by comparing lncRNA expression levels between tumor and related adjacent non-neoplastic samples of a given set. Expression data for a total of 12,727 lncRNAs was downloaded from TANRIC v2.0 for each of the eight TCGA cancer types. Differentially expressed lncRNAs (up- and downregulated) were identified (|log2(FC)| > 1) and Student’s t-test was applied to calculate p-values followed by the Benjamini and Hochberg method to control the false discovery rate (FDR) [87]. Differentially expressed lncRNAs with adjusted p-value ≤ 0.01 were considered statistically significant. We then identified common dysregulated lncRNAs (found in 2+ cancers) and unique dysregulated lncRNAs (specific to a given cancer type). Commonality was evaluated between each pair of cancers and represented by the Jaccard index (J) [88]. These analyses were implemented in MATLAB with the code available on the GitHub repository (https://github.com/VafaeeLab/PanCancer-lncRNAs). Guided by the “guilt by association” principle [89], we utilised TANRIC to explore mRNAs correlated with common dysregulated lncRNAs across each cancer type. Spearman rank correlation coefficient (rs) were calculated to examine correlation relationships between lncRNAs of interest and mRNAs expression. Lists of correlated mRNAs were extracted based on cut-offs of rs ≥ 0.5 or rs ≤ −0.5, for positive and negative correlation, respectively, with correlation p-value ≤ 0.01. Exploration of large sets of genes can be achieved by organising them based on common functional features and one of the most widely used ways to understand genes and their products is to explore gene ontologies (GO) [90,91]. Thus, to investigate functional implications of lncRNAs of interest, we performed GO enrichment analysis with particular focus on biological processes. We exploited WebGestalt (WEB-based gene set analysis toolkit), to identify GO terms enriched by mRNAs lists, found to be correlated with common differentially expressed lncRNAs, with the aim of perusing their functional role [92,93]. Statistical analysis of GO enrichment was performed using a Fisher’s exact test with a hypergeometric null distribution [94,95]. Significantly enriched GO terms were determined as FDR ≤ 0.05. GO, considered as a universal vocabulary, is structured as a hierarchical directed acyclic graph where each node represents a class of gene function (GO term), and the connection between two GO terms indicates different relationships. This hierarchy allows exploring semantic similarities among enriched GO terms, which could imply functional similarities between the associated genes [61,96]. Following the annotation of mRNAs lists by ontology, we merged GO terms enriched by each lncRNA across different cancers and distinguished two separate groups: GO terms enriched by positively and negatively correlated genes. After additional filtering, based on FDR ≤0.05, GO terms were then further investigated. In order to measure closeness of GO terms using NaviGO, an interactive software that allows the retrieval of functional similarity scores and visualisation as networks [97]. From the six different scoring schemes offered by NaviGO, we relied on Relevance Semantic Similarity (RSS), which measures the relative depth and rareness of the biological processes involved [61]. RSS ranges from 0 to 1, with 0 representing zero similarity and 1 indicating very high similarity. Functional similarity networks were created using the NaviGO visualiser based on threshold RSS ≥ 0.5. Once seen as transcriptional by-products, lncRNAs are now emerging as key players in cellular function, regulating a wide range of biological processes, and involved in their disruption. Our study provides evidence that lncRNAs may be contributing to the hallmarks of cancer, regardless of cancer type. These results are promising, suggesting that lncRNAs can serve as potential therapeutic targets to be applied in multiple cancer subtypes; future treatment strategies may potentially include non-coding genes in addition to specific protein targets. Indeed, lncRNAs have brought a promising new era to cancer biology, especially in terms of diagnosis and therapy.

PMC10003015

Ying Xu,Qing Zhu

Histone Modifications Represent a Key Epigenetic Feature of Epithelial-to-Mesenchyme Transition in Pancreatic Cancer

02-03-2023

pancreatic cancer,epigenetics,histone modification,epithelial-to-mesenchymal transition,pancreatic ductal adenocarcinoma

Pancreatic cancer is one of the most lethal malignant diseases due to its high invasiveness, early metastatic properties, rapid disease progression, and typically late diagnosis. Notably, the capacity for pancreatic cancer cells to undergo epithelial–mesenchymal transition (EMT) is key to their tumorigenic and metastatic potential, and is a feature that can explain the therapeutic resistance of such cancers to treatment. Epigenetic modifications are a central molecular feature of EMT, for which histone modifications are most prevalent. The modification of histones is a dynamic process typically carried out by pairs of reverse catalytic enzymes, and the functions of these enzymes are increasingly relevant to our improved understanding of cancer. In this review, we discuss the mechanisms through which histone-modifying enzymes regulate EMT in pancreatic cancer.

Histone Modifications Represent a Key Epigenetic Feature of Epithelial-to-Mesenchyme Transition in Pancreatic Cancer Pancreatic cancer is one of the most lethal malignant diseases due to its high invasiveness, early metastatic properties, rapid disease progression, and typically late diagnosis. Notably, the capacity for pancreatic cancer cells to undergo epithelial–mesenchymal transition (EMT) is key to their tumorigenic and metastatic potential, and is a feature that can explain the therapeutic resistance of such cancers to treatment. Epigenetic modifications are a central molecular feature of EMT, for which histone modifications are most prevalent. The modification of histones is a dynamic process typically carried out by pairs of reverse catalytic enzymes, and the functions of these enzymes are increasingly relevant to our improved understanding of cancer. In this review, we discuss the mechanisms through which histone-modifying enzymes regulate EMT in pancreatic cancer. Pancreatic cancer is the seventh leading cause of cancer-related death globally [1]. Patient prognosis is bleak, with a five-year survival rate of only 10% [2,3]. Moreover, the incidence of pancreatic cancer has risen steadily in recent years [4]. By 2025, it is expected to become the second-leading cause of cancer-related mortality in the US [1]. Surgery remains the main therapeutic approach but is only effective during the early stages of disease. The early metastases and rapid progression commonly seen in patients result in diagnosis not occurring until the advanced stages of disease in more than half of all cases, which precludes them from surgery [5,6]. Although systemic combination chemotherapy also forms a crucial component of pancreatic cancer treatment, drug resistance is a significant problem [7]. Therefore, it is essential to understand the molecular mechanisms involved in the carcinogenesis, progression, metastasis, and drug resistance of pancreatic cancer to identify precise diagnostic and therapeutic targets. Epithelial–mesenchymal transition (EMT) is a fundamental process for embryogenesis, organ development, and tissue repair, as well as for tumor invasion and early metastasis [8]. During EMT, epithelial cells lose their apical–basal polarity and cell–cell adhesion, and are transformed into invasive mesenchymal cells [9]. In addition, EMT can generate cells with stem cell properties that allow them to form tumors more efficiently [10,11]. EMT enables cancer cells at the primary site to acquire motility and invasiveness, which can drive the malignant progression of tumors. Furthermore, EMT also can regulate a variety of cancer features, such as tumor cell stemness, adaptation to microenvironmental alterations, and resistance to therapy [12]. EMT facilitates tumorigenesis and promotes the invasion, metastasis, and therapeutic resistance of pancreatic cancer, and is, therefore, associated with poor patient prognosis [13,14,15]. EMT is triggered by signals sent within the cellular microenvironment. The mechanisms underlying this process are intricate and involve multiple signaling pathways and various EMT-induced transcription factors [16]. Interestingly, the acquisition of mesenchymal properties in cancer cells is transient rather than permanent, and cancer cells can restore their epithelial state through the mesenchymal–epithelial transformation (MET) process [17]. Given the extensive gene expression reprogramming needed to complete the reversible EMT process, epigenetic regulators are likely to have essential functions [18]. Epigenetics describes heritable changes in cellular phenotypes that are independent of alterations in the DNA sequence [19]. Epigenetic changes are associated with aberrant gene functions and altered patterns of gene expression. The major epigenetic regulators include DNA methylation, histone modification, chromatin remodeling, and non-coding RNAs [19,20]. These molecular regulatory mechanisms can alter promoter accessibility and chromatin structure, so as to affect cellular gene expression and influence tissue homeostasis [20]. Indeed, we find that the most significant and complex epigenetic regulatory mechanisms detected within pancreatic cancers comprise histone modifications, which include methylation, acetylation, ubiquitination, phosphorylation, and SUMOylation [21]. Histone modifications can be dynamically regulated by enzymes with reverse catalytic activity, and these enzymes are the primary epigenetic regulators of EMT. This review provides an overview of EMT in pancreatic cancer, together with the mechanisms of histone modification involved in the regulation of EMT, focusing primarily on methylation, acetylation, and ubiquitination. Furthermore, we discuss the application of histone epigenetic regulators as therapeutics for patients with pancreatic cancer. EMT leads to significant phenotypic alterations in cancer cells that are associated with their invasion, spread, and metastasis. Epithelial cells maintain cell–cell contact through tight junctions, adhesive junctions, desmosomes, and gap junctions [22]. During EMT, these cell–cell junctions are lost, and significant cytoskeletal reorganization occurs. Epithelial cells lose top-basal polarity and are transformed into mesenchymal cells, gaining motility and invasiveness [9,23]. The activation of EMT leads to a downregulation of the expression of epithelial genes, including E-cadherin, ZO-1, and occludin. Concurrently, cells acquire a mesenchymal morphology and express mesenchymal markers, such as N-cadherin, vimentin, and fibronectin [8]. The downregulation of E-cadherin (which binds to β-catenin to form mature adhesion junctions between cells [24,25]) is a key step in EMT and is often associated with the invasive potential and undifferentiated phenotype of tumor cells. Moreover, E-cadherin downregulation can disrupt cell adhesions and activate various EMT-related intracellular signaling pathways [26]. EMT is induced by a variety of extracellular stimuli and intracellular signaling pathways, including the transforming growth factor (TGF), Wnt, and hedgehog (Hh) signaling pathways, etc. [16] (Figure 1). TGF-β can induce EMT through different signaling pathways: those that are dependent on the SMAD (suppressor of mothers against decapentaplegic) transcription factor family, and those that are SMAD-independent [27]. In the SMAD-dependent pathway, TGF-β signals through a tetrameric complex containing type I and type II receptors (TβRI and TβRII) to activate SMAD2 and SMAD3. Phosphorylated SMAD2 and SMAD3 form trimers with SMAD4 to regulate EMT-related transcriptional regulators. In the SMAD-independent pathway, TGF-β activates the extracellular signal-regulated kinase 1/2 (ERK)/mitogen-activated protein (MAP) kinase, Rho GTPase, and phosphoinositide 3 (PI3) kinase/Akt pathways to promote EMT [28]. The Wnt signaling pathway is also crucial for the induction of EMT. In the absence of Wnt signaling, β-catenin is phosphorylated by casein Kinase 1 (CK1) and adenomatous polyposis coli (APC)/AXIN/glycogen synthase kinase-3 beta (GSK3β) complexes, prior to being ubiquitinated and degraded by proteasomes. When Wnt ligands bind to frizzled receptors, this degradation process is inhibited, and accumulated cytoplasmic β-catenin transfers to the nucleus and activates the transcription of EMT-related genes [29]. In Hh signaling, Hh ligands bind to the transmembrane receptor patched-1 to inhibit the transmembrane G protein-coupled receptor Smoothened (SMO), initiating intracellular cascades and activating the glioma-associated oncogene (GLI) transcription factors that induce the expression of EMT-related genes [30]. In addition, tyrosine kinase receptors are also involved in pancreatic cancer EMT through the regulation of the PI3K/AKT and ERK/MAPK signaling pathways [31,32]. These signaling pathways activate EMT transcription factors (EMT-TFs) [12], which include the Snail family (Snail1/Snail and Snail2/Slug), TWIST family (Twist1 and Twist2), and Zinc finger E-box binding homeobox family (Zeb1 and Zeb2) of proteins [33]. The tumor microenvironment (TME) is crucial in EMT. The pancreatic cancer microenvironment consists of cancer cells, stromal cells, and extracellular components [34]. TME-inducible factors secreted by cancer cells and cancer-associated fibroblasts (CAF) create an inflammatory microenvironment by recruiting immune cells [35]. Many of these cells secrete cytokines and chemokines that induce EMT [36]. For example, IL-6 regulates the expression of EMT-related genes in pancreatic cancer cells through the STAT3-mediated signaling pathway [37]. As pancreatic cancer contains abundant stromal cells and extracellular matrix but lacks vascularization, severe hypoxia persists within the tumor, causing broad effects on cellular behavior [38]. The adaptive response of pancreatic cancer cells to hypoxia is mainly mediated by hypoxia-inducible factors (HIFs), which bestow more aggressive and therapeutically resistant phenotypes [39]. During hypoxia, the ubiquitin-proteasome degradation pathway mediated by HIF-1 is inhibited. As a consequence, HIF-1α accumulates in cells and binds to HIF-1β to form a functional transcriptional complex [40]. HIF-1α drives hypoxia-induced EMT programming in pancreatic cancer cells through interaction with the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcriptional complex [41]. In addition, HIF-2α can promote EMT in pancreatic cancer cells by regulating the binding of Twist2 to the E-cadherin promoter [42]. The two most common genetic alterations in pancreatic cancer are mutations in the Kirsten rat sarcoma viral (KRAS) oncogene and inactivation of SMAD4 [43]. KRAS-driven tumors frequently exhibit EMT induction [15,44,45,46]. The most extensively studied mechanism for inducing EMT is the TGF-signaling pathway [47], and SMAD4 is an effector of this pathway [28,48]. The function of SMAD4 in the EMT of pancreatic cancer cells remains controversial. Whilst the majority of studies have demonstrated that EMT requires the entire TGF-β signaling pathway (including SMAD4) [28,49,50,51], others have shown that the inactivation of SMAD4 can induce EMT [52,53]. Nevertheless, it is clear that SMAD4 is a major factor in the EMT seen in pancreatic cancers. Cancer stem cells (CSCs) are undifferentiated quiescent cells that possess properties of self-renewal and cellular plasticity [54]. The molecular features of CSCs are influenced by cells exhibiting an EMT phenotype, and CSCs themselves show an EMT phenotype [55,56,57]. Pancreatic cancer stem cells (PCSCs) are subsets of pancreatic cancers with specific cell surface markers that have important functions during tumor recurrence and therapeutic resistance [58,59,60]. Key signaling pathways that regulate PCSCs can also activate many EMT-related pathways, promoting pancreatic cancer progression and resistance to therapeutics [61,62]. Cancer was initially recognized as a genetic disease. However, it is now widely believed that the initiation and progression of cancer cannot be accounted for by genetic alterations alone, but must also involve epigenetic changes [20]. Epigenetic modifications are reversible changes that regulate gene expression without altering DNA sequences. They include DNA methylation, histone modification, chromatin modification, and alterations in noncoding RNA profiles (Figure 2). Chromatin is the carrier of genetic information, and the nucleosome is its basic unit. Each nucleosome consists of a histone octamer composed of the core histones (two copies each of H2A, H2B, H3, and H4), which is wrapped in approximately 147 bp of DNA [63]. DNA methylation transfers a methyl group to the C5 position of cytosine in CpG dinucleotides to form 5-methylcytosine (5mC). The DNA (cytosine-5)-methyltransferase 3A (DNMT3A) and DNMT3B enzymes are responsible for de novo DNA methylation, which is maintained by DNMT1 [64]. Chromatin-remodeling complexes use ATP as an energy source to mobilize, eject, and exchange histones. The SWI/SNF complex alters nucleosome positioning and structure by sliding and ejecting nucleosomes to make the DNA more accessible to transcription factors and other chromatin regulators [65]. Noncoding RNAs (ncRNAs), including circular RNA (circRNA), long non-coding RNA (lncRNA), and microRNA (miRNA), can regulate other epigenetic processes, and be regulated by them. Some specific lncRNAs are extensively associated with chromatin remodeling and modification complexes, and target them to specific genomic loci to alter DNA methylation and the structure and modification of chromosomes [66]. Histone modifications affect chromatin structure, which plays an important role in gene regulation and carcinogenesis [67]. The most common changes observed in histone modification patterns in pancreatic cancer are methylation, acetylation, and ubiquitination. Multiple histone-modifying enzymes are involved in the dynamic regulation of these changes, and a balance between histone-modifying enzymes is critical for maintaining normal cellular function (Table 1). A common histone modification is methylation, which takes place on arginine, lysine, and histidine residues [68]. Lysine and arginine methyltransferases (KMTs and PRMTs) catalyze the transfer of the methyl group, while lysine demethylases (KDMs) control its removal. All methyltransferases use S-adenosyl methionine (SAM) as a substrate to transfer methyl groups onto the lysine and arginine residues of histones [69,70]. Histone acetylation is regulated by histone acetyltransferases (HATs) and histone deacetylases (HDACs). Acetylation can reduce the positive charge of lysine residues, leading to reduced binding between histone tails and negatively charged DNA, leaving the underlying DNA exposed [71]. Histone ubiquitination occurs primarily on H2A and H2B [72]. Ubiquitin (Ub) covalently binds to the target lysine residue under the continuous action of three proteins, the E1 activating enzyme, E2 conjugating enzyme, and E3 ligase [73]. E3 is essential and specifically required for histone ubiquitination [74]. Conversely, the deubiquitinating enzyme (DUB) is responsible for removing Ub [75]. PRMT1 in EMT: Protein arginine methyltransferase 1 (PRMT1) is the principal methyltransferase that catalyzes the methylation of H4R3 and functions as a transcription co-activator [147]. PRMT1 expression is increased in patients with pancreatic cancer, and higher expression is associated with poorer prognosis [77,79]. PRMT1 can bind to the β-catenin promoter region, increasing the expression of the β-catenin protein in pancreatic cancer cells [79]. Stimulation of the Wnt/β-catenin signaling pathway promotes pancreatic cancer proliferation, migration, and invasion while regulating therapeutic resistance [148,149,150,151]. Increased levels of β-catenin in the nucleus can promote EMT-related gene expression. Furthermore, β-catenin can form a complex with E-cadherin to regulate the intercellular connections that are important in cell–cell adhesions [25,152]. The Hh signaling pathway is aberrantly activated during tumorigenesis in the pancreas [153]. Hh signaling induces the expression of EMT-related genes, such as PTCH1, WNT, and SNAI1, by activating Gli transcription factors. The methylation of Gli1 by PRMT1 at R597 improves the capacity of Gli1 to bind to its target gene promoter, thereby enhancing the transcriptional activity of Gli1 [81]. Moreover, ZEB1, a zinc finger E-box binding homeobox transcription factor, is crucial for the EMT process and abnormal expression of ZEB1 has been reported in pancreatic cancer [128]. Overexpression of ZEB1 can significantly reverse the anti-tumor effects induced by PRMT1 downregulation [77]. PRMT5 in EMT: PRMT5 catalyzes the methylation of arginine on H2AR3, H4R3, and H3R8, and acts primarily as a tumor-promoting factor [147,154]. Patients with pancreatic cancer who display higher levels of PRMT5 expression present lower overall survival [83,84]. PRMT5 induces the phosphorylation of the epidermal growth factor receptor (EGFR), upregulates the expression of β-catenin through the EGFR/AKT/β-catenin pathway, and promotes the EMT of pancreatic cancer cells to enhance tumor migration and invasion [83]. EGFR belongs to the membrane-bound ErbB/HER family of receptor tyrosine kinases (RTKs) and plays an important role in the maintenance of epithelial tissues. When EGFR signaling is altered, it becomes the grand orchestrator of epithelial transformation and promotes EGF-induced EMT in pancreatic cancer [155]. SETD2 in EMT: SETD2 is the sole enzyme responsible for H3K36me3 [156]. SETD2 is downregulated in pancreatic cancer, and a low expression of SETD2 is linked to poor clinical prognosis [93,94]. During pancreatic carcinogenesis, loss of SETD2 promotes KRAS-driven acinar-to-ductal metaplasia, as well as EMT and metastasis through sustained AKT activation and loss of α-catenin [94]. KMT5 family in EMT: KMT5A (SET8/PR-SET7) and KMT5B/C (SUV4-20H1/2) belong to the KMT5 family of lysine methyltransferases. H4K20 is monomethylated by KMT5A, before stepwise methylation occurs through the function of KMT5B/C from H4K20me1 to H4K20me2/me3 [21,157]. KMT5A upregulates the expression of stemness and EMT-related genes in pancreatic cancer cells by inducing the expression of the receptor tyrosine kinase-like orphan receptor 1 (ROR1) [99]. ROR1 is a transmembrane protein that induces EMT in breast cancer by enhancing EGFR signaling [158,159]. KMT5C has no direct effect on EMT-related transcription factors but instead regulates EMT by regulating the expression of MET-related transcription factors such as FOXA1, OVOL1, and OVOL2. Targeting KMT5C can activate epithelial transcription programs and inhibit the invasion and migration of pancreatic cancer cells [101]. EZH2 in EMT: Enhancer of zeste homolog 2 (EZH2) is the enzymatic subunit of the polycomb repressor complex 2 (PRC2) that promotes transcriptional silencing by methylating H3K27 [160]. EZH2 is overexpressed in patients with pancreatic cancer and is associated with poorer clinical outcomes [104,106]. The best characterized pathway involved in the induction of EMT is mediated by TGF-β signaling. TGF-β stimulates the expression of the SRY-box transcription factor 4 (SOX4) protein, which is an important developmental transcription factor involved in the regulation of the TGF-β signal transduction pathway [161]. SOX4 not only regulates the expression of EMT-related genes but also reprograms the epigenome to induce EMT by inducing EZH2 expression [162]. In pancreatic cancer, increased expression of SOX4 and EZH2 is associated with poor patient prognosis [116]. The downregulation of E-cadherin is a crucial step in EMT, which promotes metastasis by boosting cancer cell invasion and dissociation. EZH2 can stimulate the migration and invasion of pancreatic cancer by inhibiting the expression of E-cadherin [106]. EZH2 may achieve this through its interaction with the lncRNA MALAT-1, which promotes the proliferation and metastasis of pancreatic cancer [163]. KDM2B in EMT: KDM2B, also known as Ndy1, FBXL10, and JHDM1B, demethylates H3K36 and is overexpressed in human pancreatic cancer cells [164]. A core component of the Hippo signaling pathway is the adaptor protein MOB1 [165], which functions to depress Hippo transcriptional activity by increasing the phosphorylation of the yes-associated protein 1 (YAP) and tafazzin (TAZ) proteins. KDM2B transcriptionally inhibits the expression of MOB1 and promotes pancreatic cancer migration and invasion by promoting Hippo signaling [112]. KDM2B also inhibits the expression of several epithelial marker genes such as CDH1, miR200a, and CGN by modulating histone H1A ubiquitination [109]. KDM3A in EMT: KDM3A catalyzes the demethylation of H3K9me1/me2, which mediates transcriptional activation [166]. KDM3A mediates the upregulation of doublecortin-like kinase 1 (DCLK1), which is critical for the development and progression of pancreatic cancer during hypoxia. Under hypoxia, HIF1α activates KDM3A, which, in turn, increases DCLK1 mRNA expression [113]. DCLK1 activates EMT and promotes the migration and invasion of pancreatic cancer cells [167], while knockdown of DCLK1 reduces the expression of EMT transcription factors in these cells [168]. KDM4B in EMT: KDM4B is a member of the jumonji domain 2 (JMJD2) demethylase family [169], which catalyzes the demethylation of H3K9 and H3K36 [170]. KDM4B positively regulates the EMT process by activating the transcription of ZEB1, which plays a key role in TGF-β-induced EMT [116]. KDM5A in EMT: KDM5A, also known as JARID1A or RBP2, can remove the lysine of H3K4me2 and H3K4me3, resulting in activation or inhibition of transcription. KDM5A is overexpressed in pancreatic cancer cells, and is a member of the JMJC family of oxygen-sensitive enzymes [118,119,171]. KDM5A can be blocked by increased NOX4, which is the main endogenous source of reactive oxygen species (ROS). In pancreatic cancer cells under hypoxia, NOX4 expression is upregulated [172]. NOX4 regulates SNAIL1 transcription to induce EMT and promote the invasion and metastasis of pancreatic cancer cells [117]. KDM6A in EMT: KDM6A, also known as UTX, specifically catalyzes the demethylation of H3K27me3 [173] and is downregulated in pancreatic cancer cells [120,121,122]. The transcriptional activator hepatocyte nuclear factor-1a (HNF-1a) is thought to be a key tumor suppressor in pancreatic cancer [174], and recruits KDM6A to indirectly inhibit the expression of genes involved in tumorigenesis and EMT [122,123]. In pancreatic cancer cells, reductions in KDM6A lead to the increased expression of activin A, a member of the transforming growth factor-β superfamily of cytokines that activates a noncanonical p38 MAPK pathway to induce mesenchymal identity [120] and promote EMT [175,176]. The CREB-binding protein (CBP) and p300 mediate histone lysine acetylation. Due to their considerable sequence homology and functional overlap, they are often referred to as a single entity (CBP/p300) [177]. CBP/p300 activates gene transcription through the acetylation of histone H3 lysine 27 (H3K27ac) [177]. Aberrant expression of p300 has been shown in pancreatic cancer cells [178]. p300 maintains the expression of the GATA-binding factor 6 (GATA6), thereby affecting the differentiation program regulated by this transcription factor [179]. GATA6 directly and indirectly inhibits dedifferentiation and EMT in pancreatic ductal adenocarcinoma (PDAC) [180]. P300/CBP-associated factor (PCAF) is a member of the GCN5-related N-acetyltransferase family that promotes transcription as a histone acetyltransferase [181]. PCAF/p300 has a synergistic effect in regulating the transcriptional repression/activation of ZEB1, forming the P300/PCAF/ZEB1 complex on the miR200c/141 promoter. PCAF/P300 induces the lysine acetylation of ZEB1 to activate miR200c transcription [182]. Loss of miR-200 family members and the upregulation of ZEB1 and ZEB2 are involved in the regulation of EMT. Transcriptional repression of the miR-200 family by ZEB1/ZEB2 is a major factor in the maintenance of mesenchymal characteristics and the induction of EMT [183]. Moreover, PCAF functions in the Ras ERK1/2 pathway and promotes the motility of pancreatic cancer cells, suggesting that PCAF is involved in pancreatic cancer EMT through multiple pathways [184]. HDACs prevent gene expression. In pancreatic cancer, HDACs regulate proliferation, apoptosis, and metastasis [185]. High levels of HDAC1 and HDAC2 expression are linked to distant pancreatic cancer transitions, and both proteins enhance tumor invasiveness [129]. Pancreatic cancer cells proliferate and migrate more readily because of HDAC1 and HDAC2-mediated inhibition of E-cadherin expression in tumor cells [127,128]. HIF-1α plays a vital role as a transcriptional regulator of hypoxia-induced EMT, and a significant correlation exists between HIF-1α and HDAC1 expression in pancreatic cancer. In addition, high levels of these proteins are associated with a poorer prognosis for malignancies in patients, which may suggest that HDAC1 mediates HIF-1α stability through epigenetic regulation [186]. SIRT1 is a mammalian NAD+-dependent class III HDAC, which can regulate the Wnt/β-catenin signaling pathway by deacetylating β-catenin [187]. In the acinar-to-ductal metaplasia (ADM) of the pancreas, SIRT1 interferes with Wnt/β-catenin signaling by regulating the acetylation of β-catenin [133]. K119 is the most common ubiquitination checkpoint for H2A. The main E3 ubiquitin ligase of H2AK119ub1 is the catalytic subunit of the polycomb inhibitory complex (PRC1) [72]. This subunit consists of Ring1A and Ring1B and is regulated by Bmi1 (also known as PCGF4) [188]. The transcriptional repressor Snail can induce EMT by inhibiting the transcription of E-cadherin. In pancreatic cancer, Ring1A and Ring1B are critical for this regulatory process. Furthermore, EZH2 promotes Snail to recruit Ring1A and Ring1B more efficiently [189]. Concomitantly, Bmi-1 is overexpressed in pancreatic cancer, and this dysregulation is associated with abnormal expression of miRNAs. Overexpression of Bmi-1 can also promote EMT by downregulating E-cadherin [138,190]. The ubiquitin-specific peptidases (USPs) are the primary members of the deubiquitinase family [191], where USP22 and USP28 are overexpressed in pancreatic cancer cells [139,140,141,142,143,144,145,146]. USP22 regulates the levels of H2Bub1 and H2Aub1 through deubiquitination, thereby promoting the transcription of downstream genes [192]. Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase that mediates a variety of signal transduction pathways [193]. USP22 induces the occurrence of EMT in pancreatic cancer cells by activating FAK signaling. Upregulation of USP22 can increase the expression of the ZEB1 and Snail transcription factors, significantly reduce the expression of E-cadherin at cell–cell junctions, and upregulate the expression of mesenchymal markers [143]. USP28 regulates the process of histone H2A deubiquitination [194]. USP28 deubiquitinates and stabilizes the forkhead box M1 (FOXM1) transcription factor, which, in turn, activates the Wnt/β-catenin pathway and subsequently the expression of many EMT-related genes [146,195]. As a key mediator of Wnt/β-catenin signaling, FOXM1 mediates the nuclear accumulation of β-catenin and the ensuing downstream target gene expression in pancreatic cancer cells [196]. Our understanding of the therapeutic potential of drugs targeting epigenetic modifiers has grown immensely in recent years. Histone modifiers are attractive targets for prospective therapy because they contain unique, druggable catalytic domains. Some FDA-approved inhibitors are already used in clinical practice, and others are currently in clinical trials [197]. Indeed, several drugs targeting EZH2 have been developed [198]. 3-Denitrogen-neplanocin A (DZNeP) and GSK126 are two newly discovered inhibitors of EZH2. Combination therapy of DZNeP and gemcitabine can act synergistically to inhibit pancreatic tumor cell growth and migration. DZNeP enhances the anti-proliferation activity of gemcitabine and significantly promotes apoptosis [199]. Similarly, GSK126 and BET bromine domain inhibitors have synergistic antitumor effects in the treatment of pancreatic cancer [200]. Thus, in combination with other therapeutics, EZH2 inhibitors possess great potential in the treatment of pancreatic cancer. Histone deacetylase inhibitors (HDACIs) are becoming an important class of therapeutics in the treatment of pancreatic cancer. In preclinical studies, HDACIs have shown significant antitumor potential and low toxicity. HDACIs exert antitumor effects by stalling the cell cycle, activating apoptosis, inhibiting angiogenesis, and inhibiting metastasis [201]. However, when used alone, HDACIs are not as effective in the treatment of solid tumors. Many studies have now shown that HDACIs have synergistic effects with traditional cytotoxic and targeted therapeutic drugs against pancreatic cancer. The small molecule Domatinostat (4SC-202) is a class I selective HDACI that induces antitumor effects and sensitization to chemotherapy. It functions by reducing the expression of the transcription factor FOXM1, which impairs the redox homeostasis of cancer stem cells [202]. MPT0E028 is a novel pan-HDACI that targets both classes I and II HDACs. The co-administration of MPT0E028 and mitogen-activated protein kinase (MEK) inhibitors has synergistic effects in KRAS-mutated and KRAS-wild-type pancreatic cancer cells. This combination therapy induces a strong apoptotic response and significantly reduces cancer cell viability [203]. Additionally, the combination of radiation therapy with either CUDC-101 (simultaneously inhibits targets such as HDAC, EGFR, and HER2) or SAHA (inhibits class I and class II HDACs) could enhance radiation-induced cytotoxicity in human pancreatic cells [204]. Close interactions exist between the various histone epigenetic regulators, and many can be combined to synergistically regulate transcription. The use of dual inhibitors targeting different epigenetic regulators is an effective strategy to improve the safety and efficacy of single epigenetic target drugs and to overcome drug resistance. UDC-907 is a dual inhibitor of HDAC and PI3K that inactivates RAF-MEK-ERK signaling in pancreatic cancer cells by inhibiting the PI3K-AKT-mTOR pathway [205]. Metavert is a dual inhibitor of GSK3β and HDAC that induces cancer cell apoptosis and reduces both migration and the expression of stem cell markers, thereby slowing tumor and metastatic growth. Metavert has also been shown to provide synergistic effects with gemcitabine [206]. A new and effective strategy for the treatment of pancreatic cancer is 13A, a dual BET/HDAC inhibitor. 13A is more effective against pancreatic cancer than either BET inhibitors or HDAC inhibitors alone or when they are combined [207]. Finally, XP-524 is a dual-BET/EP300 inhibitor that prevents KRAS-induced tumor transformation. XP-524 can bind to anti-PD-1 antibodies, which reactivates the cytotoxic immune response [208]. The role of EMT in pancreatic cancer and the molecular mechanisms by which histone modifications regulate EMT-related molecules have been the subject of intense research over the past few years. The EMT process governs both physiological and pathological development, and abnormally active EMT phenotypes have been associated with pancreatic cancer initiation, progression, and therapeutic resistance. There is a now a large body of evidence demonstrating that many histone changes can reversibly control the expression of EMT markers during EMT and MET. Inhibitors of histone modification enzymes have been shown to raise the sensitivity of pancreatic cancer cells to chemotherapy and immunotherapy, thereby providing potential therapeutics. Combining histone modification enzyme inhibitors with established anti-tumor drugs is a promising treatment method. Thus, the elucidation of the molecular mechanisms by which histone-modifying enzymes regulate EMT in pancreatic cancers will enhance our understanding of the underlying tumorigenesis and metastatic progression, thereby facilitating the development of alternative treatments that may have important implications for disease outcomes.

PMC10003020

Matteo Ferro,Gennaro Musi,Michele Marchioni,Martina Maggi,Alessandro Veccia,Francesco Del Giudice,Biagio Barone,Felice Crocetto,Francesco Lasorsa,Alessandro Antonelli,Luigi Schips,Riccardo Autorino,Gian Maria Busetto,Daniela Terracciano,Giuseppe Lucarelli,Octavian Sabin Tataru

Radiogenomics in Renal Cancer Management—Current Evidence and Future Prospects

27-02-2023

renal cancer,radiomics,radiogenomics,genomics,artificial intelligence,machine learning

Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.

Radiogenomics in Renal Cancer Management—Current Evidence and Future Prospects Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice. Renal cell carcinoma (RCC) is one of the most common solid tumors in both male and female patients [1]. Early diagnosis, correct treatment choice based on individual risk stratification, accurate prediction of treatment response, and survival are the cornerstones of RCC treatment. A correct diagnosis, especially for small renal masses, is fundamental for treatment planning. Several studies have pointed out the risk of over-diagnosis and over-treatment in patients with small renal masses [2]. A correct pre-operative diagnosis might reduce the number of useless treatments and their possible harms. With this aim in mind, renal biopsies have been used. Unfortunately, recent series showed an 80% biopsy core diagnostic rate without differences in the re-biopsy outcomes in terms of the quality of the obtained cores for diagnosis. The non-diagnostic rates at re-biopsy remained in the 20% range [3], with such results limiting the diffusion of renal biopsy in clinical practice. In the last few years, several tumors and hosts’ characteristics have been investigated to better stratify patients according to individual risk characteristics [4]. Based on these characteristics, several tools have been deployed with the aim of achieving an accurate treatment response prediction, including various biomarkers [5] and scoring systems [6]. However, to date, all these tools have shown only fair accuracy [6,7]. A helping hand might arrive from the use of new technologies that combine and analyze a huge amount of information, allowing an important improvement in all these aspects related to RCC management. Radiogenomics integrates a massive volume of quantitative data derived from imaging with individual genetic characteristics [8]. The use of deep learning (DL) allows the building of prediction models to better stratify patients, guide therapy methods, and evaluate clinical results [8]. The aim of the current review of the literature is to provide physicians with a complete and comprehensive review of the most recent studies on radiomics and radiogenomics use in the field of RCC, to emphasize the current knowledge of radiomics, genomics and molecular tumor characterization and its derived molecular imaging, and to identify the future course of radiogenomics-related research. We have identified studies from the PubMed/Medline database, and the workflow of radiogenomics in renal cancer is depicted in Figure 1. The aim was to access original research on the subjects of radiomics, genomics, molecular imaging, and radiogenomics related to renal cancer. Keywords used to search the database were renal cancer, radiomics, radiogenomics, genomics, artificial intelligence, and machine learning (ML). We have included articles up to December 2022 with no time frame limit and, we have excluded non-English, reviews, and case report studies. Radiomics, which focuses on improving the analysis of large data sets using semi-automatic or automatic software, is a quantitative image analysis of textures and features provided by imaging tools (e.g., multiparametric magnetic resonance imaging (mpMRI)) [9,10]. Numerous malignancies were examined using this model [11,12,13,14,15]. Human readers conduct qualitative analysis on radiological pictures. Instead, radiomics seeks to quantitatively map out pictures. Focused on various imaging techniques that are utilized as a starting point, this method is based on the extraction, analysis, and modeling of multiple image elements in connection to specified goals that may be both anatomical and functional [16]. The phases that make up a radiomics investigation include data selection, medical imaging, feature extraction, exploratory analysis, and modeling. The sixteen separate components that make up the radiomics quality score examine every facet of the radiomics process through the five stages mentioned above. The radiomics quality score specifically took into account trial registration, image availability, cut-off and accuracy analyses (calibration and accuracy statistics), multiple segmentations, the phantom study, imaging time points, adjustment for multiple testing, the use of multivariable analyses, the detection and discussion of biological correlates, as well as cost-effectiveness analysis and comparison with the current gold standard [16]. All the processes on which radiomics is based on are called the radiomics pipeline. Radiomics has been developed to assist physicians in improving the diagnosis and management of several oncological diseases. Quantitative evaluation of data from imaging has demonstrated improvements in the diagnostic, prognostic, and predictive roles of conventional radiological images [17,18,19,20]. Current applications of radiomics in RCC management include differentiation of benign from cancerous kidney tumors, differentiation of angiomyolipoma (AML) from RCC, differentiation of oncocytoma (ONC) from RCC, differentiation of different subtypes of RCC, nuclear grade prediction, and evaluation of treatment response of renal masses [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77]. Table S1 summarizes radiomics studies on RCC management according to these specific purposes. Radiomics allows a better characterization of renal lesions in the pre-operative setting and could potentially lead to the avoidance of many unnecessary surgeries for benign lesions. ML and DL algorithms have been extensively used in research studies to extract and analyze numerous quantitative features (i.e., histograms, textures, and shapes) from different image modalities. Histogram-based features of skewness and kurtosis from computed tomography (CT) images have been used for the discrimination of benign lesions from cancerous lesions [22]. CT and ML texture analysis based on random forest (RF) algorithm radiomics was used to discriminate RCC from other benign renal lesions [24]. In a larger cohort of renal lesions, CT features were selected and used to build a radiomics ML classification model of RCC versus other renal masses [26]. The best ML algorithm, based on images obtained from 18 different CT scanners, was the RF, which performed better than radiologists’ assessments, highlighting the role of radiomics in limiting the inter-observer and inter-machine variability of standard methods [25]. Similar results have been obtained by an ensemble DL model [30]. Using magnetic resonance imaging (MRI) to gather quantitative and qualitative data and analyze it through artificial intelligence (AI) algorithms had confusing results in different studies [29,30,31,32]. The application of radiomics for a better differentiation of clear cell (cc)RCC from other tumor types would allow for a tailored management of RCC. For this specific aim, both CT and MRI features were analyzed in multiple studies. CT images and features, in combination with ML algorithms, were used for differentiating non-ccRCC from ccRCC. The best performance was achieved by an artificial neural network (ANN) classifier [54] and DL neural networks based on CT images along with a ML algorithm, which showed promising results [55] to discriminate ccRCC from papillary (pap)RCC [57]. The possibility to preoperatively assess the tumor nuclear grade by imaging has been evaluated using numerous studies by both CT- and MRI-based radiomics approaches, which have shown the ability to accurately predict the presence of high- versus low-grade RCC, often by the use of texture analysis [61,62,63,64,65,66,67,68,69,70]. Diffusion-weighted imaging (DWI)-MRI was evaluated as a possible biomarker for overall survival (OS) in patients treated with sunitinib [72], but OS had no correlation with MRI features. Similarly, integrated positron emission tomography/MRI (PET/MRI) radiomics analysis was used to evaluate the response to sunitinib [71]. Moreover, texture parameters on CT images were assessed as predictive radiomics markers of response to therapy in metastatic (m)RCC patients [73,74,75,76,77], with texture uniformity discovered to be an independent predictor of time to progression (p = 0.005) [74], entropy modifications being a good predictor for OS (p = 0.02 and p = 0.04) and normalized standard deviation (nSD) that can predict progression free survival (PFS) (p = 0.01 and p = 0.003). The current results cannot definitively lead to the conclusion that radiomics could improve the prediction of treatment response rates. Renal cell carcinoma occurs either in sporadic or inherited forms. RCC subtypes are classified according to histopathological features and molecular drivers. Generally, hereditary RCC syndrome is transmitted in an autosomal dominant manner. In cases of de novo germline mutation or incomplete penetrance, a family history of RCC will be lacking. An increased risk of RCC is associated with germline variants of at least 12 genes. Genetic counseling should be offered to patients with multi-centric/bilateral tumors, an early age of diagnosis (<45 years of age), or a first/second degree relative with any kidney cancer. Understanding the genomic features of RCC may lead to a better screening and management of at-risk individuals and improve patients’ prognosis [78,79,80,81,82]. The first step in ccRCC development is the loss of the short arm of chromosome 3 (3p loss), frequently because of chromothripsis: multiple breaks will occur in chromosome 3p, followed by a random joining of segments [83]. Four tumor suppressor genes map in this region: VHL in 3p.25, PBRM1 (subunit of the PBAF SWI/SNF chromatin remodeling complex), BAP1 (histone deubiquitinase), and SETD2 (histone methyl transferase) in 3p.21. The latter genes are involved in the maintenance of chromatin status [84,85]. This event will lead to several genomic rearrangements (first hit in tumorigenesis). Later, a “second hit” will provoke the biallelic inactivation of these tumor suppressor genes. Clear cell RCCs are characterized by marked intratumor heterogeneity (ITH), which is referred to as the selection of tumor cell subpopulations with different driver mutations [86]. Remarkably, somatic mutations of VHL are observed in approximately 92% of patients diagnosed with ccRCC, whereas they are not found in non-clear cell RCC. Less frequently, alterations in TP53, mTOR, TSC1, TSC2, PIK3CA, KDM5C, and SMARCA4 are observed in ccRCC [87]. Von Hippel Lindau (VHL) disease is a systemic disorder transmitted in an autosomal dominant manner [88,89]. Incidence is estimated 1:34,000 and will likely complete penetrance by age 60. The mean age of onset of ccRCC is 44 years (two decades earlier than sporadic tumors). The risk of metastases is virtually nil when tumors are below 3 cm in size. Besides ccRCC, affected patients develop hundreds of renal cysts, benign pancreatic cysts, central nervous system and retinal hemangioblastomas, and neuroendocrine tumors (NET) such as pheochromocytoma. According to the predisposition to pheochromocytoma, VHL subclasses have been classified. The VHL gene encodes for pVHL, which is part of the E3 ubiquitin ligase complex (VCB complex) with cullin 2 (CUL2), Elongin B and C [90]. Broad spectrums of germline mutations in VHL gene have been described. The VCB complex targets the hypoxia-inducible factors (HIF-1α and HIF-2α). Under normal oxygen conditions, HIF-α becomes hydroxylated on specific sites by HIF-prolyl hydroxylases (PHDs). Molecular oxygen, 2-oxoglutarate (2-OG), and iron are demanded as cofactors. Then, pVHL binds hydroxylated HIF-α through its β-domain, thus targeting its ubiquitination and its proteasomal degradation. Conversely, in the case of hypoxia, the accumulation of HIF-α will lead to the activation of the hypoxia-induced response element (HRE) genes. The loss of VHL leads to the constitutive activation of HRE in the absence of hypoxia (“pseudohypoxia” is typical of both sporadic and hereditary ccRCC). HRE genes enhance altered anaerobic metabolism (GLUT1, PDK1, and EPO), angiogenesis, proliferation, and cell survival (VEGF, PDGF, TGF-α, and cyclin activation). Typically, mutations occur in the pVHL α binding domain to Elongin C [91,92]. Papillary renal cell carcinomas (papRCC) have been classically divided into two different subtypes according to their histology and genetics. Sporadic and hereditary forms exist. Type 1 papRCC is characterized by the gain of chromosomes 7 and 17 and the loss of chromosomes 2, 3, 12, 16, and 20. Activating mutations of the MET gene on chromosome 7 are usually observed [93,94,95]. In turn, type 2 papRCCs do not present a specific pattern of copy number alterations. According to The Cancer Genome Atlas Research Network, type 2 papRCC may show CDKN2A silencing, SEDT2 mutations, TFE3/TFEB gene fusion, and increased expression of the NRF2-antioxidant response element pathway. Currently, a heterogeneous group of RCCs with papillary features and more aggressive behavior have been described, including translocation RCCs, FH-deficient and SDH-deficient RCCs. New potential RCC entities include papillary renal neoplasm with reversed polarity (PRNRP) and biphasic hyalinizing psammomatous RCC (BHP RCC), which have distinct driver mutations (KRAS and NF2, respectively) [96,97,98,99]. HpapRCC is an autosomal dominant disorder with missense mutations of the MET protoncogene on chromosome 7q. MET encodes the hepatocyte growth factor (HGF) receptor. As a result of these mutations, constitutive activation of HGF’s downstream pathway occurs. Affected individuals are at risk of developing multifocal, bilateral type 1 papRCC. Complete penetrance is approximately described by the age of 80, even if the age of onset is associated with a specific missense mutation. No extrarenal manifestations are observed [100,101,102,103]. A distinct pattern of chromosomal alteration characterizes chRCC. Chromosomes 1, 2, 6, 10, 13, and 17 are lost in approximately 80% of cases of chRCC. Less frequently observed loss involves chromosomes 3, 5, 8, 9, 11, 18, and 21q. The next most common mutations affect TP53, PTEN, CDKN2A (loss of 9p21 or hypermethylation), and TERT. Moreover, increased mitochondrial deoxyribonucleic acid (DNA) copy numbers and increased expression of the mitochondrial regulator PPARGC1A suggest increased biogenesis in chRCC [104,105,106,107]. Birt-Hogg-Dubé (BHD) syndrome is an autosomal dominant cancer predisposition due to germline mutations in the FLCN gene (17p11) encoding folliculin [108,109,110]. Apart from bilateral and multifocal kidney tumors, affected patients develop benign cutaneous fibrofolliculomas and pulmonary cysts (risk factor for spontaneous pneumothorax). No associations between genotype and phenotype exist. Renal tumors display different histological features: hybrid oncocytic tumors (50%), chRCCs (34%), and oncocytomas (9%) are common. Folliculin (FLCN) may be involved in the PI3K/AKT/mTOR pathway through FLCN-interacting proteins FNIP1 and FNIP2 [111,112,113]. Renal medullary carcinoma (RMC) accounts for less than 1% of kidney cancers. Early metastases are responsible for poor OS. It afflicts predominantly patients with sickle cells trait. Common genetic mutations are the loss of expression of the SMARCB1 protein (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B member 1), BRG1-associated factor 47 (BAF47), or sucrose non-fermenting 5 (SNF5). SMARCB1 is part of the SWI/SNF chromatin remodeling complex: its loss deregulates many transcriptional pathways [114]. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome is inherited in an autosomal dominant manner. Mutations may occur throughout the entire fumarate hydratase (FH) gene on chromosome 1q43. Missense, frame shift, nonsense, splice-site mutations, or complete gene deletions have been described. No genotype-phenotype linkage is observed. Patients are at risk to develop benign skin and uterine leiomyomas and an aggressive form of RCC (formally a type 2 papillary RCC). RCC lesions are typically solitary with rapid tumor growth and early metastatic seeding [115,116,117,118,119,120]. Germline mutations of succinate dehydrogenase (SDH) subunits are associated with hereditary adrenal or extra-adrenal pheochromocytoma (PCT) and head and neck paraganglioma (PGL) syndrome, gastrointestinal stromal tumors (GIST), and RCCs with different histological features. Clinical manifestations depend on the mutated SDH subunit; missense, frame shift, and nonsense mutations are included. Solitary and unilateral RCC are usually diagnosed [121,122,123]. SDH and FH (enzyme of Krebs cycle) loss leads to the accumulation of succinate and fumarate [124]. These oncometabolites competitively inhibit the HIF-PHD interaction, which requires 2-oxoglutarate. This pseudohypoxic phenotype results in HIFα- stabilization and upregulation of HIF-inducible genes [125,126,127,128]. In addition, they block a group of α-KG dependent dioxygenases leading to epigenetic dysregulation. KDM4A and KDM4B dioxygenases blockade causes the suppression of the homologous recombination DNA-repair pathway. Furthermore, the aberrant succination of KEAP1 leads to the upregulation of the NRF2-mediated antioxidant signaling pathway. Moreover, a significant decrease in mtDNA content and an increase in mtDNA mutations have been described due to the accumulation of these oncometabolites [129,130,131,132,133]. Translocation renal cell carcinomas (T-RCCs) are driven by somatic translocation involving a member of microphtalmia (MiT) transcription factor family genes on chromosome X (i.e., TFE3, TFEB or MITF) with other partner genes [134]. This gene fusion alters many biological processes such as organelle biogenesis and cell proliferation [135,136,137,138]. They account for the most common forms of RCC in children and young adults. T-RCCs typically present with papillary architecture, even if papillary or clear cell subtypes of T-RCCs have been described in adult patients. The recent re-evaluation of cancer as a metabolic disorder has led to the discovery of specific oncometabolites with an important role in different processes of tumor biology such as proliferation, progression, and metastatisation [139,140,141,142,143]. In this scenario, recent studies showed that an altered metabolism has a fundamental role in the development of RCC [144,145]. In fact, it has been shown that many genes that are mutated or aberrantly expressed in this tumor also control different cell metabolic activities [144,145]. In particular, in ccRCC, we observe a metabolic reprogramming characterized by an anaerobic switch that induces the rerouting of sugar metabolism toward the pentose phosphate pathway (with the aim of promoting both nucleotide biosynthesis and redox homeostasis) and impairs the mitochondrial activity through the overexpression of NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4-like 2 (NDUFA4L2) [146,147,148]. NDUFA4L2 is one of the most expressed genes in ccRCC and encodes a protein that reduces mitochondrial oxygen consumption through inhibiting the electron transport chain Complex I. This protein is also involved in additional processes such as cell proliferation, cancer cell migration, and angiogenesis [148]. RCC is also characterized by significant accumulations of polyunsaturated fatty acids in association with increased expression of stearoyl-CoA desaturase (SCD1) and FA elongase 2 and 5 [149], as well as metabolic heterogeneity that may allow for subtyping of cancers and prediction of clinical outcomes [150]. Molecular imaging (MI) is the branch of radiology that enables the in vivo visualization and quantification of both physiological and disease-specific biological events at the cellular and molecular levels in living organisms. It employs MI probes or contrast agents that specifically interact with molecules to target tissues of interest. In the field of oncology, by allowing the visualization of metabolic processes and specific targets of tumor, differently from conventional imaging methods which only provide structural information, MI has been recently used as non-invasive tool of precision medicine for an optimized cancer management [151]. Specifically, for RCC, by targeting imaging using biomarkers involved in processes related to a specific RCC subtype, such as overexpressed proteins or dysregulated biological pathways, MI could not only allow for RCC detection (i.e., distinguishing benign from malignant renal lesions) but also for tumor subtyping; moreover, it could be valuable for staging, prognosis prediction, and treatment response assessment. To date, several radiotracers have been used for these aims, and the main MI modalities for RCC management are summarized in Table S2. 99mTc-sestamibi is a lipophilic cationic mitochondrial radiotracer that specifically accumulates in cells with high mitochondrial content and low multidrug resistance pump (MDR) expression. Since ONC is characterized by an elevated mitochondrial content with low MDR expression, while ccRCC by a decreased mitochondrial content with high MDR expression, SPECT/CT with 99mTc-sestamibi has been explored for distinguishing between ONC and ccRCC [152,153,154,155,156,157,158]. In the study by Gorin et al., SPECT/CT with 99mTc-sestamibi showed a sensitivity of 87.5% and specificity of 95.2% for the detection of ONC and hybrid oncocytic/chromophobe tumors (HOCT) [155]. Moreover, SPECT/CT with 99mTc-sestamibi was found to properly identify 91.6% and 100% of ONC and HOCT, respectively [157]. These promising results, together with the fact that it is cost-effective [159] and already approved for other diseases (e.g., myocardial and parathyroid), make this MI modality of particular promise for the management of renal lesions, with a potential translation into clinical practice in the near future. Girentuximab is a humanized monoclonal antibody (mAb) that selectively binds to carbonic anhydrase IX (CAIX), a transmembrane protein of the carbonic anhydrase family that, in physiological conditions, catalyzes the hydration of carbon dioxide in response to hypoxia. CAIX is overexpressed in almost all ccRCCs (>95%), due to inactivating mutations of the VHL gene [160]. Since CAIX can be labeled with numerous radionuclides, radiolabeled girentuximab has been evaluated for ccRCC management. In a pilot study by Divgi et al., 124I-girentuximab PET/CT correctly diagnosed 93.5% of ccRCC [161]. Subsequently, the same group evaluated its performance in comparison with standard CT imaging for ccRCC diagnosis, and, according to their results, 124I-girentuximab PET/CT performed better than conventional imaging (86.2% sensitivity and 85.9% specificity versus 75.5% sensitivity and 46.8% specificity, respectively) for the detection of ccRCC [162]. Since I-labeled tracers tend to accumulate in thyroid tissue, other radiotracers have been explored [163]. Several studies have suggested that labeling girentuximab with 89Zr can lead to higher tumor uptake and retention and perhaps be more sensitive in the detection of ccRCC than 124I. A multicenter prospective trial is ongoing to evaluate the use of 89Zr-girentuximab PET/CT for this purpose (ClinicalTrials.gov Identifier: NCT03849118). Moreover, 89Zr-girentuximab PET/CT performed better than both conventional CT and 18F-FDG PET/TC for ccRCC metastases detection (detection rates of 70%, 56%, and 59%, respectively) [164]. MI targeting CAIX has also been used to assess adjuvant treatment responses. In the study by Muselaers et al., a significant reduction in tumor uptake of 111In-girentuximab (38.4% reduction rate) was seen in patients treated with sorafenib [165]. 111In-girentuximab was also evaluated with SPECT/TC for the diagnosis of ccRCC, showing a PPV of 94% [166]. However, despite this encouraging result, SPECT is less advantageous than PET as MI modality [167]. Of note, although results with mAb are promising, several barriers to a widespread clinical application of mAb as probes for MI exist, such as logistical issues related to the long timeframe between their injection and image acquisition; for instance, this interval is 3–7 days for girentuximab, while it is only 75 min with 99mTc-sestamibi. Thus, although 124I- and 89Zr-girentuximab have proven value in distinguishing benign from malignant renal lesions, as well as in detecting and monitoring primary and metastatic sites of ccRCC, future studies should focus on new MI agents (e.g., low-molecular-weight agents) targeting CAIX to overcome current limitations. 2-deoxy-2-[18F] fluoro-D-glucose (18F-FDG) is a small molecule radiotracer that targets tumor cells with increased aerobic glycolysis. It is the most used PET radiotracer in oncology and has been largely evaluated for RCC management at different steps, yet it has limited utility in the initial diagnostic workup of renal lesions [168]. Indeed, it is excreted through the kidneys—making the distinction of tumors from the normal renal parenchyma difficult—, and some RCC exhibit a low 18F-FDG uptake due to tumor heterogeneity; furthermore, 18F-FDG is non-specifically taken up by any malignant cells with cytosolic aerobic glycolysis—thus it is not suitable for proper RCC subtyping [169,170]. The pooled sensitivity for renal mass diagnosis with 18F-FDG PET was 62% [171], and the performance did not improve with PET/CT [169,171,172]. 18F-FDG PET/CT has also been evaluated for the diagnosis of recurrent RCC. In the study by Alongi et al., 18F-FDG PET/CT showed a sensitivity and specificity of 74% and 80%, respectively (sensitivity and specificity were 88.8% and 70.2%, respectively, with conventional CT) [173]. The pooled sensitivity and specificity for recurrence detection with 18F-FDG PET/CT were 92.3% and 97%, comparable to conventional imaging [174]. For distant metastases detection, 18F-FDG PET/CT showed a sensitivity and specificity of 92.5% and 99.6%, respectively (compared to 93.3% and 94% with conventional imaging), performing better than CT with regards to lymph node, bone, and soft tissue metastases, whereas CT was superior for lung evaluation [175]. A high 18F-FDG PET uptake has also been associated with RCC aggressiveness and worse prognosis (e.g., nuclear grade and sarcomatoid features) [176,177,178]. Finally, 18F-FDG PET/CT might play a role in the prediction of treatment response in metastatic RCC patients treated with either TKI or ICI, since metabolic changes related to therapies occur well before structural changes [179,180,181]. In the study by Tabei et al., elevated SUVmax after ICI was an independent predictor of the response to treatment [181]. Of note, 18F-FDG PET/CT does not require contrast agents—which is particularly useful for monitoring patients with renal dysfunction—and has a lower radiation dose than CT. Prostate-specific membrane antigen (PSMA) is a cell surface protein with folate hydrolase activity, which is overexpressed on most prostate adenocarcinomas, yet also in tumor-associated neovascular endothelial cells of numerous solid tumors [182]. With specific regards to RCC, a positive PSMA staining was found in 76.2% of ccRCC neovasculature, and 31.2% of chRCC, whereas papRCC was PSMA negative. Although a few PSMA ligands have been studied for RCC, 68Ga-PSMA-11 is the most widely studied PSMA-targeted PET tracer. Due to its high accumulation in the kidney, it has a limited role in the characterization of renal lesions. However, after a case report demonstrated 68Ga-PSMA-11 PET/CT could detect RCC metastases, several studies have demonstrated its superiority in the detection of RCC metastases (sensitivity of 92.1% and PPV of 97.2%) when compared to CT (sensitivity of 68.6% and PPV of 80%) [183]. This MI modality was also explored for RCC aggressiveness assessment. SUVmax was associated with high nuclear grade and adverse pathology (e.g., tumor necrosis and sarcomatoid features) [184]. To date, MI using PSMA still requires further research and comparative clinical trials; furthermore, the development of new compounds, such as tracers with hepatobiliary clearance or with improved renal clearance, may optimize the performance of the RCC workup. Acetate is an important substrate for energy metabolism in the tumor since it is involved in numerous metabolic processes, including lipid synthesis, which is significantly upregulated in RCC. However, RCCs show a high heterogeneity for acetate uptake, and the data are still conflicting in the literature. For instance, in the study by Oyama et al., 11C-acetate PET was found to differentiate between malignant lesions—which absorbed more acetate—and benign masses [185], whereas in the study by Kotzerke et al., RCC did not concentrate acetate [186]. Interestingly, in the study by Ho et al., RCC patients underwent 11C-acetate and 18F-FDG dual-tracer PET/CT, and a higher acetate uptake was seen in benign renal masses than in malignant [187]. With regards to specific patterns of uptake by different RCC subtypes, chRCC was found to take up only acetate, papRCC only FDG, while ccRCC FDG and acetate for high- and low-grade tumors, respectively. Dual-tracer PET/CT may help with RCC subtyping. The need for two PET studies due to the short half-life of 11C and the limited evidence that we have in the literature make this MI modality far from application into clinical practice. Thus, the future application of such technologies will widely depend on the current paradigm of screening and diagnosis [188], which still will play a key role in the decision making for surgical scenarios [189] and in the prediction of perioperative outcomes in RCC management with the possible and promising integration of haemato-chemical biomarkers, which might improve molecular imaging accuracy as it has been previously demonstrated in the diagnosis and monitoring of other several genito-urinary (GU) diseases and malignancies [20,190,191,192,193,194]. The approach of combining radiomics features and gene expression in renal cancer has achieved new heights in the last few years. Almost all of the studies had pursued this approach in clear cell renal cell carcinoma. This is possible in some way due to the small number of mutated genes in ccRCC, which can translate into a direct association of radiomics features and genomics [195]. The proper management of ccRCC is closely related to its diagnosis, treatment, follow-up, and prognosis. Diagnosis using imaging techniques and its advancements in characterizing the obtained cross-sectional images is still struggling to better predict the ccRCC subtypes and their underlying molecular and gene characteristics and has its limitations [196,197]. The rise of AI and the related machine and deep learning models and algorithms, combined with an increase in computational power and adjusted statistical models that are able to process the high amount of data coming from radiology that are extracted by conventional imaging, were combined with genomic data and therefore gave birth to a new and exciting new area of research, radiogenomics [198,199]. Treatment is also posing challenges when it comes to establishing the prognosis and prediction of evolution, especially in the early stages of the disease, because of the genetic modifications that could potentially alter the personalized and individualized choice of treatment. It is well known that the intra-tumoral molecular heterogeneity of ccRCC can lead to an incomplete diagnosis, poor choice of treatment, and errors in predicting the post-therapy evolution of the disease [195,200,201,202]. By assessing the whole tumor molecular pattern, radiogenomics can improve the tumor characterization because it analyzes a broader tissue sample. The combined imaging phenotypes and genetic data (genotypes) can boost biomarkers discovery that can predict tumor response to a certain therapy or enrolling the patient in an active surveillance program [203]. The current published research that aimed to analyze if radiomics features are associated with mutational status, could predict mutated genes or the one that goes beyond molecular characterization, that of establishing clinical outcomes through radiogenomics, are summarized in Table S3. Radiogenomics is a novel field of research in many types of cancer. Researchers are just at the beginning of discovering the relation between radiomics features and genomics-related gene signatures to better characterize tumors. In RCC and mostly in ccRCC, the studies performed so far have aimed to identify the link between radiomics features, or phenotypes, and genomics features, or genotypes [195]. The research began with the aim of identifying if radiomics features are associated with mutational status in RCC. As early as 2014, Karlo et al. [204] in a retrospective analysis aimed to identify the relationship between phenotypes and gene mutation status and found that VHL, KDM5C and BAP1 SETD2, KDM5C and BAP1 mutations correlates with radiomics features and that the last three mentioned mutations were absent in multicystic lesions, and VHL and PBRM were associated with solid lesions [204]. Following studies also aimed to identify a relationship of radiomics features with genetic expression for BAP1 and PBRM1 [205,206,207,208,209], molecular subtypes [210], whole-transcriptome sequencing (WTS) [211], CT radiomics subtypes [212], gene modules associated with radiomics features [213], or microribonucleic acid (miRNA) expression [204,214,215,216,217]. Some clinical outcomes have been explored, such as OS [212,218,219,220,221,222,223,224], DSS [225] and metastasis prediction [211,213]. Although this research is mandatory in the early phases of a novel area, these studies achieved good and statistically significant results in the correlation between the above-mentioned parameters [204,205,214]. Up to this point, there are a number of advantages and drawbacks that limit the translation of radiogenomics into clinical practice. Advantages are coming from the increased use of AI statistical models (from ML and DL algorithms) [206,226], the new and ongoing discovery of genes that have clinical implications in ccRCC, the innovative research of radiomics in the characterization of extracted features from different scanner platforms (CT, multiphase CT, contrast-enhanced computed tomography (CECT), MRI, PET-CT, and PET-MRI), and the agreement between expert radiologists to create standard protocols and scanners to duplicate the results obtained in pilot studies [195]. Another advantage is that ccRCC has a high landscape of genetic mutations, which can be better assessed as a whole by CT [204], but these mutations are difficult to sample for whole-genome sequencing [204]. Limitations of radiogenomics are due to the existence of many retrospective studies, a limited number of patient data sets, and a few pilot prospective studies due to the imaging methods currently in use, which are performed with different scanners with no standardization of protocols for obtaining the images and little or no assessment of the sensitivity and specificity of radiomics features [203,204]. Multivariate models of mutational status have not been performed in some studies [214] due to the low number of enrolled patients with identified gene mutations. Studies are an incipient discovery phase with little or without external validation of their results, counting as little as just identifying the results of mutations or no mutations (ccRCC exhibiting a high degree of intra-tumoral heterogeneity with altered genomics [227]). Many of the images obtained from scanners are from daily practice and not from well-designed clinical trials, further limiting the reproducibility of results [215]. Associations between imaging features and the mutational status of ccRCC identified that poor edges of the tumor and calcifications are associated with the BAP1 mutation [214] and predict the RUNX3 methylation level [224], and well-defined tumor edges are associated with the VHL mutation [204], as well as the m1 mutation subtype and the less accurate m3 subtype, which is negatively associated with well-defined margins [215]. It is well known that renal vein and urine collector system invasion are predictors for infiltrative phenotypes and are negatively associated with the m3 subtype [215] and positively associated with KDM5C and BAP1 mutations [204]. An exophytic development of ccRCC has been associated with the MUC4 mutation [214] and the VHL mutation with a nodular appearance of ccRCC tumors [204]. CT texture parameters and the association with miRNA expression profiles have been studied by Marigliano et al. [216] and were found to have a weak association using the computer tomography texture analysis (CTTA) samples. Texture analysis is being studied as it has shown good results in predicting OS and response to therapy in different tumor types [228]. Entropy was found to be slightly positive and associated with miR-21-5p expression, and to date there is no explainable reason for this association, except probably the young age of patients and hyper-expression of miRNAs [216]. Vascularity of tumors has been assessed in studies, in order to correlate the tumor enhancement with gene expression, and it was found that brute enhancement of vascularity is associated with VHL mutation [204], high RUNX3 methylation [224], and good PFS in patients receiving tyrosine kinase inhibitors (TKI) and MRI high vascularity [229]. The prediction of gene mutation status has been assessed in numerous works since 2015 [205]. Authors highly used ML techniques to compare radiomics features and to predict mutation of different genes (BAP1, PRBM1, or molecular subtypes of ccRCC such as ccA and ccB) [205,206,207,208,209,210]. These studies can be seen as an initial and preliminary effort to discover the potential of radiogenomics and how we can manage renal cancer using this technique. All studies were of retrospective design with a limited number of patients and identified a vast range of AUCs (from 0.52 to 0.987) [205,206], but with relatively good sensitivity, specificity, and accuracy for prediction of gene mutation status. Having these in mind, we can discuss the potential of radiogenomics that can add more value in the management of renal cancer diagnosis and follow-up, but there is still a long way to go before implementation in clinical practice. Radiogenomics has elevated the interest of many disciplines in the medical sciences due to the possibility to correlate imaging with genomic data, aiming to reach the concept of tailored and personalized medicine [230,231]. Nevertheless, considering the mechanisms of gene expression and signaling pathways, the relationship between imaging features and genomic data could be biased, and no proper application in the clinical setting has been established [232]. Given the complex process represented by the radiomics flow, one of the main limitations of radiogenomics is that the large amount of data obtained by extracted radiomics features may cause over-fitting in the radiogenomics model when compared to diagnosed genetic mutations [233]. The discrepancies between the dimensionality of imaging and the whole-genome sequencing or molecular profile are quite evident; indeed, it has to be stated that only a handful of studies could be considered real radiogenomics studies in the sense that whole-genome data was used [8]. Another limitation and bias is instead related to the inter-observer variability, which is added to the issue of manual or semiautomatic image segmentation, as well as the reasonable lack of standardization of protocols and scanners among centers [199,234]. The automatic extraction of features is still underpowered compared to manual or semiautomatic segmentation of regions of interest (ROIs), albeit this could also be explained by the limited implementation of automatic imaging feature extraction in the studies [235]. Additionally, the heterogeneity of results and the high cost of genomic testing make the design of prospective studies quite difficult, and a potential temporary solution could be the use of public data resources such as The Cancer Genome Atlas (TGCA) [236]. Another relative limitation is the small sample size of patients involved, which is partly linked to the difficulty in obtaining appropriate imaging and adequate tissue samples for genomic analysis from the same cohort. This limitation also applies to the concept of validation cohorts, which could be underpowered [237]. As a result, the current challenges of radiogenomics are mainly focused on resolving the aforementioned issues, and a helpful aid could be represented by the increasing role of artificial intelligence and deep neural networks, which could allow the combination of genomic, transcriptomic, proteomic, and metabolomic data in a multidimensional manner in order to limit the reported bias [203,231]. The possibility of accessing the large public databases of imaging and genome data could further improve the standardization and management of radiogenomics. In particular, future research in this field should be aimed to increase the size of involved cohorts and provide prospectively built evidence. Future studies should aim to incorporate imaging phenotypes and molecular signatures, constructing clinical trials aimed at further assessing this relationship. In Table 1, we have introduced a summarization of the currently known advantages and limitations of the use of radiogenomics in the management of RCC. The role of radiogenomics in renal cancer and in its most common subtype, clear cell renal cancer, is appealing and promising. Considering that the evaluation of a renal lesion is routinely based on CT or MRI images, the possibility to characterize a potentially malignant lesion in terms of genetic, epigenetic, and pathologic heterogeneity via a non-invasive methodology is an undoubted advantage [232]. As reported in our review, the most common somatic gene mutations in renal cancer are related to VHL, PBRM1, BAP1, and SETD2, although a relatively small number of other mutated genes are reported to be involved in kidney cancer. In addition, considering the high intratumoral mutation heterogeneity that has been observed in this malignancy, it is probable that other genetic mutations could be found in a subset of renal malignancies [239]. In this scenario, the role of radiogenomics could be far more valuable than other standard methods of histopathology assessment (such as fine needle aspiration biopsy, for example) [240,241]. Naturally, the method of assessment of gene mutations in radiogenomics is based on different imaging characteristics that are associated with a gene rather than another [199]. VHL mutations, for example, are associated with defined tumor margins, nodular tumor enhancement, and intratumoral vascularization, while a greater vein invasion is significantly associated with BAP1 mutations [56,209]. The successive step is to assign a prognosis inferred from the expression of mutated genes in the analyzed tumors. Another great advantage related to the use of radiogenomic resides in the possibility to limit the inter-observer variability among radiologists, further adding another strong point for radiogenomics utilization in the clinical practice. The novelty of radiomics and radiogenomics could provide a more objective interpretation of extracted images. In particular, an important percentage of renal lesions, accounting for up to 30% of diagnosed lesions, are completely benign at histopathology [241]. It is consequential that the use of these models could greatly impact the management of these lesions. In addition, the possibility to obtain gene profiling from imaging could permit not only to identify aggressive lesions from other indolent lesions but also to tailor the treatment for every individual patient. Finally, the possibility to obtain genetic profiles for every scanned lesion could, in addition, improve the clinical research toward the role of genes and epigenetic changes involved in renal carcinogenesis [203]. Albeit the majority of studies have focused on developing models for the prediction of mutational profiles, the current panorama is gradually shifting towards the prediction of gene expression patterns as well as epigenetic changes within the tumor and tumor microenvironment. The use of these models may complement the management of localized renal tumors, in particular regarding the clarification of risk profiles of examined tumors. The clinical applicability of radiogenomics remains however limited by several factors such as the limited cohorts of patients involved or the use of the same publicly available cohort, as the TGCA, which could overfit the predictive models. Secondly, considering that radiomics and radiogenomics studies are heavily dependent on the quality of acquired images, the difference in technical factors such as CT scanners, acquisition modes, and voxel reconstruction algorithms could represent another limitation of these models. Finally, the extraction of radiomics features is still too heterogeneous in terms of automated/semi-automated software and ROI delineations [237,242]. Radiogenomics, before it can enter clinical practice, must be able to predict the clinical outcomes of patients with RCC, such as OS, DSS, PFS, and metastasis prediction [211,212,213,218,219,220,221,222,223,224,225,229]. Radiogenomics biomarkers and nomograms have been constructed for accurate survival and prognostic prediction of ccRCC, with good AUCs (0.91) for the association of hypoxia-related genes and radiomics features that predict survival and were also externally validated to increase the prognostic power by combining radiogenomics information with clinical and pathological factors [222,223]. The limitations of the current field research are due to the small number of patients and the retrospective nature of certain studies, with only a few that assess outcomes prospectively [220,229]. Most of the data has been obtained through the TCGA and TCIA portals, with little potential for model overfitting and limited external validation [222]. Radiogenomics research in kidney cancer represents a promising and constantly developing field. The possibility of associating imaging features with gene expression could heavily modify the clinical practice and the surgical approaches to renal lesions. Nevertheless, the road toward this objective is still under construction and further and larger studies are required in order to improve the applicability of radiogenomics and limit the current pitfalls related to small cohorts and heterogeneity of data acquired.

PMC10003023

Domenico Arcuri,Brandon Ramchatesingh,François Lagacé,Lisa Iannattone,Elena Netchiporouk,Philippe Lefrançois,Ivan V. Litvinov

Pharmacological Agents Used in the Prevention and Treatment of Actinic Keratosis: A Review

05-03-2023

actinic keratosis,squamous cell carcinoma,SCC,NMSC,pharmacotherapy,5-FU,acitretin,nicotinamide,calcipotriol,salicylic acid,imiquimod,diclofenac,photodynamic light therapy,PDT,daylight,dPDT,ALA,MAL

Actinic keratosis (AK) is among the most commonly diagnosed skin diseases with potentially life-threatening repercussions if left untreated. Usage of pharmacologic agents represents one of many therapeutic strategies that can be used to help manage these lesions. Ongoing research into these compounds continues to change our clinical understanding as to which agents most benefit particular patient populations. Indeed, factors such as past personal medical history, lesion location and tolerability of therapy only represent a few considerations that clinicians must account for when prescribing appropriate treatment. This review focuses on specific drugs used in either the prevention or treatment of AKs. Nicotinamide, acitretin and topical 5-fluorouracil (5-FU) continue to be used with fidelity in the chemoprevention of actinic keratosis, although some uncertainty persists in regard to which agents should be used in immunocompetent vs. immunodeficient/immunosuppressed patients. Topical 5-FU, including combination formulations with either calcipotriol or salicylic acid, as well as imiquimod, diclofenac and photodynamic light therapy are all accepted treatment strategies employed to target and eliminate AKs. Five percent of 5-FU is regarded as the most effective therapy in the condition, although the literature has conflictingly shown that lower concentrations of the drug might also be as effective. Topical diclofenac (3%) appears to be less efficacious than 5% 5-FU, 3.75–5% imiquimod and photodynamic light therapy despite its favorable side effect profile. Finally, traditional photodynamic light therapy, while painful, appears to be of higher efficacy in comparison to its more tolerable counterpart, daylight phototherapy.

Pharmacological Agents Used in the Prevention and Treatment of Actinic Keratosis: A Review Actinic keratosis (AK) is among the most commonly diagnosed skin diseases with potentially life-threatening repercussions if left untreated. Usage of pharmacologic agents represents one of many therapeutic strategies that can be used to help manage these lesions. Ongoing research into these compounds continues to change our clinical understanding as to which agents most benefit particular patient populations. Indeed, factors such as past personal medical history, lesion location and tolerability of therapy only represent a few considerations that clinicians must account for when prescribing appropriate treatment. This review focuses on specific drugs used in either the prevention or treatment of AKs. Nicotinamide, acitretin and topical 5-fluorouracil (5-FU) continue to be used with fidelity in the chemoprevention of actinic keratosis, although some uncertainty persists in regard to which agents should be used in immunocompetent vs. immunodeficient/immunosuppressed patients. Topical 5-FU, including combination formulations with either calcipotriol or salicylic acid, as well as imiquimod, diclofenac and photodynamic light therapy are all accepted treatment strategies employed to target and eliminate AKs. Five percent of 5-FU is regarded as the most effective therapy in the condition, although the literature has conflictingly shown that lower concentrations of the drug might also be as effective. Topical diclofenac (3%) appears to be less efficacious than 5% 5-FU, 3.75–5% imiquimod and photodynamic light therapy despite its favorable side effect profile. Finally, traditional photodynamic light therapy, while painful, appears to be of higher efficacy in comparison to its more tolerable counterpart, daylight phototherapy. Actinic keratosis (AK), synonymously referred to as solar keratosis, is among the most commonly diagnosed skin pathologies by dermatologists in the United States and Canada [1]. AK lesions are frequently found on sun-exposed areas of the body, such as the face, neck, dorsum of the hands, forearms and lower legs [2]. The risk of developing AK appears to be associated with cumulative ultraviolet (UV) exposure, as older individuals with lighter phototypes (Fitzpatrick I or II) tend to be the most vulnerable to developing the disease [3,4]. Indeed, studies analyzing AK prevalence among various age groups have revealed higher rates of the disease in countries whose populations have greater solar UV exposure (Australia vs. the United Kingdom), with older demographics (>60 years) demonstrating elevated prevalence compared to younger individuals (<40) [5]. Randomized control trials (RCTs) have demonstrated a decrease in both the incidence and the development of additional AK lesions if using sunscreen [6]. Indeed, while the most effective strategy in preventing AK is avoidance of UV radiation (UVR), photoprotection such as sun-protective clothing and sunscreen use, serve as important mitigation strategies. Furthermore, individuals receiving common photosensitizing medications such as hydrochlorothiazide have long been suspected of being at higher risk for developing the disease [7]. In line with the common association between excessive UV exposure and the development of skin cancer, it is widely accepted that AK serves as the precursor to cutaneous squamous cell carcinoma (SCC) [8] and, if left untreated, has the potential to transform into such. This association is strengthened via genetic analysis of AK and SCC lesions, with both demonstrating signature UVB-mediated mutations in p53, among other genes [9]. UVB rays particularly interact with the basal layer of the interfollicular epidermis, damaging its DNA and catalyzing the formation of SCC [10]. UVA rays, while more abundant in the environment and deeper-penetrating into the skin (dermis), are not as intimately associated with keratinocytic dysplasia, instead promoting damage via the formation of indiscriminate free (hydroxyl) radicals [5]. Importantly, lapses in immune function (e.g., iatrogenic immunosuppression in solid organ transplant recipients (SOTRs)), known to be an important contributor to oncogenesis, were shown to promote SCC formation from AK precursors [11,12]. Interestingly, apart from UVR-mediated damage to key oncogenes, chronic sun exposure has also been shown to promote a state of epidermal immunosuppression [13]. AK lesions present along a spectrum of different phenotypes; they are usually characterized by scaly, erythematous, and sometimes hyperkeratotic papules that may be pruritic. The severity of an AK lesion is graded histologically, and is predominantly organized according to three degrees of keratinocytic atypia—keratinocytic intraepidermal neoplasia (KIN) I, KIN II or KIN III. KIN III—with the most significant of the grades referring to an AK that can also be considered as an SCC in situ [14]. Nevertheless, while AK biopsies can be used to prognosticate suspicious lesions, resultant grades do not habitually guide treatment options [15]. In fact, there are no clinical “gold standards” in classifying AKs, and treatment is often recommended regardless of the lesion’s morphological or histological underpinnings [16]. Figure 1 depicts a pathogenesis overview for actinic keratosis. Treatment selection is primarily guided by the overt features of AK, the size of the surface area being treated, demonstrated efficacy, tolerability of the enlisted intervention and patient preference [16]. Pharmacologic therapy in particular focuses on clearance and/or prevention of AK lesions, an approach that is derived from the theory of “field cancerization”. Field cancerization is the concept that areas of the body with extensive UV damage are prone to produce both higher numbers of AK lesions as well as lesions with greater potential to transform into SCC [17]. Cancerized skin may present with poikiloderma (hypo and hyperpigmentation telangiectasia and atrophy), or contain other features of dermatoheliosis and is important to treat [18,19]. Skin-directed pharmacologic therapy can be described as field-directed or lesion-specific (“spot treatment”). Field-directed therapies are capable of targeting larger areas of damaged skin and can therefore be used to both prevent and treat AK lesions [17]. Lesion-specific therapies are somewhat more destructive and are usually reserved for eradication of established AK lesions. Whether employing field-directed or lesion-targeted therapies, it is important to note that not all areas of the body are as amenable to treatment intervention. For example, it has been observed that AK presenting on the upper limbs is more difficult to treat compared to regions such as the face and scalp [20,21]. While many physical modalities can be used to treat AKs (cryotherapy, cauterization, curettage, and excision), this review will focus on pharmacologic interventions, analyzing research findings made over the past decade pertaining to drug efficacy, optimal dosage and adverse drug reactions (ADRs) in order to help both clinicians and patients select the most appropriate therapy. Chemoprophylaxis against AK can be defined as the prevention of (additional) AK lesions in the setting of UV-damaged skin. Unsurprisingly, there are strong recommendations and evidence favoring sunscreen usage in the prevention of AK lesions, mainly through the hinderance of initial and repeated UV-mediated damage [16,22]. While we acknowledge the essential role that sunscreen plays in the chemoprophylaxis against AKs, this section will focus on other commonly used pharmacologic chemoprotective interventions, namely oral/systemic nicotinamide, acitretin and topical 5-fluorouracil (5-FU). Nicotinamide, also known as niacinamide, the water-soluble amide form of vitamin B3, is involved in the formation of NAD+, a key intermediate in the generation of ATP. Interestingly, UVB-irradiated keratinocytes have demonstrated a marked decrease in NAD+, which is purported to increase tumorigenic potential secondary to loss of adequate energy production required for DNA repair [23]. Supplementation of keratinocytes with NAD+ has also been shown to increase DNA repair following UV-irradiation compared to placebo treatment [23]. In accordance with these results, it was hypothesized that increasing endogenous NAD+ levels, possibly through supplementation with nicotinamide, could lessen the formation of AKs and SCCs. Fortunately, nicotinamide has indeed been shown capable of enhancing repair of UV-mediated DNA damage in keratinocytes, reducing UV-mediated inflammation and protecting against UV-induced immunosuppression, all of which serve to limit the formation a pro-tumorigenic environment and solidify the drug’s potential as a favorable chemoprophylactic agent [24,25]. Clinical work in 2010 noted that 1% topical nicotinamide applied twice daily vs. vehicle alone reduced AK formation after 3 to 6 months of treatment [26]. This appears to be among the only published studies analyzing the topical formulation, as subsequent work has instead favored oral administration. A phase II dose-optimizing trial in 2012 determined that twice daily supplementation with nicotinamide 500 mg proved more effective at reducing AK counts with minimal reported ADRs compared to daily dosing [27]. It was a landmark phase III trial published a few years later, however, that substantiated nicotinamide 500 mg twice daily use as an effective and tolerable prevention strategy against AK lesions if used continuously for one year [28]. The strength of evidence associated with a 2022 meta-analysis citing a dose-dependent increase in digestive side effects (diarrhea) with nicotinamide use was considered to be very low [29]. Notably, most of the studies have been conducted in an immunocompetent population, although a number of publications regarding nicotinamide chemoprophylaxis in immunocompromised individuals also exist. A 2017 case–control study by Drago et al. did demonstrate a significant decrease in AK size in SOTRs taking 500 mg nicotinamide daily compared to placebo [30]. These results contradict findings made in 2016 by Chen et al.’s double-blinded phase II RCT, which noted non-significant decreases in AKs or keratinocyte carcinomas (KC)s in SOTR taking nicotinamide 500 mg twice daily [31]. Drago et al. suggested that this discrepancy may be due to a lack of consideration for the types and dosages of immunosuppressive drugs taken during Chen et al.’s study, subsequently affecting the efficacy of nicotinamide. Another small but notable difference is that while Chen et al. focused primarily on renal transplant patients, Drago et al.’s work also included liver transplant recipients (n = 8). A 2022 meta-analysis partially agreed with the findings made by Drago et al., resulting in a weak recommendation for the use of nicotinamide 500 mg twice daily in either immunocompetent or SOTR patients with a prior history of skin cancer [29]. Fortunately, a clinical trial assessing solo nicotinamide efficacy in immunocompromised individuals is currently underway and should better clarify the role that nicotinamide has in AK chemoprophylaxis for this population [32]. It has also been speculated whether or not nicotinamide could replace acitretin, a second-generation retinoid, for AK prophylaxis in SOTRs due to the former’s more favorable ADR profile. A 2021 meta-analysis revealed no significant efficacy difference between acitretin and nicotinamide in SOTR AK chemoprophylaxis, but could not comment on the duration of treatment, type of transplantation or optimal dosages of chemopreventative drugs [33]. Given the current lack of concrete findings supporting nicotinamide use in SOTR/immunocompromised individuals, it would be plausible to suggest utilizing nicotinamide in place of acitretin should the latter’s side effect profile prove intolerable to the patient. Another potential niche use for nicotinamide over acitretin would be due to the former’s lack of significant drug-drug interactions relative to acitretin, thereby reducing the risk of iatrogenic harm in a demographic traditionally known for polypharmacy [34]. Of note, there is little to no evidence either favoring or discouraging the simultaneous use of nicotinamide and acitretin in treating complex cases, although from a pharmacokinetic standpoint there appears to be little to no risk of significant drug interaction between either agent. The most recent literature regarding acitretin chemoprophylaxis against AK has been focused on the SOTR population. Indeed, SOTR patients are at an increased risk of AKs and SCC due in part to a complex interplay between their chronically immunocompromised dispositions, exposure to potentially pro-carcinogenic medications and possible increases in susceptibility to UV radiation [35,36,37]. For decades, acitretin has been commonly used for the prevention of KCs in this demographic [38]. It works by binding all known subtypes of the retinoid X-receptors and retinoic acid receptors to normalize keratinocyte differentiation in the epidermis, as well as hindering the expression of pro-inflammatory cytokines such as IL-6, MRP-8 and IFN-γ [39]. Acitretin in doses measuring up to 30 mg per day has demonstrated beneficial effects on the number and thickness of AK lesions, as well as the number of new skin cancers [40]. A recent efficacy and cost analysis review of acitretin chemoprophylaxis in SCC and basal cell carcinoma (BCC) revealed a 54% and 73% reduction in both cancers, respectively, and suggested that acitretin may be underutilized due to its significant cost (in the United States), teratogenic risk and the need for regular blood test monitoring [41]. Nevertheless, acitretin has a notable mucocutaneous ADR profile which has been observed in individuals taking higher and subsequently more efficacious doses of the drug [40]. Patients on acitretin require monitoring for elevation in liver function tests and changes in triglyceride and lipid profiles. The drug should be avoided in females of childbearing age due to a significant risk of teratogenicity even up to 2–3 years after stopping the medication. This last point is important, as acitretin is metabolically converted to etretinate, a compound with a long-enough half-life to persist in the body for multiple years [42]. Studies have analyzed lower-dose acitretin regimens in an attempt to minimize ADRs while maintaining a similar efficacy. A 2022 retrospective case-crossover clinical trial tested 10 mg acitretin regimens in patients with one previous keratinocyte carcinoma and a history of SOTR and observed a 53% reduction in pretreatment KCs with no notable ADRs after at least two years of treatment [43]. Another retrospective cohort study published in 2022 analyzed long term (ranging from 6 months to 9 years) acitretin usage in SOTRs with a median/mode dose of 10 mg daily and found a 50% reduction in keratinocyte carcinomas during the first five years of treatment with only mild mucocutaneous ADRs [44]. In comparison to 30 mg doses, acitretin 10–20 mg daily does appear to maintain AK reduction capabilities in SOTR patients while reducing ADR incidence, although head-to-head trials are lacking. 5-Fluorouracil (5-FU) is a thymidylate synthase inhibitor used in pathologies necessitating apoptosis of rapidly dividing cells. 5-FU is also known to increase p53 expression [45]. The Veterans Affairs Keratinocyte Carcinoma Chemoprevention (VAKCC) trial published in 2015 demonstrated that a single course of 5-FU 5% cream applied twice daily for up to 4 weeks on the face and ears decreased the incidence of new AKs for over two years [46]. Additional studies using data from the VAKCC trial surmised a 75% risk reduction in SCC, as well as a reduction in the need for surgical interventions caused by an SCC 1 year after treatment [47]. Furthermore, topical 5-FU usage has also been shown to incur lower costs over 3 years (USD 771) in comparison to placebo, making it a tolerable and cost-effective treatment strategy [48]. Common side effects of topical 5-FU include pain, pruritis, erythema and crusting, with rarer adverse events including infection and ulceration [49,50]. A post hoc treatment analysis revealed that twice daily 5% 5-FU led to a significant increase in the rate of crusting, scaling, erythema, stinging, burning and severe pruritis compared to patients taking 4% 5-FU daily [51]. Reducing the dosing frequency of 5-FU (weekly vs. daily) effectively diminishes the incidence of ADRs but comes at the cost of treatment efficacy and is generally not supported in clinical practice [52]. Unfortunately, the dose-dependent nature of 5-FU ADR onset entails that effective treatment with the drug is invariably intertwined with unpleasant side effects. Nevertheless, 5-FU, alongside nicotinamide and acitretin, are viable and generally tolerable chemoprophylactic options for dermatologists seeking to impede AK development and progression. Table 1 provides a brief summary of the discussed randomized-controlled, case–control trials and cohort studies since 2010. Patients already presenting with numerous AKs or those at high risk for developing AKs and SCC may not only necessitate chemoprevention but actual treatment. Ingenol mebutate, a once very popular medication used to treat AK, has been discontinued in the United States, Canada and elsewhere around the world. As such, our review will only focus on specific and available pharmacotherapies. Resultantly, retinoids as a class of medications will also not be assessed despite their demonstrated efficacy in AK. Nevertheless, an in-depth review on retinoid utilization has recently been published by our team [53]. 5-FU has been used for many decades in the treatment of AKs. Identical to its chemoprophylactic regimen, 5-FU 5% cream is used twice daily over the course of 2–4-weeks as a field-treatment in order to eradicate AK lesions in immunocompetent patients [8,46]. 5% 5-FU has also been studied in immunocompromised individuals, with twice daily applications to the face of SOTR patients (three-week treatment duration) resulting in 79% AK clearance after 12 months of follow-up [54]. Provided 5-FU’s irritating nature, researchers have attempted to identify less caustic dosing regimens. Specifically, 0.5% 5-FU applied daily for 4–6 weeks has been shown to have the same efficacy as and better tolerability than the twice-daily 5% formulation in reducing the number of AK lesions from baseline [55]. Advocates for the 0.5% formulation have also suggested its use in elderly patients in order to diminish systemic 5-FU absorption while increasing compliance for those struggling to tolerate higher doses of the drug [56]. Even strengths as high as 4% 5-FU have been found to be as efficacious and better tolerated than 5% 5-FU cream when applied daily or twice daily for up to 4 weeks [57]. In spite of these findings, 5% 5-FU continues to be favored likely due to the abundance of empirical evidence available at this dosage, as well as its demonstrated efficacy in multi-treatment comparative and cost-effectiveness trials [58,59]. Of special importance to clinicians are the rare toxicities associated with topical 5-FU application in patients with dihydropyrimidine dehydrogenase (DPD) deficiency (DPDD). DPD is involved in the rate-limiting step in 5-FU metabolism; deficiencies in the enzyme subsequently lead to toxicity-inducing accumulation of the drug in the body. Severe lethargy, fever, mucositis, weight loss and neutropenia have been reported following application of 5-FU on patients with suspected DPDD [60,61]. It has been suggested that testing be performed for DPDD prior to systemic use of 5-FU to prevent toxicity, although this call has not been made for topical formulations of the drug [62]. Nevertheless, should a patient present with diagnosed DPDD, it would be best to resort to other non-DPD-associated AK treatments. It is also worth counselling patients using topical 5-FU to terminate treatment and return for clinical testing should, in a very rare event, they develop the aforementioned systemic symptoms. Nonetheless, dose optimization is only one approach at reducing 5% 5-FU-associated ADRs and many studies within the past decade have focused on modifying 5-FU delivery to minimize the ADR incidence. Transfersomes, a group of specialized drug-delivering liposomes, have been studied for topical 5-FU administration with noted improvements in skin penetration, drug retention and irritation potential [63]. Pre-treatment barrier breakdown via microneedling seemingly potentiates the effects of 5-FU, leading to higher clearance rates for both 5% and 0.5% 5-FU compared to drug administration alone [64]. Additionally, a 2020 RCT assessed whether concomitant use of either petrolatum, clobetasol propionate or a controlled-release skin barrier emulsion (CRSBE) decreased ADRs associated with 5-FU facial usage [65]. Petrolatum was shown to be the most effective intervention at reducing erythema and increasing hydration without affecting 5-FU efficacy. Treatment with a 70% glycolic acid and 5% 5-FU solution every 2 weeks has also been shown to be as effective and tolerable as twice daily application of 5% 5-FU cream alone [66]. New drug options and combination treatments are also actively being investigated. A presently ongoing phase I clinical trial is seeking to determine whether a novel plant-derived compound named GZ17-6.02, when used in conjunction with 5-FU, can better eliminate AK lesions [67]. Current in vitro results demonstrate higher eradication of AK cells compared to 5-FU, and researchers hope that concomitant administration of both compounds can be used as a future treatment option. There already exist a few well-established treatment strategies incorporating 5-FU. One widely used and significantly efficacious combination therapy is 5-FU with calcipotriol. In addition to the anti-cancer effects associated with 5-FU, calcipotriol is thought to induce a T-cell-mediated anti-tumorigenic response when applied topically [68]. 5-FU and calcipotriol has also been shown to increase HLA Class II and thymic stromal lymphopoietin (TSLP) expression in lesional keratinocytes, indicating immune-mediated rejection of the AK [68]. This effect is thought to be aided synergistically by 5-FU, as it has been shown that monotherapy with calcipotriol results in only a modest clearance after 12 weeks without evidence of a robust immune response [69]. A double-blinded, 2017 RCT sought to clarify the efficacy and safety of 0.005% calcipotriol and 5% 5-FU cream, applied twice daily for 4 days [68]. There was an 87% reduction in AK lesions on the face, ~76% reduction on the scalp, and ~69–79% reduction on the upper extremities by week 8. Additionally, 27% of patients experienced complete clearance of AK lesions on the face, with 82% of patients finding the combination to be more efficacious than previous treatments they had received. The study also mentions that one included immunosuppressed patient had lower actinic clearance after receiving 5-FU + calcipotriol, demonstrating the importance of an intact immune system in generating a response with this treatment combination. Burning and erythema were the most common ADRs noted, and a follow-up, blinded, prospective cohort study noted that erythema extent and intensity was much higher on the face and scalp than on either upper extremity 1 day following treatment, which they attributed to an intense CD4+ T-cell response [70]. Perilesional skin biopsies taken during this second study demonstrated a marked increase in epidermal CD4+ memory T-cells in 5-FU + calcipotriol-treated skin, indicating a form of immunologic memory that was found to help reduce the 3-year risk of SCC on the face and scalp. A 2021 retrospective chart review of data collected between 2016 and 2018 tested the combination of cryotherapy followed by no drug, 1% 5-FU, 1% 5-FU + 0.005% calcipotriol and calcipotriol alone [71]. Treatments were applied in 3-week cycles for 5 nights on the face and 7 days elsewhere, followed by a two-week rest period before recommencing treatment. Cryotherapy and 5-FU + calcipotriol demonstrated earlier and significant AK reduction compared to 5-FU or calcipotriol alone. These results also contribute to the hypothesis that 5-FU + calcipotriol act synergistically to induce hastened anti-tumorigenic effects. Curiously, patients reported less irritation using 5-FU + calcipotriol than 5-FU alone; the most commonly reported adverse events included transient redness, dryness and itching. Some practitioners have anecdotally chosen to administer cyclic 5-FU + calcipotriol until the skin is clear; however, no evidence supports this practice. 5-FU and salicylic acid (SA) is another efficacious combination treatment for AKs. SA is a keratolytic agent which causes physical destruction of keratotic lesions, including more difficult to treat hypertrophic AKs [72]. A pilot study published in 2010 using 0.5% 5-FU in combination with salicylic acid (SA) 10% observed complete clearance in 77% of assessed AK lesions with tolerable burning following four weeks of three times per week applications [73]. Indeed, many patients respond to treatment periods less than 6 weeks, although longer therapy durations may be required depending on lesion location (for example, forearms) or if the patient has a previous treatment history [74]. Field-directed treatment using 0.5% 5-FU + 10% SA for 12 weeks has significant complete- and partial-clearance of AK lesions with appreciable efficacy against notably hyperkeratotic lesions on the face and scalp [75]. A 2017 study also demonstrated efficacy for AK lesions located on the hands and forearms irrespective of cornification or hypertrophy severity [76]. Most recently, an observational study assessing the early response of 5-FU + SA in treating actinic keratosis through the use of the AKASI system, a newly proposed quantitative tool to assess AK severity on the head, noted 84% clearance of AK lesions after 12 weeks of follow-up [77,78]. It appears that 5-FU + SA is an effective treatment for AK lesions, and especially hyperkeratotic AKs. The notable erosions observed in these studies may either be directly due to SA-induced keratolysis or the increased ability of 5-FU to penetrate deeper into the skin following concomitant administration with SA. Regardless of the mechanism, the combination may be better suited as a spot treatment versus field-directed therapy due to this particular ADR. It would be of interest to assess how head-to-head trials including 5-FU + SA, 5FU + calcipotriol and 5FU alone would compare in treating hyperkeratotic lesions, lesions on the upper extremities, face and scalp. Imiquimod topical cream is an established treatment of AKs with original case reports dating back to 2001 [79]. Imiquimod stimulates cell-mediated attack against AK lesions via the production of IFN-α, TNF-α, IL-6 and IL-8 as well as through the recruitment of activated CD4+, CD8+ T cells and mast cells [79,80,81,82,83,84]. Our understanding is that imiquimod exerts this function through Toll-like Receptors 7 and 8 on antigen-presenting cells, while also simultaneously inducing cytochrome-mediated apoptosis [85,86,87,88,89]. Dosing of imiquimod has traditionally included an application of a 5% cream 3 times weekly for 12–16 weeks [82,83,90,91,92]. Shorter treatment durations (4 weeks) have demonstrated similar efficacy to 16-week trials [93,94]. Application of imiquimod more than 3 times per week is associated with a higher rate of systemic adverse events and decreased tolerability [95]. The 5% formulation is also effective for treating AK lesions in SOTR patients with no evidence of undesirable immunoactivation [96,97]. Recent studies have assessed the use of 3.75% imiquimod cream with satisfactory results; a 2014 trial demonstrated a reduction of approximately 18 AK lesions per patient 8 weeks after of imiquimod 3.75% use on the face and scalp [98]. A 2020 study analyzing two case reports found that using 3.75% imiquimod applied in a field-directed manner successfully treated early-stage AK lesions with only mild erythema, burning and fatigue [99]. Another small 2020 study using 3.75% imiquimod also found efficacious and safe outcomes in 13 immunosuppressed patients [100]. Nevertheless, the ability of either 5% or 3.75% imiquimod to trigger autoimmune-induced organ rejection in SOTRs needs to be carefully considered and more robust data on medication safety is needed before definitive recommendations can be made. Kidney transplant recipients, where dialysis is readily available should the rejection occur, appears to be the safest SOTR demographic. Adverse events for imiquimod 3.75% and 5% creams are typically comprised of local skin reactions such as erythema, pain, inflammation, erosion, scabbing and pigmentation which typically self-resolve following termination of treatment and are positive indicators of dermal immune activation. [82,83,90,91,92,93,95,101,102]. However, systemic, flu-like symptoms such as fatigue, myalgia, fever and headache have also been associated with imiquimod 5% use [95,103,104,105]. While cutaneous reactions appear to precede flu-like symptoms by 7–11 days, there is no evidence of systemic cytokine activation nor of an association between the severity of skin reactions and the onset of systemic symptoms [103,106]. Nevertheless, imiquimod has very little circulatory absorption and exerts its effects locally, which may explain why only few patients sporadically experience systemic ADRs [103]. Diclofenac is a non-steroidal anti-inflammatory drug capable of inhibiting both cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2), thereby preventing the formation of inflammatory mediators such as prostaglandins and thromboxanes. Traditionally, its mechanism of action in treating AK was thought to primarily involve reduction in angiogenesis and cell proliferation, as well as induction of apoptosis when administered in hyaluronic acid [107,108]. Recently, a 2019 study observed increased infiltration of dermal CD8+ T cells accompanied with high IFN-γ mRNA expression in diclofenac-treated AK lesions, suggesting an immune-mediated component in the drug’s mechanism of action [109]. Regardless, diclofenac’s suspected efficacy in treating AK lesions stems as far back as the late 1990s [110]. It has been studied at a dose of ~3% diclofenac in 2.5% hyaluronan (HA) gel applied twice daily for 30–90 days with favorable effect [111,112]. However, immunohistochemical and histopathologic assessments have revealed that a 12-week treatment period may not be sufficient to fully eliminate AK lesions [113]. Nevertheless, a multi-center, randomized, open label study compared a 3- vs. 6-month treatment course of diclofenac 3%/HA 2.5% while analyzing clinical and histopathologic clearance and determined no significant differences in treatment outcomes [114]. There is an otherwise dearth of studies seeking to optimize diclofenac dose or reduce the incidence of adverse events. Indeed, adverse events associated with diclofenac 3%/HA 2.5% are minimal and usually include well-tolerated erythema, pruritis and dryness [107]. A 2019 study combined diclofenac with a group of naturally occurring compounds suspected of having activity against AKs by using self-assembling nanoparticles to deliver the drug in vitro into pig ear skin [115]. While much work remains to be done, one combination coined “Hybrid 1” (a combination of diclofenac with the antiproliferative and antioxidant compound “HT” in a Nano3Hybrid20 formulation) proved promising to the researchers, who claimed that it could serve as a scaffold for the development of new AK and SCC treatments. Nevertheless, this compound remains to be tested in clinical studies. Tirbanibulin is a novel drug option in the treatment of AKs. It serves as a microtubule and Src kinase inhibitor, which elicits the drug’s antiproliferative effects, as well as a p53 inducer, thereby potentiating apoptosis in target cells [116]. Although it’s potential as an anti-tumorigenic agent has been discussed over a decade ago, its efficacy in AK treatment has only recently been established [117,118]. Phase I and II studies have utilized tirbanibulin 1% ointment over 25 or 100 cm2 once daily for 3–5 days during a 45 (Phase I) or 57 (Phase II) day evaluation period [116]. Complete clearance of AK lesions on the face and scalp were noted to be 43% (5-day course) and 37% (3-day course) at day 57. The sustained treatment response 12 months after day 57 measurements was observed to be 43% for the 5-day regimen versus 30% for the 3-day regimen. A phase III study divided 702 patients into two trials and observed complete clearance of AK lesions in 44% (Trial 1) and 54% (Trial 2) of patients at 57 days post-treatment [119]. However, the authors did note the recurrence of lesions in 47% of patients who initially presented with complete clearance one year following treatment termination and subsequently called for comparative trials between tirbanibulin and standard AK treatments (e.g., topical 5-FU) to better qualify the compound’s role in AK management. Encouragingly, the adverse event profile for tirbanibulin appears favorable, with transient erythema, flaking and scaling being most commonly reported [119]. Evidently, more studies are required to determine whether or not it can supersede 5-FU or imiquimod as a popular and reliable treatment option. Photodynamic light therapy (PDT) in conjugation with 5-aminolevulinic acid (ALA) for the treatment of AK was initially described in the mid 1990s with promising success [120]. Similar trials published a few years later using the photosensitizer methyl 5-aminolevulinate (MAL) also yielded satisfactory results [121]. Indeed, PDT has remained an important treatment strategy for AKs; it relies on the higher uptake of ALA and MAL, two prodrugs which are eventually metabolized into protoporphyrin IX (PPIX), by neoplastic cells [122,123,124,125]. Subsequent illumination at particular wavelengths promotes PPIX-induced, mitochondrialy-mediated destruction of abnormal tissue relative to healthy skin [126]. A 2004 phase III trial determined that ALA 20% solution applied and dried onto the skin 14–18 h before blue-light exposure, believed at the time to be more potent than red-light exposure, led to complete AK clearance in 73% of patients after 12 weeks [127]. This particular regimen was also effective as a spot treatment against AKs on upper extremities, initially offering clinicians another viable alternative against these treatment-resistant lesions [128]. Nevertheless, innovations in ALA-delivery have demonstrated the clinical utility of red-light PDT. BF-200 ALA, a nanoemulsion gel formulation containing the equivalent of 10% ALA-HCl with better penetration into the epidermis, has shown 91% complete clearance of AK lesions located on the face and scalp 12 weeks after redlight exposure [129,130]. Later studies have also found success with red-light BF-200 ALA-PDT in clearing AK lesions located on the hands and arms [131]. Occlusion with ALA-impregnated patches is another alternative yet effective drug delivery method recently shown capable of treating AK lesions on the hands and arms [132]. Interestingly, a 2019 chart review including 59 patients determined that 10% ALA generally has similar efficacy and adverse effect profiles as 20% ALA with lower associated cost of treatment, further antiquating 20% ALA-PDT as a go-to therapy [133]. Red-light exposure has also been tested with regimens involving 16% MAL-PDT, producing an apparent 89–91% clearance rate at three months follow-up [134,135]. Recent efforts have explored new compounds and adjuvant strategies in an attempt to augment PDT efficacy. Low-irradiance PDT combined with erbium:YAG laser pre-treatment prior to 16% MAL application has shown benefit in the SOTR population compared to MAL-PDT alone [136]. TAPP, a novel porphyrin derivative, shows potential for AK and adnexal neoplasm therapy, although much work remains to be done [137]. Oral vitamin D3 supplementation at 10,000 IU daily for 5 or 14 days prior to debridement and followed by ALA 20% blue-light PDT significantly improved clinical responses with acceptable tolerability for lesions on the scalp and face after 3 and 6 months [138]. A 2020 study assessing microneedling prior to ALA-PDT found marginal improvements in efficacy with no apparent increases in painfulness [139]. Indeed, dermarolling, microneedling and elongated particles have all demonstrated increased penetration and retention of MAL, although further studies on the clinical implications, such as efficacy, pain and compliance are needed [140]. Pain, erythema and post-treatment inflammation tend to be the most common and significant side effects associated with PDT, although case reports with rarer events including anaphylaxis and erosive pustular dermatosis have also been documented [141,142,143]. Of the mentioned side effects, pain in particular represents a notable adverse event which has limited the widespread use of PDT [144]. Interestingly, ALA is more commonly implicated with pain compared to treatments using MAL as a photosensitizer [145]. Strategies such as simultaneous application of 20% ALA with immediate blue-light irradiation have been shown to reduce pain compared to conventional application of ALA hours before exposure to a light source [146]. Simply shortening the drug-to-light period (for example, 1.5 hours vs. 3 hours) and allowing for 2 minute pauses during red-light illumination with ALA has also been shown to increase procedural tolerability [147]. Application with a topical anesthetic such as 7% lidocaine/7% tetracaine cream 1 h before MAL application is another useful strategy shown to significantly reduce PDT-associated pain [148]. A 2022 study found that substitution of the hydrochloride salt in ALA-HCl for phosphate (ALA-P) did not appear to improve treatment efficacy, but did lower perceived pain and favored absorption compared to either ALA-HCl or MAL-HCl [149]. Occlusion of BF-200 ALA on the scalp and face prior to illumination has been associated with increased pain, although efficacy notably improved as well [150]. Given the acceptable efficacy of PDT and already established association with patient reported pain, it is unlikely that occlusion of AK lesions on the scalp and face will be widely adopted into practice. Textile PDT using the FLUXIMEDICARE device, which advantages light-emitting knitted fabrics adaptable to the area of skin being treated, has been shown to be efficacious, tolerable and minimally painful [151,152]. Daylight PDT (dPDT) is considered to be less painful than the traditional PDT [153]. The protocol involves exposure to a natural light following application of a photosensitizer, allowing dermatologists to treat AKs without the necessary irradiation equipment. A 2019 Phase III trial using BF-200 ALA demonstrated tolerability and non-inferiority compared to MAL-dPDT in the clearance of AK lesions 12 weeks following the treatment, indicating both compounds are viable photosensitizers for daylight therapy [154]. Artificial white light alternatives have been explored due to the variability in weather conditions and, therefore, unpredictability associated with dPDT administration. Devices such as Dermaris, which deliver uniform illumination of white light, have been shown to be effective and nearly painless treatment options for patients with AK lesions on the scalp [155]. Follow-up studies using the Dermaris device noted equal efficacy when diminishing the illumination period from 2.5 h to 1 h, all the while maintaining a nearly painless treatment of AK lesions on the scalp [156]. Another artificial dPDT device, IndoorLux, also demonstrated notable efficacy and relative painlessness following a treatment [157]. Needless to say, artificial white light regimens require in-house devices and do not advantage environmental UV exposure. Pre-treatment methods including microneedling and CO2 laser use prior to dPDT also demonstrated better clinical and histological results compared to dPDT alone, indicating a possible role for physical interventions in dPDT as well as traditional PDT [158]. Sequential treatment with calcipotriol for 14 days followed by application of MAL-dPDT has recently been shown to be more effective in treating thicker, upper-extremity AK lesions compared to MAL-dPDT alone [159]. dPDT has also shown promise in the SOTR population, although further studies in this demographic are required [160]. A multitude of comparative studies exist between 5-FU and other AK treatment agents. The SPOT trial published in 2022 found that 5-FU 5% was more effective than imiquimod and sunscreen at both treating and preventing AK lesions in SOTRs [161]. The authors of this trial hypothesized that imiquimod was not fully capable of exerting its effects due to patient’s immunocompromised states. A cohort study published in 2018 also found that 5-FU was more effective in the short term (2 years) but not long term (5 years, equal effect) at preventing AK lesions compared to imiquimod [162]. A cost-effectiveness RCT conducted in 2020 also determined that 5-FU was both more effective, as well as less expensive, than imiquimod and MAL-PDT at treating AKs on the head and neck area after 12 months [58,59]. A recent comparison between imiquimod 3.75% and MAL-PDT demonstrated slightly higher AK clearance when using imiquimod (68.1% vs. 56.5%), with the author’s suggesting the potential for combination or sequential treatment with both modalities [163]. This contrasts findings of a 2007 RCT comparing 5-FU to imiquimod demonstrating greater imiquimod-induced clearance in immunocompetent patients [164]. 5-FU 5% has demonstrated greater efficacy but decreased tolerability after 8 weeks of treatment when compared to diclofenac 3% [165]. A 3-year comparative trial between imiquimod 5% and diclofenac 3% published in 2020 also found diclofenac to be inferior to imiquimod in clearing and preventing AK lesions [166]. A 2021 comparison between combination PDT (dPDT followed by conventional PDT) to conventional PDT alone found similar efficacy between both regimens and higher tolerability with combination PDT, noting mild local skin reactions as the only significant adverse event [167]. No comparative trials have been conducted between different formulations of 5-FU. Table 2 provides a brief summary of randomized-controlled, case–control and cohort treatment trials published since 2010. There exists a variety of different pharmacologic options used to prevent and treat AKs. The surveyed studies vary on their follow-up times, parameters measuring efficacy, patient population and areas of the body targeted for treatment. General patterns have emerged, with 5-FU being a relatively efficacious chemoprophylactic and interventional treatment option for patients with established or emerging AKs. Medications such as diclofenac, which are inferior to 5-FU, offer the benefit of a tolerable adverse event profile. Novel treatment options such as tirbanibulin may be promising, and alterations in drug delivery methods can improve efficacy of existing drugs while limiting adverse reactions. Photodynamic light therapy, despite being reputed as a painful and cumbersome intervention, has acceptable efficacy. It would be of interest to assess future studies directly comparing various medications while controlling for patient demographic, lesion location and efficacy parameters. Indeed, there are many more important studies to be performed before we can truly understand which drug regimens are optimal for the spectrum of patients presenting with AKs.

PMC10003025

Yi Hong,Mengna Zhang,Rugen Xu

Genetic Localization and Homologous Genes Mining for Barley Grain Size

03-03-2023

barley,grain size,yield,QTL hotspot,homolog

Grain size is an important agronomic trait determining barley yield and quality. An increasing number of QTLs (quantitative trait loci) for grain size have been reported due to the improvement in genome sequencing and mapping. Elucidating the molecular mechanisms underpinning barley grain size is vital for producing elite cultivars and accelerating breeding processes. In this review, we summarize the achievements in the molecular mapping of barley grain size over the past two decades, highlighting the results of QTL linkage analysis and genome-wide association studies. We discuss the QTL hotspots and predict candidate genes in detail. Moreover, reported homologs that determine the seed size clustered into several signaling pathways in model plants are also listed, providing the theoretical basis for mining genetic resources and regulatory networks of barley grain size.

Genetic Localization and Homologous Genes Mining for Barley Grain Size Grain size is an important agronomic trait determining barley yield and quality. An increasing number of QTLs (quantitative trait loci) for grain size have been reported due to the improvement in genome sequencing and mapping. Elucidating the molecular mechanisms underpinning barley grain size is vital for producing elite cultivars and accelerating breeding processes. In this review, we summarize the achievements in the molecular mapping of barley grain size over the past two decades, highlighting the results of QTL linkage analysis and genome-wide association studies. We discuss the QTL hotspots and predict candidate genes in detail. Moreover, reported homologs that determine the seed size clustered into several signaling pathways in model plants are also listed, providing the theoretical basis for mining genetic resources and regulatory networks of barley grain size. Barley (Hordeum vulgare L.) is one of the earliest domesticated crops, which has a variety of uses and wide adaptability in agriculture [1]. The introduction of semi-dwarf alleles (e.g., uzu, sdw1/denso) increased barley lodging resistance and fertilizer utilization in agricultural production, leading to a large increase in grain yield [2,3,4]. Thanks to the Green Revolution, the global barley yield performance has increased from 1328.2 kg/ha to 2975.5 kg/ha during the past 60 years with an overall increase of 124.02% (FAO 2022, https://www.fao.org/faostat/en/ (accessed on 26 February 2023)). However, with the harsh climatic conditions, excessive exploitation, and stalling breeding process, the barley yield will be threatened [5,6]. How to improve yield to meet the increasing global food demand remains a key issue. Grain size is a desirable alternative target trait that is closely related to yield and quality. With the technical advances in high-throughput sequencing, positional cloning of the genes regulating grain size has been sequentially reported in monocot and dicot plants including rice (Oryza sativa) [7,8], wheat (Triticum aestivum) [9], maize (Zea mays) [10], Arabidopsis (Arabidopsis thaliana) [11,12], and soybean (Glycine max) [13]. By literally studying genes mostly reported in the model plants Arabidopsis and rice, multiple genetic pathways regulating grain sizes have been proposed. These include the ubiquitin-proteasome pathway, mitogen-activated protein kinase signaling, G protein signaling, phytohormone signaling pathway, HAIKU pathway, and transcriptional regulators [14]. Apart from the Green Revolution genes (e.g., sdw1, uzu1.a) [15,16], row-number genes (e.g., vrs1, Int-c) [17,18] and the naked gene (nud) [19] are also associated with grain size. However, not a single gene in barley associated with grain size has been cloned yet via a map-based cloning technique. This is not only due to its diploid nature, but also because of the large and complex genome in barley, making it more difficult to complete sequence parse and gene annotation. In 2016, the first barley reference genome was released, which offered entry level access for genomic research given that a large number of bases are unknown [20]. Subsequently, the reference genome has been improved and updated, along with the recent release of the barley pan-genome [21,22,23]. Highly abundant repetitive elements in barley genome raise difficulties in assembly, affecting the integrity of the reference genome. Not only is the huge genome size affecting gene mapping and cloning in barley, but also the technical difficulties that sit as bottlenecks in gene functional verification. For instance, compared to rice, suitable materials that can be efficiently used for barley genetic transformation have thus far been very limited. To the best of our knowledge, only the Scottish malting barley cultivar Golden Promise has been recognized as the most efficient genotype for genetic transformation given its best shoot recovery from callus [24,25]. Marker-based mapping approaches such as QTL linkage analysis and whole-genome association studies are the current mainstream methods for identifying the preliminary QTL of grain size in barley. A segregating population used for linkage analysis usually requires bi-parents with significant differences in target traits for better QTL identifications [26]. However, the construction process is time-consuming and labor-intensive due to its specificity. The whole-genome association analysis is based on linkage disequilibrium [27], so the population employed in such an approach requires abundant genetic diversity. Combined with the algorithm, we can detect more loci associated with target traits including rare variations and minor-effect loci. Furthermore, homology-based cloning and transcriptomic analyses are also performed for gene mining. In general, more accurate and reliable localization results can be achieved through combinations of multiple methods. For example, a major QTL for kernel length–width ratio was identified using QTL mapping and further validated through bulked segregant analysis in wheat [28]. The genetic architecture of the maize kernel size was characterized by the combination of association and linkage mapping [29]. The P1pet locus with pleiotropic effects on the spike and grain-related traits was fine mapped at a genomic interval of less than 1 Mb using linkage analysis, and further RNA-Seq was performed to predict the most possible candidate gene [30]. In this review, we summarized the achievements in the barley grain size research with an emphasis on the results of QTL linkage analysis and genome-wide association studies. Our discussion covers several important QTL hotspots and candidate or homologous genes that have been reported to function on grain size. Additionally, we also list a number of barley homologs from rice, wheat, maize, and Arabidopsis, which offers a theoretical basis for homology-based cloning and molecular mechanism studies. Grain size is one of the yield components with high heritability [31,32], which is closely related to grain shape and weight. Before grain filling, the spikelet hull has already developed and set the volume of the cavity within which the integuments formed the seed coat after fertilization [14]. Both spikelet hull and seed coat affect the final shape of the barley grain. Grain filling is mainly a process of assimilate accumulation, and saccharides, proteins, and lipids are the three primary storage substances accounting for the total dry matter weight [33]. This is a key stage that determines the final grain weight and yield. The grain size affects not only the yield, but also the quality [34]. Although the quality requirements of malting barley vary among different industry standards (in different countries), the bulk density or thousand-grain weight, proportion of screenings (<2.5 mm), and protein content are all important evaluation metrics [35]. These physicochemical properties reflect the uniformity and commercial value of barley grain, which are closely associated with length, width, plumpness, and weight. A plumper and more uniform grain is preferred to ensure consistent processing and high malt extract yields [17]. Thus, genetic regions associated with grain size tend to coincide with those associated with the malt extract [36]. During the past 20 years, QTL mapping of barley grain size has produced ample results. The loci controlling grain size was distributed on all seven chromosomes including ~200 QTLs and ~270 MTAs (marker-trait associations) obtained through linkage analysis and whole-genome wide association analysis, respectively. A considerable number of these have been co-detected in multiple studies due to overlapping regions and/or inter-trait correlations. We condensed 78 QTLs and 31 MTAs into 14 QTL hotspots on seven chromosomes (Table 1). Identification of the QTL hotspots was based on the physical positions of the QTLs/MTAs previously reported during the last two decades. Generally, the physical map position of QTLs/MTAs is usually disclosed in published research cases. However, if not, genetic markers associated with the QTLs/MTAs were then used for online blasting against the barley reference genome (Marker (ipk-gatersleben.de)), which identifies the corresponding physical position on the chromosomes. Thresholds were followed when deciding the QTL hotspot: one QTL locus was repeatedly identified by over three independent research cases (overlapped physiological position exist), subsequently, the total spanning physical distance by these QTLs/MTAs was regarded as one QTL hotspot. The QTL hotspots on various chromosomes will be discussed in conjunction with a review of genes related to grain yield in barley and the homologs controlling the seed size, which are reported in other plants (Table 2). Based on multiple studies, we identified three QTL hotspots on chromosome 1H involving ten QTLs and six MTAs [5,6,36,37]. There was no QTL hotspot near the centromeric region within which high LD suppresses recombination frequencies. Located in 19–38 Mb, the QTL hotspot1H-1 contains three QTLs and two MTAs from four different studies. Among these, qSL1.1 explained the highest phenotypic variation of 16.40%, which was identified from a panel of BC3-DH lines derived from a cross between Brenda and HS584 [37]. There were two candidate genes in this region, namely, HvGSN1 and HvRSR1. HvGSN1 is an ortholog of rice GSN1 (GRAIN SIZE AND NUMBER1). GSN1 encodes the mitogen-activated protein kinase phosphatase OsMKP1 and negatively regulates the seed size in rice [47]. HvRSR1 is orthologous to rice RSR1, an APETALA2/ethylene-responsive element binding protein family transcription factor. RSR1 indirectly affects the seed size and quality by negatively regulating the expression of type I starch synthesis genes to alter the starch component and fine structure in rice [48]. Having a content ranging from 50.5% to 75.5% in barley, starch inherently affects the grain yield and starch/protein ratios, since grain filling is also a process of starch accumulation [81]. Consequently, further functional characterization of this gene may be of importance. QTL hotspot1H-2 spans 58 Mb from 333 Mb to 391 Mb and consists of three QTLs and one MTA [5,38,39,40]. QGl.NaTx-1H explained the highest phenotypic variation of 11.90%, which was identified using a DH population derived from a cross between Naso Nijo and TX9425. Despite their lower PVE (phenotypic variation explanation) than 10%, QTL_1H-6 and SCRI_RS_141598 were responsible for more than two grain-related traits. In this hotspot, HvCO9 is considered as one of the candidate genes that regulate flowering under short-day conditions. HvCO9 overexpression in rice plants caused a remarkable delay in flowering, as did Ghd7, which affected the grain size [51]. vrs3 encodes a histone demethylase and controls lateral spikelet development in barley, however, it is an independent recessive gene that has only been reported in two-rowed mutants [50]. We therefore concluded that vrs3 is not the major contributor to this hotspot, but its natural variations remain unclear. Another possible source of this QTL hotspot is suggested by the region’s overlap with two rice grain size genes, OsBSK2 and OsSM1 [49,52]. The rice OsBSK2 encodes a putative brassinosteroid-signaling kinase and positively controls the grain size. Considering that the orthologs of OsBSK2 are extremely conserved among plants (identity >80%), this gene is suggested to be an important candidate. As for QTL hotspot1H-3 (474–500 Mb), loci controlling the grain size and flowering time are located in this region, which overlap the photoperiod gene PPD-H2/HvFT3 [5,17,39,41,42]. PPD-H2 was considered to be one of the main loci affecting the heading date and yield of barley in numerous studies [54,55]. In general, spring barley varieties with PPD-H2 have an earlier heading period under short-day conditions than long-day conditions, indicating its sensitivity to a short photoperiod. While ppd-H2 is mainly distributed in winter varieties and shows relatively late maturity [56], it can be a reliable candidate for this region. Additionally, we also identified two orthologs from rice and maize co-localizing at QTL hotspot1H-3, namely, HvSLG and Hvincw1 [53,57]. Chromosome 2H is the longest chromosome with numerous loci that associate with biotic and abiotic stresses. There are two QTL hotspots identified on this chromosome involving 16 QTLs and five MTAs. As for hotspot2H-1 (17–45 Mb), three QTLs (QTL_2H-2, QTL_2H-3, and QTL_2H-4) with high LOD values but low PVE displayed pleiotropic effects and affected the multiple grain traits as described by Sharma et al. [5]. BK_12 and QTL-GL1 are associated with grain length and both showed relatively high LOD values and PVE [41,43]. In this region, another photoperiod gene PPD-H1 can be considered as a candidate gene. PPD-H1 is a major gene affecting the heading date under long-day conditions in barley and has significant effects on agronomic traits including yield components [59,60]. HvSDG725, an ortholog of rice SDG725, which encodes a H3K36 methyltransferase, is also located in this region. SDG725 plays an important role in rice plant growth and wide-ranging defects occur when SDG725 is downregulated including dwarfism, small seeds, shortened internodes, and erect leaves [58]. In hotspot2H-2, the grain size QTLs and MTAs detected in all studies overlapped in this region when the populations consisted of different row-type barleys [6,17,31,39,40,44]. A candidate gene for this hotspot is VRS1, which specifically expresses in lateral spikelets and inhibits their development. Wild and two-rowed cultivated barleys carry the VRS1 while six-rowed barley carries its recessive allele and has fertile lateral spikelets [61]. Despite the number of grains in six-rowed barley being greater, there were generally fewer assimilates accumulated in a single grain and, as a result, a smaller grain size than the two-rowed barley. Three hotspots are located in between 0–58 Mb, 454–484 Mb, and 562–565 Mb on chromosome 3H, respectively, where 19 QTLs and five MTAs were identified [5,32,36,37,39,40,41]. For hotspot3H-1, at least three candidate genes have been inferred, namely, HvGI, vrs4, and HvCKX2. HvGI, an ortholog of Arabidopsis GIGANTEA, participates in multiple processes from developmental regulation to physiological metabolism in plants [64]. vrs4 was identified from six-rowed mutants with lateral spikelet fertility and loss of determinacy. Despite this, vrs4 and vrs3 may account for the within-sample variation of grain size, as they were all derived from induced mutants and their roles in natural variations remain unknown [62]. HvCKX2 is orthologous to the rice Gn1a/OsCKX2 gene, which encodes a cytokinin oxidase. It has been identified as a major contributor to grain yield improvement in rice breeding practice [76]. uzu and sdw1/denso are two important candidate genes for QTL hotspot3H-2 and hotspot3H-3, respectively. Semi-dwarf breeding improves the lodging resistance and fertilizer utilization of crops, leading to the enhanced yield. In barley, sdw1/denso and uzu have been designated as Green Revolution genes and possess pleiotropic effects. sdw1/denso encodes a gibberellic acid 20 oxidase enzyme, which is orthologous to sd1, and has negative effects on grain weight and quality [65]. Notably, there was no evidence that sd1 was directly involved in the regulation of grain shape in rice while QTL intervals that overlapped with the sdw1/denso gene were detected to be closely associated with grain area, grain length, grain width, and grain diameter in barley [6,31]. uzu encodes a BR-receptor protein that is orthologous to D61. The BR-insensitive mutants formed small and short grains in the model plants (Arabidopsis and rice) and the uzu also reduced the grain weight by 18.8% in barley, suggesting that the phytohormone brassinosteroid plays an important role in regulating grain development [16,66,82]. In recent research, a major QTL (QGl.NaTx-3H) for grain length was identified near the uzu and explained 6.8–29.8% of the phenotypic variation, and this QTL showed a linkage to uzu but not due to gene pleiotropy [38]. However, cv.TX9425, a semi-dwarf variety carrying uzu used in this study, exhibited a similar small-grain phenotype as BR-insensitive mutants. Therefore, sufficiently strong recombination events are required to demonstrate whether such co-detection is due to the linkage drag or a novel locus controlling grain size. There is a hotspot consisting of seven stable QTLs and four MTAs on chromosome 4H. The hotspot4H spans 34 Mb from 6 to 40 Mb and contains seven candidate genes. Vrn-H2 is one of the three vernalization genes in barley that affects heading and flowering [71]. In breeding practice, the selection and utilization of different allelic combinations of vernalization and photoperiod genes can directly affect the grain yield. Another gene of interest involved in spike morphology is INT-C, an ortholog of the maize TB1. INT-C and VRS1 are functionally opposed and show effects interaction, that is, the dominant VRS1 inhibits the development of lateral spikelets, while INT-C promotes fertile spikelets [18]. Since grains from central spikelets are generally expected to be larger and more symmetrical than those from lateral spikelets, INT-C may be an essential factor affecting the grain uniformity in six-rowed barley. Five orthologs from rice (HvRGB1), maize (HvDek35, Hvemp4), and Arabidopsis (HvAHKs, HvDAR1) were identified in hotspot4H. RGB1 encodes the β-subunit (Gβ) of heterotrimeric G protein. Loss of function and suppression of Gβ result in short seeds in rice, suggesting that Gβ positively regulates the seed length [67]. Dek35 and emp4 mutants with developmental deficiency confer a seed-lethal phenotype in maize [68,70]. Genetic analysis indicated that cytokinin-dependent endospermal and/or maternal control can affect embryo size. Three histidine kinases perceive the cytokinin signal in Arabidopsis: AHK2, AHK3, and CRE1/AHK4 [69]. DA1 affects the seed size in the maternal control by regulating cell proliferation in the integuments redundantly with DAR1 in Arabidopsis [11]. Chromosome 5H shows significance across almost all grain-related traits (grain length, width, thickness, plumpness, and thousand-grain weight). A total of 16 QTLs and nine MTAs are clustered into three hotspots [5,6,36,39,40,42,43]. As for hotspot5H-1 (0–23 Mb), HvIKU2 and HvPPKL3 are two putative candidates. In Arabidopsis, IKU2 functions zygotically to control the seed size by affecting endosperm development [72]. PPKL3 encodes a protein phosphatase with the Kelch-like repeat domain, and the T-DNA insertion mutants displayed a longer grain phenotype in rice [73]. Hvdep1, a noncanonical Gγ of G protein, is a causal gene for another semi-dwarf locus (ari-e) in barley as described by Wendt et al. [75], which is located in hotspot5H-2 (427–431 Mb). The overexpression and downregulation of DEP1 result in larger and smaller grains in rice, respectively [74]. Genetic transformation also demonstrated that HvDEP1 positively regulates grain size and culm elongation in barley [75]. The QTL hotspot5H-3 (541–588 Mb) consists of seven QTLs and five MTAs and displays associations for all grain-related traits. Among these, QTL-GT2 (grain thickness) and QTL-GP2 (grain plumpness) were two consensus QTLs identified using a DH population derived from the cross Vlamingh × Buloke. There was a high PVE of 15.3% for QTL-GP2, and the linkage maker 8682-406 can be used to screen well-filled varieties in maker assisted breeding. In this region, there are three orthologs from rice (HvDST and HvSK41) and Arabidopsis (HvABA2). Rice zinc finger protein DST associated with abiotic stresses regulates CKX2 expression to enhance grain production [76]. OsSK41 is responsible for a major QTL that controls the grain size and weight in rice [83]. Abscisic acid was reported to control the seed size by regulating the HAIKU pathway, and seeds from ABA-deficient mutants exhibited increased size, mass, and embryo cellularity in Arabidopsis [77]. A total of seven QTLs and one MTA overlapped an interval of 31 Mb from 463 to 494 Mb for all grain-related traits on chromosome 6H [5,17,32,37,43]. Of these QTLs, qTGW6.1 explained the highest phenotypic variation ranging from 19.60% to 38.30% in multiple environments [37]. The linkage maker of this major QTL can also be used for marker-assisted selection. HvDEK1, an ortholog of maize DEK1, encodes a Calpain-Type Cysteine Protease and is located within this hotspot. In recent years, numerous studies have indicated that DEK1 is important for the development and mechanical stimulation of seeds, leaves, and flowers. Kernels from maize dek1 mutants are small and lacking plumpness, and deeper investigations showed that the normal DEK1 gene products are required for aleurone cell fate specification [78,84]. Another candidate gene is LEC1, which encodes a transcriptional factor that regulates seed development. Mutation in the LEC1 gene not only alters the normal developmental rhythm and pattern, resulting in abnormal embryos, but also affects the accumulation of storage substances in Arabidopsis and maize [80,85]. There are many QTLs and MTAs across the entire 7H chromosome, but most of these occupy separate positions according to multiple studies. We clustered four consensus QTLs and one MTA within this chromosomal interval from 519 Mb to 540 Mb into a QTL hotspot, where the Nud gene is a candidate for grain size [6,19,31,40,41]. Similar to VRS1 and INT-C, this region can be detected in almost all studies if the populations consist of naked and hulled barley. With the deletion of Nud, naked barley is produced free-threshing after maturity, resulting in altered grain dimension and weight compared to hulled barley. Previous studies have also reported that yield-related QTLs are tightly linked to the nud gene [86,87]. As above-mentioned, numerous mapping experiments revealed multiple QTL hotspots that control the barley grain size on seven chromosomes. According to these candidate genes, several QTL hotspots are found to share common features, especially containing phytohormone-related genes, indicating potential interactions with each other. Plant hormones play important roles in seed formation and can affect the grain size directly or indirectly. Among the 14 QTL hotspots we summarized, eight contained candidate genes related to plant hormones. Brassinosteroid (BR) is one of the hormones essential for plant height, spike architecture, and organ size. BSK2 (Hotspot1H-2) and SLG (Hotspot1H-3) affect the seed size by altering the length of the epidermal cells of the spikelet hull through cell expansion in rice [49,53]. BSK2 interacts directly with BRI1 (hotspot3H-2) and affects grain size independent of the BR signaling pathway, while SLG is involved in BR homeostasis by positively regulating endogenous BR levels. SDG725 (hotspot2H-1) can modulate brassinosteroid-related gene expression through epigenetic regulation including BRI1 to affect plant growth and development in rice [58]. Cytokinin (CK) is another key regulator of plant growth and cytokinin oxidase/dehydrogenases (CKXs) catalyze CK degradation irreversibly. In previous studies, the iku2-2 (hotspot5H-1) seed size phenotype can be partially restored by overexpressing CKX2 (hotspot3H-1) in Arabidopsis [63]. Moreover, the DST-directed (hotspot5H-3) expression of rice CKX2 affects CK accumulation in the shoot apical meristem, which controls the reproductive organ number [76]. Grain size regulation involves a complex genetic network controlling the development of spikelet hulls, integuments, and endosperms, which are all determined components of the final grain size. Recent advances have cloned numerous genes that are involved in several networks to control the grain size including the ubiquitin-proteasome pathway, mitogen-activated protein kinase signaling, G protein signaling, phytohormone signaling pathway, HAIKU pathway, and transcriptional regulators. Some of them also exhibit genetic interactions and integrate multiple signaling pathways. These findings not only shed new light on our understanding of molecular mechanisms, but also provide key ideas for the research of homologs in other crops. For instance, TaGW2 and TaTGW6-A1, which encode E3 ubiquitin ligase and indole-3-acetic acid (IAA)-glucose hydrolase, respectively, have been cloned by comparative genomics approaches. Polymorphism and haplotype analysis indicated that they are strongly associated with grain size and weight in wheat [88,89]. Orthology, which is of great interest, paralogy, and xenology are three main subclasses of homology used to describe the evolutionary relationships between species. As more high-quality genomes are being released, whole-genome alignment (WGA) is becoming a powerful tool for gaining insights into the evolutionary scope. Despite species divergence, numerous genetic features of ancestry are retained, resulting in a high level of genome collinearity among closely related species. Gene type, order, and orientation are relatively conserved within collinear blocks [90]. Based on collinearity and gene homolog analyses, 29 candidate genes related to seed shattering were identified in Chinese wild rice [91]. To facilitate homology-based cloning, here we list 190 barley orthologs of 142 grain size genes in other plants according to the Ensemble database (http://plants.ensembl.org/index.html (accessed on 26 February 2023)) (Table S1). Rice is responsible for 110 of them, maize for 46, Arabidopsis for 25, and wheat for nine. Unsurprisingly, 21 grain size genes do not create a one-to-one correspondence in barley. Some of these orthologs (e.g., HvZM-INVINH1) are the results of tandem gene duplication, while others (e.g., HvMADS87) are distributed on several chromosomes due to interspersed gene duplication. Collinearity analyses using TBtools software showed extensive genome collinearity between barley and gramineous crops, but a low degree of genome collinearity between barley and Arabidopsis [92]. In the 190 barley orthologs analyzed, 81 shared significant collinearity with other plants, indicating deeply conserved functions (Figure 1 and Table S1, References [93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212] are cited in Table S1). We finally mapped these collinearity genes to the reference genome, which can provide a theoretical basis for further studies (Figure 2). During the past two decades, significant achievements have been witnessed in crop yield and yield components, despite the threat of both biotic and abiotic stress. Grain size with high heritability has long been a primary target of breeding, which is closely related to final yield and quality. Thanks to linkage analysis and whole-genome association analysis, hundreds of grain size QTLs were identified. However, the PVE of these QTLs varied depending on the study materials and methods. How to systematically evaluate the genetic effects of these QTLs and the potential application of linkage markers in different genetic contexts are crucial in marker-assisted breeding. According to the published data, the cloning of barley genes has been relatively rare, making it hard to identify the regulatory networks of grain size. In the future, more efforts should be invested in the fine-mapping of these reported QTLs to isolate the causal gene. On the other hand, substantial evidence from genetics and molecular biology has suggested that large SVs (structure variations) identified from the pan-genome can cause the phenotypic variance affecting many important agronomic traits [22,212,213]. Compared to traditional SNP-based GWAS, PAV-based GWAS (presence and absence variation, PAV) enable the precise identification of trait-associated genomic regions and can complement SNP-based GWAS. In barley, therefore, taking full advantage of the published pan-genomic data to mine variations will become a new strategy. The CRISPR/Cas9 system serves as a revolutionary technique in molecular design breeding and varietal improvement in many crops. With gene editing, target function-deficient mutants can be created rapidly and efficiently without introducing exogenous genes into the genetic background. It can directly influence gene expression at the transcriptional levels, making it a mainstream tool for gene functional validation. The combination of comparative genomics and gene-editing technology will be very practical for the study of unknown genes or orthologs, and will help constantly refine the regulatory network of grain size in barley.

PMC10003026

Muhammad Nadeem Abbas,Mohamed Amine Jmel,Imen Mekki,Ingrid Dijkgraaf,Michail Kotsyfakis

Recent Advances in Tick Antigen Discovery and Anti-Tick Vaccine Development

04-03-2023

vaccinomics,antigen candidates,anti-tick vaccine,tick control

Ticks can seriously affect human and animal health around the globe, causing significant economic losses each year. Chemical acaricides are widely used to control ticks, which negatively impact the environment and result in the emergence of acaricide-resistant tick populations. A vaccine is considered as one of the best alternative approaches to control ticks and tick-borne diseases, as it is less expensive and more effective than chemical controls. Many antigen-based vaccines have been developed as a result of current advances in transcriptomics, genomics, and proteomic techniques. A few of these (e.g., Gavac® and TickGARD®) are commercially available and are commonly used in different countries. Furthermore, a significant number of novel antigens are being investigated with the perspective of developing new anti-tick vaccines. However, more research is required to develop new and more efficient antigen-based vaccines, including on assessing the efficiency of various epitopes against different tick species to confirm their cross-reactivity and their high immunogenicity. In this review, we discuss the recent advancements in the development of antigen-based vaccines (traditional and RNA-based) and provide a brief overview of recent discoveries of novel antigens, along with their sources, characteristics, and the methods used to test their efficiency.

Recent Advances in Tick Antigen Discovery and Anti-Tick Vaccine Development Ticks can seriously affect human and animal health around the globe, causing significant economic losses each year. Chemical acaricides are widely used to control ticks, which negatively impact the environment and result in the emergence of acaricide-resistant tick populations. A vaccine is considered as one of the best alternative approaches to control ticks and tick-borne diseases, as it is less expensive and more effective than chemical controls. Many antigen-based vaccines have been developed as a result of current advances in transcriptomics, genomics, and proteomic techniques. A few of these (e.g., Gavac® and TickGARD®) are commercially available and are commonly used in different countries. Furthermore, a significant number of novel antigens are being investigated with the perspective of developing new anti-tick vaccines. However, more research is required to develop new and more efficient antigen-based vaccines, including on assessing the efficiency of various epitopes against different tick species to confirm their cross-reactivity and their high immunogenicity. In this review, we discuss the recent advancements in the development of antigen-based vaccines (traditional and RNA-based) and provide a brief overview of recent discoveries of novel antigens, along with their sources, characteristics, and the methods used to test their efficiency. Ticks are ectoparasites that infest humans and animals and are responsible for significant economic losses. They are the second most important vectors for the transmission of diseases in humans after mosquitoes [1,2]. They are also one of the most important vectors for the transmission of diseases that impact the global cattle industry and pets [3,4,5]. Ticks have few natural enemies, making it challenging to control tick infections. Chemical acaricides have been only partially effective, with a number of nontarget disadvantages, including the selection of acaricide-resistant ticks and contamination of the environment and animal products with chemical residues [6]. In addition, to control tick-borne diseases, some antigen-based vaccines are used in various countries; however, new and more effective approaches are needed, including the development of new vaccines that target tick infestations and pathogen infections [7,8]. Traditionally, the “isolate–inactivate–inject” principle has played a crucial role in designing and developing a vaccine for the control of parasites/pathogens. First-generation vaccines were composed of pathogens that were alive, attenuated, or killed. Second-generation vaccines consisted of purified parasite/pathogen components and were developed as a result of advances in cell culture, polysaccharide chemistry, recombinant DNA technology, and immunology [9,10]. The advancement of genomics and other “omics” over the last two decades has resulted in the development of a “third generation” of vaccines, based on technologies such as functional omics, reverse vaccinology, and the systems biology approach. In order to overcome the limitations of the conventional vaccine development approaches, vaccine development has become more tailored, with a focus on the antigen moieties that are targeted by the protective immune responses [11,12], with the broad perspective of the pathogen and its interaction with the host immune system [13]. Hence, modern vaccinology relies increasingly on novel omics approaches utilizing high-throughput cutting-edge technologies, such as genomics, transcriptomics, and proteomics, along with advances in basic immunology, host–pathogen biology, immunomics, advanced bioinformatics, and computational modelling, and improved understanding and technological innovations. Compared to using chemicals, vaccination is a wise option because it is environmentally safe and cost-effective to control tick infestation [12,14]. Although vaccination is a rational strategy for controlling tick infestation, only a few vaccines have been commercialized so far, with minimal concern given to the induction of cross-reactive immunity against tick species [15]. To develop new vaccines, it is crucial to identify and characterize novel antigen candidates that would be more conserved and have the ability to induce cross-reactive immunity in the host species. The goal of this review is to provide an overview of traditional and RNA-based vaccines and the possibility of their application and novel antigens that have the potential to be exploited as promising antigen candidates for vaccine development. The identification of antigens is paramount for the development of an anti-tick vaccine. It is crucial to understand the molecular mechanisms associated with the host–parasite–pathogen interactions to identify antigen candidates that are likely to serve as candidates/targets for the development of a vaccine. The ideal antigen candidate is one that induces long-lasting and effective immune responses in the host [16,17]. Many studies have been carried out since Allen and Humphreys published their findings in 1979, employing a range of antigens, including whole tick homogenates and internal organs, to induce varying levels of immunity against ticks [16]. Several new possibilities have emerged for predicting, screening, and identifying antigens protective against tick infestations since Ixodes scapularis, the first tick species to be sequenced [18]. There are now many nucleotide and protein databases available from different tick tissues and developmental stages, and a wide variety of stimuli that affect ticks, such as tick feeding or infection with pathogens [17,19], are known. The probability of selecting protective antigen candidates derived from ticks for the control of tick infestation and pathogen infection has also increased as a result of recent advances in omics technologies (i.e., transcriptomics, proteomics, and metabolomics) [20]. In addition, the use of reverse vaccinology (RV), or vaccinomics, has allowed the discovery of new vaccine antigen candidates [20]. As a result of this, synthetic and recombinant proteins have been evaluated and demonstrated to be able to induce some level of protective immunity. The purpose of this section is to discuss antigen candidates originating from different tissues which have been identified, assessed for their efficacy, and are being considered as potential candidates for the development of an anti-tick vaccine, based on the available literature (Table 1 and Figure 1). Egg yolk is an essential component for the development of ticks, since it serves as a reservoir of various proteins that play a crucial role during the embryonic development of these arthropods [21,22]. As in insects, yolk proteins are synthesized in the fat body of ticks [21,23]. The degradation of the yolk is carried out by various types of enzymes which are found in eggs. Boophilus Yolk pro-Cathepsin (BYC) is an example of a yolk proteinase that has been isolated from R. microplus eggs, and has been reported to be involved in the embryogenesis process of the tick. In particular, these enzymes play a key role in the degradation of vitelline, a major proteinaceous component of egg yolk [21]. BYC was first isolated by da Silva Vaz Jr et al. [24] from R. microplus eggs, and was then inoculated into cattle to determine its role in the induction of host immunity. This enzyme was found to provide partial protection against ticks and trigger a protective immune response in cattle, but its efficacy was between 14% and 36%. A subsequent study expressed recombinant BYC protein in a prokaryotic expression system (E. coli). Interestingly, the recombinant protein showed an overall higher efficacy (25.24%) compared to the enzyme directly isolated from egg yolk [25,26]. It appeared that various factors may affect the efficacy of this protein, for example, the method of preparation of BYC protein can influence the protein structure and ultimately its functions. Furthermore, this variation may be also associated with the tick strain or other experimental conditions [24]. Vitellin, a lipoglycoprotein also occuring in the egg yolk similar to other yolk proteins, is synthesized in the fat bodies of arthropods [27,28]. In ticks, vitellin or vitellogenins have been shown to be crucial for egg development and oviposition as demonstrated by the silencing of three vitellogenin genes in H. longicornis [29]. Vitellin protein was purified from tick eggs as a non-covalent complex of six polypeptides of high molecular weight (44–107 kDa). Parallel to this study, an 80 kDa glycoprotein (GP80) was isolated and purified from R. microplus larvae. Both proteins were then inoculated to investigate their efficacy. Vitellin and GP80 vaccination showed an overall 68% efficacy, suggesting that a vaccine containing both antigens can induce an immune response and also provide partial protection against R. microplus in sheep hosts [28]. Remarkably, when recombinant hexahis-GP80 (HH-GP80), which was incorrectly folded and not glycosylated, was injected into the host under the same experimental conditions, it displayed no efficacy [28]. Based on the findings of the above study, it appears that vaccination of vitellin and GP80 can elicit immune responses in sheep and may partially protect sheep against the tick B. microplus. The correct folding of HH-GP80 is crucial for its activity, since protective epitopes are associated with the folding of the protein and/or the oligosaccharides attached to it, and these epitopes are essential for its activity. Vitellin degrading cysteine endopeptidase (VTDCE) is another egg-associated enzyme which was identified and isolated by Seixas et al. [30]. Similar to BYC, this enzymatic protein is not synthesized in the ovary of R. microplus and is implicated in vitellin hydrolysis, thereby providing nutrients to developing embryos. However, both enzymes were found to regulate vitellin hydrolysis differently [30]. The same research group later analyzed purified VTDCE protein as an antigen and found that this protein also provides partial protection against ticks, as the immunization of livestock resulted in 21% efficacy and a 17.6% reduction in the weight of fertile eggs [31]. The egg-associated proteins BYC and VTDCE provided limited protection to the host against tick infestation, and therefore seem to be not suitable antigen candidates when used alone in a vaccine. Ticks contain an angiotensin-converting enzyme-like protein that can control blood pressure by regulating fluid volume, similar to the angiotensin-converting enzyme in mammals [32,33]. This control allows the tick to feed continuously on the host’s blood. The salivary glands and midgut of tick B. microplus contain a low abundance glycoprotein, which is named Bm91 [32]. Bm91 is currently not included in commercial anti-tick vaccines, but it is considered to be a candidate for controlling ticks [34]. When the recombinant Bm91 protein was assessed alone under field conditions with natural tick infestation, the results were disappointing, as this protein showed only 6% efficacy, which seems to inappropriate for the development of a vaccine for tick control [35]. However, when recombinant Bm91 protein which was produced in E. coli was combined with Bm86 (an antigen candidate that is used in commercial vaccines) and then this protein combination was used as a vaccine, the results were much more promising, since the Bm91 addition enhanced the efficacy of the Bm86 antigen [33], suggesting that the combination of these two proteins (Bm91 and Bm86) seems to be an effective strategy to develop a new anti-tick vaccine. Transcriptomic and differential gene expression analyses of salivary glands have shown that the genome of tick (e.g., R. microplus and Dermacentor andersoni) species comprises a protein sequence named flagelliform silk protein [36,37]. The characterization of differential gene expression in the salivary glands of R. microplus in response to A. marginale infection highlighted the molecular mechanisms of how the tick interacts with the pathogen. Subsequent functional studies have shown that flagelliform silk protein (SILK) may play a crucial role in the infection and multiplication of A. marginale in ticks. An interaction between tick- and pathogen-derived molecules is involved in the multiplication of A. marginale in salivary gland cells [36,38]. Following this study, it was proposed that flagelliform silk protein could be a suitable antigen candidate to develop a vaccine. For this purpose, Merino et al. [14] produced recombinant flagelliform silk protein and analyzed its antigenic activity by injecting it into a cattle host. The recombinant protein was found to be an excellent antigenic candidate, as it provided 62% protection against tick infestation and tick-borne infection (e.g., babesiosis) in cattle. Vaccination with flagelliform silk protein reduced the multiplication of A. marginale in cattle. Theantigen-specific antibody titers correlated with reduced tick infestations and pathogen infection, indicating that the effect of the vaccine is a result of the antibody response. Furthermore, the expression of gene-encoding vaccine antigens in ticks feeding on cattle was also affected by vaccination and co-infection with A. marginale and B. bigemina. Thus, it appears that vaccines using tick proteins that are involved in vector–pathogen interactions can be effective in both controlling tick infestation and preventing pathogen infection at the same time [14]. Salp15 is an immune suppressive salivary protein of I. scapularis with a molecular weight of 15 kDa that inhibits the activation of CD4+ T cells, the complement activity, cytokine production, and the dendritic cell function in the host [39,40,41]. Subsequent studies investigated the molecular mechanism of Salp15. The outer surface protein, OspC, is produced by B. burgdorferi on the outer surface of the cell. The production of spirochetes (B. burgdorferi spirochetes) in the midgut of infected ticks is initiated when it feeds on blood from the host, which is then transported to the host. During the exit from the salivary glands and transmission of the B. burgdorferi spirochetes to the host, Salp15 physically interacts with OspC on the surface of B. burgdorferi spirochetes, which facilitates the survival of spirochetes, pathogen transmission, and host infection [38,42]. Salp15–OspC interaction may thus potentially obscure OspC from the host immune response so that the spirochete is protected from the immune response [38]. Recently, the Escherichia coli expression system was used to synthesize Salp15 recombinant protein, and the system was found to be efficient in producing this protein in a considerable yield with good solubility. These characteristics of Salp15 recombinant protein indicate that this has practical application and can be used to generate anti-tick vaccines [41,43,44]. Metalloproteases (MPs) are multifunctional proteins that participate in a wide variety of complex physiological and pathologic processes in living organisms [45]. A number of MPs have been identified in different tick species and are considered to be crucial for the maintenance of blood meal-associated functions in ticks [46,47,48,49]. For example, the salivary glands of ixodid ticks contain MPs that are recognized as key bioactive components in vital physiological functions and are therefore considered for use as potential targets in control strategies to combat these ectoparasites [49]. In order to evaluate the antigenic potential of MPs, Ali et al. (2015) [50] amplified a fragment of the sequence encoding a R. microplus MP, expressed it as a recombinant protein, and used the purified form of this protein as a vaccine antigen against R. microplus in cattle [50]. The recombinant R. microplus MP protein demonstrated an overall efficacy of 60%. In addition, it reduced the number of feeding ticks, the number of eggs produced, and the number of eggs hatched, making [41] it an ideal candidate for anti-tick vaccine development [50]. To further explore suitable antigen candidates from R. microplus, Maruyama et al. [51] performed an RNA-seq study on salivary glands at all feeding stages of R. microplus, and they detected a fragment from the transcriptome which was similar to MP (Rm239) along with three other genes, including Rm39, Rm76, and Rm180. Application of these proteins as vaccines showed that all of them can inhibit hemostatic responses, suppress the host’s antibody responses, and reduce the tick’s ability to bind to the host by means of a glycine-rich cement protein. Therefore, the authors developed a multicomponent anti-tick vaccine using these four different types of proteins [51]. The immunization of cattle with this multicomponent vaccine resulted in a reduction in the infestation of R. microplus by 73.2%, indicating that the formulation of a multi-antigen anti-tick vaccine may be more effective than monocomponent vaccines [51]. Ribosomes, also called protein factories, are components of all living organisms. It has been shown that the ribosomal protein P0 plays a pivotal role in regulating the translational activity of ribosomes and assisting an organism to adjust its metabolism to various environmental conditions. It belongs to a group of acidic proteins that form a stalk-like structure in the largest ribosome subunit of the ribosome [52]. There is evidence that shows that tick saliva contains ribosomal proteins that play a role in evading the defensive mechanisms of the host [53,54,55]. It was recently reported that rabbits vaccinated with recombinant ribosomal protein P0 exhibited strong humoral responses that primarily reduced nymph molting and female reproduction. The protein demonstrated a 57.5% protection against infestations of O. erraticus, but did not provide cross-protection against infestations of the African tick Ornithodoros moubata [56]. In another study, researchers chemically synthesized a peptide of 20 amino acids, which was derived from the ribosomal P0 protein of Rhipicephalus ticks, and successfully conjugated it to the Keyhole Limpet Hemocyanin (KLH) protein of Megathura crenulate to serve as an antigen against R. microplus, showing 96% efficacy in cattle [57]. In this study, the results suggested that P0 conjugated to KLH is an excellent vaccine. However, the production of such a vaccine will be expensive and may therefore not be cost-effective for livestock. It is therefore essential to conduct further research on the recombinant production of an antigenic vaccine to evaluate its effectiveness and to make its production more economically viable. Serine protease inhibitors: Attempts to isolate antigens from tick species have identified some serine proteinase inhibitors (serpins), which appeared to have antigen abilities. Serpins are involved in various physiological activities in animals, in particular in cattle, where they influence blood clotting, altering prothrombin time and partially activating thromboplastin time [58,59,60]. Serpins interfere with the immune system of ticks and thereby facilitate the initial feeding process of these parasites [61]. Andreotti et al. [62] isolated and identified R. microplus trypsin inhibitors (BmTIs) from larval extracts. To evaluate its antigenic activity, crossbred cattle were vaccinated with BmTI, which was found to interfere with leukocyte migration at the site of larvae fixation [63,64]. Vaccination of calves with BmTI antigens remarkably reduced engorged female tick numbers and their weight, resulting in a 72.8% efficacy against R. microplus. This data suggested that BmTI immunization may act in the early phase of larval development [65]. To investigate whether truncated BmTI can also induce immunization, the N-terminal fragment of BmTI was synthesized and showed a lower efficacy (18.4%) in cattle compared to the full-length protein. Thus, immunization with the N-terminal domain is apparently not sufficient to improve the effect of BmTIs on host–parasite interactions [64]. Similarly, when the recombinant R. microplus larvae trypsin inhibitors (rRmLTIs) were employed as a vaccine trial, the efficacy (32%) was again low, suggesting that both the truncated or whole recombinant protein are less effective, probably due to a lack of precise folding of the protein in vitro. Overall, these results indicate that trypsin inhibitors seem suitable candidates to produce an effective vaccine; however, the method to produce them on a large scale needs to be improved to enhance its efficacy [66]. Various other serpins have been evaluated as possible anti-tick vaccine candidates from different tick species, including Amblyomma americanum (AAS19), Haemaphysalis longicornis (HLS2), Rhipicephalus (Boophilus) microplus, and so on. All of these serpins demonstrated a partial protection to the host; however, the level of protection may vary with tick species and the type of serpin [67,68,69]. Combining proteins from one or more ticks into a single polypeptide chain represents an attractive anti-tick vaccination strategy. Therefore, trypsin inhibitors/or serpins combined with immunogenic fragments of other tick proteins can be used as multi-antigen constructs. For example, a chimeric protein containing the recombinant Bm86-Campo Grande antigen (BmCG), rRmLTI, and the heat-labile enterotoxin B subunit from Escherichia coli (LTB) as a molecular adjuvant was synthesized. This chimeric RmLTI–BmCG–LTB antigen had a 55.6% efficacy against R. microplus in cattle. Ferritin proteins are important for the physiological storage of iron in a nontoxic but biologically available form. They are crucial for the metabolism of iron from ingested blood during tick feeding [70,71]. So far, two ferritin molecules (Ferritin 1 and Ferritin 2) have been identified and characterized. Ferritin 1 (FER1) is located within cells, where it is involved in the physiological storage of iron. For Ferritin 2 (FER2), there are no functional orthologs in vertebrates. It is mainly expressed in the gut and plays a crucial biological role in iron transport to the salivary glands and ovaries [71]. The FER2 protein has been reported in various tick species including D. variabilis, R. microplus, I. ricinus, Haemaphysalis longicornis, and I. scapularis [71,72]. Based on loss-of-functions studies of FER2, it is a promising vaccine candidate, because suppression of this gene impairs tick feeding ability, lowers oviposition, and reduces larval hatching [71]. Besides FER2, FER1 has been shown as a suitable antigen candidate to control a variety of tick species. Hajdusek et al. tested the recombinant FER2 protein of R. microplus (RmFER2) to immunize cattle and found that the FER2-based vaccine showed an overall efficacy of 64% [73]. Similarly, the recombinant proteins FER1 and FER2 of H. longicornis have been used to immunize rabbits. Both proteins are highly immunogenic and induced host antibody production. Immunizing the host significantly reduced the engorged weight of the infested ticks and reduced the number of eggs and the number of ticks with completely hatched eggs. However, recombinant FER2 caused a greater reduction with a higher efficacy (49%) than recombinant FER1 (34%) [72]. More recently, Manjunathachar and co-workers [74] reported that a calf vaccinated with H. anatolicum FER2, a vector of Crimean–Congo hemorrhagic fever, was strongly protected from larval (51.7%) and adult (51.2%) tick infestations, as well as against ticks with FER2 knocked down by RNAi. Many other recent studies have also confirmed that FER2 provides significant protection to the host against tick infestation by using a recombinant protein of FER2 [75,76,77]. The molecular mechanism of protection involves mainly the production of anti-FER2 antibodies in the host body, which are transferred into tick species during the feeding process, and the anti-FER2 antibodies bind to FER2 inside the tick gut cells or hemolymph, thereby preventing FER2 assembly and/or function. It has been recently discovered that predicted antigenic regions on the FER2 protein are conserved across different tick species. This protein can therefore be used to produce a vaccine for cross-species protection [77]. In a recent study, FER2 orthologues in O. moubata (OMFER2) and O. erraticus (OEFer2) were characterized, and the researchers found that they have high sequence similarity (85.3%). The recombinant form of O. moubata Fer2 (tOMFER2) has the ability to elicit strong humoral responses in rabbits. However, in O. erraticus, this protein does not exhibit any protective effect, despite the high sequence similarity, which suggests that a slight difference in their sequences may determine whether or not they have a protective effect. In spite of this, the results of this study confirm that OMFER2 has the potential to serve as an antigen candidate for vaccines [78]. TROSPA is a tick receptor that is required for spirochete colonization in I. scapularis. The B. burgdorferi outer surface protein A (OspA) is abundantly produced on these spirochetes and is critical for adhesion to the vector via specific binding to TROSPA [79,80]. In different tick species, including R. microplus, I. scapularis, and R. annulatus, TROSPA may play a role in infection mechanisms and the multiplication of Babesia pathogens. In addition, the outer surface proteins OspA and OspB are expressed when the spirochetes enter and reside in ticks [81]. However, their expression is suppressed during transmission to the host, whereas the expressions of OspC and bba52 are upregulated. BBA52, along with the OspC protein of borrelial, has complementary but non-essential roles in the transmission process, as these antigens are all localized in the outer membrane and co-expressed in feeding ticks [82,83,84]. The biological function of the receptor is unknown, but binding of OspA to TROSPA is necessary in ticks for the bacterium B. burgdorferi to colonize the tick gut, which supports the bacterial infection in the vector [79]. Infection of B. burgdorferi induces the production of particular tick genes (TROSPA and salp15), which can be targeted to inhibit the transmission of Borrelia spirochetes and other tick-borne microbes [80,85]. Blocking TROSPA with TROSPA antisera or via RNAi reduces the adherence of B. burgdorferi to the gut of I. scapularis, and thus reduces the bacterial colonization of the vector and potentially pathogen transmission to the host [79]. As a result of this interaction, recombinant TROSPA was analyzed in cattle as an antigen vaccine to control tick infestation and pathogen transmission, but it did not affect tick feeding or fecundity [14]. Aquaporins (AQPs) or transmembrane water channels play a major role in water homeostasis and cryoprotection [86,87]. They are evolutionarily highly conserved members of a larger family of major intrinsic proteins. They form pores in the cell membrane that transport water or other solutes [86,88,89]. In addition to transporting water and small neutral solutes, AQPs are involved in numerous physiological processes [90]. In ticks, AQPs have been reported in the digestive track, Malpighian tubules, and also in salivary glands [91]. AQPs reduce the host blood volume in tick guts, an important physiological function since ticks ingest large volumes of blood relative to their size and weight [62]. A fragment of an aquaporin from R. microplus engorged females has been isolated and subsequently recombinantly produced and designated as an RmAQP1 vaccine [62]. This vaccine was tested in two cattle pen trials for efficacy against R. microplus, demonstrating 68% and 75% efficacy. This suggests that RmAQP1 may be a potential vaccine antigen [62] and that aquaporins can be used in anti-tick vaccines [62]. In a recent study on the RmAQP2 of the same species, it has been demonstrated that cattle vaccinated with the synthetic peptide of the extracellular domains of the RmAQP2 were able to reduce the number of ticks feeding to repletion by 25% overall, suggesting that this target (RmAQP2) may be a useful component of a vaccine cocktail against tick bites [92]. Another study on I. ricinus confirmed the efficacy of the tick AQP antigens for the control of tick infestations by showing the effect of IrAQP and CoAQP vaccination on I. ricinus tick larvae in rabbits. The efficacy of the vaccine containing the AQP conserved region present in the CoAQP antigen was higher than that of the IrAQP vaccine [93]. Furthermore, vaccination with synthetic immunogenic peptides derived from Ornithodoros erraticus AQPs (OeAQP and OeAQP1) provided significant protection to cattle against the homologous species O. erraticus, but the cross-species protection against Ornithodoros moubata was lower [94]. Besides, some other studies have also identified AQPs from different species, including O. moubata and Ixodid ticks, with bioinformatics analyses suggesting that these AQPs have a good potential to be used as a vaccine. Therefore, further experimental evidence is required to confirm the antigen potential of these AQPs [95,96]. I. ricinus is one of the tick species responsible for the growing prevalence of tick-borne diseases in companion animals in Europe [4]. The effect of the AQP-based vaccines on I. ricinus larvae infestation and molting could result in a reduction in tick infestations in vaccinated animals and supports that CoAQP might be a candidate protective antigen for the control of different tick species feeding on the same host. A study using expression library immunization against a mouse model of tick infestations showed that the 4D8 protein, later named subolesin (SUB), is a potential antigen that could be used as a vaccine against I. scapularis [97]. It was found that the sequences of the gene and protein of SUB are conserved across invertebrates and vertebrates. In addition, this gene has been identified and characterized in different tick species, and was found to be expressed at different developmental stages and in different tissues of adult ticks [98]. Due to SUB’s broad distribution, it was proposed to be a good antigen vaccine candidate. The antigen potential of SUB has previously been investigated in cattle using recombinant proteins, and it was found that SUB can protect (51% efficacy) against ticks. Furthermore, a combination of SUB vaccination and tick autocidal control following SUB gene knockdown in ticks feeding on cattle to control R. microplus, attained 75% efficacy after treatment [99,100]. Furthermore, Shakya and co-workers produced recombinant SUB of R. microplus and used this recombinant protein to immunize bovine. These ruminants were then challenged with R. microplus larvae. In addition, the efficacy of this protein against another geographically different tick strain was assessed. The efficacy of recombinant SUB ranged from 32.7% to 44.1% and indicated a high sequence homology between tick strains from Mexico and India [101]. In another study, recombinant SUB was synthesized as a chimeric protein with MSP1a and subsequently applied to cattle to control R. microplus. Surprisingly, this chimeric protein demonstrated an 81% efficacy [102]. As a result of the successful and promising results of SUB application, the combination of this antigen with Bm86 was tested and assumed to give better results, but the overall efficacy did not support the use of this combination as a vaccine. Although it has been shown that high levels of specific antibodies are activated for each antigen when two antigens are administered simultaneously, they are separated into different formulations and used at different inoculation sites in the animal [103,104]. Formerly known as ligandins, glutathione S-transferases (GSTs) form a family of multifunctional proteins widely distributed in the animal kingdom. These enzymatic proteins play a role in intracellular transport, digestion, production of prostaglandins, detoxification of both endogenous and exogenous substances, and defense against oxidative stress. GST expression levels are increased in organisms when exposed to insecticides and acaricides [105]. A rabbit serum containing polyclonal antibodies against GST from R. microplus reacted with the recombinant GST of H. longicornis and R. appendiculatus, suggesting that the tick GSTs could be a constituent of a universal vaccine that protects against more than one tick species [106]. Based on this preliminary study, Parizi and coworkers (2011) isolated GST from H. longicornis and produced recombinant GST and used this to vaccinate cattle against R. microplus [107]. This provided protection to cattle against R. microplus with an efficacy of 57%. The recombinant GST protein provided partial cross-protective immunity in the host, suggesting that the protein protective capacity of GST is not sufficient, and thus the use of this protein in a single-antigen vaccine would appear not to be effective in preventing tick infestation [107]. In living organisms, 5′-nucleotidases are a widely distributed group of enzymes in various tick species. There are considerable similarities between the 5′-nucleotidase of ticks and the enzymes that are present in vertebrates, and a range of putative functions are carried out by these enzymes, including involvement in the purine salvage pathways [108]. Among ticks, this group of enzymes is found in many different tissues, such as the gut, salivary glands, and ovaries. However, they are most abundant in the Malpighian tubules, particularly on the surface of the Malpighian tubules and ovarian cells. The features of 5′-nucleotidases indicate that they are a potential target for antibodies [109]. Hope et al. investigated 5′-nucleotidases for their possible involvement in host immunization, and they found that injections of recombinant 5′-nucleotidase alone in sheep caused a significant upregulation in anti-nucleosidase antibodies, suggesting that they may be good antigen for the development of a vaccine [104]. However, when the same group of researchers analyzed their functions as antigens in cattle, there was no rise in antibody levels. Therefore, 5′-nucleotidases were not investigated further as antigens for vaccine development. However, a recent study conducted by another group of researchers has found that the level of 5′-nucleotidase/apyrase production increases in O. erraticus after feeding [110]. Furthermore, they suggested that blocking of the apyrase function by host immunization with a recombinant apyrase protein can strongly reduce feeding in O. moubata ticks, demonstrating that 5′-nucleotidases/apyrases are potentially promising candidate antigens for the development of an anti-tick vaccine [110,111]. Tick cement is a mixture of glyco and lipoproteins secreted into the host via tick saliva shortly after attachment to the host, and is a valuable source of tick-derived antigens for vaccine development [112]. In addition to adhering tick mouthparts to the host skin [113], tick cement has been shown to act as a depot for B. burgdorferi sensu lato (s.l.) and the tick-borne encephalitis virus [114,115]. So far, various antigens have been identified and characterized from tick cement that have also been shown to be effective in controlling tick infestation and tick-borne diseases. Truncated constructs of 64P (64TRPs), a 15 kDa cement protein secreted by the salivary glands of Rhipicephalus appendiculatus, showed cross-protection against Rhipicephalus sanguineus and Ixodes ricinus by targeting antigens in the midgut and salivary glands, causing mortality in adults ticks and nymphs. The vaccination of tick-naïve hosts with recombinant 64P significantly reduced the number of nymphal and adult tick infestations, resulting in 48% nymphal and up to 70% adult mortality, with some effects on engorgement weight and egg masses as well [116]. From these results, it appears that this protein is a broad-spectrum vaccine antigen and is effective against adult and immature stages of different tick species, including I. ricinus [100]. This cement antigen performed a dual function (i) as a vaccine in hamster, guinea pig, and rabbit models by impairing attachment and feeding and (ii) by cross-reacting with the “concealed” midgut antigens, ultimately causing the death of engorged ticks [100,117]. This antigen not only boosts antibody titers in response to tick infestation, but also has cross-reactivity with different tick tissues; therefore, it combines the benefits of both “concealed” and “exposed” antigens [118]. Ticks are the most prevalent arthropod parasites that feed on humans and livestock and transmit diseases [19]. Zoonotic diseases account for more than 60% of all infectious diseases affecting humans, and it is estimated that 22.8% of these infections are transmitted by tick vectors [131]. There are also massive economic losses for livestock farmers worldwide due to the diseases vectored by ticks that affect their livestock [132,133]. Therefore, it is relevant to control ticks to reduce the socio-economic burden. The control of ticks has become challenging, as ticks can develop resistance to commercially available acaricides [134,135,136]. Innovative environmentally sound control technologies are needed due to concerns about the safety of acaricides for workers, food, and the environment and the rising costs associated with acaricide discovery, development, and marketing. Vaccines have many advantages over acaricides since they are generally non-toxic, non-polluting, and less expensive compared to chemicals. However, they tend to be very species-specific in nature. The pharmaceutical industry can play a crucial role in supporting research to develop a vaccine that can provide maximum protection to the host and is effective against multiple tick species [133,137]. Vaccine research programs are underway in various countries and the remainder of this article will focus on the progress of new vaccine technologies and on those that are already available (Figure 2). As with chemical applications, vaccine resistance cannot be ignored, and existing vaccines can be modified using sequencing and cloning procedures to isolate new antigens or change existing antigens to restore their efficacy. It is also possible to include two or more unrelated antigens in a single vaccine product to reduce the risk of resistance developing to any single antigen or antigenic determinant. The invention of the DNA vaccine and its use has raised safety concerns; in particular, the possibility of stable transfection of genetic material (DNA) into somatic or even germ cells, which may result in altered gene expression and mutations. An extrachromosomal plasmid-encoding luciferase vector was detectable in skeletal muscle for more than 19 months following intramuscular treatment [138]. Furthermore, intramuscular injection after electroporation greatly increased the overall transfection rate. The chromosomal integration of vector DNA at random sites is related to any increase in the transfection rate [139]. According to these studies, the integration frequency was well below the number of spontaneous gene mutations. However, Manam et al. found that the majority of plasmid DNA administered into the skeletal muscles of different rodents remained at the injection site. Minor fractions were also detected in the gonads, but were not integrated into the genome [140]. Repeated intramuscular application of a luciferase-encoding reporter vector in primates resulted in long-term reporter expression but induced no anti-DNA antibodies [141,142]. In spite of this, it should be noted that the aforementioned and additional safety concerns relating to DNA vaccines should be considered regarding their translation into clinical practice [143]. Over the last two decades, various groups of researchers have focused on developing a DNA vaccine to control tick infestation, and so far, several DNA vaccines have been introduced to immunize hosts [130,144,145]. DNA vaccines, which differ from traditional protein-based vaccines in that they are based on bacterial plasmids that encode antigenic proteins and the transcription is controlled by efficient eukaryotic promoters, have the advantages of a simple design, high stability, and safe administration [143]. In DNA vaccination, the injected plasmid DNA molecules are thought to actively enter the nucleus and remain there lifelong as episomal DNA, generating the protective antigens continuously for as long as the cell is alive [146]. The problem of repeated boosting to maintain a high antibody titer could be solved by the continuous synthesis, processing, and presentation of antigens to T cells in vivo in DNA-vaccinated animals. Furthermore, since a DNA vaccine only contains plasmid DNA and has no contaminating proteins, it seems plausible that receiving multiple or repeated vaccinations would not result in an immune reaction to the vector DNA [147]. The expressed antigen can be presented by MHC class I and II complexes, which can induce CD4+ and CD8+ T cells, stimulating cellular and humoral immune responses, respectively [148]. The evidence came from the study of De Rose et al. [144], in which Merino crossbred sheep were immunized against B. microplus using a DNA vaccine. When a plasmid containing full-length gene sequence of Bm86 was administered either alone or with a plasmid carrying the ovine genes for the cytokines, granulocyte macrophage colony-stimulating factor (GM-CSF) or interleukin (IL)-1beta induced a relatively low level of protection against subsequent tick infestation. In addition, co-vaccination with Bm86 and GM-CSF plasmids resulted in a statistically significant reduction in the fertility of ticks. In all groups injected with the Bm86 DNA vaccine, antibody titers against Bm86 were low. In addition, a low level of antigen-specific stimulation of peripheral blood lymphocytes occurred in these groups. DNA vaccination, however, resulted in a strong subsequent antibody response following a single injection of recombinant Bm86 protein in adjuvant. The production of antibodies, however, did appear to be slightly less effective than following two vaccinations with recombinant proteins. Furthermore, many other researchers investigated the efficacy of DNA-based antigens to immunize hosts against tick infestations. For example, Sayed et al. [149] extracted DNA from Argas persicus eggs and used it to immunize chickens with doses of 200–800 μg DNA/kg chicken body weight. The outcome was supportive, as the feeding success of ticks reduced by 74.64% (50 µg DNA/kg chick body weight) and 89.39% (100 µg DNA/kg chick body weight) when they were exposed to DNA-immunized chicken. In addition, the authors reported that the serum of chickens immunized with DNA has activity against the gut proteins of A. pericus; however, further analysis using other tick species indicated that the serum activity is species specific. The electrophoretic pattern of the immunized chicken serum showed three new protein bands, which were assumed to be involved in the development of the immune defense of the chicken against ticks [149]. Afterwards, many studies focused on antigen-specific DNA vaccination; however, their protection level varied with different types of antigens. It has been shown that BALB/c mice injected with Plasmid pBMC2-encoding antigen Bm86 showed resistance against Boophilus microplus. A higher dose of vaccination induced Anti-Bm86 antibody production and higher interleukin (IL) levels (IL-4, IL-5, and IL-12 (p40)) and interferon-gamma (IFN-γ) levels in the sera of mice immunized with pBMC2. Mice immunized with pBMC2 showed antigen-specific stimulation of splenocytes according to the incorporation of bromodeoxyuridine and IFN g secretion. Application of this vaccine in livestock caused antibody production, suggesting that Bm86 DNA vaccination induces a strong immune response against B. microplus [150]. Another study evaluated the immune protection elicited by recombinant plasmids encoding Paramyosin (Pmy) of H. longicornis (pcDNA3.1(+)-Pmy) in rabbits. The rabbits developed a high level of IgG, suggesting that a humoral immune response is induced by vaccination. Some ticks (27.31%) that fed on the vaccinated rabbits died, whereas the remaining ticks’ average engorgement weight and the oviposition of female adults were reduced by 36 and 39%, respectively. Thus, it seems that a Pmy DNA vaccine can induce an effective humoral immune response however it is provided and partially protect rabbits against H. longicornis infection [151]. Interestingly, a multi-epitope DNA vaccine incorporating both CD4+ and CD8+ cytotoxic T lymphocyte epitopes provided 100% protection to sheep under laboratory conditions against Ehrlichia ruminantium. However, the results were not repeated under field conditions. In this study, pLamp co-administration with MPL via the intramuscular route, in addition to topical application, provided protection to the sheep of up to 60% against ticks by inducing activation of memory T cell responses [152]. A number of other antigens, such as Salp14 and lipocalins, either alone or in combination with other antigens have recently been evaluated as DNA vaccines, which further provides hope of developing a DNA vaccine against ticks [130,153]. It has been shown that the salp14 DNA vaccine elicited erythema at the tick bite site after the tick challenge [153]. Similarly, a lipocalins (LIP) vaccine comprising the recombinant plasmid pcDNA3.1-HlLIP of the LIP homologue from H. longicornis (HlLIP) was applied to immunize a rabbit host. Although this application induced humoral immunity of the host and also influenced the engorgement weight, oviposition, and hatchability of H. longicornis, the efficacy was too low, suggesting that this antigen is not suitable for vaccines as it provides partial protection to the host [130]. Finally, the main objective of developing a DNA vaccine should be to design the vaccine in such a way that it polarizes the immune response of the host towards the Th2 response, since the humoral immune response plays a major role in tick immunity. In cattle that had been vaccinated with B. microplus midgut antigens, the levels of specific IgG1, which are modulated by Th2 cells, were found to correlate with the protection. There is a possibility that if the secretory signal sequence is placed appropriately downstream of the target gene, then the target antigen could be secreted out to the extracellular compartment and induce a greater humoral immune response. It is also likely that the selection of Th2 cells would be favored if they are coinfected with other immunomodulatory genes such as IL4 and IL10. In recent years, many attempts have been made to discover new protective antigens that can be used in the development of an anti-tick vaccine, with numerous improvements. To test the efficacy of the vaccine candidate, recombinant proteins, regardless of whether or not they are associated with other proteins or adjuvants, have been the platform of choice for testing their efficacy through the use of model organisms. Due to the ease with which DNA and mRNA vaccine platforms can be generated, there has been significant developments in the use of genetic (DNA and mRNA) vaccine platforms in recent years [130,145]. An mRNA vaccine encoding a cocktail of tick salivary proteins induced “tick immunity” in guinea pigs, thereby remarkably reducing the transmission of tick-borne Borrelia burgdorferi, the causative agent of Lyme disease (borreliosis). Despite the fact that many tick antigen candidates have been demonstrated to elicit immune responses in a host, it has not yet been possible to replicate robust tick immunity using vaccination. There is a possibility that this may be due to the fact that at different stages of feeding, the composition of salivary proteins in ticks may alter dynamically, possibly to manage host internal changes. This information was provided in a recent study, in which a group of researchers identified and rationally selected 19 salivary proteins of the black-legged tick I. scapularis, which is a common vector for Lyme disease in humans. They engineered nucleoside-modified mRNAs that encode for these proteins. In order to produce the mRNA–LNP vaccine 19ISP (19 ixodes salivary proteins), these were encapsulated in equal amounts in lipid nanoparticles (LNPs). To evaluate the impact of the vaccine on the feeding behavior of I. scapularis, guinea pigs were immunized intradermally three times in 4-week intervals, which resulted in robust antibody responses to at least ten of the encoded antigens. In the next step of the experiment, the animals were challenged with uninfected I. scapularis nymphs. The animals that had been vaccinated developed considerable erythema within 24 h. Furthermore, ticks on animals that had been vaccinated fed poorly and began to detach by 48 h, with 80% of ticks detached from vaccinated animals after 96 h, compared with 20% on animals that had not been vaccinated. To further examine whether the altered feeding behavior affects the transmission of pathogens, B. burgdorferi-infected I. scapularis nymphs were placed on guinea pigs that were vaccinated either with 19ISP or with an mRNA vaccine encoding firefly luciferase. Each of these animals received three ticks that were infected. Considering that humans are likely to remove a tick that causes erythema-related itching, the ticks were detached in a double-blind manner as soon as redness appeared. A total of 46% of the control animals were infected with B. burgdorferi three weeks after the challenge, whereas none of the vaccinated animals were infected with this pathogen. A gene expression analysis has shown that the vaccine activated several immune pathways, including T and B cell receptor, chemokine, FcεRI, and IL-17 signaling, as well as natural killer cell-mediated toxicity. Moreover, bite site analyses also showed that the vaccine had induced T cell responses [154]. Concurrently, the same group of researchers used Salp14 as a model antigen to examine tick immunity using mRNA lipid nanoparticles (LNPs), plasmid DNA, or recombinant protein platforms [153]. In this study, vaccination including the nucleoside-modified mRNA lipid nanoparticles encoding (mRNA-LNPs) Salp14 was delivered intradermally, with two boosts every 4 weeks. The development of Salp14-specific antibodies was compared among the different immunization strategies. Salp14 mRNA immunization was the platform that induced the strongest humoral response compared to DNA and protein vaccination. Guinea pigs immunized with the salp14 mRNA elicited the most robust, and intense erythema was observed at the bite site in all the immunization groups; however, it did not affect the rate of tick detachment and did not alter engorgement weights [153]. A tick vaccine should induce erythema to be effective, and one approach to change later aspects of tick feeding, including attachment and engorgement, is to use a vaccine that contains several salivary tick antigens [154]. Therefore, it seems that immunization with nucleoside-modified mRNA-LNP salp14, which can be used as a potential vaccine candidate, can lead to higher antibody titers and an earlier and higher degree of redness than immunization with either DNA or protein, which suggests that Salp14 could be a good candidate for a vaccine, either alone with optimizations or in combination with other candidate antigens [154]. On the whole, it appears that a multivalent mRNA vaccine may have the ability to elicit tick resistance in laboratory animals such as guinea pigs and to prevent tick infestation and tick-borne infection, probably by limiting the time duration of tick feeding on their host. It has also been suggested that a mRNA–LNP formulation which enables slow, continuous antigen delivery, may mimic natural tick bites. If this strategy can be translated to humans, it would be the first vaccine that does not directly target a pathogen or microbial target, but instead its vector. Moreover, since anti-tick vaccines are still being developed to assist humans in the prevention of the transmission of tick-borne diseases, the strategy of immunization and the selection of antigens for immunization need to be taken into consideration. Some protein-based vaccines are commercially available and have been shown to be effective. A vaccine program was first started in the 1970s when researchers began to experiment with two different types of vaccine formulations in order to immunize the host against the tick (D. andersoni) at the time. The first included antigens obtained from the gut and ovary, while the second included all the internal organs extracted from semi-engorged D. andersoni females. This study discovered that antibody-mediated immune responses are activated against tick intestinal tissue when the cattle host is inoculated with extracts obtained from adult R. microplus females [155]. This initial study to evaluate the effectiveness of vaccine formulation encouraged researchers around the globe to focus on the development of a vaccine for the control of ticks and tick-borne diseases. Thus, in the 1980s, two separate groups of researchers carried out the first scientific investigations using vaccine formulations to analyze the immune response of bovines against R. microplus [156]. Following the above studies, it was found that a tick gut-associated glycoprotein can induce immunoprotection in the host [157]. In a subsequent study, the same research group isolated a glycoprotein with a molecular weight of 89 kDa, which was named Bm86 and reported to be associated with the gut cells of R. microplus [158,159]. The Bm86 recombinant protein was produced on a large scale using a yeast expression system. So far, only the Bm86-based vaccine is commercialized with different brand names, for example, it is sold in Australia with the TickGARD® brand name and in Cuba under Gavac® [160,161]. These vaccines are largely used in different countries to reduce the tick pressure on cattle. It has been shown that the use of these vaccines can reduce the tick population by up to 74% and their overall efficacy ranges from 51% to 91%, which varies with the tick population and nutritional condition of the cattle [160,161,162,163]. There is evidence that some Columbian, Mexican, and Brazilian R. microplus tick strains exhibit lower overall efficacy compared to Cuban and Australian R. microplus tick strains, and even the Argentinian R. microplus strain A seems to be resistant to vaccination with Bm86 [34,164]. Further analysis was conducted on the variation in the efficacy of the Bm86 vaccine on populations of the same tick species in different parts of the world, and it was concluded that different populations of ticks most likely have a polymorphism in Bm86 antigen genes in terms of the amino acid sequence of the gene, and this is the main reason that existing Bm86-based vaccines are not so efficacious. For example, there was a polymorphism in the gene homologous to Bm86 (designated as Bm95) identified in tick populations in Argentina, resulting in differences in the sequence of the Bm86 between tick populations such as those found in Cuba and Australia, which may explain why the Bm86 vaccine was not as effective against the Argentine tick [34]. Considering the resistance problems of the Bm86 vaccine, researchers produced a recombinant Bm95 vaccine that has proven to be highly effective, with an overall efficacy of 89% in Cuba and Argentina and 81% in India in terms of reducing tick infestation [34,102,120,165]. Besides the above-mentioned commercial vaccine and its efficacy trial, many other studies have focused on further improving the efficacy of the Bm86-based vaccine. Some recent studies have synthesized peptides, including SBm4912, SBm7462®, and SBm19733, which were obtained from Bm86, and also produced an rSBm7462® recombinant peptide, and analyzed their efficacy. The percentage efficacy of these peptides ranged from 35.87% to 81.05%, suggesting that these peptides, in particular, SBm7462® and rSBm7462®, play a crucial role in inducing host immunity and can be commercialized as they are highly effective in terms of reducing tick infestation [121,122]. Furthermore, in an effort to improve the Bm86 recombinant protein vaccine effectiveness, recently, Lapisa S.A. has introduced a Bm86-based Bovimune Ixovac® vaccine in Mexico. However, this vaccine has not been studied in terms of its effectiveness against ticks; therefore, studies are needed to determine its effects on different tick populations to determine its efficacy. A Bm86 homologue-based vaccine (TickGard) appears to be suitable, as this vaccine has a broad application and can trigger cross-reactive antibodies in different tick species, such as Rhipicephalus sanguineus, Hyalomma anatolicum anatolicum, Rhipicephalus (Boophilus) decoloratus, Rhipicephalus (Boophilus) annulatus, and Hyalomma dromedarii [166,167,168]. However, this vaccine has been shown to be unable to induce cross-reactive protection in some other tick species (e.g., Rhipicephalus appendiculatus, Amblyomma variegatum, and Amblyomma cajennense) [169,170]. It is interesting to note that the Bm86 vaccine has a 100% efficacy against R. annulatus, resulting in greater efficacy than the reported efficacy of the homologous vaccine with R. microplus. The reason for this might be due to physiological factors (e.g., less blood engorgement and lower levels of protease activity in the body) or tick genetic factors. It is possible that these factors influence BM86 protein levels or tick physiological processes such as feeding and protein degradation, leading to more efficient antibody–antigen interactions [171]. Bm86 vaccination provides excellent protection against R. microplus ticks, but it is challenging to extrapolate these experiences to an Ixodes tick vaccine. In contrast to I. ricinus and I. scapularis, R. microplus is a single host tick that feeds exclusively on cattle [168]. It also has a brief life cycle, does not molt and finds a new host when the blood meal is finished. The efficacy of the Bm86 vaccine was investigated in cows that had been exposed to R. microplus tick larvae, and measurements were made of the parameters relating to tick immunity on the engorged adult females that dropped off following vaccination. Thus, the measured protection is the sum of the influence on two molting periods and three tick stages. It has been shown for R. microplus that Bm86 vaccination causes damage and subsequently reduces the engorgement weight in adult female ticks [172]; nevertheless, the relative influence of Bm86 vaccination on the immature life stages of R. microplus is not precisely known. Bm86 homologues have also been isolated and identified from Ixodes ticks. I. ricinus contains two homologues of Bm86, Ir86-1, and Ir-86-2, and I. scapularis also has two homologues of Is86-1 and Is86-2 [173]. A subsequent study explored that vaccination of recombinant Ir86 proteins although enhanced the serum IgG titers against recombinant Ir86 proteins; however, the antibodies were not able to protect rabbits against I. ricinus challenge; neither the number of attached ticks nor tick weights were reduced [174]. Therefore, vaccination against Bm86 homologues in Ixodes is not considered to be an effective approach to control Ixodes ricinus populations, despite the fact that Bm86 vaccination has a clear effect against R. microplus. Even though the Bm86 vaccine has shown considerable success, it is critical to understand that the vaccine is unlikely to replace acaricides because it lacks the “knock-out effect” associated with acaricides. In spite of this, field experience has shown that the use of Bm86 considerably reduces the requirement of applying acaricide treatments in the field. For example, Cuba’s tight regulation of its tick control program led to a reduction in the amount of acaricide used in the country by 87%, which is comparable to the results of a recent study conducted in Venezuela [161,175,176]. Furthermore, the use of the Bm86 vaccine has also considerably decreased tickborne diseases, including Bovine anaplasmosis and Bovine babesiosis. The application of this vaccine has also enhanced the productivity of livestock, e.g., cattle, and consequently reduced the economic losses of farmers [160]. The above aspects of Bm86 vaccination show that it is a highly cost-effective method compared to chemical applications in dealing with tick infestations. As such, this vaccine may prove to be highly useful in reducing tick-borne diseases as well as in improving the management of tick outbreaks on livestock farms to decrease tick-borne diseases. Ticks feed on blood for development, growth, and reproduction, and they are responsible for the transmission of various tick-borne diseases. Ixodes ticks, for example, transmit a large number of pathogens, including bacteria, protozoa, and viruses. It is important to note that anti-tick vaccines reduce tick infestation and prevent pathogen transmission, and in addition are safer than chemical control, which may have negative side effects. A number of novel antigens from a variety of tissues/organs have been identified and their efficacy has been examined in laboratory animals, which has led to important progress towards developing a vaccine against ticks with no reported side effects. Vaccines based on the Bm86 protein have been commercialized in various countries, and their use against R. microplus has shown that vaccination against ticks can be efficiently used. However, Bm86-based vaccines are not equally effective against other tick species, such as Ixodes ticks. It has been shown that vaccination with the Bm86 homologue of I. ricinus does not have any effect on tick feeding [174]. Additionally, because R. microplus only feeds on one host, larvae were used to challenge cows, which resulted in fully engorged adult female ticks, which not only reduced the number of ticks but also had a significant impact on all three life stages of the tick. In contrast to R. microplus, Ixodes ticks change hosts throughout their life cycle, and therefore Ixodes tick vaccination requires the effective prevention of attachment and/or feeding of ticks during one blood meal on one host. Nonetheless, vaccination against Ixodes ticks seems possible and realistic. It is thus important to note that cross-protection of the host can be a challenging task with this type of vaccine. There are some other proteins, besides Bm86, that might also have therapeutic potential as immunosuppressive or anticoagulant agents [39,61]. Recent advances in genomics and proteomics have enabled us to discover novel antigens and employ molecular techniques to manipulate identified proteins and test new vaccines considerably more quickly and cost-effectively than in the past. DNA vaccination is also an excellent option; however, in general, this type of vaccination can only lead to low levels of antigen expression and limits the non-professional antigen-presenting cell activating CD4+ T helper cells via the MHC class II pathway [177]. However, DNA vaccination not only provides significant protection to the host but is also considered to provide cross-protection against ticks if it is followed by a chimeric vaccine or recombinant protein vaccination [178]. Furthermore, mRNA-LNPs may help in the elicitation of erythema at the tick bite site, which is one of the most important early indicators of acquired tick resistance. mRNA-LNPs containing tick genes are a useful platform for the development of vaccines that can potentially prevent selected tick-borne diseases [153,154]. Both DNA and mRNA vaccination also seem to be effective strategies and there is future hope that a mRNA or DNA vaccination for the control of tick infestation and tick-borne diseases may be developed and also provide cross-protection. However, so far no vaccine has been commercialized, indicating that further studies are needed to determine the efficacy of increasingly more antigens for their use to develop a DNA or mRNA vaccine. The identification and characterization of novel tick vaccine candidates can prevent tick feeding and pathogen transmission. Using these antigens in vaccines for domesticated animals and wildlife, let alone humans, remain a challenge.

PMC10003030

36786037

Kasra Moeinabadi‐Bidgoli,Malihe Rezaee,Nikoo Hossein‐Khannazer,Amirhesam Babajani,Hamid Asadzadeh Aghdaei,Mandana Kazem Arki,Siamak Afaghi,Hassan Niknejad,Massoud Vosough

Exosomes for angiogenesis induction in ischemic disorders

14-02-2023

angiogenesis,exosomes,hypoxia,microRNA,physiology,regenerative medicine,stem cells

Abstract Ischaemic disorders are leading causes of morbidity and mortality worldwide. While the current therapeutic approaches have improved life expectancy and quality of life, they are unable to “cure” ischemic diseases and instate regeneration of damaged tissues. Exosomes are a class of extracellular vesicles with an average size of 100–150 nm, secreted by many cell types and considered a potent factor of cells for paracrine effects. Since exosomes contain multiple bioactive components such as growth factors, molecular intermediates of different intracellular pathways, microRNAs and nucleic acids, they are considered as cell‐free therapeutics. Besides, exosomes do not rise cell therapy concerns such as teratoma formation, alloreactivity and thrombotic events. In addition, exosomes are stored and utilized more convenient. Interestingly, exosomes could be an ideal complementary therapeutic tool for ischemic disorders. In this review, we discussed therapeutic functions of exosomes in ischemic disorders including angiogenesis induction through various mechanisms with specific attention to vascular endothelial growth factor pathway. Furthermore, different delivery routes of exosomes and different modification strategies including cell preconditioning, gene modification and bioconjugation, were highlighted. Finally, pre‐clinical and clinical investigations in which exosomes were used were discussed.

Exosomes for angiogenesis induction in ischemic disorders Ischaemic disorders are leading causes of morbidity and mortality worldwide. While the current therapeutic approaches have improved life expectancy and quality of life, they are unable to “cure” ischemic diseases and instate regeneration of damaged tissues. Exosomes are a class of extracellular vesicles with an average size of 100–150 nm, secreted by many cell types and considered a potent factor of cells for paracrine effects. Since exosomes contain multiple bioactive components such as growth factors, molecular intermediates of different intracellular pathways, microRNAs and nucleic acids, they are considered as cell‐free therapeutics. Besides, exosomes do not rise cell therapy concerns such as teratoma formation, alloreactivity and thrombotic events. In addition, exosomes are stored and utilized more convenient. Interestingly, exosomes could be an ideal complementary therapeutic tool for ischemic disorders. In this review, we discussed therapeutic functions of exosomes in ischemic disorders including angiogenesis induction through various mechanisms with specific attention to vascular endothelial growth factor pathway. Furthermore, different delivery routes of exosomes and different modification strategies including cell preconditioning, gene modification and bioconjugation, were highlighted. Finally, pre‐clinical and clinical investigations in which exosomes were used were discussed. Ischemic disorders are the result of insufficiency in blood supply, leading to limited oxygen and nutrient transfer. Ischemia could involve most of the organs/tissues including the heart, brain, peripheral vessels, limbs, skin, retina, intestine and kidney. , Ischemic diseases are the leading cause of disability and mortality which impose an enormous burden on human healthcare systems worldwide. Although current therapies for reperfusion including thrombolytic drugs, using vasodilator, , surgical bypass, and endovascular intervention, have shown significant benefits in the treatment of the ischemic damage, however, these therapies often are not optimal for remodelling vascular beds, thereby ischemic diseases remain the leading cause of long‐term disability. In addition, reperfusion has been found to be able to induce subsequent injury in ischemic tissue, a phenomenon termed ischemia–reperfusion (I/R) injury, which is a critical therapeutic challenge. Besides, ischemia‐induced and I/R‐mediated injuries could lead to fibrosis and dysfunction of the damaged tissues in a long‐time period. , Altogether, researchers have leaned towards finding the therapeutic strategies which could stimulate and enhance the regeneration of the ischemic tissues. Ischemic disorders are contributed by vascular dysfunction, endothelial cell function impairment, vascular integrity deterioration and enhanced expression of adhesion molecules and inflammation mediators. It is estimated that more than 500 million people worldwide will benefit from the treatment of the ischemic disorders. Cell‐based therapies are a revolutionary approach that have raised hopes for the treatment of ischemic disorders through various mechanisms such as angiogenesis induction, apoptosis inhibition and blocking inflammatory process. Stem cells are the most frequently used cells in cell‐based therapies, with properties including differentiation capacity, self‐renewal ability and secretion of beneficial paracrine factors. Stem cells have been shown to induce angiogenesis and provide blood supply in the ischemia‐damaged organs. , Although cell‐based therapies have shown promising results for treating various ischemic diseases, they are associated with multiple hindrances including low cell survival in the host's tissue and high expenses which emphasize the need for improving cell‐based therapy strategies. It has been shown that most transplanted cells could not survive more than 4 days post‐transplantation. It has been reported that <1% of systemic administered mesenchymal stem cells (MSCs) differentiate into the functional cells in the target tissue and a vast majority of them are trapped in the lung and liver. It is believed that transplanted cells exert their therapeutic effects and participate in angiogenesis via their paracrine activity. Extracellular vesicles (EVs), main agents in cellular paracrine activity, are micro‐ and nano‐sized vesicles which contain bioactive agents and are released by roughly all cells through fusion of multivesicular bodies with the plasma membrane and subsequent release to the intracellular space. Exosomes are a subgroup of EVs with an average size of 30–150 nm. , , Exosomes are considered long‐range intercellular communication tools that transfer various molecules including proteins, DNA, long non‐coding RNAs (lncRNAs), message RNAs (mRNAs) and microRNAs (miRs) to the recipient cells. Exosomal content represents the conditional and functional situation of the parent cell. , They easily pass vascular barriers (such as blood brain barrier) due to the nanoscale size and do not have any risk of tumorigenicity formation. Exosomes possess low immunogenicity as they lack the expression of major histocompatibility complex (MHC). Exosomes have a long‐term storage capacity and could be stored at −20°C for months while their biological activity is preserved. , Exosomes are used as ‘cell‐free therapy’ agents as they are responsible for the vast majority of cell‐therapy‐induced beneficent outcomes. Exosomes exert anti‐apoptotic, anti‐fibrotic, cell differentiation, immunomodulatory and pro‐angiogenic effects. , It has been reported that the destruction of exosomes by ultrasonication abolishes cardiac progenitor cells (CPCs) angiogenic capacity, demonstrating the importance of exosomes in angiogenic induction. It has been reported that the beneficial effects of endothelial progenitor cells (EPCs) in endothelial repair may greatly depend on their paracrine impacts in which exosomes play a central role in. Better performance of CPCs transplantation compared with cardiosphere‐derived cells (CDCs) transplantation in the treatment of myocardial infarction (MI) is mostly due to the greater angiogenesis induction of the CPC‐derived exosomes (two‐fold higher) and higher angiogenic capacity of miRNA cargo of CPC‐derived exosomes. In this review article, we discussed exosomes and their role in angiogenesis and highlighted recent application of them in ischemic disorders in preclinical models and clinical studies. Angiogenesis is a complex biologic process attributed to the formation of new vessels in which a variety of cells, mediators and signalling pathways are involved. The central cells involved in the angiogenesis process are endothelial cells (ECs) and pericytes, with their angiogenesis‐promoting dynamics, behaviour and signalling pathways. These cells participate in four fundamental steps of angiogenesis: (a) basement membrane and surrounding extracellular matrix (ECM) degradation, (b) EC proliferation, (c) EC migration and (d) formation of the tubular structures and sprouting. , Besides the angiogenesis‐associated cells, several pro‐angiogenic factors such as vascular endothelial growth factor (VEGF), angiopoietins, fibroblast growth factors (FGFs), platelet‐derived growth factor (PDGF) and hypoxia inaudible factor‐1α (HIF‐1α) play crucial roles in neovascularization. , , , , Many prominent angiogenesis‐associated factors such as proteins and nucleic acids are incorporated in exosomes, released by special cells and delivered to the recipient cells. Therefore, exosomal content and original cell types impressively affect the angiogenic potential of exosomes. Exosomes promote angiogenesis by transferring their content into recipient cells. The transferred molecules exert biochemical alterations in the recipient cell, leading to enhanced angiogenic activity. , Exosomes are considered ‘mini‐cells’ because they contain multiple bioactive molecules according to their parent cell. Considering the formation process of exosomes, their content is categorized into surface molecules and inner content. Same as a typical cell, the exosomal membrane consists of lipids, carbohydrates and proteins. however, cell‐type‐specific proteins are a wide range of exclusive proteins mediating various therapeutic and pathologic effects of exosomes. Exosomes' pro‐angiogenic content includes a variety of surface and internal molecules. More prominently, the internal proteins such as VEGF, angiopoietin‐1 (Ang‐1) and heat shock proteins (HSPs), as well as nucleic acids including miRNAs, lncRNAs and circular RNAs (circRNAs) participate in angiogenesis. , It is noteworthy that the internalization of exosomes by recipient cells is dependent on multiple factors, including exosome type and recipient cell type. For instance, it has been demonstrated that ECs and cardiac fibroblasts ingest MSC‐derived exosomes with higher amounts compared with cardiomyocytes. Cardiomyocytes uptake EC‐derived exosomes to a greater extent compared with MSC‐extracted exosomes, demonstrating the importance of exosome type. This phenomenon may be partially due to connexins and integrins inserted in the exosomal membrane from different cell types. After administration of exosomes and subsequent entrance to systemic circulation, exosomes are distributed into tissues. Following cellular uptake, the endocytic pathway results in breaking down of the exosomal cargo into their metabolites. Kidneys, liver, spleen and lungs which possess a mononuclear phagocyte system, closely contribute to clearance of exosomes from circulation. In vivo tracking of exosomes after administration by using sensitive, efficient and biocompatible methods and imaging techniques are highly desired to evaluate the pharmacokinetics of exosomes. In this regard, pharmacokinetic analysis of gLuc‐lactadherin labelled exosomes by bioluminescent imaging after intravenous injection demonstrated rapid clearance of exosomes with a half‐life about 2 min. Also exosomes were mainly distributed to the liver followed by the lungs. Consistently after 4 h of IV injection of I125 labelled exosomes approximately 1.6%, 7% and 28% of the radioactivity was detected in the spleen, lungs and liver, respectively. Exosomal content and composition depend on the original cell and the environmental condition. Various cells, including stem cells, mature cells, immune cells and tumour‐associated cells, have been used to isolate exosomes for therapeutic angiogenesis. Stem cell‐derived exosomes could significantly boost angiogenesis and re‐establish blood supply when administered to ischemic areas. Several stem cell sources have been administered regarding pro‐angiogenic properties, such as MSCs, induced pluripotent stem cells (iPSCs), and adult progenitor cells. It is of crucial importance to note that some factors such as miR‐20 or VEGF receptor‐1 (VEGFR‐1) demonstrate both pro‐angiogenic and anti‐angiogenic properties depending on the type of the recipient cell, dosage and microenvironment. , , , The pro‐angiogenic content of exsosomes in addition to common cell sources is shown in Table 1. Mechanism of exosome‐induced angiogenesis could be categorized into three major activities: inducing pro‐angiogenic factors and pathways, preserving the vascular network and regulating the inflammatory response. Exosomes could enhance angiogenesis through different mechanisms, including (1) direct transfer of pro‐angiogenic factors into recipient cells, (2) promoting the expression of pro‐angiogenic factors in the recipient cell, and (3) Interfering with the activity of angiogenesis inhibitors: Exosomes transfer pro‐angiogenic factors directly into recipient cells. These factors can influence angiogenesis directly or through regulating central angiogenesis‐related factors. It has been shown that MSC‐extracted exosomes directly transfer Ang‐1 and its receptor, Tie‐2, two central pro‐angiogenic factors, to ECs in order to promote their angiogenesis ability. Urine‐derived stem cell (USC)‐derived exosomes contain angiogenesis‐related factors, including transforming growth factor‐β1 (TGF‐β1), angiogenin and VEGF, that contribute to exosome‐induced glomerular vascular regeneration and prevention of diabetic nephropathy. , Some exosomal contents indirectly promote angiogenesis by enhancing the expression of pro‐angiogenic factors. It has been shown that induced vascular progenitor cell (iVPC)‐extracted exosomes promote cerebral microvascular endothelial cells' (CMVECs') angiogenic capacity through pentraxin 3 (PTX3) and insulin‐like growth factor‐binding protein‐3 (IGFBP3) transfer. PTX3 encourages angiogenesis via upregulating VEGF receptor2 (VEGFR2), while IGFBP3 enhances angiogenesis through IGF‐1R signalling. CPC and bone marrow mesenchymal stem cell (BM‐MSC)‐derived exosomes improve ECs' angiogenic activity via transferring extracellular matrix metalloproteinase inducer (EMMPRIN) into the ECs which enhance angiogenesis via activation and upregulation of VEGF and matrix metalloproteinase‐9 (MMP‐9). Furthermore, EMMPRIN enhances VEGF signalling via acting as a VEGFR2 co‐receptor. It has been observed that exosomes derived from renal cell carcinoma (RCC) cells are enriched with carbonic anhydrase 9 (CA9), a downstream target of HIF‐α, and promote human umbilical vein endothelial cell (HUVEC) migration and tube formation through CA9‐mediated MMP‐2 upregulation. Exosomes can alter gene expression of the pro‐angiogenic pathways in the angiogenesis‐related cells. Several angiogenesis‐related pathways are affected by non‐coding RNAs, including extracellular signal‐regulated protein kinase 1/2 (ERK1/2), phosphoinositide 3‐kinase/protein kinase B/endothelial nitric oxide synthase (PI3K/Akt/eNOS), PI3K/Akt/mammalian target of rapamycin (PI3K/Akt/mTOR), signal transducer and activator of transcription 3 (STAT3), mitogen‐activated protein kinase (MAPK), nuclear factor erythroid 2‐related factor 2 (Nrf2), and nuclear factor‐κB (NF‐κB), resulting in upregulation of pro‐angiogenic factors. It has been shown that miR‐126‐enriched‐exosomes derived from BM‐MSCs promote I/R‐injured ECs' tube formation by activating PI3K/Akt/eNOS signalling pathway. STAT3 is a master transcription factor in the angiogenesis process as it promotes angiogenesis by inducing the expression of VEGF, basic FGF (bFGF), MMP‐2 and MMP‐9. It has been demonstrated that BM‐MSC‐derived exosomes are enriched in STAT3 and promote HUVEC angiogenic capacity through STAT3 upregulation. Mitogen‐activated protein kinase is an upstream regulator of ERK that promotes EC proliferation and angiogenic capacity via increasing ERK expression and phosphorylation. It has been shown that miR‐21‐5p, enriched in USC‐derived exosomes, enhances HUVECs angiogenic activity by boosting MAPK signalling and VEGFR‐1 expression. It has been reported that umbilical cord blood (UCB) derived EPC‐isolated exosomes improve ECs' proliferation, migration and tube formation via activating ERK1/2 signalling. It has been discussed that promoting the entry of cells into S‐phase of cell cycle via ERK1/2 activation by EPC‐derived exosomes may induce angiogenesis. In addition to ERK1/2, upstream genes including FGF‐2, interleukin 6 (IL‐6) and IL‐8, and some downstream genes, including inhibitor of DNA binding 1 (ID1), cyclooxygenase‐2 (Cox‐2), VEGF, c‐Myc and cyclin D1 were also considerably upregulated. Tube formation capacity of EPCs is impaired during MI due to C‐X‐C chemokine receptor type 7 (CXCR7) suppression. CXCR7 is a receptor of C‐X‐C motif chemokine 12 (CXCL12); CXCL12, also known as SDF‐1, is a downstream target of Nrf2 and regulates EPCs migration to the ischemic region. Silent mating type information regulation 2 homologue 1 (SIRT1) activates Nrf2; It has been shown that exosomes derived from SIRT1‐overexpressing adipose‐derived MSCs (AD‐MSCs) notably enhance EPCs' migration and tube formation through Nrf2 upregulation and subsequent CXCL12/CXCR7 signalling activation in EPCs. , Nuclear factor‐κB improves angiogenesis through induction of VEGF expression. It has been reported that myocyte‐derived exosomes stimulate the NF‐κB pathway by inducing superoxide dismutase 2 (Sod2), probably via miR‐130a transfer. Sod2 is a mitochondrial enzyme that protects the cell from oxidative stress via converting O2 − into H2O2. , It has been shown that USC‐derived exosomes could promote angiogenesis via deleted in malignant brain tumours 1 (DMBT1)‐mediated activation of PI3K/Akt/mTOR signalling and inducing VEGF expression. 3 Some pro‐angiogenic effects of exosomes are impeding the activity of the angiogenesis‐inhibitor factors and pathways. Non‐coding RNAs target some important angiostatic mediators and pathways, including phosphate and tensin homologue (PTEN), thrombospondin 1 (TSP‐1), delta‐like 4 (DLL4), E2F transcription factor 2 (E2F2), ataxia telangiectasia mutated (ATM) gene, protein tyrosine phosphatase non‐receptor type 9 (PTPN9), transient receptor potential cation channel subfamily M member 7 (TRPM7), receptor tyrosine kinase ligand ephrin‐A3 (EFNA3), Serpin E1 and homeobox proteins growth arrest A5 (HoxA5). Hampering these mediators and pathways finally results in the enhanced expression of angiogenic factors such as VEGF, Ang‐1 and HIF‐1α, as well as the upregulation of cell cycle proteins. Considering VEGF as a crucial pro‐angiogenic factor, preventing the inhibitors would increase the angiogenesis rate. PTEN is a potent angiostatic gene that suppresses the angiogenesis process by inactivating PI3K/Akt signalling and upregulating the TSP‐1 anti‐angiogenic factor. It has been reported that miR‐221‐3p of BM‐MSC‐derived exosomes promotes ECs' VEGF levels and angiogenesis through suppressing PTEN expression and subsequent activation of the Akt/eNOS/VEGF pathway. Through oxygen–glucose deprivation (OGD), miR‐29b‐3p and Akt are downregulated, and PTEN is overexpressed in neurons and brain microvascular endothelial cells (BMECs). It has been shown that BM‐MSC‐derived exosomes transfected with miR‐29b‐3p by lentiviral transfection could promote angiogenesis of OGD BMECs via PTEN suppression, VEGF‐A and VEGFR‐2 upregulation and induced Akt expression in rat model of ischemic stroke. It has been reported that exosomal miR‐17‐5p extracted from nasopharyngeal carcinoma cells improves ECs' angiogenic activity via suppressing bone morphogenetic protein (BMP) and activin receptor membrane‐bound inhibitor (BAMBI) expression, which abrogates inhibitory effect on Akt/VEGF‐A signalling, resulting in Akt/VEGF‐A upregulation. PTPN9 is an anti‐angiogenic factor, hampering angiogenesis via inhibiting Akt and ERK phosphorylation and subsequently downregulating VEGFR‐2 expression. It has been shown that miR‐126‐3p and miR‐126‐5p improve HUVECs proliferation, migration and tube formation via PTPN9 repression. MiR‐210, the primary miRNAs for angiogenesis induction under hypoxic stress, upregulates VEGF and VEGFR‐2 and hampers the EFNA3 activity, leading to augmented angiogenesis induction in ECs. MiR‐130a promotes ECs' tube formation through VEGF and VEGFR‐2 upregulation and hampering anti‐angiogenic factors, including growth arrest homeobox (GAX) and HoxA5. MiR‐143 enhances angiogenesis via Serpin E1 suppression; Serpin E1, also named plasminogen activator inhibitor‐1 (PAI‐1), hampers angiogenesis through VEGF/VEGFR2 signalling downregulation. Jagged1/Notch signalling is an angiostatic pathway, inhibiting VEGFR‐2 expression via hairy and enhancer of split 1 (HES1). It has been elucidated that miR‐199b‐5p promotes HUVEC migration, proliferation and tube formation via Jagged1/Notch repression and subsequent VEGFR‐2 upregulation. RAF1/ERK1/2 signalling enhances angiogenesis via triggering EC proliferation. It has been shown that miR‐126 boosts angiogenesis through silencing sprouty‐related EVH1 domain containing 1 (SPRED1) and phosphoinositide‐3‐kinase regulatory subunit 2 (PIK3R2), which results in RAF1/ERK1/2 upregulation and subsequent VEGF enhanced expression. , As with other proangiogenic factors, enhancing angiopoietin and HIF‐1α has a desirable effect on angiogenesis. It has been revealed that miR‐21‐5p, which is abundant in endometrium‐derived MSC (EnMSC)‐extracted exosomes, enhances angiopoietin levels in HUVECs via PTEN suppression and subsequent increased Akt phosphorylation, which leads to VEGF upregulation. DLL4 is an angiostatic factor that suppresses angiogenesis by prohibiting the formation of endothelial tip cells. It has been revealed that miR‐125a promotes HUVECs proliferation, migration and tube formation by suppressing the DLL4 expression and inducing the expression of Ang‐1 and VEGFR‐2. , It has been shown that AD‐MSC‐derived exosomes promote ECs angiogenic capacity under OGD by miR‐181b‐mediated TRPM7 downregulation, leading to increased HIF‐1α expression and decreased expression of tissue inhibitor of metalloproteinase‐3 (TIMP‐3) expression. MiR‐135b, which is abundant in hypoxic multiple myeloma cell‐derived exosomes, increases angiogenesis via hampering factor‐inhibiting HIF‐1 (FIH‐1). FIH‐1 silencing results in HIF‐1α overexpression, which leads to overproduction of VEGF and Ang‐1. AD‐MSC‐extracted exosomes promote EC migration and tube formation via miR‐31‐mediated FIH1 inhibition which enhances HIF‐1α transactivation. HIF‐1α is able to promote EPCs migration to the ischemic areas via CXCL12/CXCR4 enhanced expression and creating a concentration gradient which all lead to improved EPC migration angiogenesis. Prolyl hydroxylases (PHDs) are enzymes that degrade HIF‐1α in a normoxic condition. It has been reported that miR‐23a promotes angiogenesis via hampering PHD1 and PHD2 activity, resulting in enhanced HIF‐1α levels. Finally, non‐coding RNAs impress the cell cycle by altering the cell cycle regulators. It has been shown that M2 macrophage‐derived exosomes which enriched in miR‐155‐5p and miR‐221‐5p promote ECs migration, proliferation and tube formation through E2F2 anti‐angiogenic factor downregulation. It has been shown that EC‐derived exosomes contain high amounts of miR‐214 that suppresses the expression of ATM in recipient endothelial cells. ATM induces senescence and cell cycle arrest, and its downregulation leads to the enhanced angiogenic capacity of endothelial cells. Taken together, exosomes could be an ideal tool for angiogenesis induction in ischemia‐damaged tissues as they transfer pro‐angiogenic factors into ECs and boost angiogenesis pathways and inhibit angiostatic signalling. In Figure 1, molecular mechanism underlying exosomess' pro‐angiogenic activities are summarized. Ischemia/reperfusion injury, senescence and excessive reactive oxygen species (ROS) disrupt regeneration of vascular networks and need well‐management to increase the stability and functionality of vessels. Studies have suggested that exosomes improve vascular network stability by regulating harmful processes in ischemic tissues. Ischemia/reperfusion injury results in the cell metabolism shifting to anaerobic metabolism, the adenosine triphosphate (ATP) levels and the intracellular pH reduction, and finally, apoptosis. ECs of newly generated vessels undergo apoptosis through I/R injury, which diminishes the angiogenic capacity needed for ischemic tissue recovery. Exosomes have shown promising results in maintaining cell viability via activating cell survival pathways, especially PI3K/Akt, and decreasing apoptosis promoters such as p53 to guarantee tissue rehabilitation. PI3K/Akt pathway is among the most critical survival signalling that prevents apoptosis through various mechanisms, including upregulation of B‐cell lymphoma 2 (Bcl‐2), B‐cell lymphoma‐extra‐large (Bcl‐xL) and survivin anti‐apoptotic factors and downregulating Bcl‐2‐associated X protein (BAX) and Bcl‐2‐associated agonist of cell death (BAD) pro‐apoptotic factors. , It has been shown that exosomes extracted from HIF‐1‐modified cardiac ECs possess higher amounts of miR‐126 and miR‐210 that improve CPCs survival under hypoxic stress via increasing ERK and Akt phosphorylation and induce glycolytic switch, leading to improved CPC therapeutic activity post‐MI. BM‐MSC‐derived exosomes promote I/R‐injured ECs' survival, proliferation and migration, via miR‐126‐mediated activation of the PI3K/Akt/eNOS signalling pathway. Phosphatase and tensin homologue is a gene that facilitates the apoptosis process through repressing PI3K/Akt signalling and is significantly upregulated during I/R injuries. It has been shown that BM‐MSC‐derived exosomes inhibit cardiomyocyte apoptosis via miR‐486‐5p‐mediated PTEN silencing. It has been demonstrated that miR‐29b‐3p suppresses OGD neuron apoptosis through PTEN silencing, resulting in Akt activation and subsequent cleaved caspase‐3 and BAX downregulation and Bcl‐2 upregulation. It has been shown that miR‐125b‐5p enriched in BM‐MSC‐derived exosomes prevent cardiomyocyte apoptosis during cardiac I/R injury via P53 suppression. Cardiac telocytes‐derived exosomes hamper ischemic EC apoptosis through miR‐21‐5p‐mediated suppression of cell death‐inducing p53 target 1 (Cdip1), a key downstream target of p53 pathway‐induced apoptosis, leading to caspase‐3 downregulation and improving EC viability which leads in enhanced angiogenesis efficiency and post‐MI recovery. Ageing is a dominant risk factor for ischemic diseases such as cardiovascular disorders and limb ischemia. ECs undergo the senescence process with ageing, which diminishes their proliferative and angiogenic potential. During the senescence process, NADPH oxidase‐2 (Nox‐2) expression is upregulated and EC's ROS production is enhanced, leading to increased oxidative stress and making ECs susceptible to impaired angiogenic ability and apoptosis. It is noteworthy that although ROS are essential for VEGF‐induced angiogenesis, excessive ROS amounts have negative impact on the angiogenesis and viability of the ECs. Angiotensin‐converting enzyme 2 (ACE‐2) and eNOS, which are diminished in the senescence process, interfere with oxidative stress. ACE‐2 reduces angiotensin II via converting it to angiotensin I and is known to promote angiogenesis and alleviate oxidative stress. It has been shown that exosomes derived from ACE‐2‐modified EPCs reduce aged ECs' oxidative stress and apoptosis via downregulating Nox‐2 and alleviating ROS generation. Moreover, exosomes improve angiogenic capacity of ECs via eNOS upregulation and subsequently enhanced NO production under I/R injury. , It has been shown that co‐culture of EPCs with exosome derived from Nrf2‐overexpressing AD‐MSCs results in enhanced levels of senescence marker protein 30 (SMP30), an anti‐senescence molecule and decreased levels of Nox‐1 and Nox‐4 oxidative stress factors. It seems that activated Nrf2 translocates into the nucleus in order to activate the antioxidant response element (ARE) which induces antioxidant enzyme activity. Besides, embryonic stem cell (ESC)‐derived exosomes reduce EC oxidative stress via miR‐200a‐mediated suppression of Keap1, a negative regulator of Nrf2. Excessive ROS production is associated with impaired angiogenesis under hypoxia and OGD. Hence, attenuating oxidative stress could be a positive step in improving angiogenesis and vascular disorders treatment. MiR‐126 protects ECs against apoptosis and oxidative stress by inhibiting ERBB receptor feedback inhibitor 1 (ERRFI1), an inducer of oxidative stress, maintaining cardiomyocyte mitochondrial membrane potential and alleviating intracellular ROS accumulation after I/R injury, resulting in improved cardiomyocyte survival and decreased apoptosis rate. , Iron–sulphur cluster scaffold homologue (ISCU) is a direct target of miR‐210. Decreased amounts of ISCU alleviate mitochondrial metabolism and oxygen consumption, leading to diminished mitochondrial ROS production. Decreased metabolic activity is shown to promote cell survival under ischemic stress. It has been shown that exosomes derived from TIMP2‐modified USCs protect cardiomyocytes from H2O2‐induced oxidative stress via upregulating oxygen scavenging enzymes including Sod and glutathione (GSH) and downregulation of malondialdehyde (MDA), an oxidative stress marker. In brief, exosomes are able to diminish ischemic injury and preserve vascular network at the damaged site via inhibiting apoptosis, senescence and oxidative stress in recipient cells. Figure 2 demonstrates exosome's anti‐apoptotic, anti‐senescence and anti‐oxidative mechanism of action. Following an ischemic insult, an inflammatory response is occurred in the damaged area due to the apoptosis, oxidative stress and the release of inflammatory cytokines. The inflammatory response is associated with an increase in various pro‐angiogenic factors, including VEGF, tumour necrosis factor‐α (TNF‐α), TGF‐β, FGF, PDGF, hepatocyte growth factor (HGF), IL‐1α and IL‐6. , Macrophages, the most important immune cells through the inflammatory response, possess two main phenotypes: M1 and M2. While M1 is responsible for clearing cell debris and host defence against pathogens, the M2 phenotype primarily participates in tissue regeneration and angiogenesis induction via secretion of pro‐angiogenic factors. It has been shown that AD‐MSC‐derived exosomes induce M1 to M2 polarization via transport of miR‐21 that targets PTEN and subsequently induces secretion of colony‐stimulating factor‐1 (CSF‐1). CSF‐1 promotes polarization into the M2 phenotype via boosting PI3K/Akt signalling in an autocrine and paracrine manner. T helper 2 (Th2) cells also enhance angiogenesis via IL‐4 and TGF‐β secretion. BM‐MSC and AD‐MSC‐derived exosomes promote naive CD4+ differentiation into the Th2 cells via the transfer of miR‐21 and miR‐29. , In summary, exosome therapy could boost tissue regeneration and regulate inflammatory responses in ischemia‐damaged tissues. In Figure 3, immunomodulatory mechanisms of exosomes are shown. Strategies for delivering exosomes, as therapeutic agents, are an important determinant for a successful therapeutic intervention. The route of administration has a pivotal role in targeting ability, tissue distribution and side effects. In addition, the patient's compliance and the cost of each route are also important to choose the ideal delivery route for each pharmacological agent. Exosomes delivery routes could be categorized into two main categories: systemic and local. Exosome systemic administration is a cost‐effective and patient‐friendly delivery strategy and is appropriate for systemic disorders such as systemic inflammation and sepsis. Nevertheless, systemic administration possesses a higher risk of systemic adverse effects and diminishes the exosomes concentration in the target tissue. Intravenous (IV) injection is the most common systemic administration route used to deliver the exosomes. While IV administration is convenient and easy, the circulatory short half‐life index of IV‐administered exosomes is a major limitation. The accumulation of exosomes in the liver and then in the lungs suggests more clearance of exosomes from systemic circulation in IV administration, compared to local routes and other systemic routes. , Administration of the exosomes in an intranasal style is considered as a patient‐friendly and non‐invasive strategy. The intranasal administration route might be more effective for retaining the exosomes in the brain tissue compared with IV injection. The intranasal route diminishes the exosome loss by avoiding the intestinal and hepatic metabolism. Local administration is described to be useful in several studies, but cannot be used for every organ. Also, the direct injection method seems more efficient in providing a sufficient amount of drug in the target tissue, however, it is more invasive and expensive than a systematic injection of exosomes, as it mostly requires special techniques. The intramyocardial administration of the exosomes for treatment of cardiac disorders was used in in‐vivo studies for the treatment of cardiologic disorders such as MI. Intrathecal injection is a local administration route, which is useful for the treatment of spinal disorders. Intrathecal administration of the MSC‐derived exosomes into the mice models of spinal cord injury (SCI) results in improved sensory and locomotor performance by promoting angiogenesis. Intramuscular (IM) injection is a non‐invasive and frequently used technique for the administration of various drugs. IM injection serves as a proper exosome delivery route for treatment of limb ischemia in animal models. In conclusion, each delivery strategy pros and cons should be considered and it is up to the investigators and physicians to choose the best strategy for each disease and target organ. Moreover, comprehensive and comparative investigations are required to determine the best exosome delivery route for each disease and condition. While exosome therapy has shown promising results as a contributory therapeutic tool for the treatment of ischemic disorders, the efficacy needs to be improved to make them an acceptable part of the therapeutic guidelines. Three main strategies that could promote exosome therapeutic potency are preconditioning, gene modification and bioconjugation are highlighted in this section. Exosomes' content is extremely affected by the microenvironment in which their origin cells reside. It has been demonstrated that through myocardial ischemia, cardiomyocytes' exosome production rate, as well as their exosomal pro‐angiogenic content significantly increase. Preconditioning is a method that simulates various microenvironments such as hypoxic microenvironment, acidic microenvironment, various physical stimuli and presence of diverse biologic and growth stimulations for the cells in order to promote their therapeutic and biogeneration aspects. Different preconditioning strategies are available such as hypoxic preconditioning, physical preconditioning and preconditioning with drugs and chemicals. In the setting of exosome generation, it has been shown that various preconditioning strategies could augment a cell's exosome biogenesis as well as enhancing the secreted exosomes' pro‐angiogenic content. Hypoxic preconditioning is the most utilized strategy in which cells undergo low oxygen tension in their culture milieu or cultured with hypoxia mimetic agents. , Under hypoxic stress, HIF‐1α, the most important transcription factor in response to hypoxia, upregulates which enhances the expression of angiogenesis‐related genes such as VEGF and VEGF receptors as well as pro‐angiogenic miRNAs. It has been demonstrated that hypoxic preconditioning augments the level of pro‐angiogenic factors including VEGF, VEGF‐R2, VEGF‐R3, FGF, monocyte chemotactic protein‐2 (MCP‐2), MCP‐4, Ang‐1, Tie‐2, MMP‐2 and MMP‐9 in MSCs and cardiomyocytes secreted exosomes. , It has been shown that hypoxia‐preconditioned cardiomyocytes generate exosomes with higher ability to induce ECs' migration, proliferation and tube formation compared with normoxic cardiomyocytes, mainly due to greater circHIPK3 exosomal content. Hypoxic preconditioning of CDCs upregulates miR‐126, miR‐130a and miR‐210 content of their exosomes which promote exosomal angiogenic induction in HUVECs in vitro. Nitric oxide (NO) is a crucial mediator in the angiogenesis process as it promotes EC proliferation, migration and ECM degradation via upregulating bFGF and VEGF. It has been revealed that MSCs preconditioned with a NO donor, N‐diazeniumdiolates (NONOates), exhibit upregulated miR‐126 and VEGF levels in their secreted exosomes. Moreover, it has been demonstrated that NO‐preconditioned MSCs‐derived exosomes promote HUVECs proliferation, migration and tube formation via VEGFR‐2 and Ang‐1 upregulation. Drugs could be used as preconditioning inducers and have shown promising results in improving the cell's paracrine potency. It has been revealed that preconditioning of BM‐MSCs with atorvastatin enhanced the levels of lncRNA H19, miR‐675, VEGF and intercellular adhesion molecule‐1 (ICAM‐1) in the secreted exosomes and upregulate PDGF, epidermal growth factor (EGF), bFGF and Ang‐1 in recipient ECs as well as activating the Akt/eNOS pathway. , Preconditioning with pioglitazone, an anti‐diabetic medication, is shown to enhance the potency of BM‐MSC‐derived exosomes to hamper PTEN in recipient HUVECs which leads to upregulation of PI3K/Akt/eNOS pathway, resulting in enhanced HUVECs' angiogenic activity. Physical preconditioning is performed by exposing the cells to physical stimuli such as light and mechanical pressure. It has been shown that human umbilical cord‐derived MSCs (hUC‐MSC) primed with blue light (455‐nm) possess a higher level of miR‐135b‐5p and miR‐499a‐3p pro‐angiogenic miRNAs in their secreted exosomes. It has been demonstrated that mechanical stress with 15% static stretching could promote the production of exosomes enriched with miR‐1246 pro‐angiogenic factor from fibroblasts. Taken together, preconditioning of parent cell is a cost‐effective and efficient strategy to improve the quantity and biologic functions of the secreted exosomes. It is crucial to determine the most efficient preconditioning strategy for each cell type and biologic aspect which we intend to promote. Genetic modification is a cell manipulation strategy in which the target cell's genome is altered via using various techniques such as viral vectors resulting in DNA sequence alteration and subsequent upregulation or downregulation of specific genes. As exosome biogenesis and content is proportionate to the parent cell, genetic modification of the parent cell alters its exosome biogenesis and content. Viruses are appropriate tools for gene modification as they possess a natural instinct to infect the target cell's genome. It has been shown that induction of glyoxalase‐1 (GLO‐1) overexpression, an enzyme which inhibits extreme accumulation of toxic end products induced by oxidative stress in cells, in MSCs using a lentivirus transfection, improved their produced exosomes VEGF, FGF and IGF‐1 levels. HUVECs cultured with GLO‐1 overexpressing MSCs‐derived exosomes had promoted proliferation, survival, migration and tube formation under high glucose stress in vitro. In order to enhance exosome targeting ability, MSCs were engineered by lentiviral transfection of ischemic myocardium‐targeting peptide (IMTP) CSTSMLKAC, which resulted in promoted targeting ability and migration capacity of their extracted exosomes to the ischemic myocardium, leading to improved cardioprotective impacts in MI. It has been shown that induction of HIF‐1α overexpression in MSCs via lentiviral transfection promotes secreted exosomes angiogenic abilities partly via Jagged1 induction. Lentiviral transfection of CXCR4 gene into the MSCs enhanced CXCR4 level in the secreted exosomes. It has been reported that CXCR‐4 modified‐BM‐MSC‐derived exosomes improve HUVECs angiogenesis via VEGF upregulation. MicroRNAs could also be transferred via lentiviral transfection. Regarding, it has been indicated that miR‐126‐overexpressing synovium MSCs (SMSCs) which were transfected by miR‐126‐3p lentiviral vector could produce miR‐126‐3p enriched exosomes, which contribute to increased angiogenesis. It has been shown that miR‐29b‐3p transfected BM‐MSCs secrete exosomes that promote angiogenesis and cell survival via PTEN silencing. Also, transfection of miR‐132‐3p into the BM‐MSCs via lentiviral vector, enhanced the level of miR‐132‐3p in their secreted exosomes, which activates PI3K/Akt/eNOS signalling in recipient ECs. It has been shown that induction of Akt gene overexpression in MSCs via an adenovirus transfection system improves their secreted exosomes pro‐angiogenic capacity through enhancing the level of PDGF content. HIF‐1α is degraded in a normoxic condition and is unable to exert its influence. A research team has designed a mutant HIF‐1α gene which maintains cellular expression in a normoxic environment and transplanted it to the MSCs via an adenoviral transfection system. Mutant HIF‐1α‐modified‐MSCs' secreted exosomes with the capacity to promote recipient BM‐MSCs' proliferation and osteogenic differentiation as well as ECs' angiogenic capacity. In brief, gene modification and nucleic transfection have shown to minimally influence exosomes' structure and biochemical properties; however, they are associated with high costs, biohazard risks and time consumption which emphasize the necessity of further investigations to shed light on and overcome these obstacles. In bioconjugation, specific biomolecules are included in exosomes. A strategy to promote exosome targeting ability is conjugating target organ‐specific ligands into the exosome's membrane. It has been shown that there are specific signal molecules on the surface of the exosomes that facilitate exosome uptake by specific tissues. Conjugation of cyclo (Arg‐Gly‐Asp‐D‐Tyr‐Lys) peptide [c(RGDyK)] onto the exosome surface using bio‐orthogonal copper‐free click chemistry, improves its targeting capability since c(RGDyK) binds to integrin αvβ3 existing in reactive ECs in cerebral vascular network. It has been shown that c(RGDyK)‐conjugated exosomes have a higher migration rate after IV administration to the ischemic brain. Bio‐orthogonal chemistry method has also been used to conjugate IMTP with hypoxic preconditioned BM‐MSC‐derived exosomes and resulted in profoundly enhanced exosomal migration and retention into infarcted myocardium. Ischemic regions have a low pH due to high glycolysis rate and low oxygen supply. It has been demonstrated that conjugation of the intercalated motif (i‐motif), a pH‐sensitive DNA strand enriched with cytosine, significantly promotes exosomes delivery to acidic areas, which could promote exosome targeted‐delivery to ischemia‐bearing sites. In another study, hyaluronic acid grafted with 3‐diethylamino propylamine (HDEA) was loaded into exosomes via sonication, a physical method to load cargos into exosomes via creating pores in the exosomal membrane by ultrasonic waves; it has been shown that membrane of HDEA‐loaded exosomes significantly desbalized in pH = 6.5, which resulted in releasing their content in an acidic environment. Nanoscale cargos such as miRNAs could be loaded into the exosomes via incubation. It is possible to load miR‐210 into the MSC‐derived exosomes via cholesterol modification which creates lipophilic miRNAs that could efficiently emerge with exosome membrane; incubation of exosomes with lipophilic miR‐210 enhances exosomal miR‐210 level, which results in improved pro‐angiogenic capacity. Electroporation is another strategy to load biologic substances into the exosomes. Electroporation utilizes electrical flow to notch exosomal membrane in order to create micro‐pores and enhance exosomes' permeability, thus facilitating molecular penetration into exosomes. It has been reported that electroporation of miR‐132 into the MSCs‐derived exosomes significantly enhances their angiogenesis induction in HUVECs. Electroporation possesses a higher efficacy in loading cargos into the exosomes compared with incubation, but it is also associated with a higher risk for manipulating and disrupting the exosome' structure as well as a more complex procedure. In Figure 4 different modification strategies to improve exosomes therapeutic capacity and their effects are shown. Although a huge amount of evidence has elucidated various therapeutic potentials of exosomes in ischemic disorders, there are several challenges in the safety and efficacy of exosome therapy which need to be overcome. Appropriate preclinical models are important to evaluate the pharmacodynamics, pharmacokinetics and toxicology of exosome as a novel drug. Indeed, preclinical studies could elucidate efficacy, potency and safety of exosomes, thereby increasing the chances of successful translation into clinical setting. However, most diseases are often complicated by multifactorial aetiologies which affect clinical management and are not predictable in animal model studies with are conducted in a uniform genotype. This issue generally results in a trade‐off between convenience and physiological applicability. In this way, safety, efficacy, potency and efficient dosage identified in animal studies are generally not translated to clinical trials. To date, a magnificent number of in vivo studies have been conducted to evaluate the safety and efficacy of exosome therapy. Neurological, cardiovascular and immune‐related diseases represent the three most investigated areas for exosome therapy. However, a significant number of studies used musculoskeletal, liver, kidney and pulmonary diseases animal models. A considerable number of experimental studies on exosomes demonstrated that exosomes have a promising therapeutic potential for ischemic diseases. Application of exosomes in ischemic diseases may contribute with multiple advantages, which mostly refer to containing pro‐angiogenic factors and/or regulating the survival signalling pathways. Besides, protecting against I/R injury and oxidative stress, as well as regulation of immune response, apoptosis and necrosis contribute to the beneficial effects of exosomes in the treatment of ischemic disorders. , , Preclinical investigations in terms of ischemic diseases mostly explored cutaneous wound healing, skin burn injury, flap transplantation in the treatment of refractory wounds, fat grafting, MI, limb ischemia, ischemic stroke, hepatic I/R injury, and retinal ischemia. In addition, it has been found that exosomes may play an important role in the treatment of several diseases which could develop following ischemia and ischemia‐related conditions such as cardiac fibrosis, bone defects, osteoporosis, osteonecrosis of the femoral head (ONFH), SCI, renal fibrosis and acute kidney injury (AKI). In vivo studies regarding ischemic diseases were described in detail in Table 2. Accordingly, the safety and efficacy of exosomes administration in pathological status are approved by preclinical and animal model studies, it is critical to evaluate safety and efficacy of exosomes usage under three phases of clinical trials, before their approval for clinical utilization. In this regard, there are several valid acceptable standards for controlling quality of novel products including European Medicines Agency (EMA), Food and Drug Administration (FDA) and Health Canada, that provide certain guidelines to approve a novel drug for administration. To date, the majority of clinical trials are related to exosome utilization as early diagnostic tools or predictors of treatment outcomes and clinical trials for therapeutic usage of exosomes are limited. In the terms of main issues in clinical use of exosomes, it could be referred to providing the optimal cell culture conditions, protocols for exosome production, isolation and storage, optimal dose for humans, schedule of exosomes administration, choosing the proper route of administration, and developing a protocol for modification strategies in order to promote exosomes therapeutic potential. Most of the published clinical studies showed beneficial effects of exosome administration without serious adverse effects in cancers including melanoma, non‐small cell lung cancer and colon cancer. Table 3 summarized the published and ongoing studies regarding ischemic diseases. Although exosomes have been extensively investigated as therapeutic modalities for ischemic diseases, there are still many challenges which need to be addressed, mainly in terms of optimization and improvement of isolation protocols and effective dose escalation. One of the most important challenges that exosome‐based therapies have faced is the rapid clearance and short half‐life of exosomes in vivo. To produce practical scale of exosomes, scale‐up in vitro cell culture systems should be established. This is a considerable challenge for health experts. A technique to enhance exosome production is application of three‐dimensional (3D) culture system which supports better cell‐to‐cell communication and promotes exosome biogenesis. It has been demonstrated that hUC‐MSCs cultured in a 3D condition possess a 19.4 folds higher exosome production compared to the hUC‐MSC cultured in 2D condition. Moreover, exosomes could be used in combination with conventional therapies. For instance, integration of MSC‐derived exosomes into scaffolds and hydrogels could significantly improve the wound healing process via promoting angiogenesis and inflammation regulation. Exosome can also serve as an ideal vehicle for drug delivery. Various drugs as chemotherapeutics and angiogenesis‐stimulators could be loaded on exosomes and delivered different biomedical components to target tissues with great efficacy. As naked exosomes undergo extensive phagocytosis and clearance shortly after transplantation, it has been shown that embedding exosomes on biomaterials such as stents, cardiac patches and cell sheets could profoundly enhance their sustainability and therapeutic efficacy. Tumour‐associated exosomes contain considerable angiogenic molecules since angiogenesis is a crucial necessity for tumour development, expansion and far metastasis. It is known that cancerous cell‐derived exosomes participate in tumour angiogenesis; thus, neoplastic cells could be suitable sources for angiogenic‐exosome isolation. , Tumour cell characteristics exert an essential impact on the properties of secreted exosomes. For instance, chemoresistant ovarian cancer cell‐derived exosomes possess more powerful angiogenic impacts than those derived from normal ovarian cancer cells. Nevertheless, utilization of cancerous cells for exosome extraction may increase the risk of carcinogenesis in the target site. In conclusion, exosomes could be an ideal therapeutic tools for the treatment of ischemic disorders due to their significant pro‐angiogenic capacity and unique biological properties. However, for a prosperous clinical translation, it is crucial to optimize their therapeutic activity, define certain protocols for extraction, modification and administration, as well as conducting more investigations on their molecular mechanism of action. Kasra Moeinabadi‐Bidgoli: Conceptualization (equal); data curation (equal); investigation (equal); project administration (equal); software (equal); writing – original draft (equal); writing – review and editing (equal). Maliheh Rezaee: Data curation (equal); writing – original draft (equal); writing – review and editing (equal). Nikoo Hossein‐Khannazer: Conceptualization (equal); project administration (equal); writing – review and editing (equal). Amirhesam Babajani: Conceptualization (equal); writing – original draft (equal). Hamid Asadzadeh Aghdaie: Conceptualization (equal); project administration (equal). Mandana Kazem Arki: Visualization (equal). Siamak Afaghi: Data curation (equal); writing – review and editing (equal). Hassan Niknejad: Conceptualization (equal); supervision (equal); writing – review and editing (equal). Massoud Vosough: Conceptualization (equal); investigation (equal); project administration (equal); supervision (equal); validation (equal); visualization (equal); writing – review and editing (equal). None. The authors confirm that there are no conflicts of interest. Not applicable.

PMC10003033

Xunshan Ren,Huangming Zhuang,Fuze Jiang,Yuelong Zhang,Panghu Zhou

Ceria Nanoparticles Alleviated Osteoarthritis through Attenuating Senescence and Senescence-Associated Secretory Phenotype in Synoviocytes

06-03-2023

osteoarthritis,senescence,synoviocytes,ceria

Accumulation of senescent cells is the prominent risk factor for osteoarthritis (OA), accelerating the progression of OA through a senescence-associated secretory phenotype (SASP). Recent studies emphasized the existence of senescent synoviocytes in OA and the therapeutic effect of removing senescent synoviocytes. Ceria nanoparticles (CeNP) have exhibited therapeutic effects in multiple age-related diseases due to their unique capability of ROS scavenging. However, the role of CeNP in OA remains unknown. Our results revealed that CeNP could inhibit the expression of senescence and SASP biomarkers in multiple passaged and hydrogen-peroxide-treated synoviocytes by removing ROS. In vivo, the concentration of ROS in the synovial tissue was remarkably suppressed after the intra-articular injection of CeNP. Likewise, CeNP reduced the expression of senescence and SASP biomarkers as determined by immunohistochemistry analysis. The mechanistic study showed that CeNP inactivated the NFκB pathway in senescent synoviocytes. Finally, safranin O–fast green staining showed milder destruction of articular cartilage in the CeNP-treated group compared with the OA group. Overall, our study suggested that CeNP attenuated senescence and protected cartilage from degeneration via scavenging ROS and inactivating the NFκB signaling pathway. This study has potentially significant implications in the field of OA as it provides a novel strategy for OA treatment.

Ceria Nanoparticles Alleviated Osteoarthritis through Attenuating Senescence and Senescence-Associated Secretory Phenotype in Synoviocytes Accumulation of senescent cells is the prominent risk factor for osteoarthritis (OA), accelerating the progression of OA through a senescence-associated secretory phenotype (SASP). Recent studies emphasized the existence of senescent synoviocytes in OA and the therapeutic effect of removing senescent synoviocytes. Ceria nanoparticles (CeNP) have exhibited therapeutic effects in multiple age-related diseases due to their unique capability of ROS scavenging. However, the role of CeNP in OA remains unknown. Our results revealed that CeNP could inhibit the expression of senescence and SASP biomarkers in multiple passaged and hydrogen-peroxide-treated synoviocytes by removing ROS. In vivo, the concentration of ROS in the synovial tissue was remarkably suppressed after the intra-articular injection of CeNP. Likewise, CeNP reduced the expression of senescence and SASP biomarkers as determined by immunohistochemistry analysis. The mechanistic study showed that CeNP inactivated the NFκB pathway in senescent synoviocytes. Finally, safranin O–fast green staining showed milder destruction of articular cartilage in the CeNP-treated group compared with the OA group. Overall, our study suggested that CeNP attenuated senescence and protected cartilage from degeneration via scavenging ROS and inactivating the NFκB signaling pathway. This study has potentially significant implications in the field of OA as it provides a novel strategy for OA treatment. Osteoarthritis (OA) is the most common type of arthritis characterized by synovitis, articular cartilage degeneration, subchondral bone sclerosis and osteophyte formation [1]. About 80% of people over 65 have imaging changes in OA, affecting the quality of life of the elderly and inflicting a heavy economic burden on families and society [2]. Synovitis emerges in the early stage of OA and is associated with the symptoms and structural progression of OA [1]. In response to cartilage degradation and cytokine stimulation, synoviocytes secrete pro-inflammatory mediators, exacerbating the inflammatory responses and pain [3]. It has been reported that synovitis is positively correlated with the degree of pain [4]. In addition, matrix-degrading enzymes released by synoviocytes lead to the irreversible destruction of cartilage [5]. Thus, it is of great significance to develop the treatment for synovitis to relieve and delay the progression of age-related OA. Cellular senescence refers to an irreversible state of cell cycle arrest, which is characterized by increased activity of senescence-associated β-galactosidase (SA-β-Gal) and a senescence-associated secretory phenotype (SASP) [6]. SASP alters the cellular microenvironment by secreting excessive pro-inflammatory mediators and matrix-degrading enzymes [7]. Senescent synoviocytes play a vital role in the progression of OA, which has gradually attracted the attention of researchers. Zhang et al. reported that high expression of the senescence marker, p16, existed in synovial tissue of OA patients [8]. Jeon et al. observed an increased proportion of cells positively staining for p16 and SA-β-Gal in the OA synovium [9]. Chen et al. proposed that targeting the senescent synoviocytes could effectively alleviate the progression of OA [10,11]. The above studies indicate that the targeted intervention on senescent synoviocytes is effective for OA treatment. Reactive oxygen species (ROS), including hydrogen peroxide, hydroxyl radicals, superoxide anions and nitric oxide, are unstable and highly reactive due to their unpaired electrons [12]. ROS could lead to cellular senescence. Meanwhile, ROS production was significantly increased due to mitochondrial dysfunction and the abnormal activity of NADPH oxidases in senescent cells [13]. In OA synoviocytes, excessive ROS activated nuclear factor kappa B (NFκB) pathways, promoted the synthesis of inflammatory cytokines and matrix-degrading enzymes, and led to downstream events such as synovial cartilage inflammation and cartilage matrix destruction [14,15,16]. In addition, scavenging ROS in synoviocytes could reduce the inflammatory response, inhibit the release of matrix-degrading enzymes and promote cartilage matrix synthesis [17,18,19]. Therefore, scavenging the ROS may prevent the senescence and SASP of synoviocytes, and further delay the progression of OA. Ceria nanoparticles (CeNP) have recently attracted great attention due to their unique antioxidant capacity [20,21,22]. CeNP can mimic the activity of two key antioxidant enzymes, superoxide dismutase and catalase, abating the noxious intracellular ROS. CeNP has been shown to have therapeutic effects in ROS-related diseases such as Alzheimer’s disease, stroke, liver diseases, glaucoma and acute kidney injury [23,24,25,26,27]. However, the therapeutic effects and mechanism of CeNP on OA remain unclear. We speculated that CeNP may alleviate the SASP in senescent synoviocytes by scavenging ROS. In this study, we provide evidence that CeNP is effective in alleviating senescence and SASP of synoviocytes in vitro and in vivo, and that CeNP may serve as a new strategy for OA treatment. The uniform-sized CeNP were synthesized using the thermal decomposition method. CeNP were transferred to the aqueous phase for the subsequent experiments by coating with mPEG2k-DSPE. TEM showed that CeNP were uniformly spherical with an average size of 4.74 ± 0.59 nm (Figure 1a). Due to the coated mPEG2k-DSPE and water shell, the hydrodynamic particle diameter was 26.72 ± 1.48 nm higher than the TEM size (Figure 1b). The EDS analysis suggested a Ce:O atomic ratio of 0.49 (Figure 1c). The zeta potential measurement showed the CeNP had a zeta potential of −30.43 ± 0.48 mV (Figure 1d). In addition, UV–visible spectra confirmed that CeNP were stable in the aqueous solution at room temperature for at least one week (Figure 1e,f). Next, we evaluated the SOD and CAT enzyme-mimetic activities conferred by Ce3+ and Ce4+ in the synthesized CeNP in vitro. The SOD and CAT activity assay showed that CeNP could reduce the concentration of superoxide anion and hydrogen peroxide in a concentration-dependent manner (Figure 2a,b, p < 0.01). DPPH, a stable free radical capable of absorbing hydrogen atoms from antioxidants, is used to detect free radical scavenging activity [28]. A DPPH and hydroxyl radical detection assay revealed that CeNP could decrease the concentration of free radicals in a concentration-dependent manner (Figure 2c,d, p < 0.01). These results suggested that CeNP possessed a great ability for ROS scavenging extracellularly. We then explored the cytotoxicity of CeNP on primary rat synoviocytes. The primary synoviocytes featured as spindle-shaped under light microscopy (Figure 3a). Immunofluorescence staining showed that primary synoviocytes expressed vimentin (Figure 3b), a known marker of synoviocytes, which was consistent with previous reports [29]. Cy5 was used to label CeNP to observe the uptake of CeNP by synoviocytes. Fluorescence images indicated that Cy5-labeled CeNP dispersed around the nucleus within 24 h of co-incubation with synoviocytes, and the mean intake number of CeNP was positively related to the concentration of CeNP (Figure 3c, p < 0.05). The results of the CCK8 assay revealed that CeNP did not affect the cell viability with concentrations below 100 μg/mL. Still, cell viability was significantly inhibited after the concentration increased to 200 μg/mL (Figure 3d, p < 0.01). Combining the results above, we took 100 μg/mL as the subsequent intervention concentration and 24 h as the intervention time. The accumulation of ROS is involved in the occurrence of senescence and SASP [30]. Accordingly, we explored the effects of CeNP in the H2O2-elicited senescence model. DCFH-DA and SA-β-Gal staining results indicated that synoviocytes possessed a higher concentration of ROS and percentage of SA-β-Gal positive cells after H2O2 treatment (Figure 4a,b, p < 0.01). Additionally, higher expression of P16 and P21, the senescence biomarkers, were observed in H2O2-treated synoviocytes by Rt-qPCR (Figure 4c, p < 0.01). These results indicated the successful construction of the senescent synoviocytes model. However, the changes induced by H2O2 were partially reversed by CeNP, revealing the effects of CeNP on attenuating senescence. Then, to explore the role of CeNP treatment on SASP, we detected the mRNA level of SASP-related biomarkers iNOS, COX2, MMP3, ADAMTS5, IL-6 and TNFα by Rt-qPCR. We found that H2O2 promoted the expression of iNOS, COX2, MMP3, ADAMTS5, IL-6 and TNFα on mRNA levels (Figure 4d,e, p < 0.01). Simultaneously, western blot analysis showed that H2O2 elevated the protein levels of iNOS, COX2, MMP3 and ADAMTS5 (Figure 4f–h, p < 0.01). The ELISA results confirmed the increased secretion of IL-6 and TNFα on H2O2-treated synoviocytes (Figure 4i,j, p < 0.01). Expectedly, CeNP suppressed these alterations, indicating that CeNP could inhibit SASP in senescent synoviocytes. These results suggested that CeNP attenuated oxidative-stress-associated senescence and inhibited SASP through scavenging ROS synoviocytes. Subsequently, we constructed a multiple passaged synoviocytes model to simulate replicative senescence occurring in synovitis of OA, and the same experiments were conducted with similar results [31,32]. CeNP abolished the accumulation of ROS and senescent synoviocytes induced by multiple passages (Figure 5a–c, p < 0.01). Concurrently, CeNP reduced the expression of iNOS, COX2, MMP3, ADAMTS5, IL-6 and TNFα at mRNA and protein levels (Figure 5d–j, p < 0.01). Therefore, CeNP also attenuated replicative senescence in synoviocytes. As previously described, excessive ROS promoted the expression of inflammatory cytokines and matrix-degrading enzymes by activating the NFκB pathway in synoviocytes [14,15,16]. Therefore, we examined the impact of CeNP on the NFκB pathway in MP synoviocytes. Western blot results showed that the expression of p-p65 and p-IκBα was elevated in MP synoviocytes compared with NC synoviocytes (Figure 6a–c, p < 0.01), and the expression of IκBα was decreased (Figure 6d, p < 0.01), while CeNP significantly abolished the increased expression of p-IκBα and p-p65 in MP synoviocytes and reduced the degradation of IκBα. These results indicated that CeNP could dramatically inhibit the activation of the NFκB pathway in senescent synoviocytes. Previous studies have reported that senescent cells accumulated in the synovium after ACLT [9]. To manifest the effects of CeNP on senescent synoviocytes in vivo, we established a rat OA model via ACLT surgery. We found that the concentration of ROS was elevated in the synovium after ACLT, and that intra-articular injections of CeNP reduced ROS content as determined by lower fluorescence intensity in the CeNP treatment group (Figure 7a, p < 0.01). The immunohistochemical images and quantitative analysis showed that the intra-articular injection of CeNP inhibited the expression of P16, P21, iNOS and COX2, indicating that the senescence of synoviocytes was attenuated by CeNP (Figure 7b–e, p < 0.01). Likewise, the expression of SASP biomarkers ADAMTS5, MMP3, IL-6 and TNFα was suppressed after CeNP treatment in the ACLT group (Figure 8a–d, p < 0.01). Collectively, CeNP could attenuate the senescence and SASP via removing ROS in vivo. To assess the activation of the NFκB signaling pathway in vivo, we tested the protein levels of p65 and p-p65 on the synovium. Immunohistochemical staining and quantitative results revealed that CeNP reduced the levels of p-p65 protein (Figure 8e, p < 0.01). However, no significant difference was observed in the levels of p65 in each group (Figure 8f, p > 0.01). Finally, we performed HE and safranin O–fast green staining to evaluate the protective role of CeNP in articular cartilage. The result showed that cartilage erosions and proteoglycan loss occurred in the ACLT group, while the CeNP group exhibited more mild change and a lower OARSI score (Figure 8g, p < 0.01). In summary, CeNP could inactivate the NFκB signaling pathway and protected cartilage in vivo. Synovium is the special connective tissue wrapping the joint and is responsible for producing synovial fluid and providing nutrients to cartilage [9]. Synovial inflammation is a pathological phenomenon throughout the whole process of OA, which occurs under the stimulation of inflammatory cytokines and cartilage matrix degradation products. In this case, synoviocytes secreted pro-inflammatory mediators and matrix-degrading enzymes, and aggravated joint inflammation and cartilage degradation [3]. Histologically, synovial inflammation mainly manifested as proliferative inflammation, such as synovial lining hyperplasia, immune cell infiltration, angiogenesis and fibrosis [33]. As a result, few studies have linked synovial inflammation to synoviocytes senescence, a proliferation-suppressed phenotype. Zhang and Chen et al. recently discussed the pathogenic effects of increasing senescent synoviocytes in OA, which suggested senescent synoviocytes might accelerate the progression of OA [8,11]. Cerium is a lanthanide metal element and exists in a mixture of trivalent and tetravalent. The conversion of cerium ions between trivalent and tetravalent endows it with repeatable reducibility. Since oxygen vacancies and Ce3+ mostly existed on the surface, CeNP, with higher surface area to volume ratios, had better reducibility than cerium oxide with larger particles [34]. In this work, we synthesized CeNP with the size of 4.74 ± 0.59 nm, exhibiting good stability and ROS scavenging effects. CeNP have shown general safety and sound therapeutic effects in various ROS-related diseases, which attracted us to explore their therapeutic roles in OA. However, some studies reported the presence of concentration-dependent cytotoxicity of CeNP in multiple cell types [35,36]. Our results found that the cellular viability of synoviocytes exposed to excessive CeNP decreased, consistent with previous reports. This could be due to DNA damage, dephosphorylation of various substrates, aberrant cell signaling and alterations in the transcriptional and posttranslational levels induced by CeNP [37,38,39]. However, the toxicological mechanism of CeNP remains unknown and merits further study [40]. Oxidative stress was considered to be the crucial cause of senescent synoviocytes [41]. Meanwhile, oxidative stress signals in senescent cells promoted the occurrence of SASP [42]. Our study explored the role of scavenging ROS by CeNP in the MP and H2O2-induced senescent synoviocytes. We found that the concentration of ROS and percentage of SA-β-Gal positive cells increased, and SASP-related biomarkers iNOS, COX2, MMP3, ADAMTS5, IL-6 and TNFα were up-regulated in senescent synoviocytes. After CeNP treatment, the concentration of ROS and percentage of SA-β-Gal positive cells were reduced, and SASP-related biomarkers were suppressed. The ACLT model is the most commonly used surgical model in OA research and is suitable for pharmaceutical studies because of its slow development [43]. Meanwhile, the ROS generation and senescent cell accumulation have been observed in the ACLT-induced OA model [9,44,45]. Therefore, we sought to further confirm the ROS-scavenging capacity of CeNP in ACLT-induced OA in rats. In this study, accumulated ROS and increasing expression of P16, P21, iNOS, COX2, MMP3, ADAMTS5, IL-6 and TNFα were observed in the OA synovium. After intra-articular injections of CeNP, the concentration of ROS and the protein levels of the molecules above were inhibited apparently in the synovium. In addition, the intra-articular injections of CeNP preserved proteoglycan loss in ACLT rats. Therefore, CeNP was capable of attenuating senescence in the synovium and protecting articular cartilage from deterioration via scavenging ROS. NFκB is a family of dimeric transcription factors involved in cell differentiation, proliferation, survival, and serves the function of coordinating inflammatory responses [46]. NFκB plays a crucial role in the progression of OA. The activation of NFκB signaling led to the expression of inflammatory cytokines and matrix-degrading enzymes [47,48,49,50,51,52]. ROS activated NFκB signaling through regulating multiple NFκB signaling-related proteins such as inhibiting the phosphorylation of IκBα [53]. In this study, we found that CeNP inhibited the protein level of p-p65 and p-IκBα in multiple passaged synoviocytes, and attenuated the degradation of IκBα. Furthermore, the relative expression of p-p65 was down-regulated in OA rats after CeNP injection, demonstrating that CeNP could inhibit the NFκB pathway activity in senescent synoviocytes through ROS scavenging, thereby inhibiting the SASP. There are some limitations to this study. We failed to measure the concentration of intra-articular SASP protein due to less synovial fluid in rats. For ethical reasons, we were unable to obtain normal synoviocytes for the experiment. Moreover, OA is a whole-joint disease, and the effects of CeNP in other tissues such as chondrocytes or immune cells need to be investigated. Cerium nitrate hexahydrate (Ce(NO3)3·6H2O), oleylamine, 1-octadecene (ODE), acetone, methanol, cyclohexane and anhydrous were purchased from Aladdim (Shanghai, China). NH2-PEG2k-DSPE, mPEG2k-DSPE and Cy5-NHS were acquired from Yuanye Bio-Technology (Shanghai, China). CeNP was synthesized according to previously reported methods [54]. Briefly, Ce(NO3)3·6H2O (1.736 g, 4 mmol) and oleylamine (3.208 g, 12 mmol) were dispersed in 20 g of ODE. The mixed solution was stirred at room temperature for 2 h and then heated under a vacuum at 80 °C for 1 h to remove water. The mixture was heated and maintained at 260 °C for 2 h in an argon atmosphere. After being cooled to room temperature, acetone and methanol were added to the mixture to precipitate CeNP. CeNP were washed with cyclohexane and anhydrous ethanol and collected by centrifugation at 15,000 rpm for 20 min. This washing process was repeated five times. Finally, CeNP were dispersed in chloroform. The CeNP were decorated with mPEG2k-DSPE through ultrasound for transferring into the aqueous phase. Then, mPEG2k-DSPE (30 mg) were added into 5 mL of CeNP/chloroform (2 mg/mL), and stirred at room temperature for 4 h. After evaporating the chloroform by rotary evaporation, mPEG2k-DSPE-modified CeNP were dispersed in 10 mL of ultrapure water by ultrasonic water bath for 30 min. CeNP were purified by filtration, ultracentrifugation and dialysis (MW cutoff = 8–14 kDa). An inductively coupled plasma optical emission spectrometer was used to calculate the molality of CeNP. For the synthesis of Cy5-labeled CeNP, Cy5-NHS (5 mg) and NH2-PEG2k-DSPE (20 mg) were dissolved in 1 mL of DMSO, and the mixture was stirred overnight at room temperature under Ar protection. Cy5-PEG2k-DSPE was purified by dialysis (MW cutoff = 500–1000 Da) and lyophilized for 24 h. Cy5-PEG2k-DSPE (5 mg) and mPEG2k-DSPE (25 mg) were added to 5 mL of CeNP/chloroform (2 mg/mL) and the above procedures repeated to obtain Cy5-labeled CeNP. Morphology and elemental distribution of CeNP were detected by the transmission electron microscopy (TEM) and the energy dispersive spectrometer in JEM-2100 TEM (JEOL, Tokyo, Japan). The zeta potentials and particle diameters of the CeNP were measured by light scattering in Malvern Zetasizer Nano Series (Malvern, UK). The antioxidant capacity of CeNP was assessed by multiple assays according to the manufacturer’s protocols. The superoxide dismutase (SOD) assay kit (Nanjinjiancheng, Nanjin, China, A001-3-2) and catalase (CAT) assay kit (Nanjinjiancheng, A007-1-1) were used to assess the SOD and CAT enzyme activities of CeNP. The free radical scavenging effect of CeNP was tested by hydroxyl free radical assay kit (Nanjinjiancheng, A018-1-1) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging capacity assay kit (Nanjinjiancheng, A153-1-1). We isolated synovial tissues from Wistar rats (8 weeks, males) to isolate the primary synoviocytes. After mincing, synovial tissues were placed into DMEM/F12 medium with 0.2% collagenase II for 4 h at 37 °C. Synoviocytes were collected by filtration and centrifugation and maintained in DMEM/F12 medium supplemented with 10% fetal bovine serum (Gibco, NY, America, 10270-106) and 100 U/mL of penicillin–streptomycin (Servicebio, Wuhan, China, G4003) in an incubator at 37 °C with 5% CO2. For the multiple passaged senescent synoviocytes model, synoviocytes were subcultured for 6–8 passages till the growth rate decreased significantly [55]. For the H2O2-elicited senescent synoviocytes model, synoviocytes were treated with 500 μM H2O2(Aladdin, Shanghai, China, 7722-84-1) for 4 h [56]. Synoviocytes were treated with 100 mg/mL Cy5-labeled CeNP for 24 h and washed three times with PBS. After being fixed with 4% paraformaldehyde for 15 min, nuclei were stained with DAPI. The fluorescence images were visualized using the IX73 inverted fluorescence microscope (OLYMPUS, Tokyo, Japan). To measure the cytotoxicity of CeNP, we seeded 5000 synoviocytes per well in a 96-well plate. After adherence, the medium was replaced by the fresh medium with different CeNP concentrations (0, 25, 50, 100, 200 mg/mL), and cultured at 37 °C for 24 h [23]. Next, 10 μL of Cell Counting Kit-8 (CCK-8, Servicebio, G4103) reagent was added to each well and incubated at 37 °C for 2 h. The absorbance at 450 nm was determined using a Microplate Reader (EnVision, PerkinElmer, MA, America). Intracellular ROS was measured by DCFH-DA (Beyotime, Shanghai, China, S0033S) according to the manufacturer’s protocol. Synoviocytes were loaded with DCFH-DA by incubating with 10 μM of probe solution for 30 min at 37 °C. Then, the images were visualized by the IX73 inverted fluorescence microscope, and the mean fluorescence intensity was calculated by ImageJ (versions: V1.8.0). SA-β-Gal staining was performed by a SA-β-Gal staining kit (Servicebio, G1073) according to the manufacturer’s protocol. Synoviocytes were fixed with senescent cell staining fixative for 15 min. After washing three times, synoviocytes were incubated in SA-β-Gal staining solution at 37 °C for 24 h. The inverted fluorescence microscope was used to capture the images. SA-β-Gal positive synoviocytes were counted in three random fields per dish. The total cellular RNA was extracted by the RNA isolation kit (Beyotime, Shanghai, China, R0026) according to the manufacturer’s instructions. The RNA concentrations were measured by Nanodrop (Thermo, MA, America). Approximately 1000 ng of RNA was reverse-transcripted to cDNA using a SweScript RT II Enzyme Mix (Servicebio, Wuhan, China, G3330), and Rt-qPCR was performed using the 2 × Universal SYBR Green Fast qPCR Mix (Abclonal, Wuhan, China, RK21203) on LightCycler 480 (Roche Diagnostics, Basel, Switzerland). The fold change of targets was analyzed by the 2−ΔΔCt method, and β-actin was considered the internal reference. The primers used in this study are shown in Table S1. The total proteins from synoviocytes were extracted using RIPA buffer (Servicebio, G2008), to which PMSF (Servicebio, G2008), phosphatase inhibitors (Servicebio, G2007) and 50×Cocktail (Servicebio, G2006) were added. Synoviocytes lysis was performed for 20 min on ice, and ultrasonication and centrifugation were used to purify proteins. The concentration of proteins was measured by the BCA protein assay kit (Servicebio, G2026) according to the manufacturer’s instructions. Protein samples were reduced in SDS sample buffer, and were separated by 10% SDS-PAGE. After transferring to PVDF membranes and blocking, the membranes were incubated with primary antibodies against β-actin (Servicebio, GB11001, 1:2000), iNOS (Abclonal, A3774, 1:2000), COX2 (Abclonal, A3560, 1:2000), ADAMTS5 (Abclonal, A2836, 1:2000), MMP3 (Abclonal, A11418, 1:2000), p65 (Abmart, Shanghai, China, TA5006, 1:2000), p-p65 (Abmart, TP56367, 1:2000), IkBα (Abmart, TA5002, 1:2000) and p-IkBα (Abmart, TA2002, 1:2000) overnight at 4 °C. Next, the membranes were washed three times with PBS and incubated with HRP-conjugated secondary antibodies (Servicebio, GB23303, 1:5000) for 1 h at room temperature. The ECL substrate (Epizyme Biotech, Shanghai, China, SQ101) was used to visualize the protein bands on ChemiDoc Touch (Bio-Rad, CA, America), and the semi-quantitative analysis of images was conducted using ImageJ software (versions: 1.8.0). The concentrations of TNFα and IL-6 in synoviocyte culture media were assessed using rat ELISA (Thermo, 88-7340-88 and 88-50625-88) kits according to the manufacturer’s protocols. Animal care and experimentation were consistent with the National Research Council’s Guide for the Care and Use of Laboratory Animals, and were approved by the Laboratory Animal Welfare & Ethics Committee of the Renmin Hospital of Wuhan University (Approval No: 20220103A). Fifteen 8-week-old male Wistar rats were provided by SiPeiFu Biotechnology Co. Ltd. (Beijing, China). OA was induced by anterior cruciate ligament transection (ACLT), as reported previously [57]. The joint cavity was exposed in the sham group, but the anterior cruciate ligament was not transected. After surgery, rats in the OA group and CeNP group accepted an intra-articular injection of CeNP (100 μg/mL, 50 uL) and saline (50 uL) once a week. Eight weeks post-surgery, all rats were sacrificed. The knee joint samples were fixed with 4% paraformaldehyde, decalcified in 0.5 M EDTA, and embedded in paraffin. A part of synovium tissue was fresh frozen in OCT (Servicebio, G6059) for frozen sections, and the ROS was detected by dihydroethidium (Beyotime, S0063). The paraffin-embedded tissue was cut into 6 μm thick sections using a rotary microtome (Leica RM2016, Leica Microsystems Ltd., Weztlar, Germany). Then, the midsagittal sections were stained with safranin O–fast green. Microscope images were acquired with an inverted microscope (NIKON ECLIPSE CI, NIKON, Tokyo, Japan). The Osteoarthritis Research Society International (OARSI) system was used to evaluate the OA severity with two blinded pathologists [58]. The sections were subjected to antigen retrieval in citric acid buffer (Powerfor Biologu, Wuhan, China, B0034). Nonspecific protein binding was blocked by BSA (Solarbio, Beijing, China, A8010) in PBST for 30 min. Next, the sections were incubated with primary antibodies against P16 (Wanleibio, Shenyang, China, WL01418, 1:300), P21 (Wanleibio, WL0362, 1:400), iNOS (Servicebio, GB11119, 1:500), COX2 (Abclonal, A3560, 1:200), ADAMTS5 (Abclonal, A2836, 1:500), MMP3 (Abclonal, A11418, 1:200), IL-6 (Abclonal, A21264, 1:200), TNFα (Abclonal, A11534, 1:200), p65 (Abmart, TA5006, 1:50) and p-p65 (Abmart, TP56367, 1:50) overnight at 4 °C. After washing with PBS, the sections were incubated with goat anti-rabbit IgG HRP (Abcam, MA, America, ab205718,) at 37 °C for 50 min. A DAB HRP substrate kit (DAKO, Shanghai, China, K3468) was used for dye development, and hematoxylin was used as a nuclear counterstain. Microscope images were acquired with an inverted microscope (NIKON ECLIPSE CI, NIKON). Image Pro Plus (versions: 6.0) was used to quantify the results by measuring the mean integral optical density. All data in this study were reported as means ± standard error of mean (SEM). The Shapiro–Wilk normality test was used to perform the normality test. For the data with normal distribution, a one-way analysis of variance (ANOVA) followed by Bonferroni’s test was administrated. For the data with non-normal distribution, we performed the Kruskal–Wallis H test, followed by Dunn’s test. A value of p < 0.05 was considered significant. All reported p values are calculated from two-sided comparisons. In summary, our study is the first, to our knowledge, to explore the therapeutic roles of CeNP in OA. We confirmed that CeNP attenuate synoviocyte senescence and SASP by clearing ROS and inactivating the NFκB pathway, which will provide a novel approach to the treatment of OA.

PMC10003035

Gabriel Santpere

Genetic Variation in Transcription Factor Binding Sites

06-03-2023

Genetic Variation in Transcription Factor Binding Sites The interaction between transcription factors (TFs) and DNA is the core process that determines the state of a cell’s transcriptome. Changes in TF binding can have consequences for normal cellular development as well as function and can also be the substrate for molecular evolution. Comparing TF–DNA binding across cells, tissues, and organisms, as well as across individuals, conditions, states, and developmental trajectories, is fundamental to assessing the impact of the gene regulatory networks’ (GRNs) dynamics on normal cellular function, disease, and evolution. There are many observed mechanisms by which a given TF–DNA binding event can be altered. For example, at the TF level, variations in the concentration, subcellular localization, and post-translational modifications of TFs and their cofactors can all help to explain such differences. At the DNA level, changes in chromatin status (e.g., histone modifications and DNA methylation) and sequence variations that alter the preferred motifs of TFs or DNA shape may be determinants of GRN variation. Indeed, a large body of evidence links genetic mutations that specifically disrupt binding sites not only to the expected differences in TF binding and gene expression [1] but also to the allelic imbalance in chromatin accessibility. This latter observation applies to both segregating sites within populations [2,3] and substitutions between species [4], and further illustrates the bidirectional relationships between TF binding and chromatin accessibility that play a role in, as well as determine, target gene expression differences. Not surprisingly, TFBS-disrupting variants are particularly enriched at GWAS loci [5] and represent the best candidates with which to explain the functional consequences of evolutionarily relevant genomic regions [6]. In this Special Issue, entitled “The Role of Genetic Variation in Transcription Factor Binding Sites in Evolution and Disease”, we aim to present and promote research on these aspects, which cut across a wide range of research areas. Degtyareva et al. review the history of regulatory SNPs that modify TFBS and discuss the range of available methods that can be used to dissect the specific TFs affected by genetic variants, such as EMSA, ChIP-seq, and pull-down assays [7]. To extend this type of analysis genome-wide, with the aim of prioritizing causal GWAS variants, the authors discuss the capabilities of current state-of-the art functional genomics methods, such as eQTL mapping, massive parallel reporter assays, and ChIP-seq, as they apply to the determination of allele-specific expression, regulation, and TF binding. Finally, the review provides illustrative examples of disease-associated variants from GWAS where TFs with allele-specific binding have been identified [7]. Another practical example of using allelic asymmetries in gene expression and chromatin state to identify regulatory SNPs is provided by Korbolina et al. In their study, the authors leverage RNA-seq and H3K4me3 ChIP-seq data from human pulmonary arterial endothelial cells to identify such allelic asymmetries, a catalogue that is subsequently refined with existing eQTL and GWAS data [8]. Tseng et al. complement this by reviewing aspects of the mechanisms that influence TF binding, including histone modifications, DNA methylation, and chromatin conformation, as well as providing several instances of disease risk alleles that affect the interplay between specific TFs and chromatin status [9]. The experimental determination of TF binding sites is an essential step as it reveals a variety of nuances in motif preference that often misalign with in silico predictions. In de Martin et al., the authors focus on the complexities of TF binding to DNA of the basic helix–loop–helix (bHLH) TFs, and how motif preference is determined by a combination of factors, including spatiotemporally regulated co-factor interactions, post-translational modifications, and chromatin status [10]. Members of the bHLH family are also the subject of Yoshikawa et al., who review the evolutionary history of the regulatory elements associated with the recombination-activating genes Rag1 and Rag2, which mediate the recombination process that confers variability to T cell receptors and immunoglobulin genes, as well as their bHLH regulators [11]. TFs can also operate on regulatory regions encoded in the genomes of DNA viruses. For example, hosts’ TFs initiate and coordinate the viral cycle of the JC polyomavirus (JCPyV), the causative agent of a demyelinating disease called progressive multifocal leukoencephalopathy (PML). Wilczek et al. present their work on the structural variation affecting the JCPyV regulatory region and how this affects host TF binding. Their study found that JCPyV rearrangements resulting in more TFBS of TFs enhancing viral replication are more common in PML than in non-PML samples [12]. Finally, Wang et al. introduce the topic of gene clusters regulated by few TFs and the grammar of their components. In particular, the authors review the complexity and interactions of pathway-specific TFs involved in the regulation of biosynthetic gene clusters in two model fungal organisms [13]. Taken together, this Special Issue illustrates a wide range of molecular mechanisms that generate variation in TF function in different organisms. It also reflects the importance of combining computational modeling and prediction with the experimental determination of TFBS. I hope that this Special Issue will contribute to drawing more attention and research to variation in TF–DNA interactions in the context of evolution and disease.

PMC10003036

Alessandro Allegra,Nicola Cicero,Giuseppe Mirabile,Concetto Mario Giorgianni,Sebastiano Gangemi

Novel Biomarkers for Diagnosis and Monitoring of Immune Thrombocytopenia

23-02-2023

immune thrombocytopenia,platelet,biomarker,immune system,autoimmune disease,oxidative stress,diagnosis,prognosis,response to treatment

Lower-than-normal platelet counts are a hallmark of the acquired autoimmune illness known as immune thrombocytopenia, which can affect both adults and children. Immune thrombocytopenia patients’ care has evolved significantly in recent years, but the disease’s diagnosis has not, and it is still only clinically achievable with the elimination of other causes of thrombocytopenia. The lack of a valid biomarker or gold-standard diagnostic test, despite ongoing efforts to find one, adds to the high rate of disease misdiagnosis. However, in recent years, several studies have helped to elucidate a number of features of the disease’s etiology, highlighting how the platelet loss is not only caused by an increase in peripheral platelet destruction but also involves a number of humoral and cellular immune system effectors. This made it possible to identify the role of immune-activating substances such cytokines and chemokines, complement, non-coding genetic material, the microbiome, and gene mutations. Furthermore, platelet and megakaryocyte immaturity indices have been emphasized as new disease markers, and prognostic signs and responses to particular types of therapy have been suggested. Our review’s goal was to compile information from the literature on novel immune thrombocytopenia biomarkers, markers that will help us improve the management of these patients.

Novel Biomarkers for Diagnosis and Monitoring of Immune Thrombocytopenia Lower-than-normal platelet counts are a hallmark of the acquired autoimmune illness known as immune thrombocytopenia, which can affect both adults and children. Immune thrombocytopenia patients’ care has evolved significantly in recent years, but the disease’s diagnosis has not, and it is still only clinically achievable with the elimination of other causes of thrombocytopenia. The lack of a valid biomarker or gold-standard diagnostic test, despite ongoing efforts to find one, adds to the high rate of disease misdiagnosis. However, in recent years, several studies have helped to elucidate a number of features of the disease’s etiology, highlighting how the platelet loss is not only caused by an increase in peripheral platelet destruction but also involves a number of humoral and cellular immune system effectors. This made it possible to identify the role of immune-activating substances such cytokines and chemokines, complement, non-coding genetic material, the microbiome, and gene mutations. Furthermore, platelet and megakaryocyte immaturity indices have been emphasized as new disease markers, and prognostic signs and responses to particular types of therapy have been suggested. Our review’s goal was to compile information from the literature on novel immune thrombocytopenia biomarkers, markers that will help us improve the management of these patients. Adults and adolescents can develop immune thrombocytopenia (ITP), an acquired immune-mediated disease. ITP is defined by a temporary or permanent decrease in platelet count and, depending on the degree of thrombocytopenia, by an elevated risk of bleeding [1]. Due to its chronic nature, ITP has a substantially higher prevalence and has a global incidence of 1–5/100,000 [2]. The predominant pathogenetic theory, which is also supported by the test-therapeutic effects of therapies such as immunoglobulins and splenectomy, has been that antibodies cause platelet destruction. This theory about the pathophysiology of thrombocytopenia, however, has changed from an emphasis on increased platelet destruction caused by autoantibodies to more complicated processes where both decreased platelet synthesis and T-cell-mediated effects are involved [3,4] (Figure 1). In reality, the formation of autoreactive cytotoxic T lymphocytes against megakaryocytes, which impairs megakaryopoiesis, represents a distinct mechanism for ITP. Initiating events include Helicobacter pylori infections with an ambiguous mechanism and viral infections that exhibit a type of molecular mimicry. ITP can also develop as a result of immunological dysregulation in lymphomas and other systemic autoimmune disorders [5]. Over two-thirds of adult patients who receive current treatments for chronic ITP, including corticosteroids, thrombopoietin receptor agonists, rituximab, and splenectomy, see an improvement in their platelet count to a stable level. However, a deeper understanding of the pathogenesis of ITP and an earlier, more accurate diagnosis are urgently needed because some patients continue to respond insufficiently to present treatments [6]. In actuality, the emergence of autoreactive cytotoxic T cells represents a distinct mechanism for ITP. Since there is no particular biomarker at this time, the diagnosis of ITP is still an exclusion [7]. Current recommendations state that ITP can be identified in individuals with isolated thrombocytopenia, a platelet count of 100 × 109 L, anaemia or leukopenia, and no other thrombocytopenia-causing conditions [8]. In practical practice, the best proof that a patient has ITP is when he responds to therapy designed specifically for that condition. The lack of a trustworthy biomarker or gold-standard diagnostic test, despite the ongoing search for one, adds to the high likelihood of disease misdiagnosis. This review summarizes the state-of-the-art research in identifying novel biomarkers that can aid in ITP diagnosis, forecast prognosis, and direct therapeutic treatment through indices that can assess patient receptivity to potential therapies. Beginning with an understanding of the pathophysiology of the disease, the initial indicators utilized for ITP diagnosis were found. Given that ITP is an autoimmune disease, it was only natural to check for the presence of certain autoantibodies or research antigenic changes on the surface of platelets that could trigger an unwarranted immune response. By using the modified monoclonal antibody immobilization of platelet antigen (MAIPA) assay, it is possible to identify glycoprotein (GP) specific autoantibodies, such as GPVI, GPIb/IX, and GPIIb/IIIa autoantibodies, in the majority of platelet or plasma eluates from ITP patients. These antibodies bind to the targeted glycoproteins via an antigen-binding fragment (Fab), which then activates the mononuclear-macrophage or complement system [9,10]. About 75% of platelet autoantigens are concentrated in the GP IIb/IIIa or GP Ib/IX complex of the platelet. The antigenic repertoire in chronic ITP may be constrained, as evidenced by the inhibition of the binding of autoantibodies from several ITP patients by either another ITP autoantibody or a monoclonal anti-GPIIb/IIIa antibody. Multiple antibodies may be produced by many patients [11]. The accurate detection of platelet autoantibodies would support the clinical diagnosis, but their utility in the thrombocytopenia diagnostic workup is constrained by the low specificity and sensitivity of the currently available methods for platelet autoantibody testing. The development of techniques for glycoprotein-specific autoantibody detection has increased test specificity and made it acceptable to diagnose ITP but not necessarily exclude it. Even within studies utilizing assays that are similar, the sensitivity of these tests differs greatly. It is evident from numerous studies that this variation can be accounted for by variations in the test characteristics, such as variations in the glycoprotein-specific monoclonal antibodies, the glycoproteins that are tested, the platelet numbers used in the assay, and the cut-off levels for positive and negative results, as well as differences in the patient populations that were subjected to the tests. It may be able to further standardize and optimize direct autoantibody detection techniques to boost sensitivity without sacrificing specificity, but this will probably not be enough to separate the background signals from the frequently very weak specific autoantibody signals [12]. Therefore, additional advancements in autoantibody detection technologies will be required to boost sensitivity to a level suitable for ITP diagnosis. In ITP, there was a reduction in the expression of FC gamma receptors (FCGR) IIb on macrophages. The pathophysiology of ITP may be influenced by lower expression of FCGRIIb. A novel biomarker for ITP analysis may be the variation in FCGRIIb [13]. As a final point, serologic analyses for anti-nuclear antibodies (ANAs) play relevant roles in the identification of systemic rheumatic diseases. About 25–39% of ITP subjects have measurable ANAs [14], although their clinical significance is not clear. It has been reported that the positivity of ANAs in ITP subjects was associated with a more chronic course and a greater risk of developing systemic autoimmune disorders [15]. In a study, TP subjects with a positive ANA test were likely to attain a better early response to rituximab administration, while their long-term outcome was adverse. Thus, an ANA test could be useful for predicting rituximab response in ITP [16]. Similarly, ANA positivity in ITP may indicate unresponsiveness to eltrombopag treatment [17]. An increasing body of research outlines potential biomarkers that could support an ITP diagnosis. The immature platelet fraction (IPF) is one of these markers, which is easily accessible in contemporary automated haematology analysers with fluorescence capacity. Young platelets, also known as reticulated platelets, that have just been recently liberated from the bone marrow by megakaryocytes, constitute a particular population of platelets. It has been postulated that these platelets are more reactive than mature platelets because they contain modest amounts of RNA within the cytoplasm [18]. IPF determination is a low-cost, dependable, and reliable method for reticulated platelet evaluation that has made it possible to screen for and distinguish between thrombocytopenia from various causes [19]. The IPF (%) value was multiplied by the platelet count to obtain the absolute immature platelet count (AIPC) value, which represents the absolute number of reticulated platelets [20]. IPF can be precisely detected in blood samples even 24 h after they have been drawn [21], most likely because they live longer than mature platelets. Furthermore, by examining immature platelets, consumptive thrombocytopenic processes and those defined by platelet hypoproduction can be easily distinguished [22]. Thus, these counts may indicate whether the cause of the thrombocytopenia is central (originating in the bone marrow) or peripheral (originating elsewhere) [23]. The production of immature platelets does not appear to be impacted by gender [24] or age, as it continues even in older people with decreased platelet counts [25]. Different medications, however, can have an impact on IPF, and when immune responses target platelets, their levels can rise significantly over reference ranges [26,27]. According to reports, bone marrow attempts to counteract platelet destruction by significantly increasing the %-IPF to deal with the consumptive/destructive process [28,29,30]. These increases appear to be greater in people with chronic ITP [31], and these dynamics may help stratify patients at risk of bleeding as they seem to have a higher IPF level [32,33]. Immature platelets are therefore comparable to reticulocyte counts in the presence of anaemia and offer the clinician important information for treating thrombocytopenic patients. The closest thing to real-time information about the bone marrow’s reaction to the aetiology producing the thrombocytopenia is provided by these immature platelet counts [34]. In comparison to a control group, patients with ITP had a higher IPF value and a lower platelet count, according to a study. In an experiment, the IPF values were 13.80% and 3.00%, respectively, for the ITP and control group. The area under the curve for the IPF cut-off value with the highest sensitivity and specificity was 0.973, and the cut-off value was 6.3% [35]. Other studies have confirmed the possibility to use IPF to distinguish thrombocytopenia for platelet consumption, supporting its utility in research into the causes of thrombocytopenia [36]. In their investigation, Serramando et al. found that an IPF cut-off of 11.7% had a sensitivity of 88.2% and a specificity of 91.5% [37]. Their results show that IPF can assess platelet recovery in patients with thrombocytopenia and suggest that IPF has the discriminatory capability to identify the causes of thrombocytopenia. It has also been discovered that abnormal indicators of ITP megakaryocyte maturation exist. The protein biomarker known as tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily. Megakaryocyte maturation and apoptosis can both be aided by TRAIL. It was shown that reduced platelet formation in ITP was caused by low expression of TRAIL in megakaryocytes. Megakaryocyte TRAIL expression was downregulated, as were patient TRAIL concentrations. A proposed mechanism by which the megakaryocyte number increases in vitro may be the megakaryocyte death caused by TRAIL in the plasma of ITP patients [38]. An alteration of megakaryocyte maturation indices could be a useful parameter for the evaluation of bone marrow replicative dynamics. Some chemokines also appear to encompass a fundamentally similar meaning in terms of cellular maturity. Chemokines are tiny proteins that attach to receptors on different leukocyte types to regulate chemotactic activity and the movement of cells. Chemokines are classified into the C, CC, CXC, and CX3C families based on the conserved cysteine motif, with the CC and CXC chemokines receiving the most attention [39]. Several members of the CXC family, such as CXCL12 and its ligand (CXCR4), contribute to migration, homing, proliferation, and survival of hematopoietic stem cells [40]. Wang et al. investigated the megakaryocyte lineage from CFUMeg to platelets and found that CXCR4 was expressed in these cells [41]. In their research, flow cytometry analysis of this receptor’s expression revealed that CXCR4 expression increases with maturation and becomes virtually uniform in the final stages in circulating platelets, exhibiting the greatest expression level in circulating platelets. In a study, real-time PCR was used to examine CXCR4 gene expression in ITP patients both before and after treatment. Commonly, corticosteroids (prednisone, prednisolone, dexamethasone, or methylprednisolone) or immunoglobulins (IVG) are used as the first-line treatment. All of the patients in this study were new cases; therefore, they all received first-line treatment for a duration of 5–7 days. The expression of the CXCR4 gene showed a significant decrease in comparison with the control group, while its expression did not change before or after treatment [42]. However, the CXCR4 level is likely different in acute and chronic ITP and also in different stages of disease progression. Moreover, several studies have examined the role of this chemokine receptor in various diseases, including systemic lupus erythematosus, HIV and hematologic malignancies such as acute myeloid leukemia, acute lymphoid leukemia, essential thrombocythemia and aplastic anemia. Although CXCR4 is likely to be a mediator with several cellular functions in different stages of maturity of platelets and megakaryocytes, the use of this biomarker must take into consideration these data and the possibility that an alteration of the chemokine expression may be attributable to other causes. However, a different meaning could be the analysis of a different chemokine. A tiny cytokine from the CXC chemokine family, CXC chemokine ligand-13 (CXCL13), is mostly released by secondary lymphoid tissue, lymph glands, and serum follicular dendritic cells [43]. B1 cell homing, the synthesis of natural antibodies, and body cavity immunity all depend on CXCL13 [44]. Additionally, it has been noted that CXCL13 is a therapeutic target for a number of immunological illnesses and it is essential for the recruitment of B cells and T-cell subsets in pathological situations [45]. ITP patients had higher levels of CXCL13, according to research [46]. Children with ITP reported increased plasma CXCL13 compared to controls; however, this concentration decreased after treatment. Dexamethasone reduced CXCL13 levels in vitro in a dose- and time-dependent manner. As for the mechanism, it was demonstrated that in CD4+ T cells, miR-125-5p mimics lowered the CXCL13 level, whereas an miR-125-5p inhibitor boosted the CXCL13 level. MiR-125-5p was suggested to have CXCL13 as a target gene. A reduction in CXCL13 caused by dexamethasone was likewise prevented by the miR-125-5p inhibitor. The miR-125-5p target gene, CXCL13, may play a role in the pathogenesis of ITP and also serve as a disease marker [47]. Finally, immune problems and significant heterogeneity were present in ITP patients with CCR7, and it was shown that CCR7 was implicated in the disease’s development. In comparison to healthy controls, pretreatment ITP patients had higher CD4/CD8 ratios, lower levels of NK cells and CD4+CD25+CD127low Tregs, and lower levels of NK cells. In comparison to the relapsed group, the newly diagnosed group showed a greater CD4/CD8 ratio and more NK cells. Treg levels were higher in the group experiencing remission than in the group experiencing recurrence. When compared to controls and the remission group, the newly diagnosed and relapsed groups showed larger increases in the CD4+CCR7+, CD8+CCR7+, and CCR7+ subsets of B cells and NK cells. In comparison to the newly diagnosed group, the values for the CD4+CCR7+ and CD8+CCR7+ subsets in the relapsed group were marginally higher. When compared to the relapsed group, the CCR7+ subsets of CD4+ T-cells, CD8+ T-cells, NK cells, and B cells in the remission group had lower levels. The remission group had higher levels of the CD8+CCR7+ subset and lower levels of NK cells than the controls. ITP patients had a lower ratio of the CD4+CCR7+ to CD8+CCR7+ subsets than did healthy controls. The CD8+CCR7+ subgroup and platelet count in ITP patients had a negative correlation [48]. As our understanding of the aetiology of ITP has increased, other diagnostic indicators have been identified. The family of tumour necrosis factor ligands member B-cell activating factor (BAFF), also known as B lymphocyte stimulator, is essential for maintaining proper B-cell growth, homeostasis, autoreactivity, and T-cell costimulation [49,50]. It has been demonstrated that BAFF promotes CD19 expression and mediates the development of autoreactive B cells [51,52,53]. It has been reported that high BAFF can prevent the death of autoreactive B and T cells [54]. Compared to patients in remission and controls, individuals with active illness showed greater levels of plasma BAFF and BAFF mRNA. In in vitro tests, rhBAFF promoted the survival of of CD8+ and CD19+ cells. These results imply that BAFF may contribute to the pathogenesis of ITP by enhancing CD19+ and CD8+ cell survival, and enhancing platelet death. The importance of BAFF expression in pediatric ITP patients was recently assessed by a study. Three groups of pediatric ITP patients have been selected. Group I contained patients with acute ITP, group II patients with persistent ITP, and group III formed by healthy controls. Compared to controls, BAFF expression levels considerably increased in ITP patients. Groups I and II, however, had equivalent BAFF expression values [55]. These findings support BAFF’s potential involvement in the illness and its inclusion in the diagnostic constellation. The fundamental cause of ITP’s onset is immunological tolerance. More cytokines have been linked to ITP in recent years, according to research. The factors that can distinguish ITP from other types of thrombocytopenia and serve a specific role in the diagnosis of ITP. All immune-mediated thrombocytopenias, except for primary ITP, are classified as secondary ITP. Numerous diseases can cause secondary ITP, including autoimmune conditions such as systemic lupus erythematosus (SLE). SLE is a complex autoimmune illness that is frequently accompanied by hematological abnormalities [56], such as thrombocytopenia, which has been estimated to affect 7–30% of SLE patients [57,58]. It might be challenging to identify the kind of platelet reduction present in individuals with SLE in the initial stages when there are only thrombocytopenia symptoms [59]. Thrombocytopenia in SLE has a varied and complicated aetiology. However, it is generally acknowledged that the pathogenesis is aided by enhanced platelet clearance caused by platelet-specific autoantibodies, which is a mechanism similar to ITP [60]. There are 11 members of the interleukin (IL)-1 cytokine family of protein molecules, including IL-1 (IL-1F1), IL-1 (IL-1F2), IL-1 receptor antagonist (IL-1Ra, IL-1F3), IL-18 (IL-1F4), IL-36Ra (IL-1F5), IL-36 (IL-1F6), IL-37 (IL-1F7), and IL-36 (IL-1F8). The pathophysiology of SLE and ITP may be influenced by aberrant alterations in IL-18 and IL-18-binding protein (IL-18BP), according to several studies [61,62,63,64]. Furthermore, current research shows that IL-1 may contribute to the production of T-helper 17 (Th17) cells, which have been found to be more prevalent in individuals with SLE and ITP. This suggests that IL-1 may possibly have a role in inflammatory pathologies and autoimmune disorders [65,66]. In a study, IL-1 cytokines were measured in newly diagnosed ITP patients, SLE patients with thrombocytopenia (SLE-TP), SLE patients without thrombocytopenia (SLE-NTP), and healthy controls using a multiplex cytokine assay and RT-PCR [67]. In contrast to SLE-TP patients, SLE-NTP patients, and healthy controls, ITP patients had significantly lower serum levels of IL-1, IL-18, and IL-36. There was a favourable link between the platelet count and IL-37 level in ITP patients, despite the fact that there was no discernible difference in the serum level of IL-37 between ITP and SLE-TP patients. These findings suggested that blood levels of IL-1, IL-18, IL-36, IL-36 and IL-37 could serve as ITP biomarkers. As a result, blood levels of IL-1, IL-18, IL-36, and IL-36 could be used as biomarkers to distinguish SLE-TP patients from ITP patients [67,68]. These results deserve some comments. ITP and SLE-TP are both caused by antibodies that attack platelets; however, it is unclear what makes them different. Differences between ITP and SLETP patients’ peripheral blood absolute lymphocyte counts and neutrophil counts in this study point to distinct cellular immunity. IL-1, IL-18, IL-36, IL-36, and IL-33 are implicated in the aetiology of ITP but not SLE. The expression of IL-1 mRNA between ITP patients and SLE-TP patients did not differ significantly, which is an interesting finding. ITP and SLE-TP patients’ changes in IL-1 cytokine expression at the mRNA level did not match those seen at the protein level. Thus, it might be possible to infer from these findings that microRNAs and other post-transcriptional regulatory mechanisms may contribute to the pathophysiology of ITP and SLE-TP patients. Furthermore, in ITP patients, several other cytokines were shown to be changed. Interleukin (IL)-2 and interferon (IFN)-gamma levels were found to be higher in the serum, whereas IL-4 levels were noticeably lower. Thrombopoietin (TPO) levels have also been found to be normal, while increased levels of IL-11 have been noted [69]. These findings show that the Th1 type of T helper cytokine response is linked to ITP, but the Th2 type is downregulated. Megakaryocytes are initially found in bone marrow aspirates at normal quantities, which explains why TPO production is unaltered. The increased production of platelets per megakaryocyte may be a reflection of the rise in IL-11. Therefore, the cytokine profile and lymphocyte populations appear to be characteristic in the various forms of thrombocytopenia and could constitute a valid support for the differential diagnosis of the various pathologies. Several data revealed that more than 90% of the human genome could not be translated into proteins. Noncoding RNAs (ncRNAs), including long noncoding (lnc) RNAs and microRNA (miRNAs), are crucial in the development of human disorders [70]. MiRNAs are a subclass of ncRNAs that target the 3-UTR of mRNAs to control gene expression and protein translation [71,72]. Previous research revealed that miRNAs were dysregulated and connected to the control of ITP. For instance, miRNA-99a expression was augmented in CD4+ cells [73], while miRNA-182-5p and miRNA183-5p expression was augmented in ITP. Furthermore, in ITP, TGFB1 and IL18 were downregulated and inhibited by miRNA130A [74]. MiRNA409-3p was similarly noted to be decreased in ITP samples at the same time [75]. Additionally, lncRNAs were linked to autoimmune disorders and their symptoms. Wang et al. discovered that the expression of the lncRNA TMEVPG1 was lower in ITP subjects with respect to samples from healthy control subjects [76]. In a different study, 1177 and 632 lncRNAs were shown to be significantly up- or down-regulated in ITP patients, as compared to normal samples [77]. In an experiment that examined many open-access datasets, including GSE43177 and GSE43178, it was discovered that ITP patients had 468 upregulated mRNAs, 272 downregulated mRNAs, 134 upregulated lncRNAs, 23 downregulated lncRNAs, 29 upregulated miRNAs, and 39 downregulated miRNAs. After that, authors created networks in ITP for the coexpression of lncRNA, miRNA-mRNA, and protein-protein interactions. A bioinformatics investigation revealed that these genes controlled several biological functions in ITP, including translation, cell-cell adhesion, ubiquitin-mediated proteasome degradation, and mRNA nonsense-mediated decay. As a result, patients with ITP appear to have a particular profile of miRNAs, which may be helpful for a more accurate diagnosis. However, it is worth noting that most of the results reported have not been reproduced, which may be due to diverse blood sources, or different population sizes, as well as the use of different RNA isolation and identification procedures. Thus, standardized detection schemes are needed in the next years, comprising more sensitive miRNA detection techniques and quantitative analysis models, while a consensus on the clinical significance of a few targets is necessary for their use in clinical practice [78]. Numerous autoimmune illnesses present an altered gut microbiota, which was even recognized as one of their aetiologies. The human gut is home to more than one thousand different types of bacteria, which are crucial to both health and sickness [79,80,81,82,83]. The gut is where over 60% of human immunity is controlled. Mice raised in a germ-free environment have a weak immune system, and their immune cells significantly diminish. Recent research has revealed a connection between changes in the gut microbiota’s composition and functionality and illness symptoms, severity, and treatment response [84]. The therapeutic benefit of probiotic supplementation or fecal microbiota transplantation in individuals with autoimmune disorders is significant [85]. Additionally, several extraintestinal autoimmune diseases and immunological disorders, such as rheumatoid arthritis, type 1 diabetes, multiple sclerosis, and systemic lupus erythematosus, have been linked to gut microbiota [86]. The gut microbiome may also influence ITP. In a study, the metabolite profiles and gut microbial community were examined using feces from adult primary ITP patients who were untreated and healthy controls (HCs) [87]. According to the findings, ITP patients have lower levels of Bacteroides and higher levels of the fecal bacteria Blautia, Streptococcus, and Lactobacillus. Notably, fecal metabolites such as glycerophospholipids and fatty acids are enriched and intensely correlate with discrepant gut microbiota. Weissella and Streptococcus anginosus, Cer (t18:0/16:0), Cer (d18:1/17:0), and 13-hydroxyoctadecanoic acid mixtures may also be effective diagnostic indicators for ITP [87]. In conclusion, compared to HCs, ITP patients experience dysbiosis of the gut microbiota and metabolome. Several gut chemicals and bacteria changed by ITP can serve as ITP diagnostic biomarkers. An essential mechanism of platelet destruction is complement activation caused by anti-GPIIb/IIIa [88,89,90,91,92,93,94,95]. The complement system, a mostly blood-born protein cascade, has its evolutionary roots in homeostasis and innate immune protection [96]. ITP has been linked to shady levels of platelet-associated complement [97,98,99,100]. However, there have only been a few reports of studies on the regulation and specificity of complement activation [101]. In ITP patients with anti-GPIIb/IIIa antibodies, complement activation and improved complement activation capacity (CAC) were found both in vivo and in vitro studies. Patients in this group demonstrated decreased plasma levels of 2-GPI, which was negatively linked with C5b-9 deposition. Approximate physiological quantities of 2-GPI suppressed C5b-9 production in a dose-dependent manner [102] (Table 1). Inhibition of C3a production by β2-GPI and the presence of β2-GPI/C3 complexes in plasma suggested a control on the level of the C3 convertase. Additionally, c-Jun N-terminal kinase (JNK) phosphorylation levels were downregulated by 2-GPI, as was the cleavage of the BH3 interacting domain death agonist (Bid), which led to platelet lysis. These data suggest a unique relationship between decreased plasma 2-GPI levels and increased complement activation, suggesting that 2-GPI may be useful as a diagnostic biomarker. Finally, anti-complement 1q antibody (anti-C1q), complement factor H (CFH), complement fragments Bb (CFBb), stromal-derived factor-1 (SDF1, also known as CXCL12), and IL21 plasma levels were examined by Sahip et al. to see if there was any correlation between them and the clinical characteristics of ITP. Patients with ITP had lower levels of CFH and CFBb and greater levels of anti-C1q compared to controls. The alterations in and CFH levels following treatment support the idea that the complement system plays a role in the pathogenesis of ITP [103]. Finally, research that uses genetic analysis to find novel diagnostic indicators in ITP patients is extremely encouraging. The greatest number of platelet transcriptome samples were collected in a recent study. Using RNA sequencing (RNA-seq) transcriptomes, a thorough process of feature selection, feature engineering, and stacking classification was conducted to find the ITP biomarkers [104]. The final ITP detection model was trained using the 40 discovered biomarkers, and its overall accuracy was 0.974. The biomarkers revealed that a number of transcribed elements, such as protein-coding genes, long intergenic non-coding RNA genes, and pseudogenes with apparent transcriptions, may be linked to the start of ITP. The provided ITP detection model can also be used to diagnose ITP. Numerous biomarkers displayed expression patterns that were highly tissue-specific; for example, the genes DNAH7 and AANAT were only strongly expressed in the testis, whereas the gene KLHDC8A was only highly expressed in the ovary. DNAH10OS, NORAD, MT-ATP8, HNRNPUL2, MT-RNR2, and MT-CO2 were among the genes with high expression in various brain regions, although the majority of the 40 biomarkers had relatively low expression in the total blood. It is critical to look into the molecular processes of ITP employing platelet cells since the data revealed that the abnormal expressions of these tissue-specific expressed genes may have contributed to ITP’s development and progression when combined with their ITP-specific expression patterns. Even after receiving many lines of single-agent medications, some ITP patients continue to not react to conventional treatments, despite therapeutical advancements. Refractory ITP is linked to a severe decline in quality of life and extremely challenging therapeutic care. To make matters even more difficult, clinicians’ experience is crucial to properly treating refractory ITP because the diagnosis is still based on exclusion [105]. About 10% of ITP patients become resistive to treatment within a year, according to Psaila et al. [7]. In these situations, the lack of a clinical response calls into serious doubt the diagnosis of ITP [106] and should prompt a thorough clinical and laboratory work-up [107] to rule out other underlying illnesses, particularly myelodysplastic syndromes, drug-induced thrombocytopenia, inherited thrombocytopenia, and bone marrow failure syndromes. Additionally, type IIB von Willebrand disease and pseudothrombocytopenia should be ruled out. Refractory ITP has been defined in several ways over the years. Refractory ITP used to typically be predicated on the absence of response or relapse following splenectomy. More specifically, failure to reach a platelet count of 30,000/L and a doubling of baseline platelet counts were used by Rodeghiero et al. to determine response [108]. The 2010 ASH guidelines [109] affirmed and supported this description of refractory ITP. However, splenectomy is not an option for a sizeable percentage of ITP patients, especially those who are elderly or have other serious comorbidities. Additionally, people may be reluctant to have a splenectomy and decline the treatment. Additionally, its pediatric indication is poor [110]. Cuker et al. expanded the definition of refractory ITP to include patients who need treatment but are unable or unwilling to have a splenectomy [111], while a complete lack of response to one or more single-agent treatments, such as rituximab and TPO-RA, was the definition of refractory ITP in 2020 [20]. Shortly after, Miltiadous et al. defined “refractory” patients as those whose platelet counts do not respond to more than two treatments, and whose platelet counts are extremely low and are accompanied by haemorrhage [112]. Therefore, it is clear how important it is to have accurate indicators that can forecast how the disease will progress. Insidious onset, a higher platelet count at presentation, female gender, older age at presentation, a lack of prior infection or vaccination, positivity for antinuclear antibodies (ANA), and an inability to respond to a single dose of intravenous human immunoglobulins are all thought to be predictors of the chronic course of the disease. According to some results, children with chronic ITP have a strong family history of the condition [113]. Additionally, there is proof that ITP is inherited, with some immune-related genes perhaps playing a role [114]. The clinical characteristics and genetics of chronic refractory immune thrombocytopenia (C/RITP) in infants, as well as their significance in treatment refractoriness, have, however, received very little research attention. In a study, children with C/RITP who had immune-related gene mutations were examined for their clinical symptoms and genetic traits [115]. Children in the mutant group had more severe hemorrhages, more aberrant immunological indices, and greater levels of SLE biomarker expression. The mutant group’s peripheral T and B lymphocyte counts dramatically increased. TNFRSF13B, CARD11, CBL, and RAG2 are four genes linked to primary immunodeficiencies which are mutated in 17.6% of patients, while 23 other genes had variants in 82.4% of patients that were of unknown importance [115]. The mutant group’s elevated risk of several aberrant immunological phenotypes could be a sign of a hereditary propensity for immunodeficiencies. Immune problems manifested early in the mutation group of patients. Theoretically, this implies that they require more frequent immunosuppressive therapy and the utilization of second-line therapies, and that the prognosis for these kids is worse. The inflammasome complex was subjected to a separate genomic investigation. The well-studied inflammasome NLRP3 (NOD-like receptor pyrin domain-containing protein 3) is a component of the innate immune system that reacts to cellular stress by releasing the proinflammatory cytokines IL-1 and IL-18. Numerous inflammatory and autoimmune illnesses, including diabetes, obesity, and atherosclerosis, are triggered by the NLRP3 inflammasome [116,117]. ITP patients’ gene expression and polymorphisms for the NLRP3 inflammasome were examined using RT-PCR [118]. By using flow cytometry, T helper cells and apoptosis of peripheral blood mononuclear cell (PBMC) from ITP patients were examined. The NF-B-94ins/del ATTG genotype was found to contribute to ITP susceptibility, according to the results. Additionally, ITP patients with the WW genotype or WD genotype had lower platelet counts than ITP patients with the DD genotype of NF-B-94ins/del ATTG. ITP patients with the WW or WD genotype showed higher mRNA expression than those with the DD genotype when compared to controls for NF-B gene expression. Similar to this, the WW genotype also showed enhanced NLRP3 mRNA expression. In the group that was not stimulated, there was no discernible change in the percentage of Th17 cells for the genotypes WW, WD, and DD (WW WD DD), although there was a substantial gene dosage effect. In ITP patients, activation of the NLRP3 inflammasome may upregulate Th17 [118]. In summary, the NF-B-94ins/del ATTG genotype may be a new biomarker and possible target for ITP. Circulating microparticles (MPs), which are extracellular vesicles (EVs) that cells release in response to activation or stress, are an alternative, potential biological marker. MPs carry particular sets of proteins, lipids, and RNAs that may serve as a communication medium between cells, depending on their biological origins [119,120]. The glycoproteins CD41 and CD42b as well as phosphatidylserine are some of the surface indicators that platelet-derived microparticles (PMPs) and megakaryocyte-derived microparticles (MKMPs) have in common. However, PMPs can be separated from MKMPs by the expression of CD62P [121]. In the meantime, higher PMP levels have been linked to ITP and have been reported to give some ITP patients procoagulant characteristics [122,123]. It has been discovered that MKMPs, which are generated during megakaryocyte maturation [124], can stimulate platelet formation without the need for additional TPO [125,126]. According to these results, MKMPs could be used as biomarkers to monitor megakaryocyte dynamics and as a potential ITP treatment. Megakaryocyte maturation in ITP patients has also been found to be hindered in previous bone marrow smear and ultrastructural examinations [127]. In numerous autoimmune disorders, altered cell-derived microparticles (MPs) have been seen. However, little research has been performed on the functions of MKMPs and PMPs produced from megakaryocytes and platelets in ITP. Researchers analysed plasma MKMP and PMP levels in ITP patients and assessed the studies’ potential diagnostic utility [128]. In a discovery set of ITP patients, non-immune thrombocytopenia (TP) patients, and age- and gender-matched healthy controls, plasma MKMP and PMP levels were examined by flow cytometry. The effectiveness of the thrombopoietin receptor agonist (TPO-RA) therapy was evaluated using samples from a therapy group of ITP patients. The findings showed that plasma MKMP and PMP levels were greater in TP patients but significantly lower in ITP patients compared to healthy controls. The PMP/platelet ratios in ITP patients were higher than those in TP patients and healthy controls after normalization to platelet counts. PMP/platelet ratios had a 73.1% sensitivity and 77.3% specificity for diagnosing ITP. With a sensitivity of 74.4% and a cut-off value of 112.5 MPs/L, MKMP levels can be utilized to distinguish between ITP and TP. In addition, ITP patients who responded to TPO-RA treatment had higher MKMP and PMP levels [128]. According to these findings, plasma MKMP and PMP levels are lower in ITP patients, and they are also new prognostic biomarkers for ITP. Finally, prognostic markers that can reveal a cell’s capacity for reproduction may be valuable. The repeating TTAGGG repeats and accompanying proteins, collectively known as the shelterin complex, make up the specialized DNA-protein structures known as telomeres, which are found at the ends of linear chromosomes in eukaryotic cells. The cellular DNA-repair machinery uses the shelterin complex as a signal to discriminate between telomeres and DNA double-strand breaks [129,130]. Thus, the telomeres play a role in replication as well as the preservation of genomic and cellular stability [131]. In fact, there is an “end-replication problem” because ordinary DNA polymerases are unable to properly copy the ends of a linear DNA molecule, causing telomere shortening with each cell division. Telomere length can therefore be seen as a measure of cell proliferation history and lingering potential for replication [132,133,134]. Additionally, lymphocyte telomere length can affect immunological response [135]. Telomere shortening in lymphocytes is thought to signify immune system aging and may be a risk factor for autoimmune reactions [136]. Comparing CD4+, CD8+, and CD19+ lymphocytes from ITP patients to those from healthy controls, telomerase activity was shown to be higher [137]. In ITP patients, there was a slight negative connection between platelet count and telomerase activity of CD19+ cells. In comparison to the healthy controls, the relative telomere length of PBMC in ITP patients was considerably shorter. Telomere length of PBMC was shown to be considerably shorter in active ITP patients compared to controls, and it also tended to be shorter in inactive ITP patients [137]. In addition to the initial platelet count and the severity of the bleeding, telomere length is an independent predictor for the prognosis of ITP in this study. Patients with lower telomere lengths are more likely to get chronic ITP. On the other side, people with ITP who have telomeres that are longer typically have better prognoses. High-dose glucocorticoids are advised as the first-line treatment for adult ITP patients, according to consensus clinical recommendations [107]. Clinical problems, however, include frequent side effects and varied responses, with 20–30% of patients failing to react at safe levels [138]. Mycophenolate or rituximab may be added to glucocorticoids to boost response rates, although these drugs have lower a quality of life and more side events [139,140]. Predicting which patients are likely to fail glucocorticoid monotherapy and who would benefit from early supplemental treatment would therefore be clinically useful. When taking the immunological aetiology of the pathology into account, it is clear that a particular cytokine composition and a certain profile of the cell populations may be suggestive of a different response to immunosuppressive therapy. For instance, in the absence of the anti-inflammatory cytokine IL-10, cells that express the pro-inflammatory cytokines IL-17 and IFN-c are resistant to inhibition [141,142]. Additionally, activated CD4+ T cells from glucocorticoid-refractory ITP patients demonstrated a relative abrogation of IL-10 with persisting IL-17 in response to in vitro glucocorticoids compared to responsive individuals [143]. Furthermore, numerous cytokine gene polymorphisms, such as certain IL-10 and IFN- genotypes, have been linked to the efficiency of corticosteroid therapy in ITP [144,145]. CD4+ T cells from ITP patients were cultured in the presence or absence of dexamethasone (Dex) in a prospective cohort study [146]. The clinical response of the patients to corticosteroid therapy was then compared with intracellular cytokine expression. To determine whether findings were specific to ITP or if they might be applicable to other autoimmune disorders, a control cohort of patients with autoimmune uveitis was also investigated. Following CD4+ T cell culture with Dex, the ratio of IL-10 to IL-17 expression was able to distinguish between ITP patients with a clinically defined full, partial, or nonresponse to corticosteroid treatment. Patients with autoimmune uveitis confirmed these findings [146]. As a result, IL-10 expression has decreased somewhat, but IL-17 expression has persisted in the CD4+ T cells of subjects who clinically fail steroid treatment. This finding may help us better understand how corticosteroids work to treat ITP and serve as a biomarker for steroid-resistant disease, with potential applications to a variety of hematological and nonhematological disorders. Another study found that non responder (NR) patients’ ex vivo CD4+ T cells had a decreased IL-10:IL-17 ratio. Results from samples that were followed up after two months support this conclusion [147]. This implies that CD4+ T cells from NR patients tend to produce higher levels of IL-17 and lower levels of IL-10 over time. The stimulation of IL-10 in a variety of immune cell types, such as CD4+ and CD8+ T cells, as well as B cells, is most likely a crucial factor in the effectiveness of glucocorticoids [148,149,150]. The discovered ex vivo T cell profile might be transformed into a clinically useful biomarker to help identify NR patients, which could then guide the clinical choice to start alternative therapy early. Antibody specificity (i.e., anti-GPIIbIIIa versus anti-GPIb-IX) may play a significant role in dictating the response to therapy in ITP, with the presence of anti-GPIb-IX antibodies resulting in a decreased response to corticosteroids and IVIG, according to murine models and large cohort human studies published in recent years [151,152,153]. Most recently, a study found that anti-GPIb and some anti-GPIIbIIIa antibodies in humans caused platelet desialylation, which then led to Fc-independent platelet clearance in the liver through hepatic asialoglycoprotein Ashwell-Morell receptors [154]. This finding raises the possibility that antibody-mediated desialylation may be one of the underlying mechanisms behind resistance to steroid and intravenous immunoglobulin G treatment [155]. The removal of the terminal sialic acid residues from glycans, which starts the catabolism of glycans, modifies the structure and functions of glycans, glycoproteins, or glycolipids. Desialylation is a crucial component of sialic acid metabolism. The roles of sialic acids are well understood, while those of the desialylation process are either poorly understood or completely neglected. Nevertheless, mounting proof shows that desialylation is crucial for several physiological and pathological activities. Recent research has revealed a unique Fc-independent platelet clearance pathway, in which antibody-mediated desialylated platelets can be removed in the liver via asialoglycoprotein receptors, decreasing the response to first-line treatments that target Fc-dependent platelet clearance [156]. The study compared the levels of platelet desialylation with the effectiveness of first-line therapy to assess the importance of this result in ITP patients. They discovered that there was a statistically significant difference in desialylation levels between various treatment response groups. Importantly, correlation analysis showed a relationship between treatment response and platelet desialylation, with non-responders having considerably greater platelet desialylation levels. Interestingly, they discovered substantial platelet desialylation in secondary ITP and some non-ITP thrombocytopenias, as compared to healthy controls [156]. According to these findings, platelet desialylation is a crucial biomarker for assessing how ITP responds to conventional therapy. As for the mechanism, at asparagine 297, the Fc component of IgG has a distinctively conserved glycosylation site (Asn297). Through the alteration of the IgG Fc binding affinity for Fc receptors (FcRs) and the complement protein C1q complex, the precise composition of the attached N-glycan influences IgG-mediated effector functions such as antibody-dependent cell-mediated cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP) [157]. Inflammatory and autoimmune illnesses may be exacerbated by the glycosylation of IgG Fc, which is essential for controlling IgG’s pro- and anti-inflammatory actions. Numerous autoimmune and inflammatory conditions, including rheumatoid arthritis, systemic lupus erythematosus, inflammatory bowel disease, and autoimmune hemolytic anemia, have been shown to have skewed IgG glycosylation patterns [158,159,160,161]. In some cases, the skewed IgG glycosylation is linked to the severity of the condition and how well it responds to treatment [162,163]. In a study, the N-glycan profiles of serum proteins and the purified IgG fraction were compared between ITP patients and healthy controls. The study also looked into the relationships between N-glycans and platelet counts, and found that ITP patients had unique N-glycan patterns in both their serum and IgG [164]. Serum fucosylation, IgG galactosylation, six of twelve of serum N-glycan peaks, and six of seven IgG N-glycan peaks were all substantially different between ITP patients and healthy controls. IgG peak seven demonstrated good diagnostic performance in separating ITP patients from healthy people. Serum fucosylation was considerably reduced in ITP patients with severe thrombocytopenia compared to ITP patients with mild and moderate thrombocytopenia. In ITP patients with severe thrombocytopenia, serum fucosylation and serum peak five were linked with platelet counts, and the absolute values of the correlation coefficients were both over 0.5 [164]. Patients with ITP showed distinct N-glycan patterns in their serum and IgG. A potential biomarker for supplementary ITP diagnosis was IgG peak seven. A different study investigated the role of Asn279-linked N-glycan of auto antibodies in vitro and in vivo. AAb-induced platelet phagocytosis was inhibited by N-glycan cleavage. Injection of AAbs resulted in the rapid clearance of human platelets compared to control. Auto antibodies that were able to activate complement induced more pronounced platelet clearance in the presence of complement compared to the clearance in the absence of complement. Auto antibodies lost their ability to destroy platelets in vivo after deglycosylation. N-glycosylation of human ITP auto antibodies appears to be required for platelet phagocytosis and complement activation, reducing platelet survival in vivo. Posttranslational modification of auto antibodies may constitute an important determinant for the clinical manifestation of ITP [165]. Moreover, the relationships between n-glycan and other molecules, such as haptoglobin, appear to be particularly interesting. In fact, altered glycosylation patterns of plasma proteins are associated with autoimmune disorders and the pathogenesis of various diseases, and n-glycan can fine-tune Hp interactions [166]. A study sought to assess lymphocyte attraction as a potential additional factor in the aetiology of ITP. The TNF superfamily and the Toll-like receptor (TLR) family are two families of adaptor proteins that have biological activities that include cellular death, survival, and immunological responses [167]. Through pathways such as TRAF6, signals from receptors including CD40, RANKL, and IL-1 have been conveyed. TRAF6 has been associated with several diseases, including myeloma and myelodysplastic syndrome, due to its role in attracting lymphocytes and transmitting inflammatory signals [168,169]. With the potential for utility in the therapeutic setting as a biomarker of corticosteroid or IVIG response, a study was conducted to assess the importance of TRAF6 as an immune-signaling component in the aetiology of ITP [170]. TRAF6 levels were different in the patient group and in the control group (2348 pg/mL vs. 25.57 pg/mL) and levels were lower in corticosteroid-responding patients than in nonresponding patients. This finding points to a direct connection between TRAF6 and the pathophysiology of ITP [170]. The understanding of TRAF6 in the antibody-mediated immune system did correlate with these findings. Corticosteroid responses were weak among patients with the highest TRAF6 levels, according to the investigators’ observations. Patients with the highest TRAF6 levels, on the other hand, reacted to IVIG more quickly. These connections suggested that TRAF6 and the degree of immunological reactivity in the context of the antibody-mediated system may be connected. As a result, it is possible to evaluate TRAF6 patients at the time of the initial presentation and forecast a response to corticosteroids as well as to other treatment modalities such as rituximab, IVIG, and splenectomy. A different therapeutic option for ITP patients who do not react to glucocorticoid therapy or who need ongoing high-dose glucocorticoids to maintain a safe platelet count is splenectomy. According to the findings of various research, splenectomy is effective in about two thirds of adult patients and 70 to 80 percent of youngsters [108]. Splenectomy for ITP, however, is frequently linked to a high risk of serious morbidity and mortality, and the long-term haematological results of the treatment cannot be anticipated using commonly used indicators [171]. Younger age [172,173,174], prior response to steroids, and postoperative peak platelet count [175,176] have all been reported in several studies as potential predictors of a sustained response to splenectomy. However, the findings of other investigations were contradictory [177,178,179]. The location of autologous 111In-labeled platelet sequestration was discovered to be a reliable prognostic factor by Najean et al. [180]. However, isotope assessment methods are frequently qualitative rather than quantitative, and splenectomy is effective for many individuals with non-splenic sequestration. Hepatocytes in the liver produce most of the acute phase protein known as haptoglobin (HP). IL-6, which is created by the key cytokines TNF- and IL-1, is the main factor that stimulates the expression of Hp [181]. Serum levels of Hp are usually quite stable; hence, finding a noticeable variation in serum Hp expression has clinical importance [182]. Hp is made up of two polypeptide chains. Only one kind of chain exists, and it has a MW of roughly 40 kDa. Two isoforms of the chain, however—designated as -1 and -2—represent the chain; the MW values for -1 and -2 are, respectively, 16 kDa and 9 kDa [183]. Recent proteomic research demonstrated the significance of Hp as a biomarker in a few autoimmune disorders. The cerebral fluid of patients with Guillain-Barré syndrome, an acute inflammatory autoimmune illness of the peripheral nerve system, has elevated amounts of the protein Hp. According to other investigations, systemic lupus erythematosus and active Behcet’s illness both have increased disease activity when there are raised serum levels of Hp [184,185]. In one investigation, serum samples from ITP patients were taken both before and seven days after the splenectomy [186]. Pooled preoperative serum samples from patients who responded to splenectomy, patients who did not respond, and healthy controls were subjected to two-dimensional gel electrophoresis following the depletion of the abundant serum proteins. By using matrix-assisted laser desorption/ionization time-of-flight mass spectrometer analysis, nine protein spots with at least a five-fold difference in expression between responders and non-responders were all identified as Hp. Thirty-seven responders, thirteen non-responders, and twenty-one healthy controls underwent enzyme-linked immunosorbent tests to validate the expression of serum Hp. The non-responders had considerably lower preoperative serum levels of Hp than the responders. The preoperative platelet counts and preoperative serum levels of Hp did not significantly correlate; however, they did positively correlate with postoperative peak platelet counts. The receiver operating characteristic curve’s best cut-off value for preoperative serum Hp levels (1173.80 g/mL) resulted in 78.4% sensitivity and 84.6% specificity [186] (Table 2). Hp has been proven to modulate both innate and adaptive immune responses in several aspects. Th1 and Th2 play a crucial role in the pathogenesis of autoimmune diseases. Studies performed both in vitro and in vivo indicate that Hp exhibits a significant modulating impact on the Th1/Th2 balance via an inhibitory effect on Th2 cytokine release and therefore promotes a dominant Th1 cellular response. In a study, HP was identified as a potential serum biomarker, which may serve as a major predictor of the long-term response to splenectomy in ITP patients [186]. These findings imply that serum Hp levels could be a useful predictor of the long-term success of splenectomy in ITP and could shed light on the pathophysiological distinctions between responders and non-responders. Finally, given the wide range of consequences that this topic entails, a distinct section should be set aside to discuss the connection between ITP and oxidative stress. Free radicals are molecules or molecular fragments that have one or more unpaired electrons in atomic or molecular orbitals and are highly reactive [187]. Reactive oxygen species (ROS) are by-products of normal cellular oxygen metabolism by enzymatic reactions, such as the mitochondrial respiratory chain, nitric oxide synthases, xanthine oxidase, or NADPH oxidases [188]. ROS can also result from exposure to extracellular stressors such as radiation and inflammatory cytokines. The majority of a cell’s mitochondria produce the superoxide anion radical, which can then combine with other molecules to produce secondary ROS such as hydrogen peroxide and hydroxyl radicals [189]. Through the generation of peroxides and free radicals that harm all cell components, disturbances in this normal redox state can have harmful effects [190]. Antioxidants and antioxidant enzymes including catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD) are in charge of controlling this redox state to prevent cellular damage [191]. A biological system’s inability to quickly detoxify the reactive intermediates or quickly repair the damage that results from ROS generation is what leads to oxidative stress [189]. Diet and regular lifestyle play a role in maintaining well-being and preventing diseases. In recent years, due to their potential antioxidant activity, the use of polyphenols has increased as a barrier to ROS [192]. This class of ROS-reactive molecules are organic compounds that are abundant in many vegetable species. In recent years, scientific studies on these bioactive molecules have intensified, demonstrating that the consumption of polyphenols can contribute to the control of ROS in the physiological functions of our body [193]. In recent years many food products enriched with antioxidant substances have been created to block free radicals. In fact, the European Food Safety Authority (EFSA) has stated that the consumption of 5 mg/kg/day of polyphenols could help in the prevention of such diseases connected to the ROS [194]. Numerous hematological diseases have been found to disrupt the oxidative balance [195,196,197,198,199]. In addition, oxidative stress and autoimmune illnesses have a long history of association. Aldehyde-modified proteins have a high immunogenicity. When animals are inoculated with oxidized low-density lipoprotein (LDL) particles, autoantibodies directed against the epitopes of LDLs modified by malondialdehyde (MDA) and 4-hydroxynonenal (HNE) are formed [200]. The oxidative alteration of protein antigens may modify the adaptive immune response. In numerous autoimmune illnesses, including scleroderma, Behcet’s disease, systemic lupus erythematosus, rheumatoid arthritis, and type 1 diabetes mellitus, the oxidative alteration of proteins has been demonstrated to generate pathogenic antibodies [201]. Additionally, protein changes brought on by free radicals are highly immunogenic and can cause an antibody response by activating the adaptive immune system [202]. Regulatory T cells (Tregs) play a crucial role in self-tolerance, and a number of studies [203,204,205,206] have shown that abnormalities in Tregs lead to increased T-cell and B-cell autoreactivity in individuals with ITP. It is interesting to note that in autoimmune illnesses, NO was demonstrated to diminish Foxp3 expression and, consequently, Tregs [207]. As a result, ROS may be a factor in the Treg shortage in ITP, and redox modulation may also be involved in immune regulation. All these findings suggested that increased oxidative stress may be a significant factor in the pathogenesis of ITP and in the destruction of the platelet membrane, which results in the loss of cell membrane elasticity, an increase in cell fragility, and a shortening of cellular life. Several studies have discovered significant oxidative state changes in ITP patients. An analysis of the blood expression profiles of ITP patients and healthy individuals revealed that ITP patients had activated ROS-related molecular signaling pathways. Moreover, an unbalanced redox state results from excessive ROS production or insufficient antioxidant scavenging capacity in ITP patients. A smaller ratio denotes a higher level of oxidative stress, and the ratio of reduced to oxidized glutathione (GSH/GSSG) serves as an excellent indicator of the oxidative stress status. The value of this marker is even lower in patients with chronic ITP than in those with acute ITP, and it is significantly higher in healthy controls than in ITP patients [208,209]. As indicated by higher MDA levels in the plasma of ITP patients compared to controls, persistent oxidative stress results in lipid peroxidation and the formation of reactive aldehydes [210]. Protein carbonylation is a sort of post-translational alteration of proteins that results from either the direct oxidation of amino acid residues or the indirect oxidation caused by the addition of aldehydes (more common). In contrast to native human serum albumin (HAS), which only produced low-titre antibodies, HAS transformed in vitro by hydroxyl radical was found to be a strong antigenic stimulus, eliciting high-titre antibodies in rabbits [211]. The creation of neo-epitopes may be the cause of the ROS modified HSA’s much increased immunogenicity. Given that oxidatively changed proteins have been found to be highly immunogenic, it is conceivable to hypothesize that the development of autoantigen in ITP may have been triggered by a similar process, at least in part. Additional research appears to support the significance of oxidative stress in the pathophysiology of ITP and the potential use of oxidative stress markers in the diagnosis, prognosis, or perhaps as an effective treatment target. For instance, significantly increased levels of MDA, NO, and oxidized glutathione were found in a cohort with chronic ITP in observational research. Additionally, it was discovered that these individuals with chronic ITP had considerably reduced levels of CAT, TAC, and superoxide dismutase [212]. The pathophysiology of ITP was therefore hypothesized to involve both increased oxidative stress brought on by inflammation and decreased antioxidant levels [213,214,215,216,217]. Moreover, a genetic biomarker, the overexpression of vanin-1 (VNN-1), an oxidative stress sensor, has been proposed as a predictor of chronic disease, and other markers have been found with prognostic value [218,219]. A copper and zinc deficiency results in oxidative stress because they are components of the antioxidant system. The response to first-line therapy for primary immune thrombocytopenia and the serum copper level were found to be significantly correlated, while in relapsed patients, the serum copper level was considerably lower [220]. High-mobility group box 1 (HMGB1), a distinct redox-sensitive protein, is thought to have a role in controlling stress reactions to oxidative damage and cell death. This nuclear non-histone protein regulates chromosomal structure and function by acting as a DNA chaperone. As a damage-associated molecular pattern protein, HMGB1 can also be released into the extracellular environment and operate during several types of cell death, such as apoptosis, necrosis, pyroptosis, necroptosis, alkaliptosis, ferroptosis, and cuproptosis. After being released, HMGB1 interacts with membrane receptors to influence metabolic and immunological responses. The redox status and protein posttranslational modifications of HMGB1, as well as its subcellular location, affect its function and activity [221]. Several studies showed that the etiology of autoimmune disorders and malignancies is influenced by abnormal HMGB1 [222,223]. Rheumatoid arthritis patients had greater amounts of HMGB1 in their synovial fluid, serum, and synovial tissue. HMGB1 may also play a role in the progression of primary Sjögren’s syndrome, systemic lupus erythematosus, and other autoimmune illnesses. In an experiment, HMGB1 expression was shown to be considerably higher and Foxp3 expression to be lower in the spleen of patients with refractory ITP. Moreover, Foxp3 and HMGB1 were found to have a substantial negative connection, and HMGB1 overexpression was significantly linked with poor splenectomy efficacy. As for other immune parameters, IL-10 had a negative association with HMGB1, while HMGB1 expression increased and was positively linked with IL-17 in serum. The expression of HMGB1, RORt, and Foxp3 changed in PBMCs, with the alterations being more pronounced in the group with refractory chronic ITP. In a coculture system using PBMCs from untreated ITP patients, rHMGB1 elevated RORt expression and lowered Foxp3 expression, while an antiHMGB1 antibody partially reversed the aforementioned effects. These results imply that HMGB1 participates in the etiology of ITP and is linked to the imbalance of Treg/Th17 cells [224]. Additionally, this theory was supported by other investigations [225]. Evaluation of HMGB1 levels could be a useful means of monitoring the progress of the disease. Finally, as was already indicated, modulating oxidative stress may be important for treating ITP. Patients with ITP who have measurable oxidative stress may benefit from adjuvant antioxidant therapy to increase platelet count. According to a study, antioxidant therapy reduced oxidative stress in the ND and chronic ITP groups, which may have contributed to improvements in the bleeding score and platelet count [217]. Probably because of its anti-inflammatory effects in ITP patients with severe clinical symptoms necessitating medication, high-dose methylprednisolone therapy lowers oxidative stress [226]. Similar to this, Brox et al. reported on the successful use of the well-known antioxidant ascorbic acid in the treatment of a small number of adult patients with refractory ITP [227]. However, several small-scale studies were conducted in the past to determine whether ascorbic acid was effective in treating chronic ITP, and the results were highly debatable [228,229,230,231,232]. Currently, six different trials are underway to evaluate the efficacy of antioxidant therapy in the treatment of ITP [233] (Table 3). Finally, oxidative stress biomarkers could be useful for predicting therapeutic success. It was discovered that the average levels of native and total thiol in the patient group were substantially lower than those of the controls. However, IVIG therapy stopped these declines. Disulfide levels were marginally but not significantly lower in ITP patients; however, they increased after IVIG therapy [234]. In conclusion, at this time, it would be reasonable to conduct large-scale prospective clinical trials to determine whether anti-oxidants are useful in treating patients with ITP. Platelet counts and the exclusion of morphological abnormalities in peripheral blood smears are the main diagnostic criteria for the diagnosis of TP, a common bleeding condition. Without a trustworthy biomarker, incorrect diagnoses are frequent and can result in excessive bleeding incidents, patient anguish, exposure to inappropriate drugs, and the need for invasive treatments such as splenectomy. However, over the past few years, a number of biomarkers have emerged that could be used to diagnose ITP, predict prognosis, and gauge therapy effectiveness. A clinical prediction model (CPM) for the diagnosis of ITP was recently created to assist clinicians in examining patients who come with undifferentiated thrombocytopenia [235]. Based on information from patients with thrombocytopenia registered in the McMaster ITP registry, the authors created the Predict-ITP Tool, a CPM for ITP diagnosis at the time of the initial hematological consultation. A platelet count of fewer than 100 109/L and a platelet count response following high-dose corticosteroids or intravenous immune globulin were used to characterize ITP cases. A platelet count response was defined as the achievement of a platelet count of more than 50 109/L and at least a doubling of baseline. Bootstrap resampling was used for the internal validation. The c-statistic was used to evaluate model discrimination, while the calibration slope, calibration-in-the-large, and calibration plot were used to evaluate calibration. The final model had the following variables: severe bleeding history; lowest platelet count value; highest mean platelet volume; platelet count variability (based on three or more platelet count values); and lowest platelet count value (defined by the ITP bleeding scale). The optimism-corrected c-statistic was 0.83, the calibration slope was 0.88, and the calibration-in-the-large was 0.001 with a standard error of 0.001 for all performance metrics, showing excellent calibration and good discrimination. For a specific patient with thrombocytopenia at the time of the initial haematology consultation, the Predict-ITP Tool can predict the chance of ITP [235]. The instrument exhibited a high degree of prediction accuracy for ITP diagnosis. The use of various biomarkers to facilitate the diagnostic and prognostic evaluation of ITP patients was suggested by several experimental results, which is a promising advance that has undoubtedly raised interest in their application. However, it must be acknowledged that there are still some limitations since various analysers will need reference ranges to be established before application, and as technology develops and newer analysers with higher specificity and sensitivity become available, these ranges will undoubtedly need to be revised. Furthermore, it must be kept in mind that the different biomarkers do not have absolute significance in patients with ITP. It is highly likely that one candidate lower in early ITP pathogenesis may be elevated in chronic or later phases, or refractory ITP. For instance, in a study, plasma miRNAs were evaluated in patients with acute ITP (aITP) and chronic ITP (cITP). The detection of significant differences between plasma miRNA levels of aITP and cITP patients may provide useful information in the prediction of the course of disease, determination of disease etiopathogenesis, and the development of new therapeutic modalities [236]. Similarly, the frequencies of circulating B cells secreting platelet-specific antibody in acute ITP patients were notably increased compared to the chronic ITP patients [237], while both IL-2 and IFN-gamma were significantly increased in chronic ITP when compared to acute ITP and platelet associated IgM was detected more in acute than in chronic ITP [238]. Despite these apparent drawbacks, novel biomarkers may be useful for determining the cause of a thrombocytopenic presentation. A greater understanding of the pathophysiology of ITP has made it possible to find new disease biomarkers that can aid in its detection. Some of the promising disease markers include the search for platelet autoantibodies, analysis of the transcriptome and complement activity, evaluation of oxidative stress markers, valuation of chemokines and non-coding genetic material, analysis of factors that can control the growth and activity of immunological effectors such as BAFF and cytokines, and assessment of the immature platelet fraction and megakaryocyte maturation index. How many of these might actually have therapeutic utility and how many of these have a positive cost-benefit profile need to be assessed in controlled research. In actuality, some of these tests seem pricey or technically challenging to carry out. It is possible that a score created by combining some of the investigated biomarkers could serve as an effective diagnostic tool. Finally, it is necessary that the assay techniques used for the evaluation of biomarkers improve in sensitivity and specificity. Most T cells in mammals, including humans, present the αβ T cell receptor and identify a specific peptide bound to a major histocompatibility complex molecule (pMHC) expressed on target cells [239]. The weak equilibrium dissociation constant between the TCR and monomeric pMHC causes a transient complex that obstructs easy identification [240]. Mallajosyula et al. engineered a biotinylation site on maxi-ferritin to generate a 24-subunit, self-assembling protein scaffold for the multivalent display of pMHC. This spheromer platform presents several advantages, including ease of production and defined site-specific conjugation of pMHC molecules that significantly decreases interbatch variation [241]. The introduction of this method could be useful to enhance the avidity of low-affinity interactions, and to boost detection of low-affinity autoantibody detection. Last but not least, it is likely that in the future, research on additional blood markers of platelet activity [242] will yield novel indicators that will make it easier to diagnose the condition and accurately forecast how well it will respond to treatment.

PMC10003041

Philipp von Breitenbuch,Bernadett Kurz,Susanne Wallner,Florian Zeman,Christoph Brochhausen,Hans-Jürgen Schlitt,Stephan Schreml

Expression of pH-Sensitive GPCRs in Peritoneal Carcinomatosis of Colorectal Cancer—First Results

23-02-2023

colorectal,peritoneal carcinomatosis,tumor microenvironment

Solid tumors have an altered metabolism with a so-called inside-out pH gradient (decreased pHe < increased pHi). This also signals back to tumor cells via proton-sensitive ion channels or G protein-coupled receptors (pH-GPCRs) to alter migration and proliferation. Nothing, however, is known about the expression of pH-GPCRs in the rare form of peritoneal carcinomatosis. Paraffin-embedded tissue samples of a series of 10 patients with peritoneal carcinomatosis of colorectal (including appendix) origin were used for immunohistochemistry to study the expression of GPR4, GPR65, GPR68, GPR132, and GPR151. GPR4 was just expressed weakly in 30% of samples and expression was significantly reduced as compared to GPR56, GPR132, and GPR151. Furthermore, GPR68 was only expressed in 60% of tumors and showed significantly reduced expression as compared to GPR65 and GPR151. This is the first study on pH-GPCRs in peritoneal carcinomatosis, which shows lower expression of GPR4 and GPR68 as compared to other pH-GPCRs in this type of cancer. It may give rise to future therapies targeting either the TME or these GPCRs directly.

Expression of pH-Sensitive GPCRs in Peritoneal Carcinomatosis of Colorectal Cancer—First Results Solid tumors have an altered metabolism with a so-called inside-out pH gradient (decreased pHe < increased pHi). This also signals back to tumor cells via proton-sensitive ion channels or G protein-coupled receptors (pH-GPCRs) to alter migration and proliferation. Nothing, however, is known about the expression of pH-GPCRs in the rare form of peritoneal carcinomatosis. Paraffin-embedded tissue samples of a series of 10 patients with peritoneal carcinomatosis of colorectal (including appendix) origin were used for immunohistochemistry to study the expression of GPR4, GPR65, GPR68, GPR132, and GPR151. GPR4 was just expressed weakly in 30% of samples and expression was significantly reduced as compared to GPR56, GPR132, and GPR151. Furthermore, GPR68 was only expressed in 60% of tumors and showed significantly reduced expression as compared to GPR65 and GPR151. This is the first study on pH-GPCRs in peritoneal carcinomatosis, which shows lower expression of GPR4 and GPR68 as compared to other pH-GPCRs in this type of cancer. It may give rise to future therapies targeting either the TME or these GPCRs directly. Acidosis is a common physical hallmark of solid tumors. Tumor growth and metastasis essentially require changes in the microenvironmental pH value [1,2,3,4,5]. In contrast to other cells, cancer cells seem to be better adapted to a lower extracellular pH value (pHe) and can take advantage of this. Nevertheless, the intracellular pH (pHi) of cancer cells needs to be within the physiological range, otherwise cell death occurs due to cytotoxic acid [6,7]. Normal cells show a pHe of 7.2–7.4 and a pHi of 6.9–7.2. Most tumor tissues have a lower pHe (6.2–7.0) and higher pHi (7.2–7.7). This phenomenon is called the reversed (= inside-out) pH gradient [1,2,4,5]. Cancer cells use different mechanisms to maintain this pH gradient. Compared to non-tumor cells, many cancer cells obtain their energy from a significantly increased glucose metabolism. This means that the tumor cells obtain their energy mainly from glycolysis. What is special about tumor cells is that this form of energy generation takes place not only via anaerobic but also via aerobic glycolysis (Warburg effect) [8]. The resulting lactate is removed from intracellular to extracellular space by monocarboxylate transporters (MCTs 1 + 4) [2,4]. Neri et al. report on more key pH regulators in cancer cells including isoforms of the carbonic anhydrases 2, 9, and 12 (CA2, CA9, CA12), the Na+/H+ exchanger 1 (NHE1) and the plasma membrane proton pump vacuolar ATPase (V-ATPase) [2,4]. G protein-coupled receptors (GPCRs) with their heptahelical transmembrane structure [5,9] trigger different intracellular signaling cascades after receptor activation. Only a few of the approximately 800 known GPCRs—for example, GPR4, GPR65 (TDAG8, T-cell death-associated gene 8), GPR68 (OGR1, ovarian cancer GPCR1), and GRP132 (G2A, G2 accumulation protein)—are involved in sensing pH changes through the protonation of hydrogen bonds between histidine residues. Recently, another two pH-sensitive GPCRs were found: GPR31 and GPR151 [10,11,12]. It has been shown that these GPCRs are activated via a decrease in pHe through the protonation of hydrogen binding between the histidine residues. Moreover, it is thought that these GPCRs are involved in cancer cell proliferation, metastasis, angiogenesis, apoptosis, immune cell function, and inflammation [5,13,14,15,16,17,18,19,20,21,22]. Proton-sensing GPCRs are expressed in various tissues of solid tumors, but there is still a lack of knowledge about their expression in peritoneal carcinomatosis. For this reason, we investigated the expression of the proton-sensing GPCRs (GPR4, GPR65, GPR68, GPR132, and GPR151) in peritoneal tumor spots of colorectal origin. All patients showed a histological proven peritoneal carcinomatosis of colorectal origin (colorectal adenocarcinoma). Paraffin-embedded tissue samples from peritoneal tumor spots were taken. For all experiments, we used tissue samples older than 10 years from the Department of Pathology at the University Medical Center Regensburg. Handling of human tumor tissue older than 10 years was approved by the ethical committee of the University of Regensburg. Under German law, the tumor tissue left after surgery after the final diagnosis can be discarded after 10 years or is free to use. Tissue samples (embedded and fixed in paraffin) were cut into 3 µm thick sections using a microtome and then fixed on slides. Each slide was also stained with hematoxylin and eosin. This and all other subsequent staining steps were performed at room temperature. We removed paraffin from the tissue sections by incubating them for 60 min at 72 °C, and then we rehydrated the slides with decreasing alcohol concentrations as follows: 3 × xylol for 10 min, 2 × 100% ethanol for 5 min, 2 × 96% ethanol for 5 min, 2 × 70% ethanol for 5 min. To prevent false-positive results, endogenous peroxidase was blocked with 3% H2O2 (Fisher Scientific, Waltham, MA, USA, No. 1404697) for 10 min. Simultaneously, an acidic citrate buffer with pH 6 (Zytomed, Bargteheide, Germany, REF ZUC028) was boiled for 30 min. The slides were washed in distillated water and then boiled for 20 min in the precooked citrate buffer, followed by cooling on ice for 20 min. Subsequently, they were transferred to PBS (Sigma-Aldrich, Darmstadt, Germany, No. D8537) for 10 min. Afterwards, slides were fixed with cover slides and once again washed with PBS. To avoid unspecific antibody binding, proteins were blocked with blocking solution (ZytoChem Plus HRP Kit/Rabbit, Zytomed, Bargteheide, Germany, REF HRP060-Rb) for 10 min. Next, tissue sections were incubated with polyclonal primary antibodies against GPR4 (rabbit anti-human GPR4; 1:200; Abcam, Cambridge, UK, anti-GPCR GPR4 antibody, ab188606), GPR65 (1:500; Abcam, Cambridge, UK, anti-GPCR GPR65 antibody, ab188907), GPR68 (1:50; Abcam, Cambridge, UK, anti-OGR1 antibody, ab188964), GPR 132 (1:60; Abcam, Cambridge, UK, anti-GPCR G2A antibody, ab116586), GPR151 (1:400; anti-GPCR GPR151 antibody, Life Technologies, Waltham, United States Cat.Nr.PA532803), or isotype control antibody (1:200, Abcam, Cambridge, UK, rabbit IgG polyclonal isotype control, ab27478) in antibody diluent (Zytomed Systems GmbH, Berlin, Germany) overnight at 4 °C. The following day, the slides were washed three times with PBS. The tissue sections were then incubated with the secondary biotinylated antibody for 30 min, they were washed again three times with PBS, then incubated with streptavidin–HRP conjugate for 20 min and washed 3× with PBS. Positive controls were stained with AEC plus (Dako, Santa Clara, CA, USA, No. K 3469) until the expected staining appeared. The reaction was stopped with distillated water, and positive controls were counterstained with Mayer’s Haemalm (Roth, Karlsruhe, Germany, No. T865.3). The slides were scanned with PreciPoint M8, and the digital images were edited with ViewPoint online (PreciPoint, Freising, Bavaria, Germany). Positive and negative controls for immmunohistochemistry of GPR4, GPR65, GPR132, and GPR151 were published recently by our group [23,24]. A pathologist assessed the staining of the sections visually. Sections were labeled as “++” for strong positive reactions with >80% of cells being positive and/or when staining intensity was high, “+” for 20–80% of cells demonstrating a weak positive/partial positive reaction, and “−” for <20% of cells displaying weak staining (a negative reaction). Tumors with inconsistent staining were scored as weakly positive. First, all rating results for all entities were compared using Kruskal–Wallis tests. For NCN and MMs, epidermal and dermal portions were separately used for testing. Pairwise comparisons were made via Bonferroni tests. Secondly, pairwise comparisons of BCCs vs. SCCs and of MMs vs. NCN were made for each protein using a Mann–Whitney U test, and the results are given as exact significance (shown as 2 * (1-tailed significance), not corrected for ties, for BCCs vs. SCCs and epidermal portions of NCN/MMs) or asymptotic significance (2-tailed, for dermal portions of NCN/MMs). An overview of the results can be found in Table 1. Representative immunohistochemical stainings are shown in Figure 1. All samples of each patient are depicted in Supplementary Figures S1–S6. The tissue samples from 7/10 patients showed no expression of GPR4. A weak positive expression can be seen in two patients and a strong expression pattern can only be detected in one patient. One hundred percent of our tissue samples showed a positive expression pattern for GPR65. Of these, 80% were strongly positive, 20% showed a weak positive expression. GPR68 expression could be detected in 60% of our cases, whereby in 30% the expression pattern was strong. In contrast, no expression could be detected in 40% of the histological samples. The evaluation of GPR132 expression profile showed in 70% a strong expression pattern on the surface of tumor cells. One patient showed a moderate GPR132 expression, whereas in two patients no expression of GPR132 could be found. One hundred percent of the tissue samples had a strong positive expression of GPR151. Table 2 shows the statistical results. GPR4 expression was significantly lower than that for GPR65, GPR132, and also GPR151. No difference in expression was found between GPR4 and GPR68. The latter, GPR68, also showed significantly reduced expression as compared to GPR65 and GPR151. In our study, we investigated for the first time the expression of different GPCRs in peritoneal carcinomatosis tissue samples of colorectal origin. Our results show a strong expression for GPR151, GPR65, and GPR132. GPR68 was clearly expressed in 60% of the tissue samples, whereas GPR4 expression could only be seen in very few tissue samples. These pH-sensitive GPCRs are activated via protonation [17] and they are involved in a variety of processes, such as cancer cell proliferation, metastasis, angiogenesis, apoptosis, immune cell function, and inflammation. As a result of being influenced by such varied processes, it is clear that the effect of the different GPCRs can even be opposite to one another, for example, either promoting or suppressing tumor growth [5,13,15,16,17,18,19,20,21,22]. Increased GPR4 expression is known to induce an inflammatory response in human vascular endothelial cells [5,15]. Reduced GPR4 signaling impairs the growth of murine tumor allografts [5,21]. Bai et al. found that GPR4 may function via the WNT pathway molecule transcription factor 7 (TCF7). Downregulation of GPR4 leads to a downregulation of TCF7, inhibiting cell growth and cell invasion, and promoting apoptosis of ovarian cancer cells [25]. Furthermore, TCF7 plays an important role in CRC. Long non-coding RNA TCF7 (IncTCF7) is known to be highly expressed in CRC cell lines compared to normal colonic epithelial cells, and has been shown to play a critical role in human CRC development and progression. TCF7 overexpression could promote migration and invasion in CRC cells. In contrast, TCF7 knockdown significantly inhibited migration and invasion of CRC tumor cells [26]. For the development of a peritoneal carcinomatosis, migration and invasion of tumor cells are mandatory. With respect to our results, GPR4 expression was surprisingly undetectable in nearly all samples. The reason for this remains unclear. An overexpression of GPR65 promotes glucocorticoid-induced apoptosis in mouse lymphoma cells [5,27]. Upregulated GPR65 suppresses intestinal inflammation and reduces the risk of developing colitis-associated colorectal cancer in an experimental mouse model [28]. In contrast, it has been reported that GPR65 expression enhances tumor growth in Lewis lung carcinoma cells [5,29], and that GPR65 is overexpressed in glioblastoma, which is associated with an unfavorable clinical outcome for patients [30]. In addition, Li et al. investigated the role of long non-coding RNA GPR65-1 (lincRNA) in the progression of gastric cancer [31]. They found that linc-GPR65-1 was significantly upregulated in gastric cancer tissue compared to corresponding normal tissues, and that the increased linc-GPR65-1 expression was significantly associated with a poorer TNM stage, larger tumor size, presence of distal metastasis, and poor prognosis for gastric cancer patients. Moreover, they observed that linc-GPR65-1 could regulate the PTEN-AKT-slug signaling pathway, and that this pathway might act as a tumor promotor [31]. Currently, no comparable data exist for colorectal cancer or peritoneal carcinomatosis. Due to the strong expression of GPR65 we observed in our study, one could speculate that, compared to gastric cancer, at least the PTEN-AKT-slug signaling pathway is activated by GPR65 in peritoneal carcinomatosis of CRC. This activated signaling pathway might also act as a tumor promotor in peritoneal carcinomatosis of colorectal origin. GPR68 also belongs to the known proton-sensing G protein-coupled receptors involved in pH changes during development of different tumors, e.g., neuroendocrine tumors, pheochromocytomas, cervical adenocarcinomas, endometrial cancers, medullary thyroid carcinomas, and pancreatic adenocarcinomas, whereby often tumor capillaries are strongly GPR68 positive [32]. Furthermore, GPR68 may play a crucial role in tumor biology, including tumorigenesis, tumor growth, and metastasis [33]. In human ovarian cancer cells, GPR68 improves tumor cell adhesion to extracellular matrix, but surprisingly inhibits cell proliferation and migration [5,19]. Cancer-associated fibroblasts (CAFs) are responsible for a dense fibrotic tumor stroma, and an increased expression of GPR68 could be shown in CAFs, resulting in enhanced interleukin-6 (IL-6) expression via a cAMP/PKA/cAMP response element-binding protein signaling pathway [34]. The fact that GPR68 is able to increase IL-6 expression is important since IL-6 plays a fundamental role in tumor progression [35]. Besides its expression in pancreatic CAFs [34], GPR68 is also expressed in GIST CAFs [34], appendiceal CAFs [34], and colorectal CAFs [36]. The important role of GPR68 in tumorigenesis in colorectal cancer was reported by Horman et al. First, they showed that GPR68 was one of the most highly upregulated genes when CCD-18Co (human colon fibroblast) cells were activated to CAFs after co-culture of CCD-18Co and HCT116 cells (human colorectal carcinoma cells) in 3D spheroid microtumor structures. Second, they identified GPR68 as being the number one factor in regulating microtumor formation. Finally, in their in vivo studies, MC-38 murine colorectal carcinoma cells were injected into WT and GPR68 KO mice. During the first 14 days, tumor growth was reduced in the GPR68 KO group and tumors were more fibrotic, less vascular, and had more pronounced borders. Overall, they concluded that GPR68 promotes colorectal tumor initiation in mice [36]. Based on the data of these other authors, GPR68 expression would actually have been expected in all of our patients. Surprisingly, we found GPR68 overexpression in only 6/10 patients. Therefore, one could conclude that GPR68 does not play the same role in the growth of peritoneal carcinoma tumor nodes as in the primary tumor. The anti-tumorigenic effect of GPR132 is explained by cell cycle arrest at the G2 stage [5,37] although, in contrast, GPR132 nonetheless has a strong pro-tumorigenic effect influencing tumor–macrophage communication. It was Chen et al. who showed that GPR132 mediates the reciprocal interaction between cancer cells and macrophages. Activation of GPR132 leads to an increase in lactate in the acidic tumor milieu (lactat-GPR132 axis), and activates the alternative macrophage (M2)-like phenotype, which in contrast to the “normal” macrophages facilitates cancer cell adhesion, migration, and invasion. The clinical context between GPR132 expression, M2 macrophages, metastasis, and a poor prognosis in patients with breast cancer is clear [38]. Another type of immune cell influenced by GPR132 is monocytes. With respect to the energy-transfer mechanism in the inflammatory tumor microenvironment, human THP-1 monocytes take up lactate secreted from tumor cells. High levels of lactate in turn activate hypoxia-inducible factor 1a, which promotes key enzymes of prostaglandin E2 synthesis, thereby promoting the growth of human colon cancer HCT116 cells. Interestingly, only human monocytic cells affected by lactate could stimulate the colon cancer cells. Lactate itself could not accelerate tumor growth directly [39]. In our study, GPR132 is highly expressed in all tissue patterns. This shows the important relevance of GPR132 in peritoneal carcinomatosis tumor nodules of colorectal origin. This high overexpression of GPR132 probably represents the necessary strong interaction between peritoneal carcinomatosis and cells of the immune system. Recently, it was shown that GPR151 also belongs to the one family of GPCRs that is responsible for the sensing of extracellular protons. Both GPR31 and 151 are activated under acidic conditions and their activation is maximal at approximately pH 5.8 [11]. GPR151 is involved in the nervous system of vertebrates. An upregulation of GPR151 mRNA was found in the trigeminal ganglions, causing neuropathic pain, and it was shown to bind to Gai protein, activating the extracellular signal-regulated kinase (ERK) and resulting in an ERK-dependent neuroinflammation [40]. It could, however, be proven that GPR151 couples with the G-alpha inhibitory protein to reduce cyclic adenosine monophosphate (cAMP) levels in the cells [41]. In our study, GPR151 was massively upregulated in all immunohistochemistry patterns, but its role in tumorigenesis still remains unclear. Until now, only Schreml et al. have investigated GPR151 expression in tumors. They observed highly expressed GPR151 levels in squamous cell carcinomas [23]. Our study is the first to describe high GPR151 levels in peritoneal carcinomatosis tumor tissue. Since the expression of GPR151 was very strong in all of our immunohistochemical stainings, GPR151 seems to play a mandatory role in the formation and development of a peritoneal carcinomatosis of the colorectal carcinoma. pH dysregulation is a hallmark of solid tumors. The proton-sensing GPCRs are involved in sensing extracellular acidity. Cancer cells are able to use this altered environment to their advantage. We could demonstrate, for the first time, that GPCRs are extensively expressed in cancer tissue of peritoneal carcinomatosis of colorectal origin. The small number of patients is the main limitation of the study. Results of our study may help to obtain more insight into the role of GPCRs concerning peritoneal carcinomatosis. However, GPR4 and GPR68 were significantly less expressed in peritoneal carcinomatosis than other pH-GPCRs. Targeting these GPCRs and may be an attractive therapy for patients suffering from peritoneal carcinomatosis. Such a new anti-cancer therapy can probably be embedded in a multidisciplinary therapy regime. Therefore, more studies are needed to assess the specific roles of the different GPCRs in tumor biology and tumorigenesis of peritoneal carcinomatosis.

PMC10003043

Xing-An Wang,Ju-Pi Li,Kang-Hsi Wu,Shun-Fa Yang,Yu-Hua Chao

Mesenchymal Stem Cells in Acquired Aplastic Anemia: The Spectrum from Basic to Clinical Utility

24-02-2023

aplastic anemia,bone marrow failure,cell therapy,mesenchymal stem cells

Aplastic anemia (AA), a rare but potentially life-threatening disease, is a paradigm of bone marrow failure syndromes characterized by pancytopenia in the peripheral blood and hypocellularity in the bone marrow. The pathophysiology of acquired idiopathic AA is quite complex. Mesenchymal stem cells (MSCs), an important component of the bone marrow, are crucial in providing the specialized microenvironment for hematopoiesis. MSC dysfunction may result in an insufficient bone marrow and may be associated with the development of AA. In this comprehensive review, we summarized the current understanding about the involvement of MSCs in the pathogenesis of acquired idiopathic AA, along with the clinical application of MSCs for patients with the disease. The pathophysiology of AA, the major properties of MSCs, and results of MSC therapy in preclinical animal models of AA are also described. Several important issues regarding the clinical use of MSCs are discussed finally. With evolving knowledge from basic studies and clinical applications, we anticipate that more patients with the disease can benefit from the therapeutic effects of MSCs in the near future.

Mesenchymal Stem Cells in Acquired Aplastic Anemia: The Spectrum from Basic to Clinical Utility Aplastic anemia (AA), a rare but potentially life-threatening disease, is a paradigm of bone marrow failure syndromes characterized by pancytopenia in the peripheral blood and hypocellularity in the bone marrow. The pathophysiology of acquired idiopathic AA is quite complex. Mesenchymal stem cells (MSCs), an important component of the bone marrow, are crucial in providing the specialized microenvironment for hematopoiesis. MSC dysfunction may result in an insufficient bone marrow and may be associated with the development of AA. In this comprehensive review, we summarized the current understanding about the involvement of MSCs in the pathogenesis of acquired idiopathic AA, along with the clinical application of MSCs for patients with the disease. The pathophysiology of AA, the major properties of MSCs, and results of MSC therapy in preclinical animal models of AA are also described. Several important issues regarding the clinical use of MSCs are discussed finally. With evolving knowledge from basic studies and clinical applications, we anticipate that more patients with the disease can benefit from the therapeutic effects of MSCs in the near future. Aplastic anemia (AA) is a paradigm of bone marrow failure syndromes characterized by peripheral pancytopenia and bone marrow hypoplasia. The first formal description dates back to 1888 when Paul Ehrlich reported a young pregnant women with profound anemia, bleeding, high fever, and eventually death [1]. AA can be graded by the severity of cytopenias in the peripheral blood [2]. The criteria of severe aplastic anemia (SAA) are bone marrow hypocellularity of less than 25% and at least two of following: absolute neutrophil count < 0.5 × 109/L, platelet count < 20 × 109/L, and reticulocyte count < 20 × 109/L. In very severe AA, there is extreme neutropenia of less than 0.2 × 109/L. In nonsevere AA, hypocellular bone marrow is noted but peripheral blood values do not meet the criteria of SAA. SAA is potentially life-threatening if dedicated treatment is not implemented. Acquired AA can affect patients of all ages, with an annual incidence of about 2 per million population [3]. A variety of insults, such as drugs, chemicals or irradiation, and infections, can lead to the impairment of hematopoiesis, which is the main feature of AA. A specific cause cannot be identified in a large proportion of patients and is termed “idiopathic AA”. Historically, immunosuppressive therapy (IST) and hematopoietic stem cell transplantation (HSCT) have been the mainstay of treatment for these patients. Having unique properties, the clinical application of mesenchymal stem cells (MSCs) is evolving rapidly in the recent decade for many human diseases, including AA. Here, we present a comprehensive review of current concepts regarding the insufficiency of MSCs in acquired idiopathic AA and the clinical use of MSCs in patients with the disease. We also summarized the pathophysiology of AA, the properties of MSCs, and preclinical results of MSC therapy in animal models of AA. In view of different entities, a discussion about congenital AA with an identified germline mutation is outside the scope of this review. AA is characterized by pancytopenia in the peripheral blood and hypocellularity in the bone marrow. When AA is suspected, a comprehensive evaluation should be performed to exclude other mimicking conditions and search for underlying etiologies. Despite of these efforts, a specific cause cannot be identified in a large proportion of patients and is termed “idiopathic”. The pathogenesis of acquired idiopathic AA is complex, and we summarized the current concepts in the following sections (Figure 1). The immune-mediated destruction of hematopoietic stem cells (HSCs) is the most widely accepted mechanism of hematopoietic failure in AA. Available evidence suggests the gross homeostatic dysregulation of the T cell repertoire in AA, and T cell attack on marrow cells of AA has been illustrated in vitro and in vivo. It has been demonstrated that the percentage of activated CD8+ cytotoxic T cells is increased in the both bone marrow and peripheral blood of patients with AA. In vitro coculture with CD8+ T cells isolated from patients with AA was found to inhibit colony formation and enhance apoptosis of CD34+ cells isolated from normal individuals [4,5,6], suggesting CD8+ cytotoxic T cell dysfunction in AA. Abnormalities in the number and function of CD4+ T cells have also been documented in AA, with increased T helper (Th)1, Th2, and Th17 cells [7]. Regulatory T cells (Tregs) are believed to control autoimmunity by suppressing autoreactive T cells and play an important role in the maintenance of immune homeostasis. A decrease in the number of CD4+ CD25+ FOXP3+ Tregs was found in almost all patients with AA [8], and there was an inverse relationship between the numbers of Th17 cells and Tregs in the peripheral blood of patients [9]. Meanwhile, hyperactive T cells in AA may release a variety of inflammatory cytokines, such as interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and interleukin (IL)-17, thus with elevated concentrations in the serum and bone marrow plasma [10,11,12]. These cytokines were found to confer additional hematopoietic suppression by increasing Fas expression on CD34+ progenitor cells and inducing the programmed cell death of these cells [6]. On the other hand, the effectiveness of IST in the treatment of AA provides compelling clinical evidence for the immune-mediated nature of the disease. HSCs are capable of self-renewal and differentiation into various hematopoietic cells and are critical for the maintenance of the hematopoietic system. There is evidence of primary deficiencies, both quantitative and qualitative, in AA HSCs. Patients with AA have decreased numbers of HSCs at diagnosis [13,14], and these cells were found to display poor plating efficiency for colony formation [15,16]. Increased apoptosis of CD34+ cells in both the bone marrow and peripheral blood was observed in patients with AA [17,18]. Some intrinsic abnormalities predispose AA HSCs to apoptosis, resulting in HSC depletion. The upregulated expression of Fas antigen, which is a receptor molecule in the death signaling pathway, was frequently found on CD34+ cells in AA [19]. Abnormal expression of the apoptotic modulators Bcl-2 and Bcl-x was associated with the increased apoptosis of CD34+ cells in AA [20]. In addition, downregulated expression of cell cycle check point genes, such as CDK6, CDK2, MYB, MYC, and FANCG, was found in AA HSCs [21] and may compromise their replicative ability. Meanwhile, about one-third of patients with AA have telomere attrition in their leukocytes [22], and the telomere length at diagnosis correlates with disease severity and clinical outcomes [23,24]. Only a small subset of patients harbors mutations in the telomerase complex genes, such as TERT or TERC [25,26], and the majority of patients do not have these identifiable mutations. Therefore, multiple mechanisms may contribute to telomeric shortening in AA, including increased stem cell turnover, unidentified damage to telomeres, and genetic defects. Genetic factors play an important role in the pathogenesis of AA. Because patients harboring cytogenetic abnormalities may exhibit distinct pathogenesis and clinical manifestations, these patients should be discussed separately. Several studies have reported the association between certain human leukocyte antigen (HLA) alleles and the predisposition of AA. AA is more common in HLA-DR2-positive individuals than in the general population and in particular with the HLA-DRB1*15 allele in Asia. Moreover, DRB1*03, DQB1*0601, and DQB1*0603 were found to be either susceptible or protective alleles [27,28]. Although still being elucidated, HLA allelic variations may contribute to the activation of autoreactive T cells and the protective failure of Tregs. Recent advances in genomic analysis have revealed the complexity of somatic mutations and clonal hematopoiesis in AA. PIGA mutations were frequently detected in patients with AA at diagnosis but without paroxysmal nocturnal hemoglobinuria-related symptoms [29]. About one third of patients have somatic mutations in myeloid cancer candidate genes and in a limited set of genes, such as DNMT3A, ASXL1, and BCOR, and at a lower variant allele frequency [30]. The prevalence of these mutations increases with age, with a lower incidence in pediatric population. Some mutations were related to clinical outcomes; some may have potential to evolve from AA to myelodysplastic syndrome [31]. As known, bone marrow provides the distinct microenvironment for hematopoiesis. The cellular elements, including endosteal, vascular, and perivascular cells, were found to be markedly decreased in the bone marrow of patients with AA [32], implicating the possibility of microenvironmental impairment in the bone marrow. MSCs play a central role in the establishment of the bone marrow niche, and their defects may lead to the development of AA. In the following sections, the characteristics of MSCs and the alterations of bone marrow MSCs in patients with AA are discussed in detail. There are three main cellular systems in the bone marrow: hematopoietic, endothelial, and stromal [33]. The stromal cell system, which was first proposed by Owen et al. in 1985 [34], is composed of a variety of nonhematopoietic stromal cells of a mesenchymal origin. MSCs, an important component of the stromal bone marrow, constitute only a small percentage of marrow cells, about one in 3.4 × 104 [35]. Being the so-called stem cells, MSCs within the bone marrow have to maintain a level of self-renewal and give rise to various mesenchyme-lineage cells [36]. In the bone marrow, MSC-derived stromal cells provide the specific microenvironment for hematopoiesis by establishing an appropriate scaffold of extracellular matrix molecules along with a complex network of paracrine factors. MSCs secrete a number of cytokines, which can act not only on hematopoietic cells but also on stromal cells [37]. Numerous growth factors, such as stem cell factor, granulocyte macrophage-colony stimulating factor, granulocyte colony-stimulating factor, and macrophage colony-stimulating factor, have positive effects on hematopoiesis. MSCs also produce negative regulators of hematopoiesis, such as IL-8, macrophage inflammatory protein-1, and transforming growth factor-β (TGF-β). In addition, MSCs involve cell migration and homing to the bone marrow via the expression of adhesion molecules, including integrins, intercellular adhesion molecule-1, vascular cell adhesion molecule-1 (VCAM-1), and other molecules of the extracellular matrix [38,39]. Given the significant role in the hematopoietic niche, many studies have demonstrated the promotive effects of MSCs on in vitro HSC expansion [40,41,42,43]. In animal models, the infusion of MSCs has been shown to enhance the engraftment of donor HSCs after transplantation [43,44,45]. According to the consensus statement by the International Society for Cellular Therapy (ISCT), human MSCs are defined by their in vitro growth pattern, the expression of specific surface markers, and the multipotent differentiation potential (Figure 2) [46]. Having a spindle-shaped fibroblastic morphology, MSCs must be plastic-adherent when maintained in standard culture conditions. MSCs must express CD105, CD73, and CD90 and lack expression of CD45, CD34, CD14 or CD11b, CD79α or CD19, and HLA-DR. With a broad differentiation potential, the most unique property to identify MSCs is the capacity for trilineage mesenchymal differentiation, including osteoblasts, adipocytes, and chondroblasts. MSCs express HLA-class I molecules, but not class II. MSCs do not express costimulatory molecules CD80 (B7-1), CD86 (B7-2), CD40, and CD40 ligand and probably, therefore, do not activate alloreactive T cells [47,48,49]. In vivo, transplanted allogeneic MSCs can be detected in recipients at extended time points, implicating the lack of immune recognition and clearance [50]. In humans, numerous clinical reports have demonstrated that infused mismatched allogeneic MSCs do not trigger vigorous T cell responses in recipients without the risk of transferred cell rejection [51,52,53]. These data offer evidence that MSCs are immunologically inert or potentially tolerogenic, indicating the convenience for their clinical utility. MSCs are able to regulate the activities of immune cells from both innate and adaptive immune systems, but their immunomodulatory capacity is not constitutive. MSCs require “licensing” to gain their immunosuppressive function after stimulation from certain inflammatory cytokines and are therefore chemokine-dependent. IFN-γ is critical for the chemokine induction in MSCs [54,55,56]. However, the optimal induction of immunosuppression requires the concurrent addition of other proinflammatory cytokines, such as TNF-α, IL-1α, IL-1β, and IL-17 [55,56,57]. Constitutively, MSCs express low levels of immunomodulatory molecules, including indoleamine 2,3-dioxygenase (IDO), prostaglandin E-2 (PGE-2), TGF-β, and hepatocyte growth factor (HGF). These inflammatory cytokines can differentially regulate their expression under inflammatory conditions [58]. Again, IFN-γ in particular plays an important role in regulating MSC immunomodulatory factor expression [58]. On the contrary, immunosuppressive cytokines, such as TGF-β and IL-10, are believed to serve a counterbalancing role by inducing less immunosuppressive MSCs and thus become immune-enhancing. It was observed that TGF-β abolishes the immunosuppressive capacity of MSCs by downregulating the expression of IDO or inducible NO synthase (iNOS) in MSCs [59]. In addition to cytokines, Toll-like receptor (TLR) signaling has also been implicated in the licensing of MSCs, and the stimulation of specific TLRs on MSCs may greatly affect their immune-modulating responses. TLR4 priming can induce a proinflammatory signature of MSCs (MSC1 phenotype), which mostly involves inflammatory mediators, such as IL-6, IL-8, and TGF-β. In contrast, TLR3-primed MSCs represent immunosuppressive activities (MSC2 phenotype) and secrete IDO, PGE-2, IL-4, and IL-1RA [60]. These data indicate that the inflammatory status in their microenvironment determines the immunoregulatory fate of MSCs (Figure 3). They are rendered immunosuppressive in the presence of strong inflammation, but week inflammation may cause MSCs to promote immune responses [61]. Having profound immunomodulatory potential, MSCs are receptive to environmental cues and orchestrate the activation, proliferation, and function of immune cells from both innate and adaptive immune systems. Under inflammatory conditions, the immunosuppressive activities of MSCs have been demonstrated to prevent overstimulation of the immune system. Monocyte/macrophage modulation is critical in the MSC-mediated immunomodulatory process. MSCs can inhibit monocyte differentiation from CD34+ HSCs and promote macrophage polarization into an anti-inflammatory M2 phenotype [62,63]. MSCs can affect the differentiation of dendritic cells (DCs) from monocyte precursors [64,65,66]. They could inhibit DC maturation and activation by downregulating the expression of presentation molecules (HLA-DR and CD1a) and costimulatory molecules (CD80 and CD86) in DCs [67,68]. MSCs also exert immunosuppressive effects on mature DCs by inhibiting their migration, compromising their antigen-presenting abilities, repressing their stimulation of lymphocyte proliferation, and decreasing their secretion of inflammatory mediators [69]. Moreover, MSCs can modulate the immune responses of natural killer cells by downregulating their proliferation, cytokine production, and cytolytic activity [70]. MSCs exert immunomodulatory effects on these innate cells mainly through paracrine mechanisms, involving a complicated network of cytokines. MSCs act on the adaptive immune system in multiple ways, through both direct cell contacts and paracrine effects. MSCs are able to inhibit the proliferation, differentiation, chemotaxis, and immunoglobulin production of B cells [71,72,73,74]. MSCs can also promote the induction of IL-10-producing regulatory B cells, which restrain inflammation by enhancing the conversion of effector CD4+ T cells into Tregs [75]. MSCs influence the behavior of T cells significantly, including proliferation, activation, cytokine secretion, and cytotoxicity [76]. Under inflammatory conditions, MSCs inhibit the expression of Th1 proinflammatory cytokines and enhance Th2 factors, resulting in a more tolerant immune status [50]. MSCs can also regulate the balance between Th1 and Th2 cells through interactions with DCs and natural killer cells [77]. An important mechanism of MSC-mediated immunomodulation of T cells is the generation of Tregs, which are essential for immune homeostasis and the prevention of alloreactive and autoimmune diseases [78]. MSCs can directly induce Treg differentiation through the TLR–Notch pathway and the secretion of TGF-β, IDO, and iNOS [79,80,81]. By increasing IL-10 secretion and decreasing IFN-γ and IL-17 production, MSCs can also promote Treg differentiation from CD4+ T cells and suppress Th1 and Th17 differentiation [82]. MSCs play a role in modulating the balance between Tregs and Th17 cells, and the Treg/Th17 ratio is implicated in shaping the outcome of immune responses (immunosuppression versus inflammation) [83,84]. Due to their great immunomodulatory functions, MSC therapy has been used in numerous immune- or inflammation-associated disorders in humans. MSCs are derived from mesodermal progenitor cells, and they were firstly identified in the bone marrow [85]. In addition to bone marrow, MSCs can also be isolated from a broad spectrum of tissues, including adult tissues (peripheral blood, fat, and dental pulp) and fetal tissues (umbilical cord, cord blood, placenta, amniotic membrane, and amniotic fluid). The frequency of MSCs in different tissues varies greatly, and their ontological origin also has considerable influence on their performance. The umbilical cord is much richer in MSCs than cord blood [86]; adult bone marrow is a reliable source, but peripheral blood is not [35]. There are several differences between fetal-type MSCs and adult-type MSCs. Fetal-type MSCs appear to have greater expansion capacity, which may be due to their longer telomeres, greater telomerase activity, and higher expression of telomerase reverse transcriptase [87,88,89]. Fetal-type MSCs are less lineage-committed and display lower levels of HLA-class I [90]. Fetal-type MSCs and adult-type MSCs may express different cytokine profiles, immunomodulatory properties, and differentiation potential [88,89,90,91,92]. The regulation of hematopoiesis depends on the interaction between HSCs and various cells within the bone marrow niche. Several studies have demonstrated the involvement of MSCs in the functional restriction of HSCs in AA. Using a long-term culture system, bone marrow stromal cells of patients with AA were found to be insufficient to maintain normal HSCs and failed in confluent growth [93,94]. When cocultured with AA MSCs, the proliferation of peripheral blood mononuclear cells and the colony-forming capacity of CD34+ cells were significantly reduced [95,96]. These data implicated the insufficiency of AA MSCs in hematopoietic support. Downregulated expression of VCAM-1 in AA MSCs was proposed as being associated with the impairment of in vitro growth support and in vivo engraftment of CD34+ cells [97]. However, multiple intrinsic defects in the bone marrow MSCs of patients with AA may exist. Impaired proliferative potential is the hallmark of MSCs in AA. Using population doubling as the indicator, we firstly reported that AA MSCs had a worse average population doubling at each passage and a smaller cumulative population doubling from passage 4 to 6 [98]. We observed that three of five AA MSC cultures stopped proliferating at passage 5, implicating the possibility of early senescence in AA MSCs [95]. We further determined the distribution of cultured cells in different cell cycle phases by flow cytometry and found a high percentage of cells in the abnormal sub-G1 phase in AA MSCs [95]. Our data suggested that an increased apoptotic rate of AA MSCs may contribute to their poor proliferative capacity and early senescence. Our findings were confirmed by numerous studies thereafter [96,99,100,101,102,103]. The worse proliferative potential of AA MSCs was documented based on different parameters, including population doublings [96,99,100], a CCK-8 assay [100,101], growth curves [102], and colony-forming potential [103]. Higher rates of apoptotic cells in AA MSCs were measured via cell cycle analysis [100] and an annexin V-affinity assay [101,103]. AA MSCs were found to be prone to senescence, shown by a higher proportion of β-galactosidase-stained cells [100] and failure to passage [102]. Phenotypic characterization is an important ISCT criterion to define MSCs, as shown in Figure 2 [46]. Flow cytometric analysis has been used to examine the alteration in surface marker expression in AA MSCs. The study by Bueno et al. was the only one that fully complied with all the marker criteria established by the ISCT [104], and most studies used six to eight markers as the indicator. Consistent results showed that no difference was noted in the expression of any single surface marker between MSCs derived from patients with AA and controls [105]. The final criterion of the ISCT for the definition of MSCs is their in vitro trilineage mesenchymal differentiation capacity (Figure 2) [46]. We firstly reported lower osteogenic and adipogenic capacities of AA MSCs following differentiation induction [98]. Thereafter, a variety of qualitative and quantitative modalities was used to assess alterations to AA MSCs in differentiation tendencies towards osteoblasts, adipocytes, and chondroblasts, including staining methods, RT-qPCR, and Western blot analysis. Lower osteogenic and chondrogenic differentiation propensities of AA MSCs were confirmed in most studies. However, there was an apparent discrepancy in the results of adipogenesis in AA MSCs, which included increased adipogenic differentiation potency in some studies and decreased in others [105]. The discrepancy can be explained by the complex pathogenesis of idiopathic AA and heterogeneous study populations. Nevertheless, alterations in the differentiation potential of AA MSCs may exist. Immune-mediated HSC destruction is an important pathogenic mechanism of idiopathic AA, and MSCs have great immunomodulatory functions. The dysregulation of immune cells from MSCs may impact immune homeostasis in the bone marrow microenvironment. Our previous study demonstrated aberrant cytokine profiles in the conditioned medium of AA MSCs with increased concentrations of IL-1β, IL-6, IFN-γ, and TNF-α, suggesting the association between aberrant paracrine factors secreted by MSCs and the hyperinflammatory marrow niche in AA [95]. Bacigulupo et al. observed deficiency in the ability of AA MSCs to downregulate T cell priming, proliferation, and cytokine release [106]. Hu et al. demonstrated impaired inhibition of AA MSCs based on the activation of CD4+ and CD8+ T cells and differentiation towards Th1 and Th17 cells [100]. Li et al. found that AA MSCs were reduced in suppressing the proliferation and clonogenic potential of CD4+ T cells and the production of IFN-γ and TNF-α by CD4+ T cells [107]. We recently examined the influence of AA MSCs on the differentiation of CD4+ T cells into CD4+CD25+FoxP3+ Tregs under Treg polarization conditions. AA MSCs showed promotive effects on Treg differentiation, but there were inconsistent changes based on TGF-β and IL-1β levels in the supernatant, implying that a large number of dysfunctional Tregs was produced when CD4+ T cells were cocultured with AA MSCs during differentiation [108]. Collectively, these data provide evidence for the disordered immunomodulatory function of MSCs in AA. Consistent with the anomalous biological performance of bone marrow MSCs in AA, differential gene expression profiles were reported in the literature. Using microarray analysis, we found two different gene expression patterns of MSCs in children with AA, suggesting the heterogeneity of idiopathic AA. Fourteen genes associated with DNA synthesis and growth factors, including POLE2, HFG, KIF20A, TK1, IL18R1, KITLG, FGF18, RRM2, TTK, CXCL12, DLG7, TOP2A, NUF2, and TYMS, were markedly downregulated in AA MSCs [109]. Li et al. performed a comprehensive analysis and confirmed the consistency between the abnormal biological features and the alteration of gene expression profiles in AA MSCs. They observed decreased expression in a number of genes implicated in the cell cycle, cell division, proliferation, chemotaxis, and hematopoietic cell lineage in AA MSCs. Conversely, the expression of genes related to apoptosis, adipogenesis, and the immune response was increased in AA MSCs [103]. With the advance in experimental tools, Hue et al. documented the differential gene expression pattern of AA MSCs using genome-wide RNA sequencing. They found that the differentially expressed genes were principally associated with immunoregulation, cell cycle, and cell division [100]. Aside from the global view of gene expression profiles, there were several reports about the differential expression of an individual gene, which involved one or more defective properties of MSCs in AA. Regarding the contribution of MSCs to angiogenesis, downregulated expression of VCAM-1 and ANG-1 genes was noted in AA MSCs [97,110]. Jiang et al. found downregulated FGF2 expression in AA MSCs, suggesting their compromised ability of self-renewal and impaired support of HSCs [102]. As an important molecule for the maintenance of HSCs in the bone marrow, decreased CXCL12 expression in AA MSCs was found in our previous study, and the knockdown of CXCL12 compelled control MSCs to behave like AA MSCs [109]. A number of genes was reported to contribute to the alteration in the differentiation potential of AA MSCs, including CBF-α1, RUNX2, and BGLAP in osteogenesis, SOX9 and ACAN in chondrogenesis, and PPAR-γ, ADIPOQ, and FABP4 in adipogenesis [105]. In view of the promotive effects of MSCs on hematopoiesis, various murine models of AA have been used to examine the efficacy of MSC therapy in the context of AA (Table 1). Several attempts were used to induce hypocellular bone marrow in animals, including the administration of toxic or chemical agents, irradiation, and lymph node infusion, but none represented the exact etiology of human idiopathic AA. Although not perfect, lymph node cell infusion combined with irradiation may be superior to irradiation alone to mimic AA in humans because immune-mediated HSC destruction is an important mechanism. The source of MSCs was quite different among studies, being autologous, allogenic, or even xenogeneic. In addition, the dosage of MSCs and time points of MSC administration were variable. Nevertheless, MSC therapy could lead to longer survival, better hematopoietic reconstitution, and faster recovery of peripheral blood cells in most studies [111,112,113,114,115,116,117]. With the growing biologic interest in MSCs, the clinical application of MSCs has been evolving rapidly in the recent decade. More than 1000 clinical trials based on the use of MSCs were implemented to treat various pathologies, according to the US National Institute of Health-Clinical Trial Database (http://clinicaltrials.gov, accessed on 16 February 2022). Several biological properties of MSCs contribute to their therapeutic effects in cell therapy, such as immunomodulation, tissue repair/regeneration, angiogenesis, and antiapoptotic activity [118]. As expected, there are many reports in the literature regarding outcomes of MSC therapy for various human diseases [52,119]. Presumably, diseases with optimal efficacy fall into two main categories. One is associated with immune dysregulation, such as autoimmune diseases (systemic lupus erythematosus, type 1 diabetes mellitus, rheumatoid arthritis), inflammatory diseases (Crohn’s disease, acute respiratory distress syndrome), and graft-versus-host disease (GVHD) after allogeneic transplantation. The other regards tissue regeneration, such as traumatic injury (spinal cord injury, cerebral infarction, ischemic heart disease, wound repair), degenerative diseases (osteoarthritis, liver cirrhosis), and bronchopulmonary dysplasia. For patients with idiopathic SAA, allogeneic HSCT or IST should be used as the first-line therapy. The choice is determined by numerous factors, such as severity of the disease, age of the patient, donor availability, and available medical facility [120]. For pediatric and young adult patients with newly diagnosed SAA, allogeneic HSCT should be pursued when an HLA-identical sibling donor is available. IST with antithymocyte globulin and cyclosporine is the most common alternative frontline therapy for older adult patients and those without a matched sibling donor. The major advantages of HSCT over IST in SAA are the significant reduction in the risk of relapse and the abrogation of the risk for clonal evolution [121]. However, the risk of graft failure and GVHD after HSCT remains the main challenges in the context of SAA. Graft failure was noted in 11–32% of patients with SAA receiving bone marrow transplantation, and acute severe GVHD and symptomatic chronic GVHD occurred in 11–40% and 21–32%, respectively [122]. Moreover, HSCT using grafts from donors other than HLA-identical siblings, such as matched unrelated and haploidentical donors, offers an option for those who have failed previous IST and lack a matched sibling donor. However, the risk of graft failure and GVHD may significantly increase. Novel strategies are needed to improve the transplant-related mortality and morbidity. Chemotherapy and radiotherapy prior to HSCT cause bone marrow stromal damage, which may be associated with engraftment delay. GVHD is a paradigm of immune dysfunction. As mentioned above, MSCs can differentiate into various mesenchyme-lineage cells and produce a complex network of paracrine factors [37]. Along with their great immunomodulatory function, MSCs are crucial for maintaining immune homeostasis and repairing tissue damage in the bone marrow. A large body of evidence indicated that MSCs are efficient in the promotion of engraftment, the prevention and treatment of graft failure, and the management of GVHD in HSCT [123]. Furthermore, multiple MSC alterations were found in patients with AA, and these may contribute to bone marrow insufficiency in AA. Taken together, MSC therapy is rational in the context of AA. With the promising results of MSC therapy using preclinical animal models of AA, MSC transplantation alone or in combination with allogeneic HSCs was performed for patients with AA. The safety and efficacy of MSC therapy were evaluated. As of February 2023, there were nine clinical trials registered on the US National Institute of Health-Clinical Trial Database (http://clinicaltrials.gov, accessed on 16 February 2022) when searching for “MSCs and AA”. Meanwhile, there are many reports in the literature regarding the use of MSCs in AA. In the next paragraphs, the available data on the therapeutic role of allogeneic MSCs for patients with AA are discussed. Five studies regarding allogeneic MSC transplantation for patients with refractory or relapsed AA were reported in the literature (Table 2) [124,125,126,127,128]. Most patients received concomitant immunosuppressants, such as antithymocyte globulin and cyclosporine. Four of the five studies included only a small number of patients. Only one study compared the combination of MSC infusions and IST with IST alone, but the number of patients was quite small [128]. Despite some insufficiency in the quality, all of these reports demonstrated the safety of MSC infusions. However, there were no significant effects on hematopoiesis. Clinical hematologic responses were observed in only a small proportion of patients and were mainly partial. Accordingly, MSC infusions, even multiple times, may not be enough to reconstitute the hematopoiesis in patients with AA. In view of the unsatisfactory outcomes of MSC infusion, the co-transplantation of MSCs during HSCT may be a better option for patients with SAA because allogeneic HSCs can result in the direct reconstruction of hematopoiesis in the bone marrow. In addition, MSCs have the potential to overcome the obstacles in HSCT, for example, graft failure and GVHD. We and Jaganathan et al. firstly reported the promotive effects of MSC infusion on hematopoietic engraftment during HSCT in two children and one adult with refractory SAA, respectively [129,130]. No acute or chronic GVHD was found in our patients. Since then, several studies that enrolled a higher number of patients with SAA receiving MSC and HSC co-transplantation were reported (Table 3) [131,132,133,134,135,136,137,138]. Different treatment protocols were used in different studies, and only one retrospective study had a control group [138]. Nevertheless, the great benefit of MSC co-transplantation during HSCT was observed based on enhancing hematopoietic reconstitution, preventing graft rejection, ameliorating GVHD, and improving overall survival in patients with SAA. The efficacy of MSCs appears to be maintained across different patient populations and treatment protocols: the source and cell number of MSCs, the frequency and time point of MSC administration, and the donor and source of HSCs. The safety of MSC co-transplantation was also evaluated, and no immediate infusion or late MSC-associated toxicities were reported. Accordingly, co-transplantation of MSCs during allogeneic HSCT may be superior to traditional HSCT for patients with SAA. Further prospective studies with a larger cohort of patients are needed. Current clinical results showed the beneficial effects of MSC co-transplantation during HSCT in patients with SAA. Some issues related to the application of MSCs should be further explored, and consensus and guidelines are required to maximize their therapeutic efficacy. Because the number of MSCs obtained from the donor is not enough, passaged cells are used widely in clinical practice. However, the in vitro expansion of MSCs may lead to genetic instability and changes in cell behavior. For example, MSCs may gradually lose their properties of early progenitor cells with passaging, and transforming events may occur [46]. Therefore, conditions for MSC culture should be guaranteed, and it is better to use cells without extensive population doublings. Generally, MSCs within six passages are used in humans [139]. When co-transplanted during HSCT for patients with SAA, MSCs were infused for a single time or multiple times, and the cell doses were 0.5–10 × 106/kg per injection. A single injection with a dose of around 1 × 106/kg before HSC infusion was used most frequently (Table 3). Typically, MSCs are administrated intravenously at doses in 1–2 × 106/kg for most clinical conditions [52]. However, it remains to be verified whether this is the optimal strategy. Tracking studies using labeled MSCs demonstrated that most MSCs were cleared from the body within 24–48 h after infusion. Acting as a hit-and-run attack, multiple injections may be needed in some difficult situations, such as graft rejection and severe GVHD. The injection interval ranged from 3 days to 1 week in most clinical conditions, but the optimal frequency and interval in SAA should be further determined. The source of MSCs is another important issue. MSCs can be obtained from many kinds of tissues, and their ontological origins may greatly impact their properties and their performance in clinical utility. As we know now, no study has compared head-to-head clinical outcomes of MSC therapy with different origins in a single human disease. Fetal-type MSCs are less lineage-committed and have greater expansion capacity [140]. In contrast, bone marrow MSCs exhibit accelerated senescence significantly with age. In addition, umbilical cords are rich in MSCs, and no invasive procedure is needed to obtain MSCs from umbilical cords. Moreover, umbilical cord-derived MSC products from MSC banks are off-the-shelf, with well-performed characterization and the confirmation of sterility. With the great advantage of availability, umbilical cord-derived MSCs have been used prevalently in many human diseases, including SAA. However, the exact discrepancy in the clinical performance of MSCs from different sources should be evaluated. Many studies reported that no significant side effects were noted in the clinical use of MSCs. However, MSC administration is not completely free of risks and most patients were monitored only for a short period of time. While a post-infusion febrile reaction was reported as the most frequent side effect associated with the use of MSCs, other short-term adverse events, such as allergic reactions, secondary infections, viral reactivations, and thromboembolic events, should be closely monitored and promptly managed. On the other hand, cryopreserved MSC products usually contain dimethyl sulfoxide, which may cause acute infusion toxicities, such as headache, dizziness, nausea, vomiting, and allergic reactions. Premedication with antihistamines can alleviate these symptoms. Meanwhile, future studies are needed to assess possible long-term complications, such as ectopic tissue formation and tumorigenesis. Acquired idiopathic AA is a rare but life-threatening bone marrow failure syndrome, with a complex pathophysiology. In this review article, we summarized what is known today regarding the association between MSCs in the pathogenesis of the disease and the use of MSCs for patients with AA (Figure 4). On the whole, MSCs are promising for the management of AA, especially when co-transplanted during HSCT. Meanwhile, there are several important issues regarding their utility in AA and other clinical situations. A variety of challenges still lay ahead! With deeper knowledge from basic studies and clinical applications, we anticipate that more patients can benefit from the therapeutic effects of MSCs, including those with AA. While no severe short-term adverse effects have been observed, long-term safety still needs to be assessed in future studies.

PMC10003044

Carmen Tarifa,Verónica Jiménez-Sábado,Rafael Franco,José Montiel,José Guerra,Francisco Ciruela,Leif Hove-Madsen

Expression and Impact of Adenosine A3 Receptors on Calcium Homeostasis in Human Right Atrium

23-02-2023

human atrial myocyte,adenosine A3 receptor,adenosine A2A receptor,sarcoplasmic reticulum,calcium spark,transient inward current,L-type calcium current,electrophysiology

Increased adenosine A2A receptor (A2AR) expression and activation underlies a higher incidence of spontaneous calcium release in atrial fibrillation (AF). Adenosine A3 receptors (A3R) could counteract excessive A2AR activation, but their functional role in the atrium remains elusive, and we therefore aimed to address the impact of A3Rs on intracellular calcium homeostasis. For this purpose, we analyzed right atrial samples or myocytes from 53 patients without AF, using quantitative PCR, patch-clamp technique, immunofluorescent labeling or confocal calcium imaging. A3R mRNA accounted for 9% and A2AR mRNA for 32%. At baseline, A3R inhibition increased the transient inward current (ITI) frequency from 0.28 to 0.81 events/min (p < 0.05). Simultaneous stimulation of A2ARs and A3Rs increased the calcium spark frequency seven-fold (p < 0.001) and the ITI frequency from 0.14 to 0.64 events/min (p < 0.05). Subsequent A3R inhibition caused a strong additional increase in the ITI frequency (to 2.04 events/min; p < 0.01) and increased phosphorylation at s2808 1.7-fold (p < 0.001). These pharmacological treatments had no significant effects on L-type calcium current density or sarcoplasmic reticulum calcium load. In conclusion, A3Rs are expressed and blunt spontaneous calcium release at baseline and upon A2AR-stimulation in human atrial myocytes, pointing to A3R activation as a means to attenuate physiological and pathological elevations of spontaneous calcium release events.

Expression and Impact of Adenosine A3 Receptors on Calcium Homeostasis in Human Right Atrium Increased adenosine A2A receptor (A2AR) expression and activation underlies a higher incidence of spontaneous calcium release in atrial fibrillation (AF). Adenosine A3 receptors (A3R) could counteract excessive A2AR activation, but their functional role in the atrium remains elusive, and we therefore aimed to address the impact of A3Rs on intracellular calcium homeostasis. For this purpose, we analyzed right atrial samples or myocytes from 53 patients without AF, using quantitative PCR, patch-clamp technique, immunofluorescent labeling or confocal calcium imaging. A3R mRNA accounted for 9% and A2AR mRNA for 32%. At baseline, A3R inhibition increased the transient inward current (ITI) frequency from 0.28 to 0.81 events/min (p < 0.05). Simultaneous stimulation of A2ARs and A3Rs increased the calcium spark frequency seven-fold (p < 0.001) and the ITI frequency from 0.14 to 0.64 events/min (p < 0.05). Subsequent A3R inhibition caused a strong additional increase in the ITI frequency (to 2.04 events/min; p < 0.01) and increased phosphorylation at s2808 1.7-fold (p < 0.001). These pharmacological treatments had no significant effects on L-type calcium current density or sarcoplasmic reticulum calcium load. In conclusion, A3Rs are expressed and blunt spontaneous calcium release at baseline and upon A2AR-stimulation in human atrial myocytes, pointing to A3R activation as a means to attenuate physiological and pathological elevations of spontaneous calcium release events. Cyclic AMP (cAMP) signaling plays a crucial role in modulating calcium regulatory proteins involved in cardiac excitation-contraction coupling, such as L-type calcium channels, the sarcoplasmic reticulum (SR) calcium channel, also named the ryanodine receptor (RyR2), and phospholamban that regulates the activity of the SR calcium pump [1,2]. Physiological and pathological modulation of cAMP signaling, in turn, involves a large number of G protein-coupled receptors (i.e., GPCRs) and phosphodiesterases [3,4]. Within GPCRs, adenosine receptors play a key role in the regulation of myocardial function and rhythm [5]. In this context, the Gi-protein coupled adenosine A1 receptor (A1R) is expected to reduce cAMP production and attenuate the sympathetic tone, and the A1R is a pharmacological target for the regulation of supraventricular arrhythmias [6]. However, excessive A1R activation can also accelerate atrial fibrillation (AF) [7] or favor its induction by shortening the refractory period via activation of the G-protein coupled inwardly rectifying potassium channel [8]. Furthermore, both the A1R and the Gi-protein coupled adenosine A3 receptor (A3R) has been attributed important roles in ischemic preconditioning and cardio protection [9,10,11]. Moreover, the adenosine A2A receptor (A2AR) and A2B receptor (A2BR) are Gs-protein coupled receptors that are expected to stimulate cAMP synthesis and favor cAMP-dependent phosphorylation of key calcium regulatory proteins. Indeed, the A2AR displays an overlapping distribution with the RyR2 and has previously been shown to selectively modulate spontaneous calcium release from the SR [12]. Moreover, A2AR expression is upregulated in patients with AF and prevention of A2AR activation normalizes spontaneous calcium release in patients with AF to levels observed in patients without AF [13], and diminishes the induction of arrhythmic responses in electrically paced myocytes from patients with AF [14]. Because the A3R is expected to inhibit adenylate cyclase, activation of this receptor would be expected to dampen spontaneous A2AR-induced calcium release and contribute to maintaining a low incidence of spontaneous calcium release at baseline. Currently, the functional role of A3Rs in atrial myocytes remains elusive, and there are notable differences in A3R expression or binding of agonists to A3Rs in atria from humans and small rodents [15]. However, since there are species-dependent differences in the expression of G-protein coupled receptors and their binding constants for A3R agonists [15,16], this study aims to determine the expression of A3Rs in human right atrial samples and the functional impact on intracellular calcium homeostasis in human right atrial myocytes. To determine the functional impact of A3Rs in the human atrium, we analyzed the expression and functional electrophysiological impact of A3Rs in myocytes from 53 patients without a previous history of AF. Table 1 summarizes the clinical features of the study population. First, we aimed to determine the expression levels of A3R mRNA in comparison to the other adenosine receptors. The results shown in Figure 1 indicate that A1R mRNA is the most abundant, followed by the A2AR and the A3R. Specifically, the expression of A2AR mRNA constituted the 35 ± 5% of the A1Rs, while A3R accounted for only 9.2 ± 3.3%. However, since GPCRs can be located in macromolecular clusters where they exert a strong regulation of specific molecular functions [17], we first determined how selective A3R inhibition affected calcium homeostasis at baseline. As shown in Figure 2A,B, the selective A3R antagonist MRS1191 significantly increased the incidence of ITI (Figure 2A), without affecting the caffeine releasable SR calcium load (Figure 2B). Furthermore, MRS1191 did not have a significant effect on the ICa amplitude (Figure 2C), but significantly increased the ICa inactivation (Figure 2D). Since we have previously shown that A2AR activation contributes to a higher incidence of ITI in human atrial myocytes [12] and A3R activation would counteract this, we tested whether there is a crosstalk between A3Rs and A2ARs in human atrial myocytes. For this purpose, we first exposed human atrial myocytes to 200 nM CGS21680 to simultaneously stimulate A2ARs and A3Rs. As shown in Figure 3A, this significantly increased the ITI frequency four-fold. Interestingly, subsequent exposure to MRS1191 induced an additional 3-fold increase in the ITI frequency (p < 0.001), suggesting that the A3R blunts the effect of A2AR activation. Analysis of the caffeine-releasable SR calcium load revealed that the treatment with CGS21680 or CGS21680 + MRS1191 did not affect the SR calcium load significantly (Figure 3B), suggesting that the increased incidence of ITI is not caused by a higher SR calcium load. Accordingly, there was no significant correlation between SR calcium load and ITI frequency (p = 0.789; Figure 3C). Immunofluorescent labeling of the RyR2 phosphorylated at s2808 revealed that phosphorylation was significantly higher in myocytes incubated with CGS21680 + MRS1191 than in control myocytes from the same patient (Figure 3D), suggesting that s2808 phosphorylation could contribute to the higher incidence of ITI observed after exposure to CGS21680 + MRS1191. To determine whether A2AR activation increases the ITI frequency by increasing the propensity of the RyR2 to open spontaneously, we analyzed the incidence of calcium sparks resulting from the opening of individual RyR2 clusters [18]. Figure 4A,B shows that both CGS21680 and CGS21680 + MRS1191 induced a dramatic increase in the calcium spark density. This concurred with a significant reduction of the calcium spark amplitude, which was most pronounced in the presence of CGS21680 + MRS1191 (Figure 4C). On the contrary, the treatments had no significant impact on the width (Figure 4D) or the decay of the calcium sparks (Figure 4E). Table 2 summarizes the impact of the two treatments on all calcium spark features analyzed. Finally, the treatment with CSG21680 and CGS21680 + MRS1191 was used to assess the impact of A2ARs and A3Rs on ICa. Figure 5A shows that neither A2AR nor A3R activation had any impact on ICa amplitude. However, concurrent activation of A2ARs and inhibition of A3Rs with CGS21680 + MRS1191 significantly increased time-dependent inactivation of ICa (Figure 5B). Moreover, Figure 5C shows that the time constant for fast ICa inactivation (tau) was inversely correlated with the ITI frequency recorded in the same cell (p < 0.001). In contrast, Figure 5D showed only a weak correlation between tau and ICa density, suggesting that ICa inactivation by calcium influx through the proper L-type calcium channel is modest. However, Figure 5E shows that a brief transient exposure to caffeine, to eliminate SR calcium release-induced ICa inactivation, unmasks a steeper correlation between tau and the ICa density (p < 0.01). Even so, Figure 5F shows that the tau for the ICa inactivation elicited after caffeine exposure is not modified by the treatments with CGS21680 and MRS1191, suggesting that A2ARs and A3Rs have a minor impact on ICa amplitude or inactivation. While the A3R has been attributed an important role in preconditioning and cardio protection [10,19], little is known about its functional role in human atrial myocytes. Here, we analyzed the impact of the A3R on intracellular calcium homeostasis and report that even though A3R mRNA expression is modest compared to the expression of the A1R and the A2AR, endogenous activation of the A3Rs at baseline blunts the incidence of the spontaneous calcium release-induced ITI. Furthermore, crosstalk between A3R and A2AR upon activation of both receptors reduces the incidence of both calcium sparks and ITI, demonstrating that A3R activation diminishes spontaneous, A2AR-mediated, calcium release in human atrial myocytes. The findings also suggest that A3R activation could be a means of attenuating arrhythmogenic calcium release events induced by pathological elevations of the adenosine level. Previous electrophysiological studies in human atrial myocytes have reported a cAMP-tonus at baseline [20], which is regulated by phosphodiesterases and modulates ICa amplitude [21] as well as the incidence of spontaneous calcium release [22]. Consistent with this, we have also shown that the ruptured whole-cell patch configuration dialyses adenosine out of the cell, leading to a reduction of the ITI frequency, presumably because the endogenous adenosine level is sufficient to induce spontaneous, A2AR-mediated, calcium release at baseline [13]. In accordance with these findings, we here observe that selective inhibition of the A3R with MRS1191 increases the basal ITI frequency, suggesting that endogenous adenosine not only activates A2ARs, but also A3Rs at baseline, and that the latter attenuates A2AR-mediated activation of adenylate cyclase. Interestingly, we do not observe any significant effect of A3R inhibition on ICa density or SR calcium loading, pointing to compartmentalization of A3R-mediated signaling. This finding is similar to previous observations on the impact of pharmacological manipulation of Gs-protein coupled receptors in human atrial myocytes where acute pharmacological manipulation of A2AR or treatment of patients with β-adrenergic receptor blockers had no impact on ICa density or SR calcium load [12,13,23]. Since AF has previously been associated with increased A2AR expression and activation that promotes spontaneous calcium release [13], concurrent activation of the A3R would be expected to dampen A2AR-mediated stimulation of calcium release. The present findings demonstrate that when A2ARs and A3Rs are activated simultaneously, A3R activation does indeed attenuate significantly the A2AR-mediated increase in the incidence of both calcium sparks and ITI. In support of this finding, both A3R and A2AR bind adenosine with an affinity of approximately 300 nM [24]. Similar to observations at baseline, A3R inhibition did not modify the ICa density when the A2ARs and A3Rs were stimulated simultaneously with CGS21680. However, A3R inhibition did speed up ICa inactivation and this was correlated with the ITI frequency but not with the ICa amplitude recorded in the same cell. This, combined with the higher incidence of calcium sparks and increased RyR2 phosphorylation at s2808 observed upon concurrent activation of A2AR and A3R suggests that the A3R selectively targets cAMP-dependent phosphorylation of the RyR2 and that this not only leads to a higher ITI frequency, but also leads to a faster calcium-release induced ICa inactivation. Interestingly, the tau for ICa inactivation was inversely proportional to the ICa amplitude when cells had previously been exposed to caffeine to clear the SR calcium content and prevent calcium-release induced inactivation. However, even under these conditions, CGS21680 or CGS21680 + MRS1191 did not affect the ICa amplitude significantly, confirming that A2AR and A3R-dependent signaling targets the RyR2 but not the L-type calcium channel. In the present study, we have focused on the impact of A3Rs on intracellular calcium homeostasis. However, being a Gi-protein coupled receptor, it is conceivable that the A3Rs could also modulate the activity of other ion channels that are regulated by Gi-protein coupled receptors [8,9] or influence the activity of other Gs-protein coupled receptors [25]. This, in turn, would potentially influence the net impact of A3R activity on the amplitude and frequency of calcium release-induced afterdepolarizations. Similarly, the relative impact of A3Rs on A2AR-mediated signaling will depend on the spatial distribution of the A1R, the A2AR, and the A3R with respect to target proteins, such as the RyR2, L-type calcium channels, phospholamban, etc. While this issue has been addressed in non-myocardial preparations [25,26,27], such information is currently limited for atrial myocytes. In this regard, we did show that a gradual elevation of intracellular adenosine levels to pathological levels strongly increases the incidence of calcium waves and ITI and that this could be reversed by selective A2AR inhibition [13], suggesting that A2AR activation plays a prominent role in pathological elevations of the adenosine level. Moreover, this study uses human atrial myocytes that are well suited for translational studies of receptor-mediated modulation of electrophysiological function. However, we cannot rule out that our findings could potentially be affected or present variability due to variations in concurrent disease, risk factors, or pharmacological treatments among the study population. In this context, age has been shown to affect ICa density [28] and sex has been shown to have differential effects on ICa density and ITI frequency [29]. However, because this study does not compare different groups of patients, this issue is primarily expected to increase variability between measurements, rather than the effect of pharmacological treatments. Similarly, the present study was conducted in right atrial myocytes, and we cannot rule out that some of the findings may be specific to the right atrium. We have previously reported that the expression of A2ARs is upregulated in AF, and underlies a higher incidence of calcium-release induced ITI and afterdepolarizations in atrial myocytes from patients with AF [13]. The relevance of these findings is further underscored by higher plasmatic adenosine levels and lower adenosine deaminase activity in patients with AF [30]. In this context, the present findings, showing that A3R activation regulates the impact of A2AR activation on RyR2 phosphorylation and spontaneous calcium release, suggest that selective activation of adenosine A3Rs might be suitable to dampen pathological elevations of the incidence of spontaneous calcium release-induced electrical activity. In particular, cardioprotective approaches targeting the A3R during ischemia, where adenosine levels are known to surge [31], could be a point of departure to explore the potential of A3Ra as a novel target to prevent induction of atrial ectopic atrial activity. Atrial myocytes were isolated from tissue fragments collected from 53 patients, without a previous history of AF, undergoing cardiac surgery at Hospital de la Santa Creu i Sant Pau in Barcelona. Clinical and echocardiographic data of these patients are summarized in Table 1. Myocytes were isolated from right atrial samples, as previously described [28]. Each patient gave written consent to obtain blood and tissue samples that would otherwise have been discarded during surgery. Total RNA was isolated from human right atrial samples using a commercially available kit. First-strand cDNA was synthesized from 1 mg of total RNA. cDNA was amplified using TaqMan master mix and primers from Thermo Fisher Scientific (Waltham, MA, USA) for the human glyceraldehyde-3-phosphate dehydrogenase (GAPDH): Hs00266705_g1; for human A1R (ADORA1): Hs00181231_m1; for human A2AR (ADORA2A): Hs00169123_m1; for human A2AB (ADORA2B): Hs00386497_m1; and for human A3R (ADORA3): Hs00181232_m1. Isolated myocytes were subjected to the perforated patch technique using a HEKA EPC-10 amplifier (HEKA Elektronik, Lambrecht/Pfalz, Germany). Series resistance compensation was not applied. The extracellular solution contained (in mM): NaCl 127, TEA 5, HEPES 10, NaHCO3 4, NaH2PO4 0.33, glucose 10, pyruvic acid 5, CaCl2 2, and MgCl2 1.8 (pH = 7.4). The pipette solution contained (in mM): aspartic acid 109, CsCl 47, Mg2ATP 3, MgCl2 1, na2phosphocreatine 5, Li2GTP 0.42, HEPES 10 (pH = 7.2 with CsOH), and 250 µg/mL amphotericin B. ICa density and properties were measured using a 200 ms depolarization from a holding potential of −80 mV to 0 mV. A 50 ms prepulse to −45 mV was used to inactivate the Na+ current. The ICa amplitude was normalized to the cell capacitance to obtain the ICa density. The decay of the ICa was fit with a double exponential to obtain the time constants tau-1 and tau-2 for fast and slow ICa inactivation. This study focused on the fast time constant, which is modulated by calcium release from the SR and by calcium entry through the L-type calcium channel. ITI currents were recorded at a holding potential of −80 mV in 4 × 30 s intervals to determine the ITI frequency. Brief exposure (6s) to 10 mM caffeine at a holding potential of −80 mV was used to release calcium from the SR and the time integral of the resulting transient inward NCX-current was used to assess the SR calcium load. Transformation of the charge carried by the NCX-current assumed a stoichiometry of 3 Na+:1 Ca2+ for the NCX. Working solutions containing 200 nM CGS21680 and/or 1 µM MRS1191 were prepared from 1 mM stock solutions dissolved in DMSO. Isolated myocytes were fixed and permeabilized, as previously described [32] and non-specific sites were blocked by incubation with PBS/Tween 20, 0.2% and horse serum, 10% for 30 min. Total and ser-2808 phosphorylated RyR2 were inmunofluorescently labeled with mouse anti-RyR2 (C3-33 NR07, 1:1200; Calbiochem, San Diego, CA, USA) and rabbit anti-ser2808-P (1:1200, A010-30, Badrilla, Leeds, UK). The secondary antibodies AlexaFluor 488 anti-mouse and AlexaFluor 594 anti-rabbit were diluted 1:1000 and used to stain total RyR2 green and ser-2808 phosphorylated RyR2 red. Images were acquired with a Leica AOBS SP5 confocal microscope (Wetzlar, Germany) and a 63× glycerol immersion objective. Confocal calcium images (512 × 140 pixels) were recorded at 90 Hz with the Leica SP5 AOBS resonance-scanning confocal microscope in fluo-4 loaded myocytes, as described previously [32]. Experiments were carried out at room temperature. Calcium sparks were detected and clustered in 2 × 2 µm2 regions of interest, termed spark sites, using a custom-made algorithm based on continuous wavelet transform of the temporal profile at every spatial location, as described elsewhere [33]. The calcium spark frequency and the number of spark sites were normalized to the cell area to obtain the calcium spark density (sparks/s/1000 µm2) and the spark site density (spark sites/1000 µm2). In addition, we calculated the number of sparks per site (sparks/site/s). A series of morphological features were measured for each spark signal: Relative amplitude of the peak to the local baseline (F/F0), full duration at half maximum (FDHM), decay constant of an exponential fit (tau), the coefficient of determination of the exponential fit (R2), and full width at half maximum (FWHM). Experimental data were collected and analyzed without knowledge about clinical data and clinicians did not know the experimental results. Statistical analysis was carried out using RStudio 4.2.2 statistical software. Unless otherwise stated, data were averaged for each patient and results are given as mean ± s.e.m. with indication of the number of patients in each group. Fisher’s exact test was carried out for categorical data. Student’s t-test was used for paired or unpaired comparisons, and ANOVA, ANOVA with Welch correction or Kruskal–Wallis were used for comparison of multiple effects, as indicated. Tests used are indicated for each figure and statistically significant effects are indicated with p-values or *: p < 0.05, **: p < 0.01; ***: p < 0.001.

PMC10003046

Lara Valenčić Seršić,Vedrana Krušić Alić,Maša Biberić,Siniša Zrna,Tin Jagoić,Janja Tarčuković,Kristina Grabušić

Real-Time PCR Quantification of 87 miRNAs from Cerebrospinal Fluid: miRNA Dynamics and Association with Extracellular Vesicles after Severe Traumatic Brain Injury

01-03-2023

Traumatic Brain Injury,Cerebrospinal Fluid,MicroRNAs,Size Exclusion Chromatography,Extracellular Vesicles,CD81 protein

Severe traumatic brain injury (sTBI) is an intracranial damage triggered by external force, most commonly due to falls and traffic accidents. The initial brain injury can progress into a secondary injury involving numerous pathophysiological processes. The resulting sTBI dynamics makes the treatment challenging and prompts the improved understanding of underlying intracranial processes. Here, we analysed how extracellular microRNAs (miRNAs) are affected by sTBI. We collected thirty-five cerebrospinal fluids (CSF) from five sTBI patients during twelve days (d) after the injury and combined them into d1–2, d3–4, d5–6 and d7–12 CSF pools. After miRNA isolation and cDNA synthesis with added quantification spike-ins, we applied a real-time PCR-array targeting 87 miRNAs. We detected all of the targeted miRNAs, with totals ranging from several nanograms to less than a femtogram, with the highest levels found at d1–2 followed by decreasing levels in later CSF pools. The most abundant miRNAs were miR-451a, miR-16-5p, miR-144-3p, miR-20a-5p, let-7b-5p, miR-15a-5p, and miR-21-5p. After separating CSF by size-exclusion chromatography, most miRNAs were associated with free proteins, while miR-142-3p, miR-204-5p, and miR-223-3p were identified as the cargo of CD81-enriched extracellular vesicles, as characterised by immunodetection and tunable resistive pulse sensing. Our results indicate that miRNAs might be informative about both brain tissue damage and recovery after sTBI.

Real-Time PCR Quantification of 87 miRNAs from Cerebrospinal Fluid: miRNA Dynamics and Association with Extracellular Vesicles after Severe Traumatic Brain Injury Severe traumatic brain injury (sTBI) is an intracranial damage triggered by external force, most commonly due to falls and traffic accidents. The initial brain injury can progress into a secondary injury involving numerous pathophysiological processes. The resulting sTBI dynamics makes the treatment challenging and prompts the improved understanding of underlying intracranial processes. Here, we analysed how extracellular microRNAs (miRNAs) are affected by sTBI. We collected thirty-five cerebrospinal fluids (CSF) from five sTBI patients during twelve days (d) after the injury and combined them into d1–2, d3–4, d5–6 and d7–12 CSF pools. After miRNA isolation and cDNA synthesis with added quantification spike-ins, we applied a real-time PCR-array targeting 87 miRNAs. We detected all of the targeted miRNAs, with totals ranging from several nanograms to less than a femtogram, with the highest levels found at d1–2 followed by decreasing levels in later CSF pools. The most abundant miRNAs were miR-451a, miR-16-5p, miR-144-3p, miR-20a-5p, let-7b-5p, miR-15a-5p, and miR-21-5p. After separating CSF by size-exclusion chromatography, most miRNAs were associated with free proteins, while miR-142-3p, miR-204-5p, and miR-223-3p were identified as the cargo of CD81-enriched extracellular vesicles, as characterised by immunodetection and tunable resistive pulse sensing. Our results indicate that miRNAs might be informative about both brain tissue damage and recovery after sTBI. Traumatic brain injury (TBI) is a disruption of brain anatomy and function due to the action of an external force [1]. This may happen in different conditions, such as the head striking an object (blunt trauma), the brain undergoing a rapid acceleration/deceleration movement, or a foreign body penetrating the brain [2]. The two leading causes of TBI are falls and motor vehicle accidents. These injury mechanisms result in the highest incidences among specific age groups: falls are most prominent in early childhood (0–4 years) and older adults (>65 years), while adolescents and young adults (15 to 24 years) are mostly affected by motor vehicle accidents [3]. In terms of pathogenesis, TBI involves a complex process that starts as a primary injury at the moment of physical impact to the head, and continues as a secondary injury during hours, days or even weeks after the primary injury [3]. The secondary injury is a result of different biochemical and cellular events triggered by the primary injury. They include excitotoxicity, mitochondrial disfunction, oxidative stress, lipid peroxidation, neuroinflammation, blood brain barrier disruption, axon degeneration, and apoptotic cell death [4]. In clinical settings, TBI is classified as mild, moderate or severe. The initial assessment is based on the international Glasgow Coma Scale (GCS), with predefined points for eye, verbal and motor response. The scale ranges from 3 to 15 points, where 3 points are assigned to a comatose patient with no response, and 15 are assigned to a fully alert and cooperative patient. Taken together, GCS subranges of 3–8, 9–12 and 13–15 define the severe, moderate and mild TBI, respectively [5]. Before the final diagnosis is made, additional diagnostic methods, including neuroradiological imaging and neurological examination, are used to complement the GCS-based clinical profile of the patient. Next to intensive treatment measures, severe TBI (sTBI) can involve emergent surgical interventions including decompressive craniectomy and/or placing a catheter into cerebral ventricles; or a system called an external ventricular drain (EVD) to monitor and control the intracranial pressure (ICP) values [6]. Even when acute treatment is successful, long term survivors from sTBI have an increased risk of mortality and disability due to the acquired central nervous system (CNS) damage [7,8]. Despite the significant progress in the field of TBI, both in terms of pathophysiology as well as diagnostic and treatment procedures, several intrinsic TBI features are still associated with challenges in clinical settings and require a deeper understanding of processes in the brain after the injury. Not only can the clinical presentation of TBI be very different, but it can also change rapidly due to the dynamic nature of the secondary injury. On top of that, continuous monitoring of brain morphological changes via neuroradiological imaging is not applicable for both practical and safety issues. Therefore, additional diagnostic and prognostic tools for evaluating the brain function after TBI are greatly needed. Recent studies identified circulating biomarkers in body fluids such as cerebrospinal fluid (CSF) and blood with growing interest in microRNAs (miRNAs) [9,10]. miRNAs are small (19–28 nucleotides), non-coding RNAs involved in posttranscriptional gene regulation. This is especially noticeable in CNS, since approximately 70% of known miRNAs are estimated to be expressed in nervous tissue, both in physiological and pathophysiological conditions [11]. Similarly, TBI has been reported to alter different miRNAs [9]. The downregulation of plasma miR-16 and miR-92 and the upregulation of plasma miR-765 have been detected within the first 24 h after sTBI [12]. Increased plasma miR-92a and miR-16 were found in mild TBI patients [12]. A post-mortem gene expression analysis of the human cerebellum after sTBI detected 13 miRNAs, but found no clinical correlation [13]. Elevated serum miR-93, miR-191, miR-499, miR-21 and miR-335 were noticed in sTBI patients and were suggested as biomarkers for the TBI detection and progression [14,15]. Furthermore, miR-124, miR-219a, miR-9, miR-137, and miR-128 might be more CNS-specific, as determined by a bioinformatic analysis [16]. Serum levels of miR-219a-5p have been indicated as a potential indicator for the diagnosis and prognosis of sTBI while six other miRNAs, including miR-103a-3p, miR-302d-3p, miR-422a, miR-518f-3p, miR-520d-3p and miR-627, were significantly upregulated in both severe and mild TBI patients in comparison to healthy controls [17]. Another studies of plasma and CSF samples also identified a panel of miRNAs as a potential signature specific of TBI [18,19]. While the search for miRNA biomarkers in CSF and blood/plasma serum brings the advantage of analysing the body fluid which is in direct contact with the brain or is easily accessible, salivary samples have also been utilised to characterise miRNA after TBI, as recently reviewed [20]. Taken together, the majority of researches used serum and plasma samples as the main investigated biofluids in TBI patients. The resulting miRNA species with potential diagnostic and prognostic value varied, which could be due to differences in methodology in sampling and analyses. An additional feature of extracellular miRNAs, which might affect isolation and characterisation, is that miRNAs can circulate either bound to proteins or as the cargo of extracellular vesicles (EVs) [21]. EVs are membrane-enveloped nanostructures (20–1000 nm in diameter) that are secreted by cells into body fluids. They carry their diverse content including lipids, proteins and nucleic acids, such as miRNAs [22]. EVs are very heterogenous in their size and molecular cargo, but their content is believed to reflect the type and current state of the originating cells [23]. Since EV content is cell-specific and EVs are accessible from body fluids, EVs have a biomarker potential which is especially valuable for organs with no or difficult access, such as the brain, after sTBI [24]. EVs in CSF after sTBI were shown to change their number, size and protein composition, as well as to carry miRNA resulting in considering EV-miRNAs as biomarkers for TBI [25,26,27]. EV miRNAs isolated from human and mouse plasma samples also showed potential in TBI classification: a panel of eight miRNAs (miR-150-5p, miR-669c-5p, miR-488-3p, miR-22-5p, miR-9-5p, miR-6236, miR-219a.2-3p, miR-351-3p) were identified in a mouse TBI model, and four miRNAs (miR-203b-5p, miR-203a-3p, miR-206, and miR-185-5p) were differentially regulated in TBI patients when compared to healthy controls, respectively [28]. Taken together, various miRNAs from different body specimens were shown to change their levels after TBI, whereby some of these changes might be in the context of EVs. To provide a more systematic approach, we decided to monitor a set of miRNAs in several time points after sTBI. We collected CSF samples during the 12 days (d) after sTBI and combined them into d1–2, d3–4, d5–6 and d7–12 CSF pools. We quantified 87 miRNAs by real-time PCR in all CSF pools, as well as in EV- and free protein (FP)-fractions obtained after size exclusion chromatography (SEC). We found that the majority of targeted miRNAs showed the highest levels in d1–2 and d3–4, which were also compromised by haemolysis. Furthermore, most miRNAs were associated with FPs. Although the main limitation of the study is the low number of patients and CSF samples, our data show a high range of miRNA concentrations and identify miRNA candidates indicative for ongoing processes in the brain. Severe traumatic brain injury (sTBI) changes the molecular composition of cerebrospinal fluid (CSF) due to the very nature of intracranial tissue damage [25,29]. To enable better insight into CSF molecular dynamics, we included sTBI patients whose acute treatment required intracranial pressur (ICP) monitoring and management by placing the external ventricular drain (EVD) soon after the primary injury. CSF samples were obtained from 5 sTBI patients, four males and one female, with ages ranging from 19 to 49 years and a mean age of 33.8 ± 12.8 years (Table 1). All but one patient had a favourable outcome three months after discharge as defined by a Glasgow Outcome Scale (GOS) score of 4 or 5. A total of thirty-five individual CSF samples were collected daily for up to twelve days after the injury until EVD was in place, a decision which was at the discretion of the supervising physician (Figure 1). To facilitate downstream analyses, we combined consecutive CSF samples into four pools: days 1 and 2 (d1–2), d3–4, d5–6 and d7–12. The d1–2 and d3–4 were derived from five sTBI patients, while d5–6 and d7–12 CSF pools were derived from four and two sTBI patients, respectively. However, all CSF pools contained between eight and ten individual CSF samples, resulting in comparable CSF mixtures regarding the sample number and volume. The first three CSF pools contained samples from both patients with good (GOS 4–5) and fatal (GOS 1) outcomes, while the latest CSF pool was comprised of CSF from patients with good outcomes (Table 1). Several studies have shown that diverse microRNAs (miRNAs) can be detected in human CSF after sTBI, but no comprehensive comparison of miRNA types and levels during patient recovery have been described. To provide a more systematic analysis of miRNA, we decided to simultaneously quantify a set of 87 miRNAs in the consecutive CSF pools spanning the twelve days after the injury. We applied a commercially available PCR-array containing primers for CSF-associated miRNAs and enabling absolute miRNA quantification based on spike-in miRNAs (Figure 2A). We isolated miRNAs from four CSF pools and determined RNA concentrations by spectrophotometer. We detected the lowest RNA concentration of 9.2 ± 0.3 ng/µL in d1–2 CSF pool followed by increasing RNA concentrations of 11.1 ± 0.3 ng/µL, 12.9 ± 0.3 ng/µL and 14.6 ± 0.5 ng/µL in d3–4, d5–6 and d7–12, respectively (Figure 2B). The increasing RNA concentrations were surprising, since they did not match the level of haemolysis which were clearly visible by the naked eye as different shades of red, and this often compromises the miRNA analysis [30]. We assessed the haemolysis level by performing reverse transcription and applying the cDNAs to a commercially available quality control (QC) PCR plate containing miR-451 and miR-23a-3p as haemolysis dependent and independent miRNAs, respectively [31]. The difference in threshold cycles (ΔCt = Ct(miR-451) − Ct(miR23a-3p)) of 7 or more indicates a high risk of haemolysis [30]. We found the highest ΔCt values of 8.90 ± 0.19 and 9.76 ± 0.17 in d1–2 and d3–4, respectively, while in d5–6 and d7–12 we detected ΔCt values of 7.61 ± 0.04 and 6.87 ± 0.23, respectively (Figure 2C). These results indicate that d1–2 and d3–4 might be significantly more affected by haemolysis than d5–6 and d7–12. To better characterise plasma-derived content in CSF pools and their potential association with detected miRNAs, we performed a western blot analysis for albumin and some apolipoproteins (Apo). We detected similar profiles for albumin and ApoAI, with the highest protein levels in d1–2 followed by moderate but comparable levels in d3–4 and d5–6 and low levels in d7–12 (Figure 2D). We noticed moderate and comparable levels of ApoE in d1–2 and d3–4, but higher and comparable levels of ApoE in d5–6 and d7–12. These data show that the CSF during the first four days after sTBI was more compromised with the blood content in comparison to the later days. To assess whether the intracellular content from damaged cells is also present in CSF pools, we analysed several peroxiredoxins (Prdx), which are ubiquitous proteins involved in the antioxidative response in various cells, including erythrocytes and leukocytes [32]. Similar to albumin and apolipoprotein profiles, we detected the highest level of Prdx2 and Prdx6 in d1–2 followed by lower but similar levels at d3–4 and d5–6, and a very low level in d7–12. We noticed very low levels of Prdx1 and Prdx5 at d1–2 and no clearly detectable signals for these two peroxiredoxins in any of the other CSF pools. After the initial characterisation of total miRNA in CSF pools together with proteins of plasma and cellular origin, we then set out to identify and quantify miRNAs present in CSF after sTBI. To enable the quantification of miRNAs, we utilised spike-in miRNAs (UniSp2, UniSp4 and UniSp5), which were available at a 100-fold concentration difference and were included for detection in the PCR-array to be applied. We added spike-ins in the cDNA synthesis step, thereby preserving their initial concentrations. After performing a real-time PCR we used the resulting Ct values to create standard curves (Figure 3A). We were able to detect all spike-ins in every PCR-array measurement, including the UniSp5 spike-in, which corresponded in the amount of miRNAs present at a very low concentration. We obtained standard curves with R2-values ranging from 0.94 to 0.91 and used them to quantify miRNAs. We detected and quantified all 87 targeted miRNAs, but their levels differed by more than a million-fold across the four CSF pools (Table S1). Almost all of the 87 targeted miRNAs showed the highest levels at d1–2 except for miR-25-3p, miR-486-5p, and miR-92a-3p, which exhibited the highest levels at d3–4. Based on detected Ct values for d1–2, we could group miRNAs into high (Ct < 25), moderate (Ct 25 to <30), and low (Ct 30 and more) abundant miRNAs, resulting in amounts of approximately 4–16 pg, 2–4 pg and less than 1 pg, and comprising 54, 29 and 4 targeted miRNA sequences, respectively. We could not detect miR-155-5p at d7–12 or miR-181c-5p and miR-182-5p at both d5–6 and d7–12. We noticed that the following 10 miRNAs are the most abundant across all four CSF pools: miR-451a, miR-16-5p, miR-144-3p, miR-20a-5p, let-7b-5p, miR-15a-5p, miR-21-5p, miR-223-3p, miR-106a-5p and miR-15b-5p (Figure 3B). Although all of these 10 miRNAs decreased in amount with every time point, their charts showed different slopes, with miR-451a and miR-21-5p having the biggest and the smallest slope, respectively. These results might indicate different cellular sources of quantified miRNAs. The trend of a decreasing amount of miRNA was also visible when we calculated the total mass of the targeted miRNA across all CSF pools (Figure 3C). The highest amount of 23.37 ± 1.03 pg of total targeted miRNA was detected in the d1–2 pool, followed by 13.22 ± 1.29 pg, 2.05 ± 0.12 pg, and 0.55 ± 0.05 pg in d3–4, d5–6 and d7–12, respectively. Taking into account that cDNA synthesis was performed with equal RNA amounts, these results indicate that CSF from later days contains miRNAs not included in the applied PCR-array. To identify relative changes in individual miRNA levels across all CSF pools, we normalised miRNA levels against d5–6 levels, since the haemolysis at that time point was low in comparison to d1–2 and d3–4 (Figure 3D). The resulting heat map showed a common trend for the majority of miRNAs, with the highest level at d1–2 followed by decreasing levels in later days. These results also indicate that the targeted 87 miRNAs are likely to be of blood origin. To test whether some of the 87 targeted miRNAs were EV-cargo in CSF after sTBI, we first characterised the EV populations present in CSF pools (Figure 4A). By applying western blot analyses, we could detect protein markers for exosomes, i.e., medium size EVs, as per recently recommended nomenclature [33]. CD9, CD81, Flotillin-1 and -2 and TSG101 were present at high levels at d1–2, followed by a moderate decrease in levels for CD9, Flotillin-1 and -2, and a sharp decrease for CD81 and TSG101 at d3–4 and d5–6. All five EV-protein markers were detected at very low levels at d7–12. We could also detect Annexin V, the protein marker of apoptotic bodies, albeit at low levels at d1–2 and d5–6, and hardly detectable at levels at 3–4 and d7–12. These data suggest that apoptotic bodies are only a minor population of EVs in analysed CSF- pools, while a substantial portion of CD9, Flotillin-1 and -2 positive EVs might have a plasma origin, since these proteins were detected at higher levels in haemolysis compromised CSF pools. Interestingly, CD81 and Tsg101 showed low but constant and comparable levels at d3–4, d5–6 and d7–12, suggesting that haemolysis might not be the major source of CD81 and Tsg101 positive EVs in those CSF pools. After characterising EV populations, our next goal was to separate the CSF pools into EV- and free protein (FP)-enriched fractions and use them for miRNA isolation and quantification (Figure 4B). For CSF pool separation, we applied size-exclusion chromatography (SEC) followed by immunodetection of CD81 and albumin in SEC-fractions as previously shown to be an effective way of EV isolation and detection [34]. In a total of 44 fractions collected in each SEC, we detected CD81 and albumin in fractions 14–17 and 28 and/or later, respectively (Figure 4C). These data demonstrate that CD81 and albumin enriched fractions were clearly separated in all four CSF pools. After pooling CD81+ fractions, we measured the numbers and sizes of isolated EVs by tunable resistive pulse sensing (Figure 4D,E). We detected in d1–2 (4.96 ± 0.18) × 109 particles/mL, which was significantly higher in comparison to later days where we found concentrations of (0.52 ± 0.15) × 109, (1.32 ± 0.19) × 109 and (0.93 ± 0.19) × 109 nanoparticles/mL in d3–4, d5–6 and d7–12, respectively. Interestingly, EV sizes were comparable in d1–2, d3–4, and d5–6, with a median diameter of 162 nm (IQR 137–202 nm), 160 nm (IQR 137–202 nm) and 160 nm (IQR 135–197 nm), respectively, but EVs at d7–12 measured 175 nm (IQR 151–218 nm) in diameter, which was significantly higher in comparison to EVs from earlier pools (Figure 4D and Figure S1). To discover if targeted miRNAs are cargo of post-TBI EVs in CSF, we isolated miRNA from EV- and FP-enriched fractions obtained by SEC and detected RNA with mean values in a range between 4.6 and 8.0 ng/µL in total, including for both isolate types and across all of the originating CSF pools (Figure 5A). After performing cDNA synthesis and real-time PCR, we quantified targeted miRNAs in EV- and albumin-enriched fractions (Table S2). Similar to the miRNA quantification in CSF pools, we detected the highest amounts of targeted miRNAs in d1–2 followed by decreasing amounts in the following time points (Figure 5B). However, detected miRNA levels were roughly 1000-fold lower in comparison to CSF pools ranging from approximately 2.2 pg to less than 0.01 fg, and were mostly lower in the EV-pool in comparison to the FP-pool for the corresponding time point. The highest levels were detected in FP-pools of d1–2 for miR-451a, miR-144-3p, and miR-20a-5p in amounts of 2.22 pg, 0.16 pg and 0.01 pg, respectively. We could quantify levels in all four time points for only 20 miRNAs in FP-pools, while the majority of d5–6 and d7–12 levels were below detectable values. To assess the enrichment of quantified miRNAs in FP- and EV-pools, we determined corresponding ratios for available quantities and only considered ratios with at least a 5-fold change (Table 2). In line with the highest miRNA levels detected in FP-pools at d1–2 and 3–4, we found that 59 and 35 of the targeted miRNAs are enriched up to approximately >200-fold and >300-fold, respectively. We found only 3 miRNAs to be enriched in the FP-pool at d5–6 and d7–12 up to 12-fold and 14-fold, respectively. In contrast to FP-enriched miRNAs, we detected much fewer miRNAs to be EV-enriched. We found miR-223-3p to be exclusively EV-enriched at d5–6 (26-fold) and d7–12 (16-fold), followed by miR-30b-5p (9-fold) and miR-92b-3p (5-fold) being solely enriched at d1–2. We also detected miR-204-5p to be enriched only in EV-pools at d3–4 (55-fold) and d5–6 (42-fold). Additionally, d5–6 contained miR-142-3p (54-fold), miR-125b-5p (9-fold) and miR-22-3p (8-fold) as being uniquely enriched in the EV-pool. However, other miRNAs found to be EV-enriched at d3–4 (miR-99-a-5p) and at 5–6 (12 miRNAs underlined in Table 2) were also found to be FP-enriched at some other time points. This might be due to technical reasons, such as the incomplete separation during SEC or due to the different biology of some miRNAs, whereby the same miRNA originating from different sources might be associated with either EVs or other carriers. Severe traumatic brain injury (sTBI) offers a unique opportunity to investigate complex pathophysiological processes unfolding in the brain early after the injury. One of the measures in sTBI treatment includes the placement of an external ventricular drain (EVD), which provides access to the intracranial cerebrospinal fluid (CSF). Moreover, the intracranial CSF obtained by EVD might also contain signals required for the recovery and/or normal functioning of the brain. We hypothesized that microRNAs (miRNAs) released either passively from damaged tissue or actively from living cells could be such signals. Our results describe CSF dynamics in the context of miRNA types and quantities during the early days after the injury. The study included five sTBI patients with a different number of consecutive CSF samples collected after the injury (Figure 1). The reason for missing CSF samples was the removal of the EVD at the indication of the neurosurgeon due to clinical improvement and, in one case, due to the patient’s fatal outcome. Patient outcome was monitored through the international Glasgow Outcome Scale (GOS), showing overall values of four and five points for recovered patients after the sTBI (Table 1). These scores indicate moderate and mild neurological disability with minimal to no neurological deficits present. Therefore, the CSF samples included in the study originate from the early phase of neurological recovery. However, the number of included sTBI patients and corresponding CSF samples is low, which presents the main limitation of the study. We combined consecutive CSFs to enable PCR-array based screens—including CSF before and after separation by size-exclusion chromatography (SEC)—from different time points after sTBI. The combining of the CSFs samples into pools resulted in the dilution of the originating samples. While the d1–2, d3–4, and d5–6 CSF pools provide average miRNA amounts for the two days (d) included, the d7–12 CSF pool provides average miRNA amounts for the six days included. Therefore, it is very likely that at least some miRNAs at different time points were detected at low levels or not at all due to their dilution in CSF pools, posing an additional limitation of the study. CSF after sTBI has a specific composition due to the cell damage and impaired blood-brain barrier as part of the TBI pathophysiology. This also reflects the miRNA content in the CSF after sTBI, with many miRNAs most likely originating from the blood, as our and other groups have shown [30]. We found the highest miRNA levels in early days after sTBI represented by d1–2 and d3–4 CSF pools. Both CSF pools have also displayed high levels of haemolysis, as detected by real-time PCR. Our data suggest that the targeted miRNAs, although chosen as commonly present in CSF and presumably of central nervous system (CNS)-origin, might be mainly originating from damaged blood cells, predominantly erythrocytes. This is supported by miR-451a, whose d1–2 and d3–4 levels were approximately 20 ng and 10 ng, respectively, and they clearly stood out in comparison to other miRNAs (Table S1). miR-451a is highly expressed in erythrocytes and is enriched in erythrocyte EVs, which can also pass through the impaired blood-brain barrier [35,36]. miR-451a can promote apoptosis in neurons, thereby contributing to sTBI pathophysiology, but it can also mediate neurite outgrowth and regulate the endothelium, as shown in animal studies [37,38,39]. Other highly abundant miRNAs at d1–2 and d3–4 included miR-16-5p, miR-144-3p, miR-20a-5p, let-7b-5p, miR-15a-5p, miR-21-5p, miR19b-3p, miR-223-3p, miR-106a-5p, and miR-15b-5p, all of which were reported to be expressed at high levels mainly in veins and arteries, confirming earlier findings where most of the mentioned miRNAs have been detected from serum and plasma samples after brain tissue and blood vessel injury [9,35]. Some of the listed miRNAs might further aggravate sTBI by different mechanisms. Upregulated miR-16p-5p and miR-15a-5p can target BCL-2 and induce apoptosis in neuronal cells, and can also negatively impact the endothelium in the blood-brain barrier [40,41,42]. In vivo and in vitro studies demonstrated that overexpressed miR 144-3p can impair neuron viability and cognitive functions in a TBI model as well as result in a reduced response to oxidative stress [43,44]. In the ischemic and hypoxia models, miR-20a-5p was shown to downregulate NeuroD1 and Kif5A, which are required for the growth of dendrites, and the elimination of neurotoxic substances, respectively [45,46]. However, other in vitro studies show that miR-20a-5p can have a neuroprotective effect and stimulate axonal growth [47,48,49]. The positive affect in sTBI might be also attributed to miR-21-5p, which was demonstrated in animal models to inhibit apoptosis and promote angiogenesis, resulting in better neurological outcomes after TBI [45]. Additional neuro-protection is associated with miR-106a-5p, which can participate in the amelioration of oxidative stress and brain injury after intracerebral haemorrhage [50]. MiR-223-3p was shown to downregulate the NLRP3 inflammasome, which could lead to reduced brain oedema and improved neurological function [51]. Moreover, miR-233-3p is able to inhibit apoptosis in brain microvascular endothelial cells (BMCEs), and thereby provides a protective role to the integrity of the blood brain barrier, and the maintenance of the CNS microenvironment balance [52]. MiR-let-7b-5p was singled out as an miRNA with high expression in the brain tissue, arachnoid sheath, and spinal cord [53]. The effects of let-7b-5p can also be detrimental in TBI with CSF-contained let-7b-5p, which is shown to induce neurodegeneration mediated by neural Toll-like receptor (TLR) 7 [54]. Furthermore, let-7a/b-5p containing exosomes from microglia can induce apoptosis in neurons [55]. In addition, the mentioned miRNAs are detectable in different expressions in other tissues, meaning that they could possibly be products of affected organs such as lungs, kidneys, pancreas, spleen, and testicles that are afflicted with some other disease [29,53,56]. Moreover, we cannot exclude that some underlying diseases were present in sTBI patients, which might affect miRNAs, but have not been known at the time of sampling. Although all miRNAs showed a general trend of decreasing amounts towards later CSF pools with the consistent decrease of haemolysis, we noted that highly abundant miRNA levels tend to decline at different rates (Figure 3B). This would indicate that the detected miRNAs might originate from different cells. Although a more detailed characterisation of cellular markers was out of scope, all CSF pools contained peroxiredoxins 2 and 6 (Figure 2D). Both peroxiredoxins are ubiquitously expressed in nucleated cells, including leucocytes [57]. Notably, inflammation is a common complication in sTBI patients as a result of signalling pathways in secondary brain injury, and also as a general reaction of the human organism to a stressful situation [4,58,59]. A further source of miRNA in CSF after sTBI might be blood-derived extracellular miRNAs due to an impaired blood-brain barrier [52]. We could detect albumin and apolipoproteins across all analysed CSFs (Figure 2D). Both albumin and apolipoproteins were described as carriers of extracellular miRNA [60,61]. Our miRNA quantification suggests that other miRNAs, not necessarily of blood-origin, could be present in CSF. We found that the total amount of targeted miRNAs has made up only a small portion of miRNAs applied in cDNA synthesis. This particularly applies to the d5–6 and d7–12 CSF pools in which haemolysis was not pronounced so much as in earlier CSF pools (Figure 2C). To see if we can improve the detection of targeted miRNAs, we separated the CSF pools into extracellular vesicles (EVs) and free proteins (FP) to obtain more homogeneous sources of miRNAs. Both EVs and FPs were shown to be carriers of miRNAs, but EVs are especially promising for two reasons. First, miRNAs contained in EVs have higher stability. Second, EVs provide a specific delivery of their cargo, since they contain proteins and lipids on their surface that are able to interact with the targeted cell [23]. Before isolating EVs, we analysed common EV-protein markers in CSF and found high levels of Flotilin-1 and -2, TSG101, CD81 and CD9 at d1–2, followed by decreasing amounts in later days (Figure 4A). This is consistent with the blood content and haemolysis levels described in previous results, since all of these proteins are ubiquitously expressed in cells, including blood cells. We detected low levels of annexin V at d1–2 and d5–6, indicating that these CSF pools were affected by apoptosis, which is also a well-recognised part of TBI pathophysiology. Apoptotic bodies are a type of EVs of 50 to 5000 nm in diameter [62]. Due to the partial overlapping with medium sized EVs of approximately 150 to 200 nm in diameter analysed in this study (Figure 4E), we cannot exclude the possibility that a portion of the apoptotic bodies were co-isolated and therefore contributed to the detected miRNAs. We isolated EVs by size-exclusion chromatography, a method suitable for the isolation of total EVs and that was also shown to result in intact EVs [63]. Furthermore, we have previously shown that the Sepharose CL-6B applied here is effective in isolating EVs from CSF [34]. This has proven to be crucial for this study, since we were able to isolate RNAs in concentrations sufficient for cDNA analysis from both FPs and EVs (Figure 5A). We did not detect all targeted miRNAs after SEC, and we noticed much lower amounts in comparison to CSF pools (Table S2). This is expected, since the analyses only included chosen SEC-fractions based on the detection of selected proteins, with CD81 and albumin used as markers for EV- and FP-fractions, respectively (Figure 4A). A majority of miRNAs were detected in FP-fractions, with miR-451a as the most abundant miRNA, similar to the CSF pool analyses (Table 2). Considering the previously described issues with haemolysis and damage to other tissues after sTBI, it is tempting to speculate whether free protein associated miRNAs are released from lysed cells and not as a result of secretion from intact cells. We found some miRNAs to be both EV- and FP-abundant depending on the analysed days. This miRNA ambiguity might be due to a technical reason such as incomplete separation of EVs and FPs. Another possibility is that the same miRNA can be present in both EV- and FP-form depending on the cell source. Interestingly, several miRNAs, including miR-142-3p, miR-204-5p, and miR-223-3p, showed unique and strong enrichment in EVs at d7–12 when haemolysis was less present (Table 2). Taken together, we here described the quantitative changes of miRNAs in CSF of patients recovering from sTBI. We showed the high impact of haemolysis on 87 targeted miRNAs in the first four days. However, the CSF from later days contained enlarged EVs carrying RNA, which is yet to be characterised. Our results emphasise the dynamic nature of sTBI and the need to further analyse CSF at later days when neuro-recovery signals, such as miRNAs, might be present. Research included five patients with severe traumatic brain injury (sTBI) treated at the Anaesthesiology, Intensive Medicine and Pain Treatment Clinic at the Clinical Hospital Centre Rijeka and at the Clinic for Anaesthesia, Reanimation, Intensive Care Medicine and Pain Treatment at Pula General Hospital, Croatia. Clinical requirements for sTBI were Glasgow Coma Scale (GCS) ≤ 8, neurological physical examination, and neuroradiological imaging of the brain (Multi Slice Computer Tomography, MSCT). The study was approved by the Institutional Review Board of both hospitals, and informed consent was signed by the family member or a legal representative due to the patient being unconsciousness and under critical care management. Treatment included placement of an external ventricular drain (EVD) at the indication of an attending neurosurgeon for the purpose of intracranial pressure (ICP) monitoring and management. The exclusion criteria were patient age under 18 years, since it was a study conducted on adults, and patient age over 80 years, due to inevitable physiological changes in the brain. Patients with susceptible immune, malignant and infectious conditions due to potential interaction at the level of pathophysiological signalling pathways were also excluded from the study. No specific clinical parameters were considered or monitored for the purposes of this study. The control group was not included for two reasons. Firstly, applying EVD in healthy subjects, which would provide cerebrospinal fluid (CSF) from the same anatomic position as in sTBI patients, is not possible due to ethical reasons. Secondly, CSF obtained by lumbar punction includes a risk of different CSF composition due to the changed anatomical location. Additionally, lumbar-CSF has a further risk of potential contamination with other cellular content in comparison with EVD-derived CSF. Patient treatment outcomes were monitored after three months using the international Glasgow Outcome Score (GOS). CSF was sampled from the EVD and its drainage chamber daily, starting from 24 h after its placement. Samples were collected during twelve days after the sTBI in low-protein binding tubes (Eppendorf, Hamburg, Germany). The indication for stopping the sampling was the removal of the EVD indicated by the attending neurosurgeon or the fatal outcome of the patient. After sampling, CSF was stored at −80 °C. Samples were pooled in equal volumes to obtain four consecutive CSF pools (Figure 1). Generated CSF pools were mixed with 5× Laemmli buffer (1M Tris HCl pH 6.8, 50% glycerol (v/v), 10% SDS (w/v), 0.05% bromophenol blue (w/v), 2-mercaptoethanol) and boiled at 95 °C for 10 min. Pooled CSF together with a protein standard (PageRuler™ Prestained Protein Ladder, Thermo Scientific, Waltham, MA, USA) were loaded onto 12% polyacrylamide gel and electrophoresed (MiniVE SE 300, Hoefer, Holliston, MA, USA) in 1x running buffer (25 mM Tris, 192 mM glycine and 0.1% SDS, pH 8.3) on 90 V to 150 V. Separated proteins were transferred to 0.2 µm nitrocellulose membrane (Global Life Sciences Solutions Operations UK Ltd., Little Chalfont, UK) at a constant voltage of 70 V for an hour and a half in a 1x transfer buffer (25 mM Tris, 192 mM glycine and 20% methanol). Following the protein transfer, membranes were stained with Ponceau S (0.1% Ponceau S in 5% acetic acid), blocked with 5% milk in Tris-buffer saline (TBS, 20 mM Tris and 150 mM NaCl) for 15 min, and incubated with rabbit monoclonal antibodies against albumin (#4929), apolipoprotein E (#13366), CD9 (#13403), CD81 (#52892), Flotilin-1 (#18634), Flotilin-2 (#3436) and TSG101 (#72312) and mouse monoclonal antibody against apolipoprotein AI (#3350), and diluted 1:1000 in 5% bovine serum albumin (Cell Signalling Technology, Danvers, MA, USA)/TBS-T (TBS supplemented with 0.1% Tween 20) over-night at 4 °C. Membranes were washed three times for 5 min in TBS-T and incubated with horseradish peroxidase-linked anti-rabbit (#7074) or anti-mouse (#7076) secondary antibodies at room temperature for 30 min (all listed primary and secondary antibodies were obtained from Cell Signalling Technology, Danvers, MA, USA). After additional washing in TBS-T, the signal was visualised using SignalFire Plus ECL Reagent or SignalFire Elite ECL Reagent (Cell Signalling Technology, Danvers, MA, USA) and imaged with an ImageQuant LAS 500 CCD imager (GE Healthcare Bio-Sciences AB, Uppsala, Sweden). Size-exclusion chromatography (SEC) was performed on CSF pools as previously described [34]. Briefly, samples were separated using Sepharose-CL-6B (GE Healthcare Bio-Scences AB, Uppsala, Sweden), and packed in a 1.5 × 50 cm glass column equipped with a flow adaptor (Bio-Rad Laboratories, Hercules, CA, USA). Prior to separation, the column was equilibrated with sterile PBS (Life Technologies Corporation, Grand Island, NY, USA), which was used as a running buffer. A total volume of 4 mL of each CSF pool was applied onto a gravity-flown column by 5 mL sterile plastic syringe, and 46 fractions of 1.5 mL were collected in low-protein-binding tubes (Eppendorf, Hamburg, Germany). The SEC column was flushed with at least two bed volumes of PBS between each SEC run. Collected SEC fractions were mixed with a 5x Laemmli buffer without glycerol and boiled at 95 °C for 10 min. Nitrocellulose membrane (Global Life Sciences Solutions Operations UK Ltd., Little Chalfont, UK) was soaked in distilled water and placed in slot blot apparatus (Hoefer Inc., Richmond, CA, USA), connected to a vacuum pump. SEC fractions in volume of 300 µL were applied to the slot blot, pulled through a membrane by a vacuum pump, and rinsed three times with 1 mL of PBS (Life Technologies Corporation, Grand Island, NY, USA). The membrane was then removed from the slot blot apparatus, stained with Ponceau S, blocked in 5% milk, and blotted for CD81, as described above. The signal was visualised using SignalFire Elite ECL Reagent (Cell Signalling Technology, Danvers, MA, USA) on an ImageQuant LAS 500 (GE Healthcare Bio-Sciences AB, Uppsala, Sweden). Tunable resistive pulse sensing (TRPS) analysis of the size distribution and concentration of nanoparticles in the CD81+ pool of SEC fractions was conducted on a qNano Gold platform (Izon Science, Christchurch, New Zealand). The nanopore was wetted, coated and equilibrated with an Izon reagent kit as per the manufacturer’s instructions. The calibration was performed with 200nm carboxylated polystyrene beads (CPC200, Izon Science, Christchurch, New Zealand), diluted 500-fold in filtered electrolyte solution, and stretch was adjusted until the blockade magnitude for calibration particles averaged between 0.25 and 0.3 nA. Measurements were conducted at a constant 46.00 mm stretch and a baseline current at approximately 125 nA. Samples were diluted twofold in filtered electrolyte solution and vortexed for 30 s prior to TRPS measurements. Each sample was measured at two pressure steps of 5 and 2.5 mbar, in triplicate. At least 500 particles were recorded for each measurement. Before each measurement, the nanopore was washed with the electrolyte solution at a pressure of 20 mbar to avoid cross-contamination between samples. Data processing and analysis were performed in Izon Control Suite v3.4 software (Izon Science, Christchurch, New Zealand). A concentration fraction from 110 to 420 nm was applied for all measurements prior to any data analysis. Isolation of RNA from total CSF-, EV-, FP- pools was performed using Norgen’s Urine microRNA Purification Kit (Cat. No./ID:29000, Norgen Biotek Corp., Thorold, ON, Canada), as it was previously shown to be efficient in miRNA isolation from CSF [64]. According to the manufacturer’s recommendation, 1 mL of the CSF sample was used for the isolation procedure, while keeping the samples on ice. The protocol started with the lysis procedure adding the Lysis Buffer A, provided by the manufacturer, to the CSF aliquot and vortexing for 15 s, followed by the addition of 96–100% ethanol provided by the user to the lysate and vortexing for 10 s. Binding on the columns was then performed by centrifugation (Eppendorf, Hamburg, Germany) on 4 °C and 8000 RPM for 1 min until the entire lysate has been loaded onto the column. Columns were assembled with the provided collection tubes. The column was then washed applying the provided Wash Solution A prior to adding of 42 mL of 96–100% ethanol to the solution. Washing was performed by centrifugation for 1 min at 14.000 RPM in three repeated steps. The drying of the column was achieved by centrifugation at 2 min and 14.000 RPM. Columns were then assembled with the manufacturer’s 1.7 mL elution tubes and 30 µL of provided Elution Solution A was added to the columns and incubated at room temperature for 20 min. The following final step was centrifugation for 2 min at 2000 RPM and an additional 2 min at 14.000 RPM. The obtained amount of sample (about 28 µL) was stored in low-protein binding tubes (Eppendorf, Hamburg, Germany). RNA quantification was performed by the application of 1 µL of sample onto the spectrophotometer (NanoPhotometer® P330, Implen GmbH, München, Germany) in triplicates for every sample. An amount of 20 ng of miRNA isolated from each CSF-, EV- and albumin pool was reverse transcribed in 20 µL reactions using miRCURY Locked Nucleic Acid (LNA) RT Kit (Cat. No./ID: 339340, Qiagen Sciences, Germantown, MD, USA) with a thermal cycler (Applied Biosystems, Singapore, Singapore). A known amount of 5 different RNA spike-ins (UniSp2, UniSp4, UniSp5 and cel-miR-39-3p provided in Qiagen RNA Spike-In Kit, For RT, Cat. No./ID: 339390 and UniSp6 provided with miRCURY LNA RT Kit) was added to each reaction prior to the cDNA synthesis step for quality control and quantification purposes. RNA quality and reverse transcription were assessed by PCR-based QC array (miRCURY microRNA QC PCR Panel, Cat. No./ID: 339345, Qiagen Sciences, Germantown, MD, USA) before proceeding with miRNA analysis. miRNA profiling was undertaken using a PCR-based array on a 96-well plate (miRCURY LNA Human CSF Exosome Focus miRNA PCR Panel, Cat. No./ID 339325PF-1/YAHS-124Y, Qiagen Sciences, Germantown, MD, USA) and a real-time PCR machine (7300 real time PCR system, Applied Biosystems, Singapore, Singapore). This study describes quantities of 87 miRNAs in the cerebrospinal fluid (CSF) of patients with severe traumatic brain injury (sTBI). Absolute quantification was performed at four time points over twelve days after the injury, providing an insight into the dynamics of miRNAs of putative CSF origin. We showed that CSF contains miRNAs throughout the twelve days after sTBI. The targeted 87 miRNAs were detected at very different levels in CSF, with their combined amounts making only a small portion of total miRNA present in the CSF. Furthermore, our results indicated that the targeted miRNAs most likely originate from lysed erythrocytes and potentially other damaged cells. We also demonstrated that the majority of targeted miRNAs were associated with free proteins, while only some miRNAs were enriched in extracellular vesicles (EVs). However, EVs were found in all analysed CSF pools, and their content included miRNAs. Several major limitations of the study should be emphasized. First of all, the number of subjects was low and the analysed cohort of patients was heterogenous with regard to the underlying intracranial pathology, including the type of haemorrhage, site of intraparenchymal damage, and whether diffuse axonal injury was detected. This is especially critical since blood-derived content in CSF after sTBI largely influenced the amount and type of miRNAs detected in the study. Furthermore, no clinical parameters were included in the study, and therefore their potential correlation with the study findings is missing. Taken together, this is a preliminary miRNA study which further corroborates the complex dynamics of sTBI in the acute phase. Future studies should identify other miRNAs present in CSF after sTBI, including the CSF-EVs. Moreover, in contrast to the current study based on pooled CSF samples d1–2, d3–4, d5–6 and d7–12, novel research should involve more frequent time points and the investigation of unpooled samples. This might enable the detection of novel miRNAs in CSF and could improve the understanding of intracranial processes after sTBI.

PMC10003049

Matteo Pavan,Stefano Moro

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

23-02-2023

COVID-19,SARS-CoV-2,rational drug design,CADD,SBDD,homology modeling,docking,pharmacophore,protein–ligand interaction fingerprints,molecular dynamics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19. In December 2019, a cluster of pneumonia cases of unknown etiology emerged in the Chinese city of Wuhan [1]. Soon after, analyses of patients’ lung fluid, blood, and throat swabs reconducted this outbreak to a newly identified virus, tentatively named 2019-new coronavirus (2019-nCoV) [2]. Phylogenetic analyses performed on viral genomes isolated from patients’ samples revealed a close relationship between the new virus with several bat coronaviruses isolated in China (>90%). A lower degree of similarity was also found with SARS-CoV (80%) and MERS-CoV (50%), the causative agents of two recent coronavirus-related epidemics [3]. Based on phylogeny, taxonomy, and established practice, the virus was renamed SARS-CoV-2 [4], while the associated illness was defined as COVID-19 by the World Health Organization (WHO) [5]. The striking similarity between the SARS-CoV-2 genome and several bat coronaviruses led to the hypothesis that bats could be the animal reservoir for SARS-CoV-2, with pangolins or other mammals acting as the intermediate host before human transmission [6]. The assumption that bats could be the animal reservoir of SARS-CoV-2 was further reaffirmed at a later stage by the work of Temmam et al., which identified in the caverns of North Laos a series of bat coronaviruses that share a high level of sequence similarity (96%) with the SARS-CoV-2 genome [7]. From a clinical perspective, the spectrum of COVID-19 manifestation is broad, ranging from asymptomatic infections to severe viral pneumonia with respiratory failure and even death [8]. The most common symptoms, similar to influenza, are related to mild upper respiratory tract affection, such as fever, cough, myalgia, and headache [9]. Less common but still relevant ones include gastrointestinal manifestations, such as diarrhea, and more severe respiratory illnesses, such as dyspnea, and multiorgan failure [10]. The long incubation time compared to similar infections [11], the capability of asymptomatic [12] or paucisymptomatic [13] patients to transmit the virus even before the eventual symptoms’ manifestation, and the aerial transmission modality [14,15] all concurred to determine a higher transmissibility index (estimated between 2.5 and 3.0) for the SARS-CoV-2 virus, compared to similar viral infections [16]. These factors contributed to the rapid spread of SARS-CoV-2 worldwide, resulting in more than 650 million cases and more than 6.5 million deaths globally [17]. In the first stages of the COVID-19 pandemic, extraordinary sanitary measures, such as physical and social distancing, wearing face masks, and eye protection devices [18,19] were adopted to prevent the collapse of the public healthcare system [20], due to the imbalance between the high demand and the low availability of critical supplies [21,22]. Although this short-term plan has proven helpful in gaining time [23,24], more sustainable and long-term oriented strategies were needed to better cope with the socio-economic [25] and psychological [26] consequences of the pandemic, other than ensuring fair and efficient resource management [27]. Considering that bringing a brand-new drug on the market is usually a very long and expensive process [28], the so-called “drug repurposing” was the first approach to finding suitable therapeutic options for COVID-19 patients [29,30]. This strategy extends the applicability domain of already marketed drugs for treating diseases other than the one it was conceived for [31]. This approach is appealing because it involves using derisked compounds, with potentially lower overall development costs and shorter development timelines [32]. Unfortunately, despite all the promising premises [33], this approach was largely unsuccessful [34]. Indeed, several investigated drugs showed little to no efficacy in randomized clinical trials [34]. The few successful cases were primarily symptomatic treatments, mostly limited to hospital usage for the most severe cases due to the therapy’s high costs or route of administration [35]. Failure of the drug repurposing strategy against COVID-19 can be mostly traced to the very first stages of the pandemic, where few clinical pieces of evidence were available for the rational elaboration of therapy plans. For example, the combination of HIV protease inhibitors Lopinavir and Ritonavir was examined [36], despite a suboptimal predicted recognition pattern towards the SARS-CoV-2 main protease (Mpro) compared to other compounds of the same class [37]. Another example is the combined use of an antimalaria drug (hydroxychloroquine) and an antibiotic (azithromycin) despite no clear indication of the possible mechanism of action [38,39]. With more and more clinical observations becoming available, more fine-tuned treatments, especially symptomatologic ones, were adopted. This is the case, for example, of corticosteroids such as dexamethasone [40], employed to tame the inflammatory response associated with severe COVID-19 cases, and low molecular weight heparins [41], used to prevent or treat thrombo-embolic events associated caused by interference with the cardiocirculatory system. A group of antiarthritis drugs represents another successful example of drug repurposing to their ability to modulate the immune response [42] and cytokine storm [43] caused by severe SARS-CoV-2 infection. This family includes the monoclonal antibodies Tocilizumab [44] and Sarilumab [45], which both inhibit Interleukin-6 (IL-6) signaling; Anakinra [46], which interferes instead with IL-1 signaling; and the Janus Kinase (JAK) inhibitor Baricitinib [47], alone or in conjunction with Remdesivir [48], with the latest representing maybe the most successful example of drug repurposing against COVID-19 being the first approved drug against this illness [49]. Originally designed against Ebola virus, Remdesivir is a nucleotide analog prodrug that acts as a viral polymerase inhibitor [50] and is efficient in shortening the recovery time in hospitalized adult patients affected by COVID-19 [51]. Unfortunately, as previously mentioned, Remdesivir and the other repurposed drugs need parenteral administration, thereby limiting their massive-scale adoption as pharmacological treatments against COVID-19 [35]. With the first round of spontaneously healed patients, doctors started flanking standard treatment with the use of convalescent plasma (CP), i.e., the plasma derived from recently recovered donors with a sufficiently high neutralizing antibody titer [52]. A similar protocol was previously adopted to face Ebola [53] and MERS [54] outbreaks, justifying its emergency use in the first stages of the COVID-19 pandemic. Unfortunately, despite promising observational data from the first studies performed on small-size patient cohorts [55], more thorough investigations from more extensive clinical trials demonstrated the inefficacy of this treatment [56,57], leading to its dismission from routine clinical practices. Despite this failure, CP inspired the design of safer and more targeted immunological treatments in the form of monoclonal antibodies (mAbs) [58,59]. Since the beginning of the pandemic, several mAbs directed against COVID-19 have been developed, with some obtaining approval from regulatory agencies [60]. Multiple of these mAbs are often used in conjunction to combine their neutralizing power and boost their therapeutic efficiency, exploiting their ability to bind at different epitopes [61]. The list of approved ones contains the therapeutic combinations of casirivimab and imdevimab (Regeneron/Roche), redanvimab (Celltrion Healthcare), sotrovimab (GSK), and the combination of tixagevimab and cilgavimab [62,63]. Furthermore, the association of bamlanivimab and etesevimab is nearly approved, despite the previous failure of trials investigating bamlanivimab on its own [63]. As seen in the case of CP and mAbs, a targeted immune response against SARS-CoV-2 can be a beneficial treatment for patients [64]. While immunoglobulins are limited to treating ongoing infections in hospital settings due to the high costs and the parenteral administration route, a more economical and scalable approach would be instructing the human body to produce this type of response without needing external intervention [65]. Based on this assumption and parallel to the drug repurposing approach, the industry and academia spent a consistent joint effort on developing preventive tools to avoid the infection in the first place or at least mitigate the most detrimental effects of the illness. This endeavor resulted in the quick approval by regulatory agencies of several vaccines [66]. Three different classes of these therapeutic entities can be recognized [67]. The first one, related to inactivated virus vaccines, comprises the Chinese CoronaVac (Sinovac) and the Russian CoviVac. The second group is formed by adenovirus vector vaccines such as Vaxzevria/ChAdOx1-S (AstraZeneca), Sputnik V/Gam-COVID-Vac, and Jcovden/Ad26.COV2.S (Janssen). Finally, the third one is composed of mRNA-based vaccines, including Comirnaty/BNT162b2 (Pfizer-BioNTech) and Spikevax/mRNA-1273 (Moderna) [68,69]. Despite the poor performances of the first class of vaccines [70,71], several independent studies have asserted worldwide the efficacy of vaccination campaigns based on the other two types of vaccines, particularly in the case of mRNA-based ones [72,73]. The ability of the SARS-CoV-2 virus to infect human cells heavily depends on a surface glycoprotein known as the S/spike protein [74], named after its peculiar shape [75]. For this reason, both mRNA vaccines and mAbs are designed to target this protein and prevent the virus’s entry into the cell, thereby limiting its replication [76]. Concerning these, although different pathways for SARS-CoV-2 cell entry are possible [77,78], the principal and better-characterized one involves binding to the human ACE2 receptor (hACE2) [79], a membrane-anchored metallopeptidase that is abundantly present in various districts of the human body, from the vascular endothelium to the epithelia of lungs and small intestine [80]. On its own, host cell receptor binding is not sufficient to ensure entrance within host cells. Priming and activating the S protein by host proteases is required to enhance its cell–cell and virus–cell fusion processes and increase viral shielding from neutralizing antibodies [79,81]. The list of priming proteases includes, but is not limited to, TMPRSS2, a transmembrane serine protease that is often co-expressed with ACE2 in SARS-CoV-2 target cells; Furin; and cathepsin B/L [79,82,83]. The priming process entails the exposure of a lipophilic fusion peptide (FP), which penetrates the host cell membrane triggering the viral fusion [84] thanks to its strong membrane-perturbing capacities [85] From a structural perspective, the spike is a trimeric transmembrane glycoprotein composed of 1273 amino acids organized in two main subunits, S1 and S2, and several functional domains [86]. The S1 subunit comprises two main domains, specifically the N-terminal and C-terminal domains (NTD and CTD, respectively), which are both involved in the binding to host cell receptors [86]. The CTD contains the receptor-binding domain (RBD, residues 319–541), consisting of two motifs. Firstly, a core structure is formed by a twisted five-stranded antiparallel β sheet (β1, β2, β3, β4, and β7), with three short helices (α1, α2, and α3). Secondly, an extended loop (receptor binding motif, RBM) is formed by a two-stranded β sheet (β5 and β6), lying at one edge of the core and containing most of the residues involved in binding to hACE2 [87] (Figure 1). The S2 subdomain has significant roles in spike protein trimerization and in mediating the virion entry into the host cell once the molecular contacts have been established [88]. It is formed by relevant subdomains such as the transmembrane domain (TD) (residues 1296–1317), which exerts both the spike anchoring to the outer side of the viral membrane and the maintenance of the trimeric quaternary structure [89,90], and a cytoplasm domain (CD) (residues 1318–1353), which mediates viral assembly and cell–cell fusion [91]. Furthermore, the previously mentioned fusion peptide, a cleavage S2′ site (residues 815/816), and two heptad-repeat domains (HR1/HR2) (residues 984–1104/1246–1295) are also part of S2 [92]. Due to its exposition on the external surface of the SARS-CoV-2 membrane and its pivotal role in the virus’s ability to infect host cells, the spike protein is often subjected to mutations that alter the virus’s infectivity and antigenicity [93,94]. Therefore, since the spreading of the original viral strain (Wuhan-Hu-1) began, several viral variants appeared on the scene [95], particularly in third-world nations where collective sanitary practices such as social and physical distancing [96] or wearing face masks in public places [18] were hardly implementable [97]. The insurgence of novel viral strains with different susceptibility to the protective effect of vaccines [98] demands periodical updates of their original formulations coupled with multiple booster shots to maintain their efficacy [99], thus hampering the management of the pandemic based on massive vaccination of the world population [100,101]. Among the large pool of SARS-CoV-2 mutations [102], some gathered the scientific community’s attention due to their increased fitness, gaining the “variant of concern” (VOC) status [103]. The first ever SARS-CoV-2 VOC was the B.1.1.7 variant, more commonly referred to as the “Alpha” or “English” variant due to being first identified in November 2020 in the Kent region of the United Kingdom [104,105]. Despite worries about the higher transmissibility compared to other circulating variants at the time [106,107], clinical studies demonstrated how mAbs, CP, and especially vaccines, were still able to confer protection against B.1.1.7 [108,109,110], containing its impact on the sanitary system [111]. Unfortunately, soon after the emergence of the Alpha variant, a more threatening VOC arose. The B.1.617.2 variant, commonly known as the “Delta” or “Indian” variant, due to being first identified in India in late 2020, quickly overthrew B.1.1.7 thanks to its strikingly increased transmissibility [105]. The advent of the Delta variant was associated with the first signs of reduced protection provided by mAbs, CP, and most importantly, vaccines [112,113,114], thanks to its increased immune system evasion capability [115], posing a heavier workload on the sanitary system [116]. The latest hallmark in the history of SARS-CoV-2 variants is represented by the B.1.1.529 variant, first detected in South Africa and more often called the Omicron variant [117]. The combination of increased transmissibility [118] and immune system evasion [119] conferred this variant a net selective advantage in bypassing the protection provided by the complete primary vaccination cycle and a variety of clinically utilized mAbs [120,121,122] compared to other circulating strains. The ground-breaking impact the Omicron variant had on the worldwide spread of SARS-CoV-2 even led to the introduction of the “booster dose” to compensate for the reduced coverage of the primary vaccine cycle [98,123]. Lately, several subvariants germinated from the original Omicron strain (also labeled as BA.1), namely BA.2, BA.3, BA.4, and BA.5 [124,125,126]. Although different studies indicated how the first identified Omicron subvariants (BA.2 and BA.3) were similarly susceptible to existing treatments despite their increased transmissibility [127,128,129], it also emerged how the most recently identified ones (BA.4 and BA.5) are significantly more efficient in evading the immune response [130,131,132]. These findings indicate that SARS-CoV-2 continued to evolve by increasing its immune-evasion capability rather than counting on sheer higher transmissibility, sustaining the virus spread even in populations with high vaccination frequency and recovery rates [130,131,132]. Considering the uncertainty about the efficacy of existing treatments [133] and booster vaccinations [134] against present and future Omicron subvariants, the need to find more reliable and variant-agnostic therapeutic tools against COVID-19 is emerging. The previously mentioned issues with the continuously mutating spike protein, which affects most present gold-standard COVID-19 treatments, indicate that different viral targets should be explored for developing novel antiviral drugs [135]. Generally speaking, an ideal target would have to play a pivotal role in the virus replication cycle and be highly conserved across different viral strains [136]. Within SARS-CoV-2, this role is portrayed by its main protease [137] (Mpro, or 3C-like protease / 3CLpro due to similarities with the picornavirus 3C protease [138]), thanks to its conserved fold across different coronaviruses [138,139,140,141] (including SARS-CoV [142]) and essentiality for the replication of this virus’s subfamily [143]. SARS-CoV-2 Mpro, also called nsp5, is a cysteine protease composed of 306 residues [144] that steers the maturation of two partially overlapping polyproteins (pp1a and pp1ab) into individual mature nonstructural proteins (including Mpro itself) through their proteolytic cleavage [145]. Functionally speaking, Mpro exists in equilibrium between a monomeric and a homodimer form [146,147,148]. This dimerization directly influences the shape of the catalytic site [147], thus altering the enzymatic activity [138] and playing an indirect regulatory role during the virus replication cycle [149,150]. Within the Mpro functional dimer, each protomer is composed of three structural domains. The chymotrypsin-like fold, including β-barrel domain I (residues 1–99) and II (residues 100–182), hosts the active site and thus has direct control over the catalytic event [138,147], while the α-helical domain III (residues 198–306) is mainly involved in the direct regulation of dimerization, exerting only a secondary and indirect role on regulating Mpro’s enzymatic activity [151]. Between the second and third domains lies a flexible 16-residue loop (residues 183–197) [152]. As anticipated, the catalytic site is located between domains I and II, bordered by the N-terminal domain I of the second protomer in the dimer (Figure 2). Notably, the N-finger (residues 1–7) interacts with the binding site through a salt bridge between the positively charged end of Ser1 and the negatively charged end of Glu166 [153]. The latter is also involved in forming a hydrogen bond with His172, an essential interaction for the enzyme’s proteolytic activity [154]. These interactions are so crucial in stabilizing the catalytic site [155] that N-finger deletion impairs dimerization and abolishes the protease’s enzymatic activity [156]. Mpro’s shallow, plastic, and solvent-exposed active site [152,157] comprises several subpockets (ranging from S6 to S3′), hosting the corresponding substrate residues (which vary from P6 to P3′) [139]. Speaking of substrates, the SARS-CoV-2 Mpro cleaves peptide bonds at the C-terminus end of a glutamine residue (P1) [137], which is conserved across different SARS-CoV-2, SARS-CoV, and even MERS-CoV substrate sequences [152]. SARS-CoV-2 Mpro recognizes sequences as long as ten residues (P6–P5–P4–P3–P2–P1↓P1′–P2′–P3′ P4′, where ↓ indicates the scissile bond [139]), but only shows remarkable selectivity at four subsites: S4, S2, S1, and S1′ [158]. On the contrary, prime recognition subsites located at the C-terminus of the conserved P2 (Leu/Val/Phe), P1 (Gln) ↓-P1′ (Ser/Ala) sequence are not conserved and show remarkable plasticity [152,159]. Furthermore, the main structural alterations of the binding site derive from flexibility at residues that line the S1 subpocket and segments incorporating methionine 49 and glutamine 189 [152,160]. Different from many other chymotrypsin-like proteases, Mpro exerts its enzymatic functions through a catalytic dyad instead of the usual triad, where His41 and Cys145 are flanked by a conserved water molecule that substitutes the sidechain of the third component (usually an aspartate or an asparagine) [138,161]. Aside from the catalytic dyad, another vital component of the catalytic machinery is represented by a set of conserved residues contouring the S1 subpocket known as the oxyanion loop (138–145) [152,162]. Notably, the correct conformation [87,163,164] of the oxyanion hole (Gly143-Ser144-Cys145) is required for stabilizing the tetrahedral transition state through a coordinated series of hydrogen bonds involving the backbone amides [138,155,165]. Accordingly, alternative oxyanion loop conformations are associated with catalytically incompetent/inactive proteases [140,152,154,166,167]. Several characteristics of the viral proteases family, including SARS-CoV-2 Mpro, make them an attractive target for the rational development of tailored drugs against COVID-19. First, the low sequence identity with human proteases coupled with distinct cleavage-site specificities reduces the possibility of off-target/side effects associated with the therapy [168]. Second, the striking conservation of protein fold and structural organization of the active site among different members of the same family leads to the possibility of developing pan-coronaviral drugs [169]. Third, the abundance of structural data about the SARS-CoV-2 main protease (659 structures have been deposited in the Protein Data Bank [170] to date) makes it possible to exploit the state-of-the-art structure-based approaches in drug design [171]. Furthermore, a similar strategy has already proved successful in finding efficient treatments against the hepatitis C virus [172,173] and human immunodeficiency virus (HIV) [174,175]. Finally, the experience acquired studying the original SARS-CoV protease [176], in conjunction with the rapid release to the scientific community of the SARS-CoV-2 protease [164], certainly played a major role in determining its prominent place within most COVID-19 drug discovery campaigns. A detailed report on structural features of the 3CLpro protease that can guide the design of novel inhibitors can be found in the work of Xiong et al. [177]. The first attempts at finding SARS-CoV-2 Mpro inhibitors involved the repurposing of existing protease inhibitors. Particularly, the hepatitis C protease inhibitor Boceprevir [178,179] and the feline coronavirus 3CLpro inhibitor GC373 (derived from its prodrug GC376) [180] were found to be active in the low µM potency range against Mpro [181], with the latter being particularly interesting due its promiscuous anticoronaviral activity [182]. Both candidate drugs share a similar peptidomimetic scaffold, which entails the most prominent interaction features of the first identified ones [164]. Although these primary hit compounds present a good binding pattern, their evolution towards clinical candidates and drugs is prevented by two main factors: first, covalent inhibitors are usually associated with selectivity problems, due to their ability to react promiscuously with a plethora of nucleophile moieties [183]; second, the peptidomimetic scaffold is usually associated with suboptimal pharmacokinetic properties that affect the preferred route of administration [184]. In this regard, a step forward was obtained when the first SARS-CoV-2 Mpro inhibitors were able to reach clinical stage experimentation, namely PF-07304814 (lately renamed as Lufotrelvir), a prodrug for the active principle PF-00835231, and PF-07321332 (Nirmatrelvir). Lufotrelvir was originally developed by Pfizer in 2002–2003 for the SARS-CoV virus and later repurposed against the SARS-CoV-2 due to the high similarities between the two proteases [185]. Due to its efficacy against several viral strains in preclinical studies [186,187], it was advanced to the clinical stages of experimentation, albeit quickly overcome by Nirmatrelvir thanks to its more favorable pharmacokinetic profile [188]. Contrary to Lufotrelvir, which, similar to Remdesivir, requires parenteral administration, Nirmatrelvir can be administered orally [189], a must-have characteristic for the widespread adoption of drugs [190,191]. Designed by Pfizer amid the pandemic through the rational modification of Lufotrelvir [192], the structure of Nirmatrelvir was officially presented to the general audience on 6 April at the American Chemical Society Spring 2021 meeting [193], only one year after the official start of its development process [192] (Figure 3). This peptidomimetic inhibitor, which is administered in association with the pharmacokinetic enhancer Ritonavir and sold under the commercial name of Paxlovid, represents a hallmark in the history of both the COVID-19 pandemic and structure-based drug discovery, due to the groundbreaking speed of its discovery campaign [194]. Although clinical studies highlighted the remarkable therapeutic efficacy of Paxlovid in preventing the most severe COVID-19 cases [195], its effectiveness on more mild infections remains unclear [196]. Furthermore, the impact of viral mutations on present and future protease inhibitors has yet to be disclosed [197,198], thus justifying the current effort to find novel and diverse drugs that can enlarge the pool of pharmacological tools available against COVID-19. An important step in this direction is represented by the development of Ensitrelvir (formerly known as S-217622), the first noncovalent, nonpeptidomimetic, orally available Mpro inhibitor to reach clinical stage experimentation [199]. This compound has successfully reached the third and final stage of clinical experimentation, thanks to its proven efficacy against mild-to-moderate or even asymptomatic infections [200,201]. Possible approval of this active principle by regulatory agencies would provide an additional and orthogonal therapeutic tool to Nirmatrelvir in the treatment of COVID-19 cases, thus reducing the impact of resistance mechanisms associated with the emergence of mutated viral strains [197,198]. Although targeting the SARS-CoV-2 main protease was successful in individuating several clinical candidate drugs, even leading to the first approval of a COVID-19 specifically designed drug, other drug discovery campaigns aimed at different viral targets are needed for therapy diversification, potentially combined and synergic treatment, and resistance prevention [202,203,204]. Altogether, the SARS-CoV-2 genome encodes four major structural proteins, including nucleocapsid (N), membrane (M), envelope (E), and the spike as mentioned earlier (S), plus 16 nonstructural proteins, encompassing the previously mentioned main protease [205]. Although Mpro plays a pivotal role in processing the SARS-CoV-2 viral polyproteins, it is not the only component of the functional replicase complex that is required for the viral spread process [206]. Alongside this, a secondary but still relevant enzyme operates, namely the papain-like protease (PLpro, the catalytic domain of protein nsp3) [207]. Despite being a cysteine protease similar to Mpro, PLpro exerts its enzymatic functions through a catalytic triad composed of Cys111, His272, and Asp286 [208]. Further, PLpro processes peptide bonds located at the C-terminal end of LXGG motifs [209]. Functionally speaking, this 343-residue segment, which is part of the multidomain nsp3 protein, is responsible for cleaving the SARS-CoV-2 polyproteins at three different sites, resulting in the liberation of nsp1, nsp2, and nsp3 proteins [210]. Moreover, PLpro is also responsible for cleaving post-translational modifications on known regulators of host innate immune response [211]. As demonstrated by the approval of Remdesivir by regulatory agencies, another valuable target for the development of COVID-19 drugs is represented by the RNA-dependent RNA polymerase (RdRp) [49]. This complex machinery comprises four subunits, including one nsp12, responsible for the catalytic activity of the assembly; one nsp7; and two nsp8, with the latest two acting as cofactors [212]. The assembled holoenzyme presides RNA replication, a process that results in the formation of nine subgenomic RNAs [213]. The active site of nsp12 resides in its C-terminal RdRp domain and includes residues spanning from Thr611 to Met626, which are involved in binding one turn of double-stranded RNA, while residues D760 and D761 are required for recognition of the 3′ end and are essential for RNA synthesis [214,215]. Remdesivir binds within the active site, forming direct contact with residues K545, R553, D623, S682, T687, N691, S759, D760, and D761 and blocking the catalytic machinery by delaying the chain termination process [216,217]. During the RNA synthesis process, the RdRp also interoperates with nsp13 (helicase) [218], an enzyme involved in unwinding the RNA secondary structure of the 5′ untranslated section of the viral genome [219] to increase the efficiency of the copy process [220,221]. From a structural perspective, the nsp13 is a 596 residue, triangular pyramid-shaped helicase, which exploits its function thanks to the energy provided by its NTPase domain composed of six conserved residues (K288, S289, D374, E375, Q404, and R567) [222]. Adding to its helicase activity, the nsp13 active site also exerts RNA 5′ triphosphatase activity, further highlighting its importance in the maturation process of the viral mRNA [223]. The 5′ end of the newly synthetized mRNA is then subjected to post-translational modifications to boost both its stability (preventing cleavage from exonucleases), protein translation, and viral immune escape [224]. This activity is sequentially carried out by two S-adenosyl-L-methionine-dependent methyltransferases, namely nsp14 and nsp16 [225]. Specifically, the 527 residues’ nsp14 encompass both a proofreading exoribonuclease (ExoN) and an N7-methyltransferase enzymatic activity [226]. Furthermore, it has recently been suggested that it could encompass also a third, essential function for the viral replication cycle, based on the fact that SARS-CoV-2 ExoN knockout mutants are nonviable despite the 95% sequence identity with SARS-CoV [227] and the conservation of important active site amino acids including both the cap-binding residues (N306, C309, R310, W385, N386, N422, and F426) and the S-adenosyl methionine (SAM) binding residues (D352, Q354, F367, Y368, and W385) [228,229]. After its cleavage by the Mpro, evidence suggests that it forms a binary complex with nsp10, which cooperatively exerts the proofreading activity on fresh RNAs produced by the RdRp machinery [230,231]. Although the binary complex theory is the most prominent one, an alternative hypothesis based on the formation of a ternary nsp10-nsp14-nsp16 has been proposed due to the flexibility of the lid subdomain of nsp14 and the fact that nsp10 also forms a heterocomplex with nsp16 [231]. Particularly, the nsp16-nsp10 heterodimer is responsible for the 2′ O-methyltransferase activity that is required to complete the cap-0 ➔ cap-1 conversion of mRNA that is initiated by nsp14 [225]. While the catalytic activity entirely resides on nsp16, nsp10 provides a support role, aiding the recruitment of both the m7GppA-RNA substrate (which happens at a binding site defined by residues K24, C25, L27, Y30, K46, Y132, K137, K170, T172, E173, H174, S201, and S202) and the SAM cofactor (which binds in a pocket defined by N43, G71, G73, G81, D99, D114, C115, D130, and M131), thus enhancing nsp16′s catalytic activity [232,233,234]. Lastly, another essential target for coronavirus biology is represented by nsp15, a uridine-specific endoribonuclease (NendoU) [235]. The active form of this enzyme is a dimer of trimers, with each monomer composed of 345 residues organized in three different domains: N-terminal, middle, and C-terminal NendoU, where the catalytic activity resides [236]. The active site contains six conserved residues: His250, His250, and Lys290, which compose the catalytic triad, and Thr341, Tyr343, and Ser294, with the latest associated with selectivity in substrate recognition [237]. Due to their localization within the hexamer, cooperativity or anticooperativity between different binding sites is possible [238]. Nsp15 enzymatic activity involves the cleavage of both single- and double-stranded RNA at uridine sites producing 2′,3′-cyclic phosphodiester, and 5′-hydroxyl termini [239]. Functionally speaking, Nsp15 seems to directly participate in viral replication through interference with the innate immune response [237]. Indeed, to evade host pattern recognition receptor MDA5 responsible for activating the host defenses, the Nsp15 cleaves the 5′-polyuridine tracts in (-) sense viral RNAs [240], though it has also been suggested that Nsp15 degrades viral RNA to hide it from the host defenses [238]. More detailed structural information about potentially druggable SARS-CoV-2 protein targets can be found in the works of Littler et al. [241] and Wu et al. [242]. For most of its existence, the human genre has exploited natural products such as leaves, seeds, roots, bark, and flowers as medicines, based on empirical observations purely based on symptom relief [243,244]. Nevertheless, throughout the latest two centuries, the process of drug discovery has evolved rapidly from the serendipitous discovery of novel active principles derived from or inspired by natural compounds [245,246] to the rational design of brand-new chemical entities [247]. The major turning point in the history of modern drug discovery can be traced back to the 1980s when experimentally solved macromolecular structures become routinely available [248]. The enhanced accessibility of structural data about biological targets is reflected in a rapid interest in the development of computational methods that could valorize this information and aid medicinal chemists’ work [249]. Today, computer simulations are a staple point of drug discovery campaigns, thanks to their ability to streamline and reduce their attrition rate [250]. From a functional perspective, computer-aided drug discovery (CADD) techniques are employed in the earliest stages of the pipeline for hit identification, hit-to-lead optimization, and pharmacokinetic evaluations [251]. CADD methodologies can either fall into one of two subgroups, based on the rationale behind them: the first group is represented by ligand-based (LBDD) approaches, while the second one includes structure-based (SBDD) methods [252]. The main difference between these two orthogonal and complementary approaches is that the first one does not exploit any information about the target macromolecule structure (e.g., a protein or a nucleic acid), while the second one does [253]. Nowadays, with the advent of cryo-electron microscopy (cryo-EM) [254] and groundbreaking tools for de novo prediction of protein structures such as AlphaFold [255], the second approach has become the gold standard [171]. The starting point of every SBDD campaign is the identification of a target macromolecule (a protein or a nucleic acid) that is involved in the etiology and or pathogenesis of a disease of interest, whose function can be opportunely modulated through a specifically designed ligand, usually a small organic molecule [171]. Once the target has been identified, its structure must be retrieved, either through experimental methods such as X-Ray crystallography (XRC, the gold standard) [256], nuclear magnetic resonance (NMR) [257], and cryo-EM [258] or hypothesized through homology modeling or de novo prediction [259]. Homology modeling involves the use of a homologous protein with a high primary sequence identity with the target as a template for the construction of its three-dimensional model [260,261]. De novo prediction, instead, does not rely on any information about other proteins’ structures and outputs a structural hypothesis that is solely based on the primary sequence of the target of interest [262]. While the second approach has gained a lot of momentum during the last two years, thanks to its unprecedentedly high accuracy [263,264], the first one is still relevant in those cases where important structural rearrangements occur between different states of the target functional cycle, other than predicting ligand-bound conformations [265,266]. In the context of the COVID-19 pandemic, where the extraordinary effort promoted by the scientific community quickly made several experimentally determined structures available, the relevance of structural modeling was highlighted by the ability to keep up with the high mutation rate of the virus [135,207], other than providing a useful starting point for drug discovery campaigns for a target whose structure had yet to be elucidated [267,268]. For example, several studies were conducted to investigate the impact of mutations found in both the spike protein [135,269,270,271,272,273] and the main protease [135,198,274,275] of emerging strains on viral fitness and resistance to existing therapies. These studies showed that relatively inexpensive approaches such as homology modeling and positional scanning can be reliable tools to rationalize the origin of the virus [274,276,277,278], quickly track the evolution of the original strain [135,279,280], predict the impact of future possible mutations [270,272] and adjust existing therapeutics tools accordingly [198,281]. The huge amount of structural information available on several SARS-CoV-2 druggable targets was fertile terrain for various COVID-19 SBDD campaigns [282,283], both in academia and in industry, with the most effort aimed at hitting well-characterized and pivotal viral targets such as Mpro or spike [284,285]. A remarkable example is represented by the COVID Moonshot Consortium, a drug discovery campaign driven by a collaborative effort among different research groups across the world aimed at targeting the SARS-CoV-2 main protease. This project led to the advancement of novel noncovalent orally available nanomolar Mpro inhibitors to clinical stage experimentation [286]. Within every SBDD campaign, available information about the target structure is exploited to fetch molecules able to recognize it selectively and potently [287]. Usually, this involves the identification of molecules that have good steric and electrostatic complementarity with the active site [288]. Depending on the steric and volumetric features of the binding site, the ligand type can be chosen accordingly, with small organic molecules being a better solution for buried cavities [289] and peptides, aptamers, or antibodies a better one for larger, flatter, and solvent-exposed interaction surfaces [290]. To narrow down the list of potentially active molecules to experimentally test to a feasible number, and to avoid wasting resources on compounds that do not possess the appropriate features to interact with the target, most SBDD campaigns start with a virtual screening process (SBVS) [291]. The most widely and successfully adopted method for SBVS is molecular docking, a computational protocol developed in the 1980s by Kuntz et al. [292] for predicting the preferred orientation of a certain ligand within the active site of a receptor [293]. Each docking program has two major components, which cooperate to find the solution to the protein–ligand docking problem [294]. The first part is the search algorithm (SA), which explores the ligand degrees of freedom within a user-defined search space centered around the active site of the protein [295]. The SA generates several ligand conformations (poses) that are fed to the second element of the program, i.e., the scoring function (SF), which qualitatively evaluates subsisting protein–ligand interaction features [296]. In the context of the COVID-19 pandemic, docking was also the king of computational methods used for drug discovery, thanks to the combination of its accuracy [297] and rapidity, which allows it to virtually screen billions of compounds in just a few days [298,299,300]. For example, Corona et al. reported the discovery of four low micromolar nsp13 inhibitors through a virtual screening carried out with the LiGen [301] docking program on an in-house natural compounds library [302]. Kolarič et al. identified two micromolar SARS-CoV-2 cell-entry inhibitors that act by binding human neuropilin-1 (nrp-1) and preventing its interaction with the spike protein, by performing a virtual screening with the GOLD [303] program on a library of commercially available compounds [304]. Vatansever et al. performed a virtual screening based on the Autodock [305] program on a library of drugs approved by the Food and Drug Administration and by the European Medical Agency (EMA) to discover six micromolar Mpro inhibitors [306]. Kao et al. reported the discovery of three sub-micromolar, synergistic nsp1 inhibitors identified through two independently executed virtual screenings with ICM [307,308] and Vina [309] software on a library of FDA-approved drugs [310]. Zhang et al. identified 11 natural compound Mpro inhibitors active in the low micromolar range through a virtual screening purely based on the commercial software Glide [311], developed by Schrödinger [312]. Another strategic use of docking-based virtual screening based on the Glide program is portrayed by the work of Huff et al., which designed six mixed covalent and noncovalent nanomolar Mpro inhibitors [313]. Another Glide-based virtual screening performed by Liu et al. led to the repurposing of histone deacetylase (HDAC) inhibitors as SARS-CoV-2 cell entry inhibitors through allosteric modulation of ACE2 and alteration of its ability to recognize the spike protein [314]. Wang et al. used LibDock [315] to perform a virtual screening on a library composed of FDA-approved peptides, which led to the identification of a nanomolar SARS-CoV-2 cell entry inhibitor that exerts its effect by binding the human ACE2 receptor [316]. A remarkable result was obtained by Luttens et al., which identified eight Mpro inhibitors (including a nanomolar compound with pan coronaviral activity) by combining fragment-based drug design with ultralarge virtual screening based on the DOCK [292] program [317]. Welker et al. exploited the molecular docking pipeline of the LeadIT [318] program to repurpose previously identified SARS-CoV PLpro inhibitors towards its SARS-CoV-2 homolog, demonstrating their activity on viral replication in cell-based assays [319]. Otava et al. utilized docking calculations with the GOLD [303] software to rationalize the structure–activity relationship of a series of rationally designed S-adenosyl-L-homocysteine derivatives, some of which showed inhibitory activity towards SARS-CoV-2 nsp14 in the low nanomolar potency range [320]. Similarly, Wang et al. exploited docking with Vina to rationalize the SAR of a series of rationally designed phenanthridine nucleocapsid protein (NPro) inhibitors, including two compounds showing low micromolar inhibitory activity [321]. Although a very efficient and useful tool, molecular docking is rarely used on its own within SBDD campaigns and, indeed, is most often coupled with other methods to compensate for its weak points, such as neglecting receptor flexibility or the role of solvents [322], thus increasing the virtual screening success rate [323]. Another major limitation is represented by the poor ranking capabilities of classical scoring functions [324], which is the main cause of the high false positive rate of docking-based virtual screenings [325]. Indeed, in order to be universally applicable across different biological targets and computationally efficient enough to evaluate a large number of compounds, scoring functions have some limitations in the physical description of the binding event, which prevent any correlation between docking scores and experimentally determined affinity values [296]. Furthermore, little to no difference in score exists between top-ranking compounds derived from large virtual screening campaigns, making it practically impossible to distinguish active from inactive compounds solely based on the docking score [326]. For these reasons, each docking-based virtual screening cannot be blindly executed and fully automatized, and a careful setup of the experiment must be executed based on the available literature data and the knowledge of the target [326,327]. For COVID-19, the importance of this common-sense medicinal chemistry practice has been highlighted by the retrospective literature analysis provided by Llanos et al., which showcased the poor performances of structure-based virtual screenings solely based on ranking provided by docking scoring functions [323]. A possible solution to the limited physical description of the protein–ligand binding event of docking is to couple it with molecular dynamics (MD) simulations [294,328]. Molecular dynamics is a computational technique that allows investigating the time-dependent evolution of biological systems following the rules of molecular mechanics, i.e., determining the atomic trajectories by numerically solving Newton’s equation of motion, where forces between the particles and their potential energies are calculated according to molecular mechanical force fields [329]. Due to the heavy computational workload required to run these types of simulations, MD is rarely used for screening purposes, while it is more frequently exploited for the refinement of docking results, i.e., evaluating the pose stability or optimizing the protein–ligand complex geometry for a more accurate estimation of the free binding energy [330,331]. Regarding the pitfalls of the scoring component of docking programs, one possible strategy is to apply some form of knowledge-based filter upon docking results, in a similar fashion to what would happen if each pose were visually inspected [332]. For example, experimental information about critical protein–ligand interactions required for binding can be encoded within a pharmacophore filter or an interaction fingerprint, both of which can be used as constraints in the pose selection process [333]. In the case of pharmacophore filters, poses are filtered based on their ability to place a given functional group within a defined volume [334,335], while in the case of protein–ligand interaction fingerprint, the selection is usually based on the similarity between the reference and the query vector, representing the interaction features of the reference compound (a true active) and the investigated molecule respectively [336,337]. For instance, Wang et al. used a combination of structure-based pharmacophore screening, docking (both performed with the appropriate tools of the Molecular Operating Environment suite), and postdocking molecular dynamics refinement to identify a set of four sub-micromolar Mpro inhibitors among a database of in-house compounds [338]. The same protocol was successfully exploited by Tian et al. to identify four sub-micromolar PLpro inhibitors in the same in-house library [339]. Furthermore, a slight variation of the protocol was also employed by Yin et al. to discover a noncovalent cyclic peptide that simultaneously inhibits both SARS-CoV-2 Mpro and nrp-1 with an activity in the low nanomolar range [340]. Within this scientific work, pharmacophore constraints were used for scoring peptide poses on Mpro, while traditional docking scores were used for the nrp-1 screening. A remarkable joint computational work by Gossen et al. led to the molecular dynamics-driven design of a structure-based pharmacophore filter, which was then exploited to identify two nanomolar Mpro inhibitors among a library of publicly available compounds [341]. A similar approach was exploited by Hu et al., which exploited the combination between MD-based pharmacophore filtering, docking-based virtual screening within the Molecular Operating Environment suite, and MD-based postdocking refinement to identify micromolar SARS-CoV-2 cell entry inhibitors targeting the FP of the spike protein [342]. Jang et al. used protein–ligand interaction fingerprint similarity as a postdocking filter for their double virtual screening on both Mpro and RdRp with the Vina program to identify seven compounds inhibiting SARS-CoV-2 replication in cell-based assays among a library of approved drugs [343]. Due to the static nature of molecular docking, which does not consider receptor flexibility, the choice of the input structure is vital for the success rate of a virtual screening [344]. Although molecular dynamics can be a useful posterior refinement of poses, a wrong input conformation of the target macromolecule could prevent the sampling of native-like poses for active compounds, leading to a reduced hit-finding rate [345]. For this reason, multiple conformations of the same receptor derived from MD simulations or experimentally solved in different conditions can be used in parallel in a process defined as ensemble docking (ED) [346]. When this approach is used, docking calculations are independently run on each structure, with virtual hit compounds being identified either through consensus scoring or a consensus ranking approach [347,348]. In the case of consensus scoring, the docking score of the same molecule is averaged across the different virtual screenings, with the final ranking based on the consensus score [349]. Differently, consensus ranking involves the selection of top-ranking hit compounds across different virtual screenings, regardless of congruence between scores [350]. A consensus approach can also be utilized to rank molecules based on virtual screening executed on the same receptor structures with different docking protocols [351]. For example, Gimeno et al. applied a consensus scoring approach to three independently executed virtual screenings through Glide, FRED [352], and Vina software to identify two Mpro micromolar inhibitors within the Drugbank database, a library that includes all drugs approved by the Food and Drug Administration (FDA) [353]. Yang et al., instead, employed an ensemble docking approach with the Glide docking software to identify six Mpro inhibitors among a library of commercially available peptidomimetic compounds, two of which demonstrated sub-micromolar potency [354]. Rubio-Martinez et al. used a combination of ensemble docking based on QVina2 [355] and postdocking molecular dynamics refinement to identify five Mpro micromolar inhibitors within a library of commercially available natural compounds [356]. A mixture of the previous two approaches was exploited by Clyde et al. for their High-Throughput Virtual Screening (HTVS), based on both ensemble docking and consensus scoring between the FRED and Vina docking programs, that led to the discovery seven micromolar Mpro inhibitors among a set of commercially available compounds [357]. Further, a combination of consensus ranking among Autodock, Hybrid, and FlexX and postdocking molecular dynamics refinement was utilized by Glaab et al. to virtually screen a library of commercially available compounds and identify two micromolar Mpro inhibitors [358]. Similarly, Ghahremanpour et al. applied both consensus ranking among three independent virtual screenings performed with the Glide, Autodock, and Vina software and postdocking molecular dynamics refinement to identify 14 micromolar Mpro inhibitors within the Drugbank database [359]. Another possible solution to cope with inaccuracy in free binding energy determination by traditional scoring functions is to rescore docking poses using more computationally intensive and accurate methods such as Free Energy Perturbation (FEP) [360] or MMGBSA/MMPBSA [361]. The first approach relies on performing a series of alchemical transformations across a set of ligands that need to be evaluated. This conversion cycle allows calculating relative differences in the free binding energy that can be used for a more accurate ranking of hit compounds derived from a virtual screening [362]. The second approach relies instead on correcting the gas phase interaction energy calculated according to the molecular mechanics force field with a term accounting for the desolvation-free energy, where the polar component is estimated either by numerically solving the Poisson–Boltzmann equation (MMPBSA) or through the Generalized Born method (MMGBSA) [363]. Intriguingly, one of the hit compounds identified in the work of Ghahremanpour et al. was then used by Zhang et al. for the FEP-driven design of multiple nanomolar Mpro inhibitors [364]. A similar combination of Glide docking and FEP to determine the absolute binding free energy was also employed by Li et al. to identify 15 micromolar Mpro inhibitors within the Drugbank database [365]. The efficacy of FEP in estimating the binding energy of potential Mpro inhibitors was also highlighted by a retrospective study by Ngo et al. [366]. A multistep virtual screening involving semiflexible docking with Glide, Schrödinger induced-fit docking [367], MD-based postdocking refinement, and binding free energy estimation with the MMGBSA [368] protocol was exploited by Ibrahim et al. to identify one low micromolar nsp15 inhibitor [369]. Although the estimation of thermodynamic properties such as the free binding energy has been a staple point of drug discovery campaigns, both from a computational and an experimental perspective, lately there has been a major interest shift towards the determination of kinetic parameters since they better correlate with in vivo efficacy [370]. Specifically, several MD-based methods have been developed throughout the years to rank compounds based on their predicted residence time, i.e., the time that the ligand spends in the receptor-bound state [371]. Among those, Pavan et al. developed Thermal Titration Molecular Dynamics (TTMD), a new method for qualitative estimation of protein–ligand complex stability (Figure 4), which was successfully applied for correctly discriminating tight, low nanomolar binders from weak, micromolar SARS-CoV-2 Mpro inhibitors [372]. Despite the indisputable relevance of molecular docking within most SARS-CoV-2 drug discovery campaigns, other approaches were successfully implemented, especially for projects which deviate from the design of a standard small molecule noncovalent binder. For example, Zaidman et al. developed Covalentizer, an automated pipeline for the conversion of noncovalent binders to irreversible ones, which was successfully applied to the conversion of a SARS-CoV Mpro reversible inhibitor to a sub-micromolar SARS-CoV-2 Mpro irreversible one [373]. Valiente et al. reported the discovery of D-peptides that bind the spike RBD with low nanomolar affinity, hence blocking SARS-CoV-2 infection in cell-based assays. These ACE2-mimicking peptides were selected within the starting library through a combination of structural alignment, MD-based post docking refinement, and binding free energy estimation [374]. Similarly, a series of peptides mimicking the HR2 domain of the spike protein able to prevent SARS-CoV-2 infection in cell-based assays with low micromolar potency were designed through the combination between structural alignment, mutational scanning with the BeAtMuSiC [375] tool, and MD-based postdocking refinement [376]. Jeong et al. used Rosetta [377] to rationally design a mAb that recognizes a conserved surface on the spike RBD of various coronaviruses with picomolar binding affinities, thereby strongly inhibiting SARS-CoV-2 replication in cell-based assay [378]. A similar strategy was exploited by Miao et al., which employed Rosetta docking and MD-based postdocking refinement to design an RNA aptamer that binds with picomolar affinity to the spike RBD and inhibits SARS-CoV-2 replication with sub-micromolar potency in cell-based assay [379]. Further, Cao et al. utilized a combination of modeling with Rosetta and docking with RifDock [380] to design ten mini proteins which bind with picomolar affinity to the spike RBD thus inhibiting SARS-CoV-2 infection within cell-based assays [381]. Moreover, Glasgow et al. combined modeling with Rosetta and computational alanine scanning with Robetta [382,383] to rationally design “ACE2 receptor traps”, i.e., engineered proteins that bind the spike RBD with high affinity and neutralize SARS-CoV-2 infection as effectively as clinically used mAbs [384]. As thoroughly discussed in previous paragraphs, many SARS-CoV-2 drug discovery campaigns favored static, time-independent approaches such as docking or structural alignment, over time-dependent methods such as molecular dynamics. This can be attributed to the long calculation times, the reduced conformational sampling capabilities, and the lower accessibility of MD simulations to the general medicinal chemistry audience [331,385]. Despite these issues, several works demonstrated the potential of using full-fledged MD-based drug discovery pipelines, especially when smart enhanced-sampling strategies are employed [385]. For example, Bissaro et al. showed how high-throughput supervised molecular dynamics (HT-SuMD) [386], a virtual screening platform based on an enhanced sampling MD protocol, could be successfully exploited for docking fragments to the active site of SARS-CoV-2 Mpro, overcoming accuracy limitations of most docking protocols [387] in identifying the native-like binding mode for frag-like compounds [388]. Furthermore, the SuMD [389,390] algorithm (Figure 5) was successfully exploited by Pavan et al. to decipher details about the recognition mechanism of Nirmatrelvir upon the SARS-CoV-2 Mpro catalytic site before any structural detail was revealed by the drug developer, with successive structural [189] and molecular medicine [198] studies confirming the prediction validity [391]. Moreover, an evolved version of the SuMD protocol was developed by Pavan et al. and successfully applied to the study of the recognition mechanism between RNA aptamers and proteins, including an RNA-aptamer that binds to the spike RBD with picomolar affinity thus preventing the viral infection of host cells [392]. Despite an unprecedented vaccination effort, which brought at least one vaccine shot to 70% of the world’s population [101,393], the battle against COVID-19 is far from won. Indeed, there is still a huge disparity between vaccination rates across first-world and low-income countries [101,393]. Furthermore, aside from the vaccines’ availability, several cultural and sociological factors contribute to the worldwide asymmetric vaccination coverage [394,395]. Finally, even in countries with the highest vaccination rates, the continuous emergence of novel viral variants [396] with enhanced immune escape capability sustains the viral spread even among the vaccinated population [397], so that to date a hundred thousand new COVID-19 cases are reported each day, leading, on an average, to a daily toll of hundreds of deaths globally [398]. Although the task of predicting the insurgence of novel variants of concern is not trivial [399], and the debate on the mechanism behind the genesis of these viral variants is still heated [400], it is reasonable to assume, based on the history of COVID-19 so far and other virus-related illnesses such as flu [401,402], that this phenomenon will continue to occur at least into the near future, forcing the scientific community to adapt existing treatments to emerging viral strains, other than developing novel therapeutics complementary to the existing ones [403]. Moreover, even if massive vaccination sensibly lowered the harmful effect on patients’ health caused by acute infection, long-term consequences of COVID-19 infections can still manifest at later stages [404], further reaffirming the need for tools that can effectively treat the disease other than preventing it. In conclusion, the take-home message from the present pandemic situation is that, among the strategies for identifying new therapeutic classes, with timescales compatible with those marked as a health emergency caused by a shapeshifting pathogen, the integration of structural biology information and new computational approaches probably represents the most promising one. The abundant amount of information provided by structural biologists coupled with the good predictive power of established computational workflows provides a quick platform for finding temporary solutions in the form of drug repurposing, allowing necessary time to develop more specific and tailored therapeutic entities. Although this strategy is not always successful in promoting hit compounds for clinical use [405], it can serve as a rational hypothesis generator for clinical studies, identify molecules to use as pharmacological tools to expand the knowledge on the etiopathogenesis of an emerging illness, and set the basis for the development of derivatives that can overcome the limitations of first-generation hits. Despite all the scientific advancements in the field of computer-aided drug discovery, indeed, the time required for the release to the market of a new drug has not been sensibly reduced. Indeed, as highlighted in the work of Gupta et al. [406], many active compounds identified through structure-based drug design and computational techniques possess comparable activity to compounds in clinical trials. Many of these compounds, however, despite showing good antiviral activity and having a well-defined mechanism of action, fail to survive clinical stages of experimentation, due to the lack of good pharmacokinetic properties, which are essential for ensuring both good therapeutic efficacy and lack of intolerable side effects. This fact further stresses the necessity for developing novel and complementary tools to the existing ones, especially in the evaluation of pharmacokinetic properties and off-target effects, which are usually the main causes of failure for candidate drugs in the clinical stages of experimentation. Accordingly, because the presented in silico approaches serve to provide candidates for preliminary selection, to extract the most value from these tools, predictions generated from computational approaches must be verified with biological confirmation, with both in vitro and in vivo models. Furthermore, with the increasing amount of curated experimental datasets becoming available to the scientific community, physics-based methods will be flanked more and more by artificial intelligence methods, both for evaluating the pharmacodynamic and pharmacokinetic properties of investigated compounds [407,408]. Finally, as estimated by a recent study [409], the likelihood of a highly infectious disease epidemic could double in the coming decades, indicating that the successful computational strategies applied in the biology domain that have been adopted against COVID-19 will most likely come in handy soon, providing us with robust and efficient solutions in tackling challenging diseases including new pandemics.

PMC10003052

Shuai Li,Yichun Zhang,Kang Li,Yuan Liu,Shuiqing Chi,Yong Wang,Shaotao Tang

Update on the Pathogenesis of the Hirschsprung-Associated Enterocolitis

27-02-2023

Hirschsprung disease (HSCR),enterocolitis,Hirschsprung-associated enterocolitis (HAEC),pathogenesis,review

Despite the significant progress that has been made in terms of understanding the pathophysiology and risk factors of Hirschsprung-associated enterocolitis (HAEC), the morbidity rate has remained unsatisfactorily stable, and clinical management of the condition continues to be challenging. Therefore, in the present literature review, we summarized the up-to-date advances that have been made regarding basic research on the pathogenesis of HAEC. Original articles published between August 2013 and October 2022 were searched in a number of databases, including PubMed, Web of Science, and Scopus. The keywords “Hirschsprung enterocolitis”, “Hirschsprung’s enterocolitis”, “Hirschsprung’s-associated enterocolitis”, and “Hirschsprung-associated enterocolitis” were selected and reviewed. A total of 50 eligible articles were obtained. The latest findings of these research articles were grouped into gene, microbiome, barrier function, enteric nervous system, and immune state categories. The present review concludes that HAEC is shown to be a multifactorial clinical syndrome. Only deep insights into this syndrome, with an accrual of knowledge in terms of understanding its pathogenesis, will elicit the necessary changes that are required for managing this disease.

Update on the Pathogenesis of the Hirschsprung-Associated Enterocolitis Despite the significant progress that has been made in terms of understanding the pathophysiology and risk factors of Hirschsprung-associated enterocolitis (HAEC), the morbidity rate has remained unsatisfactorily stable, and clinical management of the condition continues to be challenging. Therefore, in the present literature review, we summarized the up-to-date advances that have been made regarding basic research on the pathogenesis of HAEC. Original articles published between August 2013 and October 2022 were searched in a number of databases, including PubMed, Web of Science, and Scopus. The keywords “Hirschsprung enterocolitis”, “Hirschsprung’s enterocolitis”, “Hirschsprung’s-associated enterocolitis”, and “Hirschsprung-associated enterocolitis” were selected and reviewed. A total of 50 eligible articles were obtained. The latest findings of these research articles were grouped into gene, microbiome, barrier function, enteric nervous system, and immune state categories. The present review concludes that HAEC is shown to be a multifactorial clinical syndrome. Only deep insights into this syndrome, with an accrual of knowledge in terms of understanding its pathogenesis, will elicit the necessary changes that are required for managing this disease. Hirschsprung-associated enterocolitis (HAEC) is the leading cause of serious morbidity and mortality in patients with Hirschsprung disease (HSCR) [1]. Clinically, among the various risk factors, delayed diagnosis, the type of operation employed, female sex, having a younger age at presentation, long-segment disease, family history, associated anomalies, and anastomotic leaks or strictures are the most commonly reported in the literature [2]. One of the leading causes or risk factors for HAEC has been considered to be partial mechanical obstruction. The major underlying feature of this may be anastomotic stricture, bowel-disordered motility, or functional obstruction (paralysis). There is some evidence to suggest that recurrent HAEC may be released following internal sphincter myotomy [3]. However, HAEC also occurs in patients with enterostomy, and without any evidence of obstruction. Therefore, other factors must be involved. Given the numerous advances that have been made in terms of performing meticulous operations procedures, standardized diagnostic systems [4], and postoperative management [5], the reported incidence of HAEC remains stable, ranging from 6 to 60% prior to pull-through surgery, and from 25 to 37% following surgery [4]. Several studies have found that the proximal dilated segment of the colon is mostly affected and more susceptible to HAEC [6,7,8], which seems to explain part of the reason why HAEC still occurs postoperatively. In addition, some studies have found that older age at radical surgery is a risk factor for the development of postoperative HAEC [9], and older age is also a risk factor for the development of preoperative HAEC [10]. However, the data concerning HAEC etiology remain limited. On the other hand, since the comprehensive review by Demehri [11], basic research on HAEC has made marked progress in terms of increasing the knowledge base, especially with respect to studies on genes, the microbiome, immunity, and other aspects [12,13]. In the current review, we summarize the advances (Figure 1) that have been made in understanding HAEC pathogenesis over the course of the last decade, with the intention of enabling researchers to gain a better grasp of the current status of essential knowledge on HAEC, which should be of use in terms of planning future research directions. Previous studies have revealed that genetic background influences HAEC, mainly in the form of changes in the incidence and severity of HAEC in patients with HSCR with a combination of several clinical syndromes. Kwendakwema [14] conducted a retrospective cohort study of 207 patients with HSCR, 26 (13%) of whom were trisomy 21 (T21) patients, and found that the incidence of HAEC in children with HSCR and T21 (38%) was not significantly different from that in children with HSCR alone (41%). By contrast, Halleran’s study found that, compared with patients with HAEC alone, patients with a combination of HAEC and T21 experienced more severe symptoms, including longer duration of symptoms, hypotension, greater likelihood of tachycardia and longer times on antibiotics, and were also more likely to require intensive care unit admission [15]. A higher incidence of HAEC in children with Mowat-Wilson syndrome with HSCR has also been reported [16]. The advent of whole-exome sequencing has also facilitated this type of research. Bachetti [17] identified p.H187Q in the oncostatin-M (OSM) receptor (OSMR) gene as a susceptibility variant of HAEC. It may exert a key role in HAEC pathogenesis by regulating/activating the OSM-OSMR axis. Via large-sample sequencing, the single nucleotide polymorphisms (SNPs) rs8104023 [18] and rs2191026 [19] were found to be significantly associated with postoperative HAEC. In another study, DNA was extracted from the colon tissue samples of 30 patients with HAEC, and the mRNA expression of integrin beta-2 (ITGB2; also known as CD18) was found to be negatively correlated with the incidence and severity of HAEC [20]. Taken together, the above studies have suggested that the pathogenesis of HAEC is closely associated with the underlying genes and the genetic background (Figure 2), although the specific mechanism(s) involved still require further study. The human intestinal microbiome is a complex ecosystem in which the phyla Firmicutes and Bacteroidetes are dominant, followed by proteobacteria [21], and the normal intestinal flora is in a dynamic balance. Maintaining the relative balance of the intestinal microflora is closely associated with the stability of the internal environment of the intestine and its normal function. Pierre [22] found that mice with neural crest conditional deletion of endothelin receptor B (EdnrB) exhibited impaired mucosal barrier function and developed ecological dysregulation prior to the onset of HAEC, as evidenced by decreased levels of luminal secretory phospholipase A2 (sPLA2) and increased intestinal invasion by Escherichia coli prior to HAEC and death. Cheng [23] found that the proportion of fecal bacteria in HAEC model mice increased in the case of Akkermansia and decreased in the case of Bacteroidetes, and that the genera with reduced abundance in HAEC were Dysgonomonas and Clostridium cluster XIVa, suggesting that Akkermansia may contribute to the development of HAEC, whereas Bacteroidetes, Dysgonomonas, and Clostridium cluster XIVa may exert a protective effect. It has been shown that the abundance of Veillonella parvula (VP) in intestinal microorganisms is higher in patients with HAEC compared with patients with HSCR [24]. Zhan [25] found that an excessive density of VP exerted proinflammatory effects by increasing the concentration of inflammatory cytokines and impairing intestinal motility in the colon, and VP-derived lipopolysaccharide (LPS) was used to establish a mouse model of inflammation wherein LPS both elicited a markedly enhanced paracellular permeability of mouse colonic epithelial cells and activated macrophages via the Toll-like receptor 4 (TLR4) pathway. Tumor necrosis factor-α (TNF-α) from polarized macrophages was found to impair the pacemaker function of interstitial cells of Cajal (ICCs), which subsequently inhibited intestinal motility, and intestinal dysmotility exacerbated intestinal dysbiosis, in turn promoting the development of HAEC. In another study, Mitroudi [26] cultured E. coli, Enterococcus spp., Bacillus, Proteus mirabilis, and Clostridium spp. in the mesenteric lymph nodes, spleen, liver, kidneys, and lungs of HACE-modeled rats, and found that E. coli had the highest ectopic rate. All the rats sacrificed 25 days after modeling exhibited live E. coli in extraintestinal sites, whereas the control and sham group rats did not. Although the rodent models described above differed from human physiology, Arnaud [27] found that proinflammatory bacteria (Bilophila and Fusobacterium) were more abundant in the aganglionic rectosigmoid lumen. However, it is not clear whether this situation arose consequentially after the onset of the disease, or whether it was a contributing factor toward it. Searching for risk pathogens has also been performed in a clinical setting. Parker [28] collected stool samples of patients with HAEC at different time points from the onset of symptoms to remission, and analyzed changes in the bacterial community therein; a higher abundance of Blautia was observed in the remission samples. Clostridium difficile is also considered to be a risk pathogen for HAEC [29]. It has been hypothesized that higher biodiversity could also have a role in maintaining intestinal homeostasis, and that its disruption could promote the development of HAEC [30,31]. By isolating fecal DNA, Frykman [30] observed reduced gut microbial diversity in patients with HAEC. Patients with total colonic aganglionosis, a condition that has the highest risk of HAEC, had more proteobacteria and a lower diversity of gut microbiota compared with patients with rectosigmoid aganglionosis [31]. Several studies have found significant microbiota differences when comparing between patients with HSCR and patients with HAEC, and increased populations of intestinal proteobacteria in patients with HAEC, through the use of Illumina-MiSeq sequencing [24,30,32]. Similarly, a comparison of the flora after the onset of symptoms does not confirm whether the abnormal flora is a cause or a consequence of HAEC, and therefore prospective studies are required in this regard. In a different study, Yan [32] collected samples of the intestinal contents from four patients from different sites along the intestine during surgery and isolated their DNA, also using Illumina-MiSeq sequencing. In their study, it was found that patients with HAEC exhibited greater bacterial diversity compared with patients with HSCR, in contrast with the previous studies of Frykman and Prato [30,31]. The majority of the clinical studies published to date have collected stool samples from patients for sequencing and used the results to represent the intestinal flora, whereas a minority of studies have collected surgical intestinal specimens for sequencing during surgery. Which of these methods is superior in terms of reflecting the real situation of intestinal mucosal microorganisms, in addition to the biological and clinical association with HAEC, needs to be addressed in future studies. An important physiological role of intestinal bacteria is the production of short-chain fatty acids (SCFAs), and SCFAs serve an important role in maintaining the integrity of the colonic mucosa [33]. Demehri found that stool SCFA levels were reduced >4-fold in children with a history of HAEC, and that the SCFA composition was altered, perhaps suggesting a complex interaction between colonic metabolism and the microbiota changes [34]. In another series of studies, Plekhova [35] compared fecal metabolites in patients with or without a history of HAEC, and found that patients with HAEC exhibited increased tyrosine catabolism and elevated levels of trans-4-hydroxy-l-proline (Hyp) and 4-methyl-3-penten-2-one, as well as decreased levels of ethyl pentyl ketone. Tyrosine-based compounds act as signaling molecules between the microbiome and the host [36]. Increased concentrations of Hyp may signify a decrease in the Hyp-utilizing microbiota. Furthermore, 4-methyl-3-penten-2-one and ethyl pentyl ketone can originate from the microbiome and the metabolites of the host. This implies that metabolic abnormalities may be caused by dysregulated gut microbes, which in turn further promotes colonic ecological dysregulation and, finally, HAEC development. In addition, a prospective cohort study conducted by Tang [37] found that patients with HSCR who were exclusively breastfed had lower numbers of Gram-negative bacteria, especially Enterobacteriaceae, and low concentrations of LPS, and were, therefore, less prone to HAEC; these findings led the authors to speculate that exclusive breastfeeding to regulate the gut microbiota may reduce endotoxin biosynthesis and release, thereby preventing patients with HSCR from progressing to HAEC. Considered together, the above studies suggest that HAEC is closely associated with the intestinal microflora (Figure 2), but whether abnormal microflora is a cause of the disease progression, is a consequence of it, or merely has a participatory role needs to be addressed in further prospective studies. The mucosal barrier serves as the first line of defense, protecting the healthy intestinal surface from adhesion and invasion by tubular microorganisms. The components of the intestinal barrier include the lumen, microenvironment or mucus-containing layer, epithelium, and lamina propria. Numerous studies have shown that structural defects and dysfunction of the intestinal mucosal barrier are responsible for the pathogenesis of HAEC. Several studies have analyzed the passive diffusion of particles to assess the mucus layer barrier function in the mouse colon, and these studies identified that the diffusion rate in the colonic mucosa of EdnrB−/− mice was significantly reduced compared with the wild-type mice [38,39]. Yildiz [39] found that the efficiency of active microbial transport and passive diffusion of granular material in the colonic mucosa of EdnrB−/− mice were also significantly reduced. Dariel [40] collected surgically resected intestinal samples from short-segmented HSCR neonates, and found that the intestinal epithelial barrier (IEB) permeability was significantly increased in the ganglia of patients with HSCR who developed HAEC postoperatively, which suggested that abnormal IEB is closely associated with HAEC. GCs are specialized secretory cells that are located throughout the mucosal epithelium of the intestinal tract, and form the main components of the mucus layer through the secretion of gel acting against pathogen infection [41]. Mucin 2 (MUC2) is the major mucin expressed in humans [42]. Trefoil factor 3 (TFF3) acts synergistically with mucins to enhance the protective barrier properties of the mucus layer [43]. SAM-pointed domain-containing ETS-like factor (SPDEF) drives the terminal differentiation and maturation of secretory progenitors into GCs [44]. Kruppel-like factor 4 (KLF4) is a GC-specific differentiation factor in the colon, which serves to both regulate GC differentiation and activate mucin synthesis [45]. Significant downregulation of the expression levels of TFF3, SPDEF, and KLF4, and a significant reduction in the GC population, were observed in the aganglionic and ganglionic colon of patients with HSCR [46], factors which may increase the susceptibility of patients to HAEC. However, Thiagarajah [38] discovered that, prior to the development of HAEC, patients with HSCR had increased numbers of colonic GCs, which were similar to the size of the GCs of non-HSCR controls, but reduced levels of neutral and acidic mucins derived from the GCs. EdnrB−/− mice exhibited both an increased size and number of colonic GCs in distal aganglionic segments, whereas, in proximal ganglionic segments, the size and number of the GCs were decreased both in patients with HSCR and EdnrB−/− mice. The level of the membrane-bound mucin Muc4 was reduced, suggesting an altered maturation process for the HSCR GCs. The increased number of GCs identified in this study contradicted the previous results of Nakamura [46], however, and therefore needs to be confirmed in further studies. Porokuokka [47] identified a 70–80% reduction in the expression level of the mouse glial cell line-derived neurotrophic factor (GDNF) co-receptor, GDNF family receptor alpha-1 (GFRα1), in both HSCR and HAEC. In addition, HAEC was observed in GFRα1 hypomorphic mice that were experiencing GC dysplasia, abnormal mucin production, and storage. However, progression to the conditions of epithelial damage, microbial adhesion, and tissue invasion was only observed at advanced stages in the mice, suggesting that bacterial adhesion was not the initiating factor of HAEC, and that GC dysfunction in the colon had preceded these other pathological changes. In conclusion, these studies have shown that dysfunction of GCs and reduced secretion of mucin lead to damage of the intestinal mucosal barrier, thereby leading to the development of HAEC. Restoring both normal GC function and the quantity of colon epithelium may be potential targets for preventive therapy of HAEC, and these possibilities should be further investigated from this perspective in the future. Tight-junction proteins fulfill a key role in regulating epithelial barrier function, and are composed of structural proteins, including claudin protein, occludin protein, junctional adhesion molecules (JAMs), zonula occludens-1 (ZO-1), and various types of ligand-protein molecules. Arnaud [27] observed that the expression of ZO-1 was significantly lower in piglets with hypoganglionic sigmoid, whereas the expression levels of claudin-3 and E-cadherin were increased. By contrast, Dariel [40] identified no significant differences in the expression levels of several tight-junction proteins, including ZO-1, occludin, junctional adhesion molecules A (JAMA), cingulin, and claudin-1, comparing among patients with HAEC, patients with HSCR, and patients with HSCR combined with obstructive symptoms/diarrhea. ATP-sensitive K+ (K(ATP)) channels have been described as passive transducers for ions. Previous studies have identified decreased expression levels of K(ATP) channels in HSCR specimens, and co-localization of Kir6.1 and SUR2 (subunits of K(ATP) channels) with the tight-junction protein claudin-1, suggesting that alterations in K(ATP) expression may both affect intestinal epithelial integrity and be associated with the pathogenesis of HAEC [48]. TREK-1 (also termed potassium channel subfamily K member 2 (KCNK2)) is a mechanosensitive K2P channel, and Tomuschat [49] found reduced expression levels of TREK-1 in both the ganglionic and aganglionic regions in HSCR; moreover, a deficiency of TREK-1 was reported to induce barrier dysfunction in human colonic epithelial cells [50]. The TLR4/phosphorylated (p)-p38/nuclear factor-kappaB (NF-κB) signaling pathway in the intestine, and F-actin expression in the intestinal epithelial cytoskeleton, are important for maintaining both intestinal mucosal integrity and intestinal barrier function [51,52]. Zheng [53] infected EdnrB−/− mice with E. coli JM83 cells via oral gavage in order to establish an HAEC model. The EdnrB−/− mice were found to have significantly elevated expression levels of TLR4, NF-κB, and p-p38, substantially reduced cytoskeletal F-actin protein density, and severely disrupted tight junction structures. Protease-activated receptors (PARs)-1 and -2 are known to be associated with intestinal permeability, regulation of intestinal motility, and inflammatory reactions. Increased expression of PAR-1 and PAR-2 and an excessive local release of PAR-activating proteases were observed in Tomuschat’s study in the colon of patients with HSCR [54]. In conclusion, intestinal mucosal barrier dysfunction and tissue structural disruption have been shown to be closely associated with the development of HAEC (Figure 2). However, the fundamental research on GCs and tight-junction proteins remains limited. The abnormal ENS of HSCR leads to impaired intestinal motility, resulting in functional obstruction with subsequent stasis and overgrowth of pathogenic intestinal bacteria, destruction of the mucosal layer, invasion of the intestinal wall, dysfunction of the intestinal mucosal barrier, impaired immune response and consequent HAEC. This abnormal neurological function is considered to be an important cause of preoperative HAEC episodes. Acetylcholine is an important neurotransmitter that promotes intestinal motility. Keck [55] found that a low degree of colonic mucosal acetylcholine-positive innervation led to an enhanced inflammatory immune cell state, disrupted microbial metabolism, and a higher incidence of postoperative HAEC. A similar phenomenon was observed in another animal experiment performed by Porokuokka [47]. In addition, Feng [8] found a reduced acetylcholine content and a higher level of inflammation in the dilated segment compared with the HSCR segment in EdnrB−/− mice. Taken together, these studies suggest that a correlation exists between acetylcholine and HAEC. Nitric oxide (NO) is an important second messenger and inflammatory mediator that exerts a key role in intestinal barrier failure in numerous types of intestinal inflammatory diseases [56]. NO synthase (NOS) exists in multiple isoforms, including endothelial NOS (eNOS), neuronal NOS (nNOS), and inducible NOS (iNOS). Most of the beneficial effects of NO are produced by the constitutive synthases, eNOS and nNOS, which maintain stable intestinal barrier function and mediate intestinal homeostasis [57]. Several studies have demonstrated a link between NOS and HAEC. Caveolin-1 (Cav-1) regulates the functions of different NOS isoforms, and Nakamura [58] previously found a lower expression level of Cav-1 in the colon of patients with HSCR, which led them to speculate that reduced Cav-1 expression may lead to excessive activation of iNOS, consequently leading to epithelial damage and thus increasing the susceptibility of HSCR to HAEC. However, by contrast, the results of the study by Dariel [40] showed that Cav-1 expression appeared to be higher in patients with HAEC. It should be acknowledged that a limitation of both these studies was the small number of patients involved, and further studies are required. NOS-interacting protein (NOSIP) is a modulator of NO production that is able to inhibit the production of NO. Tomuschat [59] found that an increased expression level of NOSIP in patients with HSCR may promote HAEC development by inhibiting the local production of eNOS and nNOS. Additionally, associated with Tomuschat’s study was the novel finding of an increased proportion of nNOS neurons both in patients with HSCR and in HSCR model mice [60]. In Dariel’s study [40], through comparing surgically resected bowel samples from HSCR neonates and the proximal end of the stoma of patients with anorectal malformation (ARM), the number of nNOS enteric neurons in the nerve segments of patients in the HSCR combined with obstructive symptoms group was found to be significantly reduced, whereas the proportion of nNOS to total enteric neurons was higher in patients in the HSCR combined with HAEC or diarrhea groups, similar to the results obtained by Cheng [60]. Taken together, these studies showed that an increased proportion of nNOS to total enteric neurons may lead to postoperative bowel dysfunction in HSCR, also including cases of HAEC; although, Cheng [60] did not make further comparisons based on different classifications of postoperative complications, and so the ability to compare the results in terms of the correlation between nNOS and HAEC is low, and further studies are therefore required to clarify this correlation. Research suggests that TLR4 expression can regulate ENS maturation and development [61]. Dariel [40] conducted a prospective multicenter cohort study and found that, compared with the ARM group, the HSCR combined with the HAEC group exhibited significantly lower expression levels of TNF-α, TLR2, and TLR4, increased paracellular and transcellular permeability, and a strong correlation was observed between TLR2/4−/− expression and the number of nNOS myenteric neurons. Furthermore, TLR2−/− and TLR4−/− mice were found to have overall reduced numbers of neurons and nNOS-immunoreactive (IR) neurons [61,62], which enabled Dariel to speculate that a reduced level of TLR2/4 expression may lead to an altered ENS phenotype, and therefore an increased susceptibility to postoperative bowel dysfunction. However, by contrast, Zheng [53] found significantly higher levels of TLR4, NF-κB, p-p38, TNF-α, transforming growth factor (TGF)-β, and interleukin (IL)-10 expression in EdnrB−/− mice compared with wild-type mice. TLR4 knockdown led to a reduction in the severity of small intestinal colitis, and the expression levels of IL-10, TNF-α, and TGF-β were all attenuated. These results appeared to differ from those of Dariel [40], although the subjects and controls of the two studies were different, and this may have contributed to the different results; additional follow-up experiments are therefore required in the future to further confirm this. ICCs, located between the plexuses, are considered to act as the pacemakers of gastrointestinal peristalsis, regulating the activity of the intestinal muscles [63]. Jankovic [64] found lower numbers of ICCs in both the transitional and normoganglionic zones of children with HSCR compared with normal controls, and these numbers were lower still in patients with postoperative constipation and enterocolitis. Another study found that, in the dilated colon of both patients with HAEC and EdnrB−/− mice, ICCs lost the c-Kit phenotype, leading to impaired pacemaker function and impaired intestinal motility [6]- findings that were consistent with those of Zhan [25]. Taken together, these studies suggest that a decreased population of ICCs and loss of phenotypic expression lead to both suppressed and impaired intestinal motility and an exacerbation of intestinal flora dysbiosis, which, in turn, promotes the development of HAEC. Hydrogen sulfide, synthesized from L-cysteine by two key enzymes, cystathionine-β-synthase (CBS) and cystathionine-γ-lyase (CSE), has been reported to have a key role both in regulating gastrointestinal motility and in promoting the resolution of inflammation [65]. Tomuschat [66] has shown that the expression levels of CBS and CSE in smooth muscle, ICCs, platelet-derived growth factor-α receptor-positive cells, enteric neurons, and colonic epithelium were markedly decreased in HSCR specimens, indicating that mucosal integrity and colonic contractility may have been affected, thereby rendering patients with HSCR more susceptible to developing HAEC. In conclusion, HAEC may be associated with reduced cholinergic innervation in the intestinal mucosa, a reduced density of NOS enteric neurons, abnormal receptor expression leading to abnormal neural development, reduced numbers of ICCs, and their phenotypic loss (Figure 3). Intestinal-associated lymphoid tissue is the largest immune organ in the body. Macrophages that have colonized the intestine are the first line of defense of the intestinal immune response, and serve to protect the intestine from pathogenic microorganisms. B lymphocytes mature and differentiate into plasma cells that secrete secretory immunoglobulin A (sIgA) into the intestinal lumen, which is the main immunoglobulin in the intestine and is actively transported to the mucosal surface as a dimer through the polymeric immunoglobulin receptor (pIgR), thereby maintaining the balance and normal function of the intestinal microenvironment [67]. Gosain [68] found that, compared with EdnrBNCC+/− mice, EdnrBNCC−/− mice (i.e., mice with a conditional neural crest-specific deletion of EdnrB) had smaller spleens and a lower proportion of spleen weight to total weight. Furthermore, Frykman [69] found that HAEC mice showed thymus degeneration and splenic lymphoid reduction. However, in this case, the maturation and functional markers of the immune organs were not investigated, and the underlying mechanism(s) that would account for how the immune organs are involved in HAEC remain unclear. As is already known, immune cells are heavily involved in the pathogenesis of HAEC. Macrophage phenotypes, including the classically activated (M1) and alternatively activated (M2) types, have been well studied. During the early stages of inflammation, macrophages are predominantly of the M1 type, promoting the development of inflammation, whereas M2 macrophages promote tissue stabilization and maturation [70]. In the proximal dilated colon of both patients with HAEC and EdnrB−/− mice, significant infiltration of proinflammatory M1 macrophages was observed, whereas the population of M2-type macrophages was higher in the distal colon compared with the proximal segment and the function of the ICCs was impaired [6], suggesting that M1 macrophages may contribute to the development of HAEC by causing loss of phenotype of the ICCs and consequently pacemaker function, leading to intestinal dysmotility and further HAEC. Zhan [25] found that VP released LPS in vivo to activate M1 macrophages through the TLR4 pathway, and M1 macrophages produced TNF-α, which in turn promoted the development of HAEC. This study also found that 4-octyl itaconate (OI) could reduce the production of proinflammatory factors and promote the recovery of the ICC phenotype via inhibiting macrophage activation, a discovery that may provide a potential HAEC therapeutic direction in the future. It has been shown that HAEC mainly occurs in the dilated segment of the HSCR mouse model, where the content of acetylcholine in the stenosis segment is increased, and inflammation occurs at a relatively low level. Acetylcholine acts on the α7 nicotinic acetylcholine receptor (α7nAChR) on the surface of macrophages to inhibit macrophage activation, thereby activating the JAK2-STAT3 anti-inflammatory pathway and inhibiting the NF-κB inflammatory pathway [7,8]. The above studies suggest that multiple pathways are involved in promoting the progression of HAEC through the activation of M1 macrophages, and these may exert a significant role in the development of HAEC. Lymphocytes are essential components of the immune system, are widely distributed in the body, and recognize antigens to generate specific immune responses. Keck [55] observed a decrease in Treg cells and an increase in Th17 cells in colon tissue dominated by low cholinergic fibers with a higher incidence of HAEC. Gosain [68] identified both a defect in B lymphocyte maturation and a reduction in their numbers in EdnrBNCC−/− mice. The deficiency in antibody production of the B lymphocytes was confirmed in the HAEC mouse model [64]. Frykman [69] found that EdnrB−/− mice and Edn3 ligand-knockout mice (Edn3−/− mice) had significantly reduced numbers of T cells; common lymphocyte progenitor populations were also significantly reduced, and B lymphocyte production was suppressed, with the degree of suppression being strongly correlated with the severity of HAEC. Taken together, these findings suggest that reduced numbers, or functional defects, of lymphocytes may lead to an attenuated specific immune response in the gut and, consequently, increased susceptibility to HAEC. Immunoglobulin A (IgA) is the main antibody that protects the mucosal surface of the body by binding specifically to the surface structures of pathogens, thereby blocking their adhesion to the mucosa, and preventing the occurrence of infection [71]. Gosain [68] found reduced levels of IgA secretion in the small intestine of EdnrBNCC−/− mice compared with EdnrBNCC+/− mice, whereas the level of nasal and bronchial IgA secretion was unchanged, suggesting an intestinal-specific defect in either IgA production or secretion. Medrano [72] found that, compared with wild-type mice, EdnrBNCC−/− mice exhibited reduced production levels of IgA, IgG, and IgM, and a 50% decrease in small-intestinal pIgR following the in vitro stimulation of splenic B lymphocytes. In addition to animal experiments, an association between antibodies and HAEC has also been observed in clinical studies. Frykman [73] used an enzyme-linked immunosorbent assay to detect inflammatory bowel disease-associated antibodies, namely anti-Saccharomyces cerevisiae antibody (ASCA), anti-E. coli outer membrane porin C (OMPC), anti-flagellin (CBir1), and antineutrophil cytoplasmic antibodies (ANCA), in the plasma of children with HSCR, and found that the serum OMPC antibody and ASCA IgA levels were elevated in patients with HAEC, and that elevated OMPC antibody levels were associated with the development of HAEC, suggesting that HAEC and Crohn’s disease share a common intestinal microbial–host immune response, and that these antibodies may be potential biomarkers for the diagnosis of HAEC. ILs are soluble proteins secreted by cells of the immune system that fulfill important roles in immune regulation. IL-23, a member of the IL-12 family, is an important survival factor for Th17 cells, promoting the secretion of IL-17 by Th17 cells [74]. IL-17 is a proinflammatory cytokine, and the adaptor protein Act1 interacts with the IL-17 receptor (IL-17R) [75]. IL-36γ is a member of the IL-1 superfamily, which is involved in host defense, leading to a proinflammatory response and the development of inflammatory diseases [76]. IL-36 receptor (IL1RL2) is an important mediator molecule in the inflammatory response, and is associated with mucosal repair mechanisms within the colonic epithelium in rodent models of experimental colitis [77]. It was found that the expression levels of Act1, IL-17R, and IL-36γ were significantly increased, whereas that of IL1RL2 was significantly decreased, in HSCR specimens, and that the Th17 cell-associated cytokines IL-17 and IL-23 were upregulated in HAEC [78,79,80]. Keck [55] observed an increased expression of IL-23 in colonic tissue innervated by hypocholinergic fibers, where the incidence of HAEC is higher. TNF-α is an important proinflammatory factor and immunomodulatory factor that is mainly produced by M1 macrophages and, in turn, promotes the development of HAEC [25]. Another study performed by Chen showed that TNF-α expression was significantly increased in more inflamed dilated segments compared with stenotic segments [8]. Meng [81] found that, compared with wild-type mice, not only was intestinal inflammation more severe, but the plasma levels of the proinflammatory factors TNF-α and interferon (IFN)-γ were significantly higher, whereas those of the anti-inflammatory factors TGF-β and IL-10 were significantly lower, in an HAEC mouse model. Chen [6] found that the level of TNF-α was significantly increased, and ICCs lost their c-Kit phenotype, in the proximal dilated colon of both patients with HAEC and EdnrB−/− mice. TNF-α-mediated p65 phosphorylation was shown to induce miR-221 overexpression, leading to inhibition of c Kit expression and pacemaker currents, suggesting that TNF-α participates in the mechanism through which c-Kit expression in the ICCs is inhibited via the NF-κB/miR-221 pathway. IL-10 is an anti-inflammatory factor. Feng [7] performed pathological scoring of intestinal inflammation in EdnrB−/− mice, showing that HAEC occurred mainly in the dilated segment, and found that the level of IL-10 in the stenotic segment of the colon of HSCR mice was higher compared with that in the dilated segment, suggesting that the inconsistencies in the severity of inflammation in the stenotic and dilated segments of the colon are associated with differences in IL-10 content. Different expression levels of the abovementioned cytokines may serve to regulate the inflammatory response in the intestine, which, in turn, may lead to an impaired epithelial barrier, altered mucosal response healing, and disrupted mucosal immune and repair mechanisms, subsequently leading to the development of HAEC. Inflammasomes are multiprotein complexes that are important components of the natural immune system and are involved in host-defense responses against a variety of pathogens. The most common inflammasomes are NLRP1, NLRP3, NLRC4/NAIP, NLRP12, NLRP6, pyrin and AIM2 [82]. Nakamura [83] identified significantly downregulated gene expression levels of NLRP3, NLRP12, NLRC4, ASC, and pro-IL-1, and significantly reduced protein expression levels of NLRP3, NLRP12, NLRC4, and ASC, in the colonic epithelium of patients with HSCR. Similarly, Tomuschat [84] found that the expression level of NLRP6 was significantly reduced in both HSCR aganglionic and ganglionic colon segments, and the relative expression level of NLRP6 was further reduced in patients who developed HAEC. Taken together, the above studies suggest that the downregulation of colonic inflammasome expression in patients with HSCR may lead to an altered colonic microbiome, which increases the patients’ susceptibility to developing HAEC. Inflammasomes are able to mediate the classical pathway of cell pyroptosis. Li [85] explored the role of the LPS/miR-132/-212-sirtuin 1 (Sirt1)-NLRP3 regulatory network in HAEC. The results showed that LPS induced the upregulation of miR-132/-212, activated NLRP3 inflammasomes through suppressing Sirt1 expression, and promoted secondary cell pyroptosis in postoperative HAEC patients, in an LPS-stimulated HT29 cell line, and in LPS-treated mice. In addition, transfection experiments using an miR-132/-212 inhibitor and a Sirt1-overexpression vector resulted in a reduced rate of LPS-induced cell pyroptosis. However, the above effects were not sufficient to entirely eliminate cell pyroptosis, which supports the idea that other types of cell damage mechanisms may also operate. This suggests that LPS/miR-132/-212/Sirt1/NLRP3-Caspase-1 inflammasomes have a participatory role in the mechanism of HAEC progression: LPS induces miR-132/-212 upregulation, activates NLRP3 inflammasomes via suppressing Sirt1 expression and promotes cell pyroptosis, thereby promoting HAEC development and progression. However, there are noted inconsistencies in the above findings, and the molecular mechanisms through which inflammasomes exert their functions have yet to be investigated in depth. Exosomes are small membrane vesicles containing complex RNAs and proteins that are naturally present in body fluids, being involved in intercellular communication, body immune response, and antigen presentation [86,87,88]. Chen [89] isolated exosomes from the serum and found that the expression of miR-18a-5p was significantly increased in the HAEC exosomes, and that exosomal miR-18a-5p was responsible for the downregulation of RAR-related orphan receptor A (RORA), which activated the Sirt1/NF-κB signaling pathway and induced both apoptosis and the inflammatory response in intestinal cells, thereby promoting the development of HAEC. In summary, the above studies collectively suggest the involvement of immune organs, immune cells, immunoglobulins, cytokines, inflammasomes, and exosomes in the development of HAEC (Figure 4), which, considered altogether, suggests that a close association exists between the immune system and HAEC. There are several hypotheses that have been proposed concerning the pathogenesis of HAEC and the mechanisms that interact with each other (Figure 5), so further research should be comprehensive. Targeted therapies for HAEC could be developed in the future, starting from early regulation of intestinal microbiota, restoration of the intestinal peristalsis and mucosal barrier, and promotion of the intestinal immune system. At present, the treatment of HAEC is still mainly coordinated on symptomatic and supportive bases, and further research is required to properly elucidate the precise mechanism of its pathogenesis in order to assist with the treatment and prevention of HAEC.

PMC10003053

Sini Li,Lihui Liu,Yan Qu,Li Yuan,Xue Zhang,Zixiao Ma,Hua Bai,Jie Wang

Comprehensive Analyses and Immunophenotyping of LIM Domain Family Genes in Patients with Non-Small-Cell Lung Cancer

24-02-2023

LIM domain family,LIMS1,molecular subtypes,non-small-cell lung cancer,tumor microenvironment

The LIM domain family genes play a crucial role in various tumors, including non-small-cell lung cancer (NSCLC). Immunotherapy is one of the most significant treatments for NSCLC, and its effectiveness largely depends on the tumor microenvironment (TME). Currently, the potential roles of LIM domain family genes in the TME of NSCLC remain elusive. We comprehensively evaluated the expression and mutation patterns of 47 LIM domain family genes in 1089 NSCLC samples. Using unsupervised clustering analysis, we classified patients with NSCLC into two distinct gene clusters, i.e., the LIM-high group and the LIM-low group. We further investigated the prognosis, TME cell infiltration characteristics, and immunotherapy in the two groups. The LIM-high and LIM-low groups had different biological processes and prognoses. Moreover, there were significant differences in TME characteristics between the LIM-high and LIM-low groups. Specifically, enhanced survival, immune cell activation, and high tumor purity were demonstrated in patients of the LIM-low group, implying an immune-inflamed phenotype. Moreover, the LIM-low group had higher immune cell proportion scores than the LIM-high group and was more responsive to immunotherapy than the LIM-low group. Additionally, we screened out LIM and senescent cell antigen-like domain 1 (LIMS1) as a hub gene of the LIM domain family via five different algorithms of plug-in cytoHubba and the weighted gene co-expression network analysis. Subsequently, proliferation, migration, and invasion assays demonstrated that LIMS1 acts as a pro-tumor gene that promotes the invasion and progression of NSCLC cell lines. This is the first study to reveal a novel LIM domain family gene-related molecular pattern associated with the TME phenotype, which would increase our understanding of the heterogeneity and plasticity of the TME in NSCLC. LIMS1 may serve as a potential therapeutic target for NSCLC.

Comprehensive Analyses and Immunophenotyping of LIM Domain Family Genes in Patients with Non-Small-Cell Lung Cancer The LIM domain family genes play a crucial role in various tumors, including non-small-cell lung cancer (NSCLC). Immunotherapy is one of the most significant treatments for NSCLC, and its effectiveness largely depends on the tumor microenvironment (TME). Currently, the potential roles of LIM domain family genes in the TME of NSCLC remain elusive. We comprehensively evaluated the expression and mutation patterns of 47 LIM domain family genes in 1089 NSCLC samples. Using unsupervised clustering analysis, we classified patients with NSCLC into two distinct gene clusters, i.e., the LIM-high group and the LIM-low group. We further investigated the prognosis, TME cell infiltration characteristics, and immunotherapy in the two groups. The LIM-high and LIM-low groups had different biological processes and prognoses. Moreover, there were significant differences in TME characteristics between the LIM-high and LIM-low groups. Specifically, enhanced survival, immune cell activation, and high tumor purity were demonstrated in patients of the LIM-low group, implying an immune-inflamed phenotype. Moreover, the LIM-low group had higher immune cell proportion scores than the LIM-high group and was more responsive to immunotherapy than the LIM-low group. Additionally, we screened out LIM and senescent cell antigen-like domain 1 (LIMS1) as a hub gene of the LIM domain family via five different algorithms of plug-in cytoHubba and the weighted gene co-expression network analysis. Subsequently, proliferation, migration, and invasion assays demonstrated that LIMS1 acts as a pro-tumor gene that promotes the invasion and progression of NSCLC cell lines. This is the first study to reveal a novel LIM domain family gene-related molecular pattern associated with the TME phenotype, which would increase our understanding of the heterogeneity and plasticity of the TME in NSCLC. LIMS1 may serve as a potential therapeutic target for NSCLC. Lung cancer is one of the most common cancers worldwide, which seriously endangers public health [1]. Based on the Global Burden of Disease Study in 2020, lung cancer has the second highest incidence and the highest mortality [2], of which non-small-cell lung cancer (NSCLC) accounts for approximately 80−85% [3,4]. Owing to the high invasiveness of NSCLC and the lack of significant clinical symptoms in early-stage patients, most patients with NSCLC are already in the advanced stage at the time of diagnosis, with a relatively poor prognosis and high mortality [5]. Although targeted therapy and immunotherapy have primarily improved the survival of patients with NSCLC, some patients do not respond to these treatments [6,7] owing to the molecular heterogeneity of tumors [8]. Therefore, an in-depth understanding of tumor characteristics and the identification of effective prognostic indicators are needed to develop individualized diagnosis and treatment. The LIM domain family is a specialized tandem zinc-finger structure recognized as a modular protein-binding interface [9]. The LIM domain family has been identified in both the cytoplasm and the nucleus and consists of many members, including members of the LIM homeobox (LHX), C-reactive protein (CRP), four-and-a-half LIM protein (FHL), Paxillin, LIM Domain Kinase (LIMK), LIM-only (LMO), Enigma, microtubule-associated oxygenase, calponin and LIM domain (MICAL), LIM and SH3 protein (LASP), actinin-associated LIM protein (ALP), particularly interesting new Cys-His protein (PINCH), Testin, and Zyxin families [10]. Increasing evidence reveals that the LIM domain family has diverse functions in regulating cytoskeleton organization, tissue-specific gene expression, neuronal pathfinding, cell fate determination, cell adhesion, cell motility, and signal transduction [11,12]. Moreover, it is emerging as a critical molecule in a wide variety of human cancers. The LMO proteins have important roles in cancer initiation and progression [13], and PINCH has been reported to promote tumor progression and metastasis [14,15], suggesting that the LIM domain family may be a potential therapeutic target for a range of different cancers. It has been recently reported that the tumor microenvironment (TME) is closely related to biological processes during tumorigenesis, including tumor initiation, progression, metastasis, and immune escape [16,17]. Immunophenotyping of tumors is crucial in formulating effective treatment strategies, especially immunotherapy, and is significant in the prognostic assessment of patients with tumors [18]. Increasing evidence has revealed the correlation between TME infiltrates and the LIM domain family genes. The LIM and senescent cell antigen-like domain 1 (LIMS1), a member of PINCH, was positively associated with advanced TNM stage and poor prognosis of patients with pancreatic cancer and promoted cancer cell survival in the oxygen-glucose-deprived TME [19]. The high expression of PDZ and LIM domain 2 (PDLIM2), a member of ALP, was also correlated with infiltrating immune cells and predicted poor prognoses in patients with prostate cancer [20]. However, the gene signature associated with the LIM domain family genes and its potential roles in immune infiltration remains elusive, especially in NSCLC. Therefore, immunophenotyping of LIM-mediated TME may aid in the treatment and prognosis of patients with NSCLC. First, a total of 47 genes in the LIM domain family were identified, including members of the LHX, CRP, FHL, Paxillin, LIMK, LMO, Enigma, MICAL, LASP, ALP, PINCH, Testin, and Zyxin families (Table 1). Second, we analyzed the somatic mutation frequency and copy number variations of 47 LIM domain family genes in NSCLC. Among 1067 samples with somatic mutation data, 361 exhibited LIM domain family gene mutations, with a frequency of 33.83%. Nebulin-related anchoring protein exhibited the highest mutation frequency, followed by LHX8. In contrast, some LIM domain family genes did not exhibit any mutation in NSCLC samples, including cysteine and lysine-rich protein 3 (CSRP3), ISL LIM homeobox 2 (ISL2), and LHX6 (Figure 1A). The investigation of copy number variation (CNV) alteration frequency revealed that the LIM family genes exhibited prevalent CNV alterations, most of which were copy number amplifications. However, filamin binding LIM protein 1 (FBLIM1), alkaline phosphatase placental type (ALPP), LMO1, PDLIM2, PDLIM4, and LIM domain-containing protein 1 had a widespread frequency of CNV deletion (Figure 1B). The location of CNV alterations of the LIM domain family genes on chromosomes is presented in Figure 1C. To determine the relationship between the expression of LIM family genes and lung cancer, we explored mRNA levels of these genes in NSCLC and normal tissues. According to the results, 43 of the 47 LIM family genes were differentially expressed in NSCLC compared to normal tissues (Figure 1D). Moreover, according to the expression pattern of these genes, NSCLC samples were markedly distinct from normal samples (Figure 1E). These results revealed that the expression of the LIM domain family genes in NSCLC and normal tissues is different, indicating that the LIM domain family genes may play a potential role in the tumorigenesis of NSCLC. We explored the clinical significance of the LIM domain family genes in patients with NSCLC. Consensus clustering analysis was performed to classify patients with NSCLC into subgroups based on the expression of 47 LIM domain family genes. A total of 1002 patients with NSCLC were grouped into two clusters, including 522 and 480 cases in cluster 1 and cluster 2, respectively (Figure 2A, Table S1). Interestingly, we observed that most LIM domain family genes were more highly expressed in cluster 2 (LIM-high group) than in cluster 1 (LIM-low group, Figure 2B). Additionally, we explored the distribution of somatic mutations between the LIM-low group and the LIM-high group of patients with NSCLC. We did not observe a significant difference in mutation rates of LIM genes between the two groups (Figure 2C,D). However, survival analysis revealed that patients in the LIM-low group were associated with a significant survival benefit compared to those in the LIM-high group (Figure 2E). To demonstrate the underlying biological pathways in the LIM-high group and the LIM-low group, we identified 863 differentially expressed genes (DEGs) between the two groups (Table S2). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were further performed based on DEGs to identify potential mechanisms (Tables S3 and S4). The GO analysis regarding biological processes demonstrated that DEGs were significantly enriched in extracellular matrix (ECM) organization and extracellular structure organization. In terms of cellular components and molecular function, DEGs were significantly enriched in the collagen-containing ECM and ECM structural constituents, respectively (Figure S1A). Additionally, the KEGG analysis revealed that DEGs were significantly enriched in protein digestion and absorption and ECM–receptor interaction, indicating the correlation with tumorigenesis and progression (Figure S1B). A Gene Set Enrichment Analysis (GSEA) was also performed to identify the functional enrichment of the LIM-high group and the LIM-low group of patients with NSCLC. As presented in Figure S1C–F and Table S5, the LIM-high group was prominently enriched in ECM–receptor interaction and cell–matrix adhesion (Figure S1C,D). However, the LIM-low group was markedly enriched in metabolic-related activities, including drug metabolism cytochrome P450 and olefinic compound metabolic process (Figure S1E,F). To characterize the TME features of the LIM-high group and the LIM-low group of patients, we first explored the abundance of infiltrating immune cells via an estimate algorithm. Interestingly, the LIM-low group had higher tumor purity (Figure 3A) and lower ESTIMATEScore, ImmuneScore, and StromalScore (Figure 3B–D) than the LIM-high group. These results indicated heterogeneity in TME between the patients of the two groups. To further explore the TME features in detail, we compared the component differences of 22 types of immunocytes in two groups using CIBERSORT and ssGSEA analyses (Figure 3E,F, Tables S6 and S7). Consistently, we observed significant differences in the infiltration of immunocytes in TME between the two groups. Specifically, the LIM-low group had a higher percentage of CD8+ T cells, follicular helper T cells, resting dendritic cells, and resting mast cells than the LIM-high group. However, the proportion of CD4+ resting memory T cells, resting NK cells, M0 macrophages, activated dendritic cells, activated mast cells, and neutrophils were lower in the LIM-low group than those in the LIM-high group (Figure 3E). Additionally, ssGSEA analysis also revealed that myeloid-derived suppressor cells (MDSCs), macrophages, regulatory T cells, and mast cells were significantly more abundant in the LIM-high group than in the LIM-low group (Figure 3F). Altogether, these results demonstrated that the TME features and immune status of the two molecular subtypes significantly differed. To further explore the correlation between the LIM signature and TME, we constructed a LIMscore algorithm using principal component analysis (PCA) based on the expression levels of 47 LIM domain family genes. By quantifying the LIMscore in each patient with NSCLC, we investigated the relationship between the LIMscore and infiltrating immune cells (Figure 4A). Interestingly, we observed that the LIMscore was negatively associated with the abundance of resting dendritic cells (Figure 4B), CD8+ T cells (Figure 4C), follicular helper T cells (Figure 4D), and activated NK cells (Figure 4E). A remarkable positive association was achieved between the LIMscore and the abundance of activated mast cells (Figure 4F) and macrophages (Figure 4G). These results demonstrated that a higher LIM signature may correlate with an immunosuppressive TME in patients with NSCLC. Considering that immune checkpoint inhibitors enhance the treatment pattern and provide significant benefits to patients with NSCLC, we investigated the potential relationship between the LIM signature and immunotherapy. First, we observed no significant difference in the tumor mutation burden (TMB) between the LIM-low and LIM-high groups (Figure 5A). Consistently, correlation analysis confirmed that the LIMscore was not associated with the TMB level (Figure 5B). Second, we explored the expressions of several widely used immune checkpoints in the LIM-high and LIM-high groups. As indicated in Figure 5C, compared with those in the LIM-low group, the expressions of cytotoxic T-lymphocyte associated protein 4 (CTLA4), programmed cell death (PCD) 1 ligand 2, PCD protein 1 (PDCD1), Hepatitis-A virus cellular receptor 2, and sialic acid binding Ig like lectin 15 were significantly increased in the LIM-high group. Additionally, we calculated the immune cell proportion score (IPS) for each sample and distinguished beneficiaries between the two groups. The IPSs of CTLA4_neg_PD1_neg, CTLA4_neg_PD1_pos, CTLA4_pos_PD1_neg, and CTLA4_pos_PD1_pos (Figure 5D–G) were significantly higher in the LIM-low group than those in the LIM-high group, suggesting more beneficiaries in the LIM-low group. These results indicated that the LIM-low group had more immunogenic phenotypes, and the LIM signature was intensively associated with immunotherapy. Our results revealed that the LIM domain family genes were associated with clinical significance. To identify the hub module among the 47 genes, we initially constructed the protein–protein interaction (PPI) network (Figure 6A) and used five algorithms to generate hub genes. We identified seven hub LIM domain family genes that were shared by all the algorithms, including LHX3, Zyxin, LMO3, LMO1, LHX9, CSRP1, and LIMS1 (Figure 6B). Additionally, we used the weighted gene co-expression network analysis (WGCNA) analysis to construct a module–trait matrix. As indicated in Figure 6C, hierarchical clustering grouped the LIM domain family genes into three modules. The module–trait relationship is illustrated in Figure 6D. We observed that the MEblue module was significantly positively associated with clinical traits in the tumor, suggesting that genes of MEblue were associated with tumor characteristics. In contrast, the MEturquoise module was significantly positively related to clinical traits in healthy lungs. Therefore, the genes in the MEblue module may be related to the phenotypes of NSCLC. Interestingly, LIMS1 belongs to both the hub genes in PPI and the MEbule module. We further examined the expression of LIMS1 protein in NSCLC tissues based on the Human Protein Atlas (HPA) database. As indicated in Figure 6E–J, the LIMS1 protein was strongly expressed in tumor tissues among six patients with NSCLC (three with lung adenocarcinoma and three with lung squamous cell carcinoma). To further explore the role of LIMS1 in NSCLC, we constructed two in vitro models using the H1299 and H157 cell lines. As indicated in Figure 7A, LIMS1 expression was upregulated or knocked down in H1299 and H157 cell lines, respectively. We used EdU incorporation assays to explore the effects of LIMS1 on cell proliferation. According to the results, compared with that in the control group, the number of EdU+ cells in H157 cells with decreased LIMS1 expression was significantly reduced (Figure 7B). In contrast, compared with that in the control group, the number of EdU+ cells in H1299 cells with increased LIMS1 expression was significantly increased (Figure 7C), suggesting that LIMS1 promoted the proliferation of NSCLC cells. We also explored the effect of LIMS1 on the migratory capabilities of NSCLC cells via a wound-healing assay and a transwell assay. The wound-healing assay presented that the rate of migrated H157 cells with decreased LIMS1 expression was significantly lower than that in the control group (Figure 7D). In contrast, the migration rate of H1299 cells with increased LIMS1 expression was markedly higher than that in the control group (Figure 7E). The transwell assay also revealed that, compared to the control group, the migrated and invaded tumor cells were decreased in H157 cells with decreased LIMS1 expression (Figure 7F,G). Contrasting results of migration and invasion were observed in H1299 cells with increased LIMS1 expression (Figure 7H,I). Altogether, these results revealed that LIMS1 promoted the proliferation, migration, and invasion abilities of NSCLC cell lines, suggesting that LIMS1 may function as a pro-tumor gene and promote tumor progression. Increasing evidence has demonstrated that the LIM domain family genes play an indispensable role in tumor initiation, progression, and host immunity [21,22,23,24]. Previous studies have focused on a single gene or single TME cell type; however, the role of the LIM domain family genes in TME infiltration in NSCLC has not been comprehensively recognized. The discovery of the role of the LIM domain family genes in the TME will contribute to the development of more effective treatment strategies. Our study summarized the expression and mutation patterns of the LIM domain family genes based on The Cancer Genome Atlas (TCGA)–NSCLC, and the frequency of global alterations was 33.83%. Using the unsupervised clustering algorithm, we classified patients with NSCLC into two gene clusters. We observed that most LIM domain family genes were more highly expressed in cluster 2, namely, the LIM-high group. Interestingly, patients in the LIM-low group had a better survival rate than those in the LIM-high group. Moreover, the analysis of the TME for both groups revealed a higher proportion of CD8+ T cells and follicular helper T cells in the LIM-low group. However, the proportions of MDSC, macrophages, and regulatory T cells were significantly higher in the LIM-high group. Additionally, the LIM-high group revealed a higher stromal score with significance, whereas the LIM-low group exhibited a higher tumor purity. Meanwhile, to further explore the association between the LIM signature and TME in NSCLC, we constructed the LIMscore based on the expression level of 47 LIM domain family genes using PCA. We demonstrated that the LIMscore was negatively associated with CD8+ T cells and activated NK cells, albeit positively associated with MDSC, M0 macrophages, and activated mast cells. These results indicated the possibility of an immunosuppressive microenvironment in the LIM-high group. Additionally, the IPS was significantly increased in the LIM-low group, suggesting its higher sensitivity to immunotherapy. Conclusively, there were significant differences in the characteristics of TME between the LIM-low and LIM-high groups, suggesting that the LIM domain family genes can provide reasonable recommendations for personalized immunotherapy for patients with NSCLC. Several studies have elucidated the potential mechanism of the LIM domain family genes involved in tumorigenesis and progression. In breast cancer, abnormal expression of LMO4 could enhance the transforming growth factor-β (TGF-β) signaling pathway and may promote breast cancer progression by regulating epithelial–mesenchymal transformation (EMT) regulated by TGF-β [25]. Malvi et al. reported the potential mechanism by which LIMK2 promotes the metastatic progression of breast cancer by activating SRSF protein kinase 1 [26]. In prostate cancer, patients with a high expression of PDLIM2 had a poor prognosis, and PDLIM2 was correlated with EMT and immune cell infiltration by acting as an oncogene [20]. LMO2 may also promote prostate cancer progression by inhibiting E-cadherin expression [27]. In colorectal cancer, PDLIM1 could inhibit EMT and the metastatic potential of colorectal cancer cells via stabilizing the E-cadherin/β-catenin complex [28]. The imbalanced expression of LIMK1 and LIMK2 could promote β-catenin nuclear translocation and activate the wnt signaling pathway, thus leading to colorectal cancer progression [29]. Furthermore, FHL3 could promote EMT and chemotherapy resistance via up-regulating Slug and activating TGF-β/Smad-independent pathways, thus leading to metastasis of gastric cancer [30]. The above studies show that the LIM domain family genes are closely related to EMT, suggesting that it may be an important mechanism of the LIM domain family genes involved in tumor development. Moreover, previous studies have identified the crucial roles and potential mechanisms of LIM domain family genes in NSCLC. Shi et al. found that PDLIM5 contributes to the migration, invasion, and lung metastasis of NSCLC cells. Mechanistically, they demonstrated that PDLIM5 promotes TGF-β signaling and malignance of lung cancer by specifically interacting with SMAD3 and preventing its degradation [31]. Hou et al. discovered that FHL3 promoted the growth, proliferation, and invasion of NSCLC cells [32]. LMO1 can also act as an activated tumor promoter that activates AKT signaling in NSCLC [33]. LIM domain-containing protein 1 (LIMD1) is a tumor suppressor gene occasionally ablated early in lung cancer development [34]. Moreover, LIMD1 is a prognostic indicator for NSCLC, and its loss significantly worsened patient survival [35,36]. LIMS1, a member of the PINCH family, plays important roles in cell–ECM adhesion, migration, proliferation, and survival [37]. Recent studies have reported its vital role in cancer progression. For instance, a high level of LIMS1 promoted tumor progression in breast cancer, and the LIMS1–myoferlin signaling axis may contribute to this process [15]. In skin cancer, LIMS1–neural precursor cells expressed a developmentally downregulated protein 4-insulin-like growth factor-1 receptor signaling axis, which is critical for promoting skin cancer cell proliferation and survival [14]. Guo et al. discovered that LIMS1 is highly expressed in lung adenocarcinoma and promotes proline synthesis, cell proliferation, and tumor growth [38]. In this study, the protein expression of LIMS1 in NSCLC tissues was analyzed in the HPA database, and the results revealed that LIMS1 protein was strongly expressed in NSCLC tissues. Subsequently, we performed some in vitro experiments to explore the function of LIMS1. These results exhibited that LIMS1 expression was positively associated with the proliferation, migration, and invasion of NSCLC cells, indicating that LIMS1 may function as an oncogenic gene and be a potential target in NSCLC. Although we performed a comprehensive analysis of the LIM domain family genes and TME infiltration characterization in NSCLC, which lays a foundation for future exploration of NSCLC progression, this study still has some limitations. Since our NSCLC samples were only obtained from retrospective studies based on the TCGA databases, more cases from prospective research are required. Furthermore, the role of LIMS1 was explored in NSCLC cell lines in vitro; however, comprehensive functions of LIMS1 and its relationship to TME remain elusive, which needs to be further explored through in vitro and in vivo experiments and clinical samples. Additional research is crucial to identify the specific molecular mechanisms of the LIM domain family genes regulating NSCLC progression. We downloaded RNA-seq transcriptome data, nucleotide variation data, and the clinical records from the NSCLC (n = 1089) datasets from the TCGA database. Patients without corresponding clinical data were further excluded. We downloaded the RNA-seq data with count value from the Genomic Data Comments (GDC, https://portal.gdc.cancer.gov/, accessed on 12 November 2022) and transformed them as fragments per kilobase of transcript per million mapped read values using R software. We also downloaded the somatic mutation data from the TCGA database and processed it with the maftools package in R software. We identified a 47-gene panel as the LIM domain family through retrieval of the relevant literature (Table 1). Further, we compared the expression of these genes in NSCLC tumors with that of normal tissues and identified 43 differentially expressed LIM domain family genes in patients with NSCLC. We used the limma package in R software to process all the data. Based on the expression levels of 47 LIM domain family genes, we used an unsupervised clustering analysis with the optimal k value with the ConsensClusterPlus package in R software to generate gene clusters. Patients with NSCLC were divided into two groups (LIM-high and LIM-low groups). A consensus clustering algorithm was used to determine the optimal number of clusters and their stability. Further, we used PCA to construct the LIMscore based on the expression levels of 47 LIM domain family genes. Both principal component 1 and principal component 2 were selected for calculating the LIM signature scores. Survival analyses were performed using the Survminer and survival packages in R software and visualized as Kaplan−Meier (KM) survival curves. GO and KEGG analyses were performed using the clusterProfiler and org.Hs.eg.db packages in R software based on the DEGs between the LIM-high group and the LIM-low group. The critical value of the false discovery rate (FDR) was <0.05. GSEA was performed using the enrichplot, clusterProfiler, and org.Hs.eg.db packages in R software according to the GSEA algorithm. We used the estimate package in R software to estimate the abundance of the infiltrating immune cells in NSCLC tumors. Additionally, we quantified the relative abundance of each infiltrating cell population in the TME of the NSCLC tumors using single-sample GSEA (ssGSEA) with the gsva package in R software. Using the ssGSEA algorithm, the relative abundance of different infiltrates in each sample was calculated according to the enrichment scores. We initially used STRING (version 11.5) to perform PPI network and functional enrichment analyses. Then, the PPI network was exported into Cytoscape software to determine the hub genes of the LIM domain family genes. We used the cytoHubba plug-in to identify the hub genes in the network according to the five different algorithms. Furthermore, we performed WGCNA using the WGCNA and limma packages in R software to determine tumor-related modules and hub genes. Genes were classified into modules based on the topological overlap matrix (TOM)-based dissimilarity measure. The parameters used for WGCNA were as follows: cut height 0.25, soft-thresholding power 9, and minimal module size 7. Human NSCLC cell lines H1299 and H157 were obtained from the American Type Culture Collection. The Roswell Park Memorial Institute (RPMI)-1640 medium (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (Gibco, Thermo Fisher Scientific) and 1% penicillin–streptomycin antibiotic solution was used for cell culturing. The specific small interfering RNAs for LIMS1 and a negative control siRNA were purchased from Ribobio Company (www.ribobio.com, accessed on 5 August 2022). Overexpression of LIMS1 was also conducted with plasmids synthesized in Shanghai GeneChem Company (www.genechem.com.cn, accessed on 4 August 2022) via transfection. The transfection was performed per the manufacturer’s instructions of the Lipofectamine 3000 Transfection Kit (Invitrogen, Thermo Fisher Scientific). Forty-eight hours following transfection, tumor cells were collected for subsequent experiments. First, H1299 and H157 cells were entirely lysed, and total protein was extracted using RIPA lysis buffer (Beyotime, China). Second, protein loading buffer was added to the protein sample, mixed to a concentration of 1×, and boiled for 8 min. Third, a 30-µg protein sample was added to each well for electrophoresis, which was then transferred to a polyvinylidene fluoride (PVDF) membrane. Last, the membrane was blocked with 5% skim milk for 2 h and subsequently incubated with the primary antibodies (LIMS1/β-Actin, Abcam, Waltham, MA, USA) overnight at 4 °C. Bands were then incubated with the secondary antibody (Abcam, Cambridge, UK) for 2 h at room temperature. The immune complex was detected using chemiluminescence (Amersham Imager 600, General Electric, Boston, MA, USA). The EdU Imaging Kit (RIBOBIO, China) was used for evaluating cell proliferation following the manufacturer’s instructions. One hundred microliters of 1× Hoechst (RIBOBIO, Guangzhou, China) were used to stain the cell nuclei. Cells with EdU+ were visualized using a fluorescence microscope (Olympus, Tokyo, Japan). The cells were seeded densely in a six-well plate and cultured to confluence. Further, a 200-μL sterile tip was used to scratch a wound line across the monolayer cells. The detached cells were further washed away with phosphate-buffered saline. Cells were cultured in RPMI-1640 and photographed at 0 and 24 h post-wounding. Images were captured using a phase-contrast microscope (OLYMPUS, Japan). Each assay was replicated thrice. The migration assay was performed with a 24-well transwell chamber without Matrigel (Corning, NY, USA) coated in the upper chamber, and the invasion assay was performed with its upper chamber coated with Matrigel. A total of 2 × 105 (invasion) or 105 (migration) transfected H1299 or H157 cells in 200 µL of serum-free RPMI-1640 was first seeded in the upper chamber. Next, 700 µL of medium containing 10% FBS was added to the lower chamber. Following 24 h incubation, the cells on the upper membrane were carefully removed with a cotton swab. The invaded cells that traversed the membrane were identified with crystal violet staining and photographed. The invaded cells were counted manually and confirmed using ImageJ software (NIH, Bethesda, MD, USA). Data are presented as mean ± standard error of the mean. Comparisons between groups were performed using Student’s t-tests for continuous variables and χ2 tests or Fisher’s exact tests for categorical variables. The log-rank test was used to determine the statistical significance of the difference between survival curves. p < 0.05 was considered statistically significant. The KM survival curves were plotted using the Survminer package in R software. All statistical analyses were performed using R software and GraphPad Prism 8. In this study, a comprehensive assessment of the expression and mutation profiles of 47 LIM domain family genes in NSCLC was performed, and we comprehensively analyzed the role of the LIM domain family genes in TME and immunotherapy. Initially, the patients with NSCLC were stratified into two LIM-related clusters based on 47 LIM domain family gene expression levels: the LIM-high group and the LIM-low group. Further analyses demonstrated that the two groups had different prognoses and TME-infiltrated immune cells, indicating that the LIM domain family genes played crucial roles in the TME of NSCLC. Moreover, we determined that LIMS1 was the hub LIM domain family gene based on the bioinformatic analysis. Further assays verified that LIMS1 may act as a pro-tumor gene and promotes tumor progression, thus presenting as a potential biomarker and therapeutic target in NSCLC.

PMC10003056

Nikita Shepelev,Olga Dontsova,Maria Rubtsova

Post-Transcriptional and Post-Translational Modifications in Telomerase Biogenesis and Recruitment to Telomeres

06-03-2023

telomerase,modifications,telosome,biogenesis,processing,telomerase RNA,TERT,hTERP

Telomere length is associated with the proliferative potential of cells. Telomerase is an enzyme that elongates telomeres throughout the entire lifespan of an organism in stem cells, germ cells, and cells of constantly renewed tissues. It is activated during cellular division, including regeneration and immune responses. The biogenesis of telomerase components and their assembly and functional localization to the telomere is a complex system regulated at multiple levels, where each step must be tuned to the cellular requirements. Any defect in the function or localization of the components of the telomerase biogenesis and functional system will affect the maintenance of telomere length, which is critical to the processes of regeneration, immune response, embryonic development, and cancer progression. An understanding of the regulatory mechanisms of telomerase biogenesis and activity is necessary for the development of approaches toward manipulating telomerase to influence these processes. The present review focuses on the molecular mechanisms involved in the major steps of telomerase regulation and the role of post-transcriptional and post-translational modifications in telomerase biogenesis and function in yeast and vertebrates.

Post-Transcriptional and Post-Translational Modifications in Telomerase Biogenesis and Recruitment to Telomeres Telomere length is associated with the proliferative potential of cells. Telomerase is an enzyme that elongates telomeres throughout the entire lifespan of an organism in stem cells, germ cells, and cells of constantly renewed tissues. It is activated during cellular division, including regeneration and immune responses. The biogenesis of telomerase components and their assembly and functional localization to the telomere is a complex system regulated at multiple levels, where each step must be tuned to the cellular requirements. Any defect in the function or localization of the components of the telomerase biogenesis and functional system will affect the maintenance of telomere length, which is critical to the processes of regeneration, immune response, embryonic development, and cancer progression. An understanding of the regulatory mechanisms of telomerase biogenesis and activity is necessary for the development of approaches toward manipulating telomerase to influence these processes. The present review focuses on the molecular mechanisms involved in the major steps of telomerase regulation and the role of post-transcriptional and post-translational modifications in telomerase biogenesis and function in yeast and vertebrates. Telomerase provides eukaryotic cells unlimited proliferative potential by maintaining their telomeres [1,2]. Telomeres shorten with each division of somatic cells because of the end-replication problem [3,4] and endonuclease action [5]. When telomeres become critically shortened, they cannot protect the ends of linear chromosomes from DNA damage signaling, and the affected cells become subject to DNA damage arrest and/or senescence [6,7]. However, some cells manage to survive by activating telomerase to elongate telomeres. This phenomenon has been observed in the majority of cancer cells [8]. Telomerase is active in cells that should divide continuously during the life of an organism, and it is activated in special cases in which extended proliferation is required [9,10]. Immune cells activate telomerase during differentiation and activation [11,12,13]. Regenerative processes also require telomerase activation [14]. Telomerase action is important, as it preserves telomere length during embryonal development [15,16]. A deficiency in telomerase activity during development and in stem cells is associated with diseases related to premature senescence because of the decreased regenerative capacity of the affected stem cells [17]. Only a minority of cancer cells can undergo the alternative lengthening of telomeres (ALT) without the involvement of telomerase [18]. Telomerase RNA and telomerase reverse transcriptase are two major components of the telomerase complex (or telomerase holoenzyme), which are sufficient for the telomerase activity in vitro [19,20,21]. However, the telomerase holoenzyme’s assembly and interaction with telomeres require many additional components. Hereinafter, we use the terms “telomerase complex” or “telomerase holoenzyme” to refer to a fully assembled and catalytically active telomerase ribonucleoprotein (RNP) complex. “Telomerase RNP” is used as an immature telomerase ribonucleoprotein complex, which lacks some auxiliary proteins unless otherwise specified. The deficiency and mutations of additional telomerase components affect the telomerase action of telomeres. The biogenesis of these components is regulated at every step, from transcription and processing to maturation and the posttranslational modifications of telomerase reverse transcriptase and telomerase auxiliary proteins. It is essential to understand the regulatory mechanisms of telomerase biogenesis and activity to develop approaches with which to manipulate telomerase, thereby influencing regeneration, maintaining fitness, and preventing senescence and cancer progression. The present review focuses on the molecular mechanisms that regulate the major steps of biogenesis and the function of telomerase components in yeast and vertebrates. The main components of budding yeast telomerase complex are telomerase RNA (TLC1) and telomerase reverse transcriptase (Est2). Est1, Est3, Pop1, Pop6, Pop7, the yKu70/80 heterodimer, and the heptameric Sm7 protein ring are also part of the telomerase holoenzyme and are relatively stably bound to TLC1 via a set of protein–RNA and protein–protein interactions (Figure 1). Although in vitro telomerase activity requires only TLC1 and Est2 [19], the listed auxiliary proteins are absolutely indispensable for the full activation of telomerase in living cells. Sm7 is required for the stabilization of the cytoplasmic pool of TLC1 by binding near the 3′ end of TLC1 in a structure called a terminal arm or Sm arm [22,23]. Est2 binds to the pseudoknot and the template region in a proximal center of TLC1 where three large TLC1 stems meet [24]. Est1 mediates the major pathway of telomerase recruitment to telomeres in the late S phase, as it can bind Cdc13 telomeric protein and telomerase RNA [25,26,27,28,29,30]. Moreover, Est1 participates in the activation of telomerase at telomeres, changing the Cdc13 conformation and influencing its ability to retain the telomeric 3′ end and hide it from telomerase [31]. Est1 binding relies on hinge–hairpin and bulge elements in a part of TLC1 known as an Est1 arm [32]. The yKu70/80 heterodimer is a key factor of DNA break repair because of its ability to specifically associate with double-stranded DNA breaks. However, its DNA binding domain allows it to recognize a short stem-loop structure within another TLC1 arm (yKu arm) [33,34,35]. In addition, the yKu80 protein can bind Sir4 (silent information regulator 4) telomeric protein, thus providing telomerase with an alternative means of finding the telomeric end [35,36]. Perhaps the least understood protein within the telomerase holoenzyme is Est3, which is a small, oligonucleotide/oligosaccharide-binding fold (OB-fold) containing protein whose binding is thought to be required for the correct conformation of the complex, potentially regulating the telomerase assembly pathway [37]. The Est3 protein binds to the complex via interactions with Est1 and Est2 [37]. OB-fold proteins are a hallmark of an important evolutionarily conserved subclass of proteins that are involved in maintaining the integrity of the genome, particularly with respect to telomeres [38]. Finally, the telomerase complex contains a set of Pop proteins (Pop1, Pop6, and Pop7), which it shares with the RNase P and RNase MRP complexes [39]. Pop proteins bind to the CS2a/TeSS domain of the Est1 arm near the Est1 binding site. The presence of Pop proteins was found to be important for the biogenesis of telomerase and its nuclear localization [40,41]. It is worth noting that telomerase is an extremely lowly abundant complex (~30 of TLC1 molecules per cell), which complicates the comprehensive investigation of its composition [42]. More than 100 proteins were found to co-precipitate with overexpressed Est1 and Est2 subunits in a study conducted by Lin et al., suggesting that other telomerase holoenzyme components might be revealed in future [43]. In the late G1 phase of the cell cycle, RNA polymerase II synthesizes a ~1220 nt primary TLC1 transcript, which is subsequently processed, giving rise to the mature 1157 nt poly(A) form [44,45]. Nrd1/Nab3-dependent transcription termination was found to be crucial for the generation of mature TLC1, thus mirroring the maturation pathway of the snRNA transcripts in budding yeast [45,46]. The Nrd1 protein can bind to the phosphorylated C-terminal domain (CTD) of RNA polymerase II, with a preference for the phospho-Ser5 form of the CTD repeat. At a later stage of transcription, Nrd1 forms a heterodimer with the Nab3 protein, and they recognize motifs located near the mature 3′ end of TLC1. The termination of TLC1 transcription most likely ends with the concomitant exonucleolytic cleavage of TLC1 [45,46]. However, ~10% of cellular TLC1 is present in a longer ~1240 nt form (plus a ~80 nt poly(A) tail), which is likely generated via the termination near the A/U-rich sequences akin to the majority of mRNA species [45,47]. The potential functional roles of the longer poly(A)+ species (e.g., whether it serves as a precursor to the 1157 nt poly(A) form) have yet to be established; it could be simply generated as a by-product of a redundant “fail-safe” mechanism of transcription termination [45,48]. At the 5′ end, TLC1 is capped by 7-methylguanosine, which is later converted into the 5′-2,2,7-trimethylguanosine (TMG) cap, thereby resembling snRNA maturation [22]. Interestingly, the 3′-processing mechanism of S. cerevisiae may be a notable exception within the fungi kingdom. First discovered in a fission yeast species Schizosaccharomyces pombe [49], the spliceosomal cleavage reaction was shown to be an alternative pathway for telomerase RNA maturation in filamentous fungi (Neurospora crassa [50] and different Aspergillus species [51]). Even within the budding yeast clade, telomerase RNAs from distantly related branches were found to contain conserved intronic elements downstream of the mature 3′ end positions [52,53,54], and the mutational analysis of telomerase RNA (TER) from Hansenula polymorpha confirms the importance of these sequences for the RNA accumulation [53]. Although there is no experimental evidence to support this supposition, the newly synthesized TLC1 is most likely bound by the cap-binding complex (CBC) and transcription–export complex 1 (TREX-1), as is the case for other m7G-capped RNAs [55,56]. These complexes are thought to provide assistance during the early steps of TLC1 maturation, including the recruitment of the Xpo1 exportin. Data suggest that TLC1 cytoplasmic export is entirely dependent on Xpo1 [23,57]. However, the export receptor heterodimer Mex67-Mtr2 likely serves as an adaptor during export and a stabilizer of RNA, as in mex67-5 mutants cells, TLC1 is rapidly degraded by the nuclear exosome [23,58]. After its exportation to the cytoplasm, the Sm7 heptameric ring is assembled around the sequence near the 3′ end of TLC1 [55]. Contrary to the earlier proposal [57], the Sm complex is not required to ensure RNA stability immediately after transcription, thus allowing TLC1 molecules with mutations within the Sm site to reach the cytoplasm in an intact form [23]. Slight variations in 3′ end protection mechanisms exist among fungi; for instance, only the precursor form of S. pombe telomerase RNA (TER1) is bound by the Sm7 complex, and its substitution by a Lsm2-8 heptameric ring is required for the stability of the mature RNA [59]. In addition, the evolutionarily conserved Lar7 protein (also known as Pof8) is important for the stabilization of the binding of the Lsm protein to TER1 [60]. Thc1 and Bmc1 work cooperatively with Lar7 to recognize correctly folded TER1 and promote the recruitment of the Lsm2-8 heptamer [61,62]. We should note that fission yeasts highly diverged from budding yeasts [63], particularly in the context of telomere protection, as discussed below. In the absence of any Est proteins, S. cerevisiae telomerase RNA accumulates in the cytoplasm, indicating that the assembly of the active RNP takes place in the cytoplasm and is required for re-import into the nucleus [57]. However, these data are not inconsistent with the binding of (at least one of) the Est proteins in the nucleus; thus, the exact timing of the addition of each Est protein is unclear [55]. A study conducted by Tucey and Lundblad [37] revealed a complex regulated process, with the Est3 subunit acting as a switch controlling the assembly/disassembly pathways of RNP. Est2 and Est1 can directly bind specific regions of telomerase RNA [24,25,26,64], and the accumulation of the Est1–TLC1–Est2 subcomplex can be detected early in the cell cycle [37]. The existence of the complete telomerase complex containing all three Est subunits appears to be transient, as closer to the end of the cell cycle, the Est1–TLC1–Est3 subcomplex accumulates [37]. The dissociation of Est2 in the G2/M phases may be explained by its interaction with another protein. PinX1 protein, which is reported to be an Est2 arrest factor in the nucleolus, fits this role [65]. Experiments with alternative budding yeast systems underscore the additional complexities within the suggested models of telomerase assembly. Perhaps the most prominent example is the absence of EST1 genes from the genomes of Candida parapsilosis and Lodderomyces elongisporus and the increased size of their EST3 open reading frames (ORFs), which were shown to play an important role in the interaction between Est3 and Est2 [66]. On the other hand, there are Candida albicans and H. polymorpha, which are apparently completely dependent on the Est1–TLC1 interaction during the prior binding of Est3 (thus suggesting an inability to form the Est1–TER–Est2 subcomplex) [67,68]. In addition, the loss of either Est1 or Est3 leads to the strong destabilization of the telomerase RNP and the degradation of the catalytic subunit in H. polymorpha [68]. Deciphering which of the described inconsistencies reflect different sides of the same process or the evolutionary plasticity of the telomerase assembly mechanisms could be an interesting challenge for future studies. The additional stabilization of the ‘Est-bound’ telomerase RNA was found to require the binding of Pop proteins to the CS2a/TeSS domain of TLC1. In their absence (in pop1 and pop6 mutants), Est1–TLC1 binding is reduced, and telomerase RNA accumulates in the cytoplasm [40,41,69]. As one of the essential RNA-processing machineries, Pop proteins are present in most organisms, and elements similar to the CS2a/TeSS of TLC1 can be discerned in telomerase RNAs from many yeasts (including S. pombe and H. polymorpha [39]). It has yet to be determined whether Pop proteins also interact with Est3 and influence its association with the telomerase complex. This may represent an important topic to study. In contrast, the binding of another telomerase subunit—the yKu70/80 heterodimer—may be specific to S. cerevisiae and its close relatives [53,54,70]. Consistent with this idea, a stable association between yKu70/80 and TER (TLC1 orthologue) in an RNA co-immunoprecipitation experiment was not observed in H. polymorpha [71]. This may be reflected by the fact that even in S. cerevisiae, the role of the yKu70/80–TLC1 interaction is relatively minor, and it seems to play a secondary role in telomerase recruitment to telomeres compared to the major Cdc13–Est1 pathway [35]. However, the binding of Ku to TLC1 may be important for the robust import of the telomerase RNP into the nucleus, as TLC1 molecules accumulate in the cytoplasm in the ∆yku70 mutant [57]. Irrespective of the exact composition and conformation of the telomerase RNP, the importin Mtr10 and karyopherins Kap122 and Cse1 were implicated in the nuclear import of telomerase [57,69,72]. However, their importance is debatable, since the mtr10 knock-out strain has a pleiotropic phenotype and low TLC1 levels [72], and the effect of ∆kap122 mutation was found to be minor in another study [23]. The final step of telomerase maturation is the addition of a TMG cap at the 5′ end of TLC1 and the 3′ end’s trimming by the exosome, which most likely happen in the nucleolus after the import into the nucleus of the fully assembled telomerase complex [23,69]. Finally, it is worth mentioning that the existing data are not inconsistent with the repeated shuttling of telomerase between the nucleus and the cytoplasm; this possibility was discussed by Bartle et al. in 2021 [55]. In Figure 2, we compiled a general scheme of the telomerase complex’s biogenesis in budding yeast. Budding yeast telomeres are protected by a telomere chromatin structure called telosome (Figure 2), which is distinct from the structure found in metazoans and fission yeast. Fission yeast protects telomeres using orthologues of vertebrate telomeric proteins [73,74], which are discussed below. The major telosome protein is repressor/activator protein 1 (Rap1) [75]. Rap1 binds to telomeric double-stranded DNA, as well as Rif1 and Rif2 proteins (Rap1-interacting factors 1 and 2), which negatively regulate telomere length [76,77]. Rif1 and Rif2 also compete with the Sir2, Sir3, and Sir4 proteins for association with Rap1. Sir2/Sir3/Sir4 mediate gene silencing at the telomere [78,79]. Additionally, a telomere-specific RPA-like complex, which contains Cdc13/Stn1/Ten1 (the CST complex), binds to telomeric single-stranded DNA [80]. Hrq1 and Pif1 helicases can also bind to telomeres and play a dual role in telomere length homeostasis [81,82]. On the one hand, they can remove telomere structures such as G-quadruplexes, thereby promoting telomerase recruitment [83]. On the other hand, they can unwind the DNA–RNA hybrid formed by the 3′ end of telomeres and TLC1, thereby inhibiting telomere elongation [84,85]. Telomerase recruitment to telomeres in budding yeast occurs via two different mechanisms: the Sir4–yKu80 interaction, which mostly occurs in the G1 phase of the cell cycle, and the Cdc13–Est1 interaction, which is the prevailing recruitment pathway during the late S phase, when telomere elongation takes place [86]. Disrupting the Sir4–yKu80 pathway results in only mild telomere shortening, highlighting the critical role of the Cdc13–Est1 interaction during S phase as the primary functional pathway for telomerase recruitment [35,87]. Telomerase function is also limited by telomere length, as telomerase preferentially targets short telomeres [88]. The preference for short telomeres is mediated by the Rap1-interacting partners Rif1 and Rif2. Together, they form a negative feedback loop that regulates telomere elongation in a length-dependent manner [89,90]. The Rap1/Rif1/Rif2 regulatory mechanism relies on the number of Rif proteins associated with a telomere as an indicator of individual telomere length. Thus, only telomeres with low concentrations of Rif1 and Rif2 will be elongated. Late S phase telomeres have a notable characteristic that distinguishes them from G1 and G2 chromosome ends, namely, the formation of detectable 3′ single-stranded telomeric overhangs [91]. The formation of telomeric overhangs requires 5′ end processing in late S phase after the passage of the replication fork [92]. This process is largely reliant on the Mre11–Rad50–Xrs2 (MRX) complex with the assistance of the Sae2 protein [93,94]. However, the MRX complex may also play a structural role in telosome maintenance [95]. The checkpoint kinase Tel1 preferentially localizes to short telomeres and also mediates telomerase’s preference for short telomeres [96,97]. The balance between Tel1 and Rif2 activities determines the extent of telomere processing via the MRX complex [98]. On the one hand, Tel1 enhances MRX-dependent 5′ telomere processing, while Rif2, on the other hand, inhibits MRX activity [98,99,100]. The mechanism of counting Rif proteins, which ultimately targets telomerase to short telomeres, relies on an elaborate network of physical and functional interactions between the Rif1 and Rif2 proteins, Tel1, and the MRX complex. There is some evidence that Cdc13 is phosphorylated by Tel1 and Mec1 checkpoint kinases (orthologues of ATM in metazoans) to promote the Cdc13–Est1 interaction in the S phase [101,102]. In turn, the action of PP2A phosphatase and Aurora kinase on Cdc13 limits telomere elongation during the G2/M phases [102]. Interestingly, fission yeast orthologues of ATM and ATR also promote the recruitment of telomerase to telomeres [103]. The Cdc13–Est1 interaction permits telomerase recruitment, while the CST complex prohibits it to prevent the excessive elongation of telomeres [104]. The switch between these two complexes might serve as an additional regulatory mechanism of telomerase’s function with respect to telomeres. Thus, post-translational modifications of telomeric proteins also play an important role in the recruitment of yeast telomerase to telomeres. Some other modifications are briefly discussed in [105]. Despite several decades of investigation into yeast telomerase, only one PTM of a telomerase subunit has been studied (in the context of telomerase function): the ubiquitination of the Est1 protein from S. cerevisiae. The amount of Est1 is regulated during the cell cycle (with a peak in S phase), and proteasomal degradation is considered to be responsible for this [106,107,108]. In the related studies, the addition of ubiquitin by the Ufd4 E3 Ub ligase was detected, while the while the cdc48-3 mutation (a component of a complex targeting proteins to the proteasome) and the ufd4 deletion increased the amount of Est1; this affected telomerase assembly and telomere homeostasis [43]. The possibility of Est3’s phosphorylation was suggested by Tuzon et al. [109]. However, which residue could be modified, and by which kinase, and the potential functional consequences of such a modification were not identified. Several papers have reported the PTM of the yKu70/80 heterodimer with small ubiquitin-like modifiers (SUMO) or through yKu70/80 SUMOylation. Three SUMO E3 ligases (Mms21, Siz1, and Siz2) were implicated in the modification of the C-terminus of yKu70 [110,111,112], while it was also determined that Siz2 can also modify yKu80 [111]. Although the disruption of yKu70/80 SUMOylation leads to significant changes in telomere length, these changes were not linked to problems with the telomerase assembly process. Defects in telomere silencing and anchoring were also described; however, the effects caused by mutations in SUMO E3 enzymes are difficult to interpret, as multiple proteins are affected by SUMOylation (including several telomeric proteins [113]). Finally, the phosphorylation of the Ser623 residue of yKu80 by the Pho85 kinase was discovered, but telomere maintenance does not seem to be perturbed by the yku80S623A mutation [114]. Notably, a number of post-translational modifications in telomerase proteins were identified during several genome-wide screenings [115,116,117]. Although the existence of these PTMs must be carefully confirmed, it would be interesting to study their potential involvement in telomere maintenance. Considering the crucial roles PTMs play in the control of diverse cellular processes and the fact that, so far, only one has been implicated in telomerase biogenesis, it is likely that some of the mentioned (or yet unidentified) modifications will be found to regulate the assembly of the yeast telomerase holoenzyme. The biogenesis of the vertebrate telomerase complex has been most extensively studied in humans, which is largely due to the medical significance of the appropriate functioning of telomerase. Therefore, the results obtained primarily from human cells will be considered further. One well-known, rare hereditary disease associated with the downregulation of telomerase activity is dyskeratosis congenita (DC) [118]. The disruption of the functioning of the protein dyskerin (DKC1) leads to a decrease in the content of telomerase in cells and the shortening of telomeres. Point mutations in dyskerin lead to the formation of an X-linked form of DC [119], in which a drop in telomerase level is accompanied by defects in actively proliferating tissues, bone marrow, lungs, and skin. Autosomal dominant forms of DC [120] have been observed with mutations in telomerase reverse transcriptase, telomerase RNA [121], and telomeric protein TIN2 [122]. These diseases indicate a direct and important link between the pathophysiology of DC and telomere shortening. Human telomerase RNA (hTR) and human TERT (hTERT) are sufficient for the generation of telomerase activity in vitro in rabbit reticulocyte lysate, which provides accessory proteins for the assembly of the telomerase complex [20,21]. However, the effective functioning of the telomerase complex in vivo requires many additional proteins [123]. Thus, we briefly consider the secondary structure of telomerase RNA and the domain organization of telomerase reverse transcriptase (Figure 3A,B). For more details on the structure of the human telomerase holoenzyme (Figure 3C), the reader may refer to a recent review [124]. Phylogenetic comparison of telomerase RNAs among vertebrates has identified several conserved regions, including a pseudoknot, CR4/5 domain, and H/ACA domain [125]. Other important elements include the template and template boundary element (TBE) (Figure 3A). In most organisms, including vertebrates, TERT contains four domains: the telomerase essential N-terminal domain (TEN), telomerase RNA-binding domain (TRBD), reverse transcriptase domain (RT), and the C-terminal extension domain (CTE) [126] (Figure 3B). The amino acid linker between the TRBD and TEN domains is a low-complexity proline/arginine/glycine-rich region that may promote TERT dimerization or may be a site of protease cleavage in human cells [127] (Figure 3B, shown in gray). Human telomerase RNA is synthesized by RNA polymerase II in the form of a precursor elongated at the 3′ end [128,129,130] and monomethylated at the 5′ cap [131]. After numerous stages of processing, human telomerase RNA turns into a mature form consisting of 451 nucleotides, which makes up about 70% of the total hTR in a human cell [132]. Mature hTR differs in many ways from processed mRNA, which is also transcribed by RNA polymerase II. For example, mature telomerase RNA does not have a poly(A) tail [133] and also contains a trimethylated 5′ cap [131]. Several studies have demonstrated the presence of different forms of immature hTR; however, establishing their biological role requires further study [132,134]. It was demonstrated that a primary transcript of hTR elongated at the 3′ end primary region is transported into the cytoplasm [135] and translated into a protein named hTERP (human Telomerase RNA Protein) [136]. hTERP protects cells from apoptosis and regulates autophagy through the modulation of the activity of AMPK and TSC2 kinases [137]. Moreover, another study recently revealed the import of hTR in mitochondria where it is processed into a TERC-53 product, which is then re-exported into the cytoplasm [138]. The level of TERC-53 in the cytoplasm responds to mitochondrial function and plays a regulatory role in cellular senescence [139]. Near the 5′ end of the hTR transcript is a series of guanosines forming a G-quadruplex that protects hTR from degradation at the beginning of transcription [140]. The DHX36 RNA helicase (also known as RHAU) binds and resolves the G-quadruplex, which contributes to the correct folding of telomerase RNA and the formation of the P1 helix in the template boundary element (TBE) [141,142] (Figure 3A). In subsequent work, it was demonstrated that the heterogeneous nuclear ribonucleoproteins F, H1, and H2 (hnRNP F/H complex), which regulate alternative splicing by binding G-rich RNA sequences [143,144], also interact with the G-rich region at the 5′ end of hTR [145]. hnRNP F/H is assumed to contribute to TBE stabilization due to the preferential binding of the G-rich region without the folding of the G-quadruplex [145]. Mediator and Integrator are multi-subunit complexes that serve as links between specific transcription factors and RNA polymerase II bound to common transcription factors. Mediator and Integrator coordinate effective transcription by RNA polymerase II [146,147]. Mediator is necessary for the formation of a pre-initiation complex for the transcription of most mRNAs [146]. In turn, the Integrator complex is responsible for regulating the transcription of non-coding RNAs [147]. Recent work has shown that the termination of the transcription of the hTR occurs with the assistance of the Integrator complex [148]. The depletion of Integrator subunits results in the accumulation of elongated hTR transcripts. Elongated hTR transcripts are processed into a mature form, degraded in a competing manner, or carry out alternative functions [133,136,138,148]. The hTR-processing steps were discussed in further detail in a recent review [149]. Biogenesis and hTR accumulation do not require the participation of hTERT [150]. The correct processing of telomerase RNA requires the presence of an H/ACA motif. The H/ACA motif has a conservative secondary structure that consists of two hairpins separated by a single-stranded H box with a consensus sequence 5′-ANANNA-3′, where N represents any nucleotide. The structure ends with a single-stranded 3′ tail that includes three ACA nucleotides [129]. Small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs (scaRNAs) harbor an H/ACA motif. These families of small RNAs are mainly involved in the modification of ribosomal RNAs (by snoRNAs) and small nuclear RNAs (by scaRNAs), wherein the specific sites for the conversion of uridine to pseudouridine are identified [151]. To date, no telomerase RNA target for pseudouridylation has been identified. The distinguishing feature of hTR, as compared to other H/ACA RNAs, is the presence of P6.1 and P6b helices [152] located on the 5′ hairpin within the conservative CR 4/5 region. Additionally, hTR contains a BIO box on the 3′ hairpin, which is unique with respect to other human H/ACA RNAs. The BIO box assists in the assembly of the telomerase RNP [153]. The 3′ hairpin of hTR also includes a Cajal body box, which is referred to as a CAB box [154] (Figure 3A). In yeast, H/ACA snoRNAs are transcribed as separate RNA molecules by RNA polymerase II and processed from synthesized precursors [155]. In ciliates, telomerase RNA is also expressed independently, but by RNA polymerase III [156]. Interestingly, in humans, H/ACA snoRNAs and scaRNAs are usually produced as processing products of spliced introns from mRNA [157]. Therefore, the biogenesis of telomerase RNA is distinct from the majority of human RNAs that carry the H/ACA motif. If hTR is transcribed by RNA polymerase III or if the H/ACA domain of hTR is transcribed within the intron of mRNA by RNA polymerase II, only the 3′ end of the RNA molecules carrying the H/ACA motif can be detected [129,134]. In contrast with other human H/ACA RNAs, processing in the 5′–3′ direction must be suppressed in order to preserve the pseudoknot and the template region. The H/ACA motif is involved in the formation of a ribonucleoprotein complex with the proteins dyskerin, NHP2, NOP10, and GAR1 (H/ACA proteins) in all snoRNAs and scaRNAs of vertebrates [158,159]. Dyskerin, NHP2, and NOP10 were identified by telomerase immunoprecipitation followed by mass spectrometry [160]. Each H/ACA hairpin of telomerase RNA binds protein complexes consisting of dyskerin, NHP2, NOP10, and GAR1 [123]. Dyskerin, NHP2, and NOP10 have RNA-binding activity; GAR1 is attracted through protein–protein interactions only [124]. However, these proteins are not capable of the independent formation of a complex with an H/ACA motif in vivo without auxiliary proteins [161,162]. The assembly of the telomerase complex mediated by the H/ACA motif proceeds as follows. First, the assembly factor SHQ1 binds to dyskerin in the cytoplasm and stabilizes it, presumably preventing non-specific binding to RNA and non-specific pseudouridinylation [163,164]. The dyskerin–SHQ1 complex is then imported into the nucleus via the nuclear localization signal on the dyskerin. After its import into the nucleus, SHQ1 is separated from dyskerin by the R2TP chaperone complex consisting of the target-recognizing proteins PIH1D1, RPAP3, and the AAA+ ATPases RUVBL1 and RUVBL2 (also known as pontin and reptin) [162]. The assembly of the H/ACA complex may be facilitated by the NUFIP protein, which binds NHP2 and interacts with PIH1D1 [165]. The disruption of the activity of any of these assembly factors leads to accumulation disorders of the mature telomerase RNA in vivo [162,166]. The binding of dyskerin to telomerase RNA occurs during transcription in order to ensure the proper processing of telomerase RNA [167,168]. Chaperones place two tetramers [123], each of which consists of dyskerin, NHP2, NOP10, and the assembly factor NAF1; the latter is later replaced by structurally similar GAR1 [167,169] through an unknown mechanism speculated to involve the SMN protein [167]. Replacement occurs before the transportation of the H/ACA ribonucleoprotein into Cajal bodies or nucleoli, as NAF1 is only found in the nucleoplasm and thus not in Cajal bodies or nucleoli [161,167]. NAF1 may be recruited to the C-terminal domain of RNA polymerase II, thus promoting snoRNP assembly [170]. The mechanism of the tetramers’ assembly and R2TP complex recruitment remains unclear. Experiments involving the mutagenesis of the 3′ and 5′ hairpins in H/ACA snoRNA and the cryo-electron microscopic (cryo-EM) structure of human telomerase indicate that the first dyskerin, NHP2, NOP10, and NAF1 tetramer binds to the 3′ hairpin during the assembly of the H/ACA ribonucleoprotein complex. This initial binding allows for the second tetramer to assemble on the 5′ hairpin [123,124]. The proteins dyskerin, NHP2, NOP10, and NAF1 are necessary for the stability of telomerase RNA and other H/ACA RNAs in vivo [171,172,173,174]. Despite the fact that GAR1 is a stoichiometric partner for the binding of snoRNAs with the H/ACA motif, it is not necessary for their stability in vivo [172]. GAR1 may be less associated with the telomerase complex compared to dyskerin, NHP2, and NOP10, according to the results of immunoprecipitation [160]. This is consistent with the model of NAF1 replacement by GAR1 at later stages of telomerase assembly. The interaction between H/ACA tetramers (dyskerin/NHP2/NOP10/GAR1) in the structure of the human telomerase complex explains why mutations in the case of DC lead to a disruption in the maintenance of telomere length and not defects in the biogenesis of spliceosomal and ribosomal RNPs [175]. DC mutations disrupt the interaction between H/ACA tetramers, which leads to the incorrect assembly of the H/ACA ribonucleoprotein on the 5′ H/ACA hairpin of telomerase RNA. hTR has a shortened version of the 5′ hairpin compared to snoRNA and scaRNA, which leads to poor H/ACA tetramer binding due to RNA–protein interactions alone [124]. Posttranslational modifications also affect the biogenesis of H/ACA ribonucleoproteins. It has been proposed that the poly-ADP-ribosylation (PARylation) of dyskerin and GAR1 affects their ability to bind to RNA and form a telomerase complex [176]. In addition, numerous studies have revealed that dyskerin, GAR1, NHP2, NAF1, and R2TP chaperone proteins (RPAP3, pontin, and reptin) undergo modifications with small ubiquitin-like modifiers (SUMO) [177,178,179,180,181]. The covalent posttranslational modification of SUMO, termed SUMOylation, is involved in a variety of processes in the cell [182]. Recent work has revealed several SUMOylation sites in the lysine-rich region of the nuclear/nucleolar localization signal at the C-terminus of dyskerin, the most important of which is K467. The replacement of K467R leads to a loss of localization of dyskerin in the nucleolus and a drop in telomerase activity in vitro [183]. In addition, GAR1 contains a hydrophobic motif that interacts with SUMO and promotes the effective binding of dyskerin to GAR1 [183]. It has been proposed that dyskerin dissolves in the dense fibrillar component of the nucleolus due to the motif in GAR1 interacting with SUMO, which recognizes this modification on dyskerin [183]. Interestingly, recent work has shown that one-third of the dyskerin molecules are statically associated with the nucleolus [184]. We speculate that this might be related to dyskerin SUMOylation. Surprisingly, the functioning of reptin and pontin is also regulated by SUMOylation [185,186]. The role of SUMOylation in the functioning of the assembly factors and components of the telomerase complex has yet to be properly assessed. In addition to SUMOylation, the single-strand selective monofunctional uracil DNA glycosylase 1 (SMUG1) is involved in the nucleolar localization of dyskerin [187]. Mouse embryonic fibroblasts with SMUG1 homozygous knockout exhibit the mislocalization of dyskerin [188]. Quantitative phosphoproteomics has shown that H/ACA proteins, dyskerin, GAR1, NHP2, NOP10, and NAF1 change their phosphorylation status during the cell cycle [189], which may also affect telomerase biogenesis and its functioning. The difference between scaRNAs and snoRNAs is the presence of a conservative sequence of four nucleotides, namely, a CAB-box necessary for localization in Cajal bodies [154]. Cajal bodies are dynamic and membraneless organelles found in the nucleus of eukaryotic cells. Cajal bodies are involved in the maturation and processing of ribonucleoproteins, including small nuclear RNPs (snRNPs) and small Cajal-body-specific RNPs (scaRNPs) [190]. Telomerase RNA contains sequences of H/ACA and CAB boxes and is localized in Cajal bodies, as well as scaRNAs, only after the processing and attachment of H/ACA proteins, according to the results of in situ hybridization [134,191,192]. The co-purification of dyskerin complexes from tumor cell lines allowed the detection of the protein TCAB1 (also known as WDR79 or WRAP53), which is associated with telomerase [193]. TCAB1 stably binds scaRNAs but not snoRNAs. This protein is localized in Cajal bodies but not in nucleoli. The first studies showed that TCAB1 knockdown leads to the localization of telomerase RNA outside Cajal bodies, presumably in nucleoli, and ineffective telomere elongation without a drop in telomerase activity in vitro [193,194]; recently, this finding was confirmed [184]. However, later studies have shown that TCAB1 knockout also leads to a drop in telomerase activity in vitro in cancer and embryonic stem cells without a consistent change in hTR accumulation [195,196]. TCAB1 is proposed to mediate the correct folding of the distant P6b and P6.1 loops of telomerase RNA, thereby enabling the effective interaction of the CR4/5 domain and hTERT and moderately stimulating telomerase activity in vitro [196]. Cryo-EM enabled the establishment of the fact that TCAB1 is a stable subunit of the telomerase holoenzyme [197]. Chaperone TRiC is required for TCAB1 folding and correct telomerase assembly [198]. TCAB1 is released from hTR in mitotic cells coincident with TCAB1 delocalization from Cajal bodies. At the same time, the total hTR level, the total TCAB1 protein level, and the telomerase activity in vitro remains consistent across the cell cycle, suggesting that TCAB1 may allow the telomerase holoenzyme to elongate telomeres [199]. hTERT interacts with the CR4/5 domain and the pseudoknot/template domain of hTR through the TRBD domain. In addition, TEN domains also shape the pseudoknot/template domain to stabilize the RNA–DNA duplex at the template’s 3′ end [200]. It has been proposed that the assembly of the hTERT–hTR complex occurs with the assistance of the chaperone Hsp90 [201,202], which is involved in the regulation of the cell cycle, the maintenance of the integrity of chromosomes, and other signaling pathways [203]. The p23 protein forms a complex with Hsp90. The suppression of p23’s functioning leads to the downregulation of telomerase activity in vitro [204,205]. The inhibition of Hsp90 by geldamycin lowers the content of the active telomerase complex and causes the degradation of hTERT in the proteasome. The immunoprecipitation of Hsp90 and p23 leads to the enrichment of active telomerase, which indicates their interaction with a mature telomerase complex [206]. The treatment of cells with geldanamycin also leads to a loss of NHP2 protein, indicating the involvement of Hsp90 in NHP2 stabilization [165]. However, the interpretation of the effect of Hsp90 is difficult, since the disruption of one of the key chaperones in the cell can have an indirect effect. Another protein, AAA-ATPase NVL2, may also act as an hTERT chaperon. NVL2 interacts and co-localizes with hTERT in the nucleolus. NVL2 depletion decreases hTERT levels and telomerase activity in vitro [207]. In addition, it has been shown that the expression of the dominant-negative form of the snRNP assembly factor survival of motor neuron (SMN) disrupts the localization of hTERT in vivo and telomerase activity in vitro [208]. SMN may play a role in the assembly of a catalytically active telomerase complex [208] since SMN associates with GAR1 in vivo [209,210]. The SMN complex is concentrated in nuclear bodies, where it may promote NAF1–GAR1 exchange. Interestingly, the localizations of hTR and hTERT only overlap at telomeres for most of the cell cycle [199]. Unlike hTR, hTERT tends to localize in parts of the nucleus other than Cajal bodies, especially in the nucleoli in cancer cells [191,211]. While the PinX1 protein may facilitate the nuclear localization of hTERT, this has only been observed in the context of overexpression [212]. However, a recent article has argued that endogenous, tagged hTERT is excluded from nucleoli [184]. There are currently several models of hTR and hTERT assembly. The first model suggests that this assembly occurs through the interaction of hTR-bearing Cajal bodies and hTERT-bearing nucleoli. As in the S phase of the cell cycle, the concentration of hTERT shifts from the nucleoplasm to the nucleoli [213,214], and Cajal bodies are assumed to move to the periphery of the nucleoli, carrying telomerase RNA with them [214]. The second model suggests that assembly occurs in nucleoli. It has been shown that hTERT can localize in the nucleoli and may bind to RNP in the nucleolar dense fibrillar component [215,216], while continuing to interact with nucleolin [216,217], until the mature complex is attracted to Cajal bodies by TCAB1 [216]. However, the active role of nucleoli in telomerase assembly is disputable [218]. The third model suggests that assembly occurs in Cajal bodies. According to structured illumination microscopy, hTR is located on the periphery of Cajal bodies. This suggests that hTERT may gather telomerase RNA at the exit from Cajal bodies [219]. In principle, the results obtained do not contradict the possibility that assembly may occur simply in the nucleoplasm without the participation of special nuclear compartments. Despite numerous experiments that have been conducted to determine its localization, the exact location of hTERT–hTR assembly in the nucleus remains elusive. This can be partly explained by the limitations of the methods used. For example, it has been observed that the N-terminal tagging of hTERT affects its functioning in cells [220]; alternatively, the cause could be hTERT overexpression. Another important issue is the liquid–liquid phase separation during the formation of various nuclear bodies involved in telomerase biogenesis. This topic is discussed in further detail below. Recent advances in cryo-electron microscopy have revealed that the H2A and H2B histone dimer is also a telomerase subunit [197]. Interestingly, H2A–H2B binds to the P6.1 stem in the catalytic lobe of telomerase and not in the H/ACA lobe [197]. The P6.1 stem in the CR4/5 domain is highly conserved among mammals [152]. Histones are also highly conserved proteins [221]. Therefore, it can be anticipated that the H2A–H2B dimer is part of the telomerase complex in other mammals, possibly contributing to the correct folding of the CR4/5 domain. Currently, there are no data confirming the stage at which the H2A–H2B dimer joins the telomerase complex. However, we can assume that this happens after hTERT–hTR assembly due to hTR folding. Further studies should reveal the role of this dimer with respect to the functioning of telomerase. The hypermethylation of the telomerase RNA 5′ cap by trimethylguanosine synthase 1, TGS1, also plays an important role in telomerase trafficking and recruitment. Two differentially distributed isoforms of TGS1 have been found [222]. Besides Cajal bodies, the full-length isoform may localize in the cytoplasm, whereas the shorter isoform is located solely in Cajal bodies and associates with components of box C/D and H/ACA snoRNPs [222]. Interestingly, treatment with an inhibitor of TGS1, sinefungin, significantly reduced the number of Cajal bodies in cancer cells and tumor organoids [223]. Upon TGS1 knockout, the number of Cajal bodies also reduced, and scaRNAs tended to be mislocalized in nucleoli [131]. Meanwhile, hTR fluorescence in situ hybridization (FISH) combined with anti-TRF2 immunofluorescence revealed a significantly reduced degree of recruitment of telomerase RNA to chromosome ends upon TGS1 knockdown [223]. The removal of TGS1 also led to the accumulation of telomerase RNA in the cytoplasm. In addition, the total amount of hTR increased without changing the content of unprocessed forms of telomerase RNA [131]. Therefore, the TGS1-mediated hypermethylation of the hTR 5′ cap may, in principle, limit telomere elongation. Recent work proposes that the 2,2,7-trimethylguanosine capping of human telomerase RNA by TGS1 is required for direct telomerase-dependent telomere maintenance, although 2,2,7-TMG capping itself is dispensable with respect to telomerase activity in vitro [223]. The trafficking of the telomerase complex is the most controversial aspect of its biogenesis. The main issue is how subnuclear compartmentalization affects the maturation of the hTR and telomerase complex. Currently, all works are focused on revealing the roles of Cajal bodies and nucleoli in this process. FISH of 3′-extended telomerase RNA suggests that at least part of hTR 3′ end processing takes place in the nucleolus [224]. At the same time, the interaction of hTR with TCAB1 leads to the concentration of telomerase RNPs in Cajal bodies [193,194,219]. A loss of TCAB1 leads to the nucleolar accumulation of hTR [184]. A notable finding from crosslinking studies of the interactions between coilin, the main component of Cajal bodies, and RNA is that all snoRNAs may migrate through Cajal bodies to the nucleolus, while scaRNAs are uniquely retained therein [225]. The transport of scaRNAs into Cajal bodies is carried out by the PHAX factor. Presumably, m7G-capped telomerase RNA is also transported by PHAX since it is associated with hTR [226]. Nopp140, an intrinsically disordered Cajal body phosphoprotein, co-purifies with dyskerin, as does TCAB1 [193]. Nopp140 is required to recruit and retain all scaRNPs in Cajal bodies. Nopp140 plays an important role in the formation of Cajal bodies and the localization of scaRNAs and the telomerase RNA within them [227]. Nopp140 may also function as a transport factor between the nucleolus and Cajal bodies [228]. The trafficking of hTR to telomeres and Cajal bodies also depends on hTERT in cancer cells. The depletion of hTERT leads to a loss of hTR from both Cajal bodies and telomeres without a change in hTR levels [229]. At the same time, hTERT overexpression also leads to a reduction in the localization of MS2-tagged hTR in Cajal bodies [219]. Live-cell analysis of the diffusion coefficients of tagged hTERT revealed three separate populations of telomerase particles. There were two rapidly diffusing populations, which may represent unbound hTERT and diffusing telomerase RNPs, and a less mobile population that may represent telomerase RNPs bound to Cajal bodies or telomeres [230]. Interestingly, even in cells without hTR, 25–30% of hTERT particles were slowly diffusing or static [184]. All these results suggest that there could be structures other than Cajal bodies, nucleoli, or telomeres that retain hTERT to achieve optimal telomerase assembly. It is possible that the proline/arginine/glycine-rich region of hTERT is needed for this to occur. Retainment can be performed by other nuclear bodies, for example, nuclear speckles. Therefore, we would like to note that the current approach to considering the role of Cajal bodies and nucleoli in telomerase biogenesis has a number of limitations. Cajal bodies and nucleoli are not entirely separate structures but have complex relationships. They can sometimes overlap, as evidenced by electron microscopy and the co-localization of Cajal-body-related and nucleolar factors [231]. Cajal bodies need nucleoli to maintain their integrity, but not vice versa. This indicates that Cajal bodies may have an auxiliary function. In principle, the nucleoli can perform at least part of Cajal bodies′ functions, depending on the conditions. In our opinion, this explains a number of contradictions in the literature regarding their role in telomerase biogenesis. Additionally, in principle, other nuclear bodies might participate in human telomerase biogenesis in a less pronounced way. Post-transcriptional modifications may affect the functioning of telomerase RNA. Cytosines C106, C166, C323, and C455 have been identified as m5C sites in hTR [232,233]. It was shown that the RNA-binding protein HuR associates with hTR and promotes the methylation of C106 by an unknown methyltransferase. This modification can change the secondary structure of hTR, thus affecting the association of hTERT and hTR [233]. A subsequent study revealed that neural-specific HuB and HuD compete with HuR during hTR binding and antagonize HuR’s functions [234]. An initial study of hTR pseudouridinylation sites identified several candidate bases, including U159, U161, U179, U306, U307, U316, and U370. The pseudouridylation of U306 and U307 changes the conformation of the highly conserved P6.1 hairpin [235]. A large-scale search confirmed the occurrence of the significant pseudouridinylation of U307, as well as a less pronounced modification of U179 [236]. Later, a chemical-probing analysis helped to identify 18 pseudouridines in hTR [237]. It can be assumed that the pseudouridinylation of U307 may play a role in the correct folding of the CR4/5 domain and in its interaction with the histone dimer H2A–H2B. Telomerase RNA may carry other post-transcriptional modifications that affect the processing, transport, and assembly of the telomerase complex. There is indirect evidence that hTR has several modified bases between the CR4/CR5 domain and H box [188]. Currently, the functional role of hTR modifications remains poorly understood. hTERT is a limiting factor in the formation of an active telomerase complex. The estimated half-life of telomerase activity in vitro is no more than 24 h [238,239], which is less than 5 days of telomerase RNA’s half-life [150]. At the same time, the level of hTR remains constant during cell cycle progression [199,216]. Based on this, it can be assumed that the stability control of telomerase protein components, including hTERT, contributes to the regulation of telomerase. The expression of hTERT is actively regulated by different transcriptional factors and epigenetic modifications (reviewed in [240]). The hTERT promotor is often mutated in different types of cancers [241]. The hTERT gene consists of 16 exons and 15 introns. The full-length isoform of the 16 exons is only capable of elongating telomeres [242]. Twenty-two isoforms of hTERT mRNA have been identified [243]. The most studied alternative splice variants of hTERT encode proteins lacking catalytically active RT and are generated by the alternative splicing of the α and/or β sites. Skipping 36 nucleotides results in an α– isoform, whereas the β– isoform produced by 183-nucleotide deletion (exons 7 and 8) harbors a premature termination codon. The β– protein competes with full-length hTERT in binding to hTR, thereby inhibiting telomerase activity in vivo [242]. The same mechanism was proposed for the α– isoform [244]. Splicing may be directed by the action of RNA-binding proteins. The production of full-length hTERT transcripts is promoted by NOVA1, which enhances the inclusion of exons in the RT domain of hTERT [245]. A recent study proposed that the developmental control of telomerase activity in vivo is driven by the alternative splicing of hTERT exon 2. Protein SON promotes the skipping of exon 2, which triggers hTERT mRNA decay in differentiated cells [246]. hTERT must move from the cytoplasm to the nucleus after its synthesis to produce an active telomerase complex. The hTERT nuclear localization signal (NLS) includes two clusters of basic amino acids [247]. The nuclear localization of hTERT requires the classic nuclear import machinery involving importins α/β and Ran GTPase. Importin α binds to hTERT N-terminal’s nuclear localization signal, while its partner importin β1 interacts with a nuclear pore complex [248]. The Hsp90–FKBP52 complex also mediates hTERT nuclear import. Hsp90-binding immunophilins, FKBP51 and FKBP52 (also known as FKBP5 and FKBP4), engage in co-immunoprecipitation with hTERT [249]. The FKBP52 co-chaperone interacts with the hTERT–Hsp90 complex and promotes the nuclear transport of hTERT via a dynein/dynactin-dependent mechanism. The depletion of FKBP52 results in the cytoplasmic accumulation of hTERT and its ubiquitin-dependent proteolysis [250]. Interestingly, hTERT contains potential signals of nuclear import and export [251]. This indicates that the shuttling of hTERT between the nucleus and the cytoplasm may be one of the forms of telomerase regulation [247]. A number of works have revealed that hTERT is phosphorylated at different sites. Five putative phosphorylation sites have been reported: serine 227 [247], threonine 249 [252], serine 457 [253], tyrosine 707 [254], and serine 824 [255]. The phosphorylation of serine 227 is required for hTERT’s translocation in the nucleus [247,248]. The Akt-mediated phosphorylation of S227 increases hTERT′s affinity for importin-α and promotes the nuclear import of hTERT [248]. A recent study identified that hTERT is phosphorylated at threonine 249 during mitosis by the serine/threonine kinase CDK1. The phosphorylation of threonine 249 is necessary for hTERT-mediated RNA-dependent RNA polymerase activity but is not required for reverse transcriptase activity in vitro [252]. An analysis of clinical samples revealed that the phosphorylation of threonine 249 is associated with aggressive phenotypes in various types of cancer [256]. Dual-specificity tyrosine-(Y)-phosphorylation-Regulated Kinase 2 (Dyrk2) phosphorylates serine 457 of hTERT. The phosphorylated hTERT associates with the EDD–DDB1–VprBP E3 ligase complex for subsequent ubiquitin-mediated hTERT protein degradation. Dyrk2 interacts with hTERT during the G2/M phases [253], which could be the mechanism for the cell-cycle-dependent regulation of telomerase activity in vivo. Src kinase has been shown to regulate the nuclear export of hTERT under oxidative stress by phosphorylating tyrosine 707 [254,257]. In turn, protein tyrosine phosphatase Shp-2 counteracts Src kinase. Shp-2 promotes the retainment of hTERT in the nucleus via the downregulation of tyrosine 707’s phosphorylation [257]. It has been shown that the phosphorylation of hTERT serine 824 by Akt kinase and kinase C correlates with increased telomerase activity in vitro [255,258]. This is presumably due to the enhanced translocation of hTERT into the nucleus from the cytoplasm [255,258]. At the same time, hTERT modification by c-Abl kinase leads to a threefold decrease in telomerase activity in vitro. The knockout of c-Abl in a mouse model lead to increased telomerase activity in vitro and better telomere elongation [259]. Serine/threonine-protein phosphatase 2A (PP2A) is proposed to dephosphorylate hTERT and inhibit telomerase activity in vitro by accumulating hTERT in the cytoplasm [260]. The ubiquitination of hTERT plays a role in the regulation of telomerase activity in vivo by regulating its stability. It has been shown that E3-ubiquitin ligase MKRN1 interacts with hTERT in a yeast two-hybrid system. MKRN1 overexpression leads to the degradation of hTERT [261]. In addition, the effect of MKRN1 on telomerase activity during cell differentiation has been shown. The human leukemia cell line HL-60 expresses MKRN1 at a low level. However, with the induction of differentiation, expression increases significantly, which is combined with a significant decrease in telomerase activity in vitro [262]. Thus, the degradation of hTERT mediated by MKRN1 can provide a decrease in telomerase activity in vivo in differentiated cells when it becomes unnecessary. Another interesting observation is that lysophospholipid sphingosine 1-phosphate (S1P), which is generated by sphingosine kinase 2 (SK2), binds hTERT at the nuclear periphery in human and mouse fibroblasts. S1P binding inhibited the interaction of hTERT with MKRN1 [263]. E3 ubiquitin ligase MDM2 (HDM2) can interact with hTERT through multiple domains on both proteins. In this case, hTERT undergoes polyubiquitination and degradation by the proteasome. The removal of MDM2 leads to increased hTERT content in cells and increased telomerase activity in vitro [264]. Interestingly, the E2-ubiquitin-conjugating enzyme UBE2D3, which is one of the partners of MDM2, can also affect the ubiquitination of hTERT. The overexpression of UBE2D3 also leads to a lower level of hTERT protein and decreased telomerase activity in vitro and in vivo [265]. In another study, it was shown that the CHIP E3 ligase regulates the stability of hTERT in the cytoplasm. Interaction with CHIP leads to polyubiquitination, prevents the transfer of hTERT into the nucleus, and completes the proteolytic degradation of hTERT [266]. This interaction peaks during G2/M phases and decreases during S phase. At the same time, telomere elongation occurs. Thus, CHIP might modulate telomerase activity in vivo throughout the cell cycle by controlling the trafficking and stability of hTERT [266]. It has been proposed that the Plk1 protein is associated with telomerase and promotes the retention of hTERT in the nucleus, preventing its ubiquitination and degradation in the cytoplasm [267]. A recent study reported that hTERT is SUMOylated by SUMO1 at lysine 710. The polycomb protein CBX4 acts as the SUMO E3 ligase of hTERT. The SUMOylation of hTERT results in the upregulation of telomerase activity in vivo, which can be inhibited by the process of SENP3-mediated deSUMOylation. Interestingly, it has been discovered that hTERT SUMOylation plays a role in the repression of E-cadherin gene expression. This can lead to the activation of the epithelial–mesenchymal transition (EMT) in breast cancer cells [268]. There are many other examples of hTERT functions besides telomerase in the literature, including the regulation of gene expression or mitochondrial function and oxidative stress response (reviewed recently in [269]). Negative regulation of telomerase activity may occur due to the arrest of telomerase complex in the nucleolus when hTERT temporarily moves from the nucleoplasm to the nucleolus. It is assumed that this translocation reduces the likelihood of telomere formation at the ends of damaged DNA [213]. PIN2/TRF1-interacting telomerase inhibitor 1 (PinX1) can regulate telomerase activity by arresting hTERT. PinX1 has been shown to bind directly to the telomere protein TRF1 [270] as well as hTERT and telomerase RNA and inhibits telomerase activity in vitro [271] and in vivo upon overexpression [272,273]. However, the silencing of PinX1 leads to telomere shortening in telomerase-positive cancer cells of various origins [274,275], indicating its dual role in telomere length maintenance. Nucleophosmin (NPM) can partially attenuate the PinX1 inhibition of telomerase activity in vitro, and NPM loading to hTERT requires PinX1 [276]. hTERT/PinX1/NPM interaction peaks during telomere extension in S phase [277]. Human microspherule protein 2 (MCRS2) is also a negative regulator of telomerase activity in vitro and in vivo. MCRS2 binds to PinX1 and is colocalized with it in the nucleus and on telomeres. At the same time, its expression is limited to S phase, unlike PinX1. MCRS2 could be another partner of PinX1, which regulates its operation in S phase [278]. Despite active research, the exact functional role of the PinX1 protein remains elusive. hTERT expression is necessary for hTR localization in telomeres. Human telomerase mainly associates with telomeres solely during S phase [167,183,231]. Most enzymes meet the substrate by simple diffusion. However, it is estimated that telomerase and its telomere substrate have very low concentrations in a normal cell: approximately 250 telomerase holoenzymes per 184 telomeres during late S phase [252]. Therefore, a special mechanism may be required to recruit telomerase to telomeres. However, we note that the accurate mathematical modeling of the process of attracting telomerase to telomeres and their elongation is required. Therefore, low telomerase content does not indicate the presence of a special mechanism for the delivery of telomerase to telomeres. Initial in situ hybridization experiments demonstrated that Cajal bodies are in contact with some telomeres. These results led to the hypothesis that Cajal bodies move through the nucleoplasm and deliver telomerase RNA to telomeres in the S phase of the cell cycle [214,279]. The following studies showed that the loss of coilin, the structural protein of Cajal bodies, disrupts Cajal body formation and telomerase recruitment to telomeres [280,281]. A CAB box mutant of hTR fails to accumulate in Cajal bodies and forms an active telomerase complex, but is strongly inefficient with respect to telomere extension [282]. The overexpression of hTR and hTERT leads to the formation of new Cajal bodies on telomeres according to one study’s FISH results [281]. However, the results of several subsequent studies do not support the model wherein the delivery of the telomerase holoenzyme to telomeres is performed exclusively by Cajal bodies. First, it was shown that a minimal portion of telomerase RNA can be assembled without the H/ACA motif, and this portion can form an active telomerase that effectively elongates telomeres, thereby bypassing the assembly pathway through the H/ACA motif and Cajal bodies [195]. In addition, localization in Cajal bodies is not strictly necessary to maintain telomere length in all cells since the removal of coilin does not lead to the impairment of telomere elongation in cancer cells [195,283] but, instead, a modest increase in telomerase activity in vitro [196]. TCAB1/hTR foci are detected transiently during S phase at telomeres in the absence of coilin [283]. Even the earlier study supported the notion that TCAB1 can localize to telomeres in Cajal body-independent manner [280]. Surprisingly, the absence of telomerase in Cajal bodies due to the knockdown of Nopp140 leads to gradual telomere elongation in cancer cells [227]. Moreover, recent imaging data obtained from living cells have shown that no more than 10% of hTR is localized in Cajal bodies; the rest is distributed throughout the nucleoplasm [219]. Meanwhile, hTERT overexpression does not enhance the co-localization of the telomeric protein TRF1 with the Cajal body protein coilin. Despite this, hTR resides in Cajal bodies for a longer time than in normal diffusion [219]. Interestingly, telomerase trafficking in mice is reported to be Cajal-body-independent [284]. Numerous studies have demonstrated that human telomerase resides in Cajal bodies for a considerable proportion of its life cycle. However, the functional significance of this remains unclear. Perhaps the role of Cajal bodies is more pronounced with low telomerase expression in normal cells. This remains to be clarified, as most studies have been performed using cancer cell lines or in the context of telomerase overexpression. We speculate that the telomerase complex may diffuse between the nucleoli, Cajal bodies, and nucleoplasm. However, in normal conditions, the presence of TCAB1 shifts the balance in favor of Cajal bodies. Thus, Cajal bodies limit telomerase activity in vivo rather than promoting it by sheltering the assembled telomerase complex. In vertebrates, telomeres are protected by a special protein complex (shelterin), which consists of six proteins found in humans: TRF1, TRF2, TIN2, RAP1, POT1, and TPP1 [285,286] (Figure 4). Shelterin prevents the recognition of the ends of chromosomes as double-stranded DNA breaks [287]. TRF1 and TRF2 proteins directly bind double-stranded DNA as homodimers [288,289], while POT1 protein binds single-stranded DNA [290,291]. TPP1 interacts with both TIN2 and POT1 and promotes POT1–telomere binding [292]. TIN2 interacts with both TRF1 and TRF2 and tethers shelterin [286]. RAP1 binds to TRF2 and contributes to telomere protection [293]. To learn more about shelterin functioning, refer to a recent review [294]. The recruitment of human telomerase to telomeres requires the proteins TIN2 and TPP1 [281,295]. TPP1 interacts directly with the TEN domain of hTERT via a patch of amino acids known as the TEL patch [281,296]. In turn, TIN2 performs a critical bridging function that is necessary for telomerase recruitment [295]. It has been shown that the POT1–TPP1 complex enhances the processivity of the minimal telomerase complex in vitro by maintaining the association of the complex with the DNA product and during its translocation [297]. In addition, the POT1–TPP1 complex prevents the binding of the RPA protein to the 3′ telomere overhangs, thereby limiting the activation of the DNA damage response [219]. Notably, the CTC1/STN1/TEN1 complex, which comprises human orthologues of the yeast CST complex, can bind to the 3′ single-stranded telomere overhang and obstruct telomerase’s access to the telomere during the late S/G2 phases [298,299]. Recent cryo-EM results showed that CST forms a ring-like decameric DNA–protein supercomplex [300]. The single-stranded telomere overhang can invade the double-stranded telomere region to form a displacement loop (D-loop) and a telomere loop (T-loop). The T-loop’s formation is regulated by shelterin, and TRF2 plays a crucial role in this process [301]. T-loop restricts telomerase’s access to the single-stranded overhang [302,303]. RTEL1 helicase is a crucial component of telomere homeostasis, and mutations in RTEL1 cause a severe form of DC known as Hoyeraal–Hreidarsson syndrome [304], which is a hereditary disorder associated with severely shortened telomeres and diverse clinical symptoms. RTEL1 is recruited to shelterin by TRF1 and TRF2 [305,306,307]. RTEL1 is essential for the proper disassembly of T-loop and the unwinding of telomere G-quadruplexes during S phase [307,308,309]. RTEL1 was also shown to stabilize long, single-stranded telomere overhangs [310]. hTERT recruitment to telomeres during the S phase is dependent on the dissociation of TRF1 from the telomere, a process promoted by ATR/ATM kinases [311,312]. Phosphorylated TRF1 is subsequently directed to proteasomal degradation [313]. The dissociation of TRF1 releases the 3′ telomeric overhang from a protective T-loop with the assistance of RTEL1, allowing for telomere elongation via telomerase [314]. ATM was shown to collaborate with the MRE11–RAD50–NBS1 (MRN) complex to promote telomere elongation by the 5′ end processing of telomeres, thus resembling the yeast mechanism [315,316]. In summary, the recruitment of vertebrate telomerase to telomeres is also regulated by post-translational modifications of telomeric proteins. While there are other modifications of telomeric proteins, their addressal is beyond the scope of this review. Some of these modifications were reviewed in [105,317,318]. In Figure 4, we combine the current data and propose a model of human telomerase biogenesis. Telomerase biogenesis in both yeast and vertebrates involves similar stages and molecular agents, but there are notable differences. In vertebrates, the regulation of telomerase biogenesis is more complex and is accurately tuned by various signaling pathways and chromatin modifications [240]. In both yeast and vertebrates, the biogenesis of the telomerase complex involves transcription by RNAP II and the processing of the telomerase RNA [44,45,133]. Prior to being bound by telomerase reverse transcriptase, yeast and vertebrate telomerase RNAs recruit proteins that remain part of the active holoenzyme and are required for telomerase RNA stability in vivo. While yeast utilizes Sm or Lsm proteins for this purpose [55,59], vertebrates employ H/ACA proteins [167,168]. Yeast and vertebrate telomerase RNAs are first capped by MMG at the 5′ end and later converted into the TMG cap in the later stages of biogenesis [22]. In humans, hTERT isoforms exist due to alternative splicing that increases regulatory complexity [243]. Hsp90 and p23 chaperones associate with human TERT and promote telomerase assembly [202,205]. Yeast Hsp90 and p23 orthologues have been shown to promote telomerase activity in vitro and in vivo by increasing the DNA binding of telomerase [202,321,322]. Their functional role in telomerase assembly is yet to be assessed. Hsp90 and p23 orthologues likely have a direct influence on telomere extension by telomerase in yeast, while in vertebrates, these chaperones mainly specialize in telomerase assembly. Interestingly, both yeast and vertebrates control the assembly of the telomerase complex through compartmentalization, but in different ways. Yeasts most likely rely on the export of telomerase RNA to the cytoplasm and its subsequent assembly therein [57]. In vertebrates, nuclear bodies most likely play a decisive role [214,215,219]. The activity of the telomerase complex seems to be regulated more directly in yeast than in vertebrates by the process of assembly–disassembly. In yeast, Est1 is degraded in the G1 phase [106,107,108], and Est2 dissociates in G2/M phases [37], limiting telomerase assembly. Alternatively, telomerase activity in vitro does not change significantly throughout the cell cycle in humans. However, TCAB1 leaves the complex in the M phase [199], which should lead to a drop in telomerase activity in vitro [195,196]. In general, the exact mechanism behind the assembly–disassembly of the telomerase complex has not been well established in vertebrates. Furthermore, the mechanisms of telomerase recruitment to the telomeres also differ, especially between budding yeast and vertebrates. In budding yeast, telomerase is recruited to telomeres through two distinct mechanisms: the Sir4–yKu80 pathway and the main Cdc13–Est1 pathway [86,87]. In vertebrates, the recruitment of telomerase to telomeres is mediated by multiple factors, including TPP1, POT1, and TIN2 [281,295]. The holoenzyme recruitment mechanisms also exhibit some similarities across the phylogenetic groups. The regulatory activities of Cdc13, Est1, and Est3 in yeast could parallel the roles of TIN2-bound TPP1 in vertebrates. The same considerations apply to the CST complexes. The crucial stages of telomerase biogenesis and recruitment in yeast and vertebrates share some functional similarities. At the same time, the composition of the telomerase complex, the peculiarities of biogenesis regulation, and the mechanisms of recruitment to telomeres differ significantly between the two systems. It is known that the formation of membrane-free organelles such as Cajal bodies or nucleoli occurs due to liquid–liquid phase separation [323]. An interesting example is the nuclear bodies of promyelocytic leukemia involved in alternative telomere elongation (ALT) due to the clustering of telomere and DNA repair factors [324]. The condensation of these bodies occurs during the SUMOylation of telomeric proteins due to the interaction of SUMO and a motif interacting with SUMO (SIM) [325]. The further study of membrane-free organelles may reveal new details regarding the transport of telomerase within the nucleus and its recruitment to telomeres in yeast and vertebrates. The limitation of telomerase activity in vivo by the end of the S phase in vertebrates remains poorly understood because the cellular level of active telomerase complex is not cell-cycle-regulated [199]. Interestingly, the level of interaction between the chaperones pontin and reptin with hTERT peaks in the S phase of the cell cycle [166]. These observations support the hypothesis of the cell-cycle-regulated activation of the telomerase complex in vivo. It is possible that telomerase regulation involves post-translational modifications of telomerase protein subunits and chaperones specific to the phases of the cell cycle in both yeast and vertebrates. In addition, it is interesting to study the role of telomeric protein modifications in telomerase recruitment. For example, the level of TRF1 decreases due to poly-ADP-ribosylation by tankyrase, which leads to a weakening of the binding of TRF1 to telomeres [326]. ATM and ATR kinases promote telomeric elongation in human cells by increasing the frequency of the recruitment of telomerase to the telomere ends [219,311,312]. The main question is how the post-translational modifications of telomerase-associated and telomeric proteins achieve the timely adjustment of the assembly of the telomerase complex and its recruitment to telomeres. Thus, the study of these post-translational modifications and the modifications of telomerase RNA may help reveal new aspects of telomerase biogenesis and functioning. In addition to investigating the biogenesis of the telomerase complex, studying the functions of hTERT and hTR beyond the context of telomerase is also an intriguing area of research. Although many of the observed effects are controversial, future studies should elucidate the non-canonical functions of hTERT and hTR. The biogenesis of telomerase components, complex assembly, localization to the place of action, and recruitment to the telomeres comprise a complicated system, in which each step must be regulated to meet cellular requirements. Any impairment in the function or localization of the participants of telomerase biogenesis will affect the maintenance of telomere length, which is critical to processes such as regeneration, immune response, embryonic development, and cancer progression. At present, the key components of the telomerase complex in various organisms have been identified. In addition, great progress has been made concerning the determination of the structure of the telomerase complex. However, the functional roles of the post-translational modifications of telomerase-associated proteins and the modifications of telomerase RNA remains largely unexplored. Moreover, we still must elucidate the physical principles of the operation of nuclear bodies in general and their role in the biogenesis of the telomerase complex in particular.

PMC10003057

Elisa da Silva Menezes,Francisco Cezar Aquino de Moraes,Amanda de Nazaré Cohen-Paes,Alayde Vieira Wanderley,Esdras Edgar Batista Pereira,Lucas Favacho Pastana,Antônio André Conde Modesto,Paulo Pimentel de Assumpção,Rommel Mario Rodríguez Burbano,Sidney Emanuel Batista dos Santos,Ney Pereira Carneiro dos Santos,Marianne Rodrigues Fernandes

Influence of Genetic Variations in miRNA and Genes Encoding Proteins in the miRNA Synthesis Complex on Toxicity of the Treatment of Pediatric B-Cell ALL in the Brazilian Amazon

23-02-2023

acute lymphoblastic leukemia,toxicity,miRNA,ancestry,SNVs

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer in the world. Single nucleotide variants (SNVs) in miRNA and genes encoding proteins of the miRNA synthesis complex (SC) may affect the processing of drugs used in the treatment of ALL, resulting in treatment-related toxicities (TRTs). We investigated the role of 25 SNVs in microRNA genes and genes encoding proteins of the miRNA SC, in 77 patients treated for ALL-B from the Brazilian Amazon. The 25 SNVs were investigated using the TaqMan® OpenArray™ Genotyping System. SNVs rs2292832 (MIR149), rs2043556 (MIR605), and rs10505168 (MIR2053) were associated with an increased risk of developing Neurological Toxicity, while rs2505901 (MIR938) was associated with protection from this toxicity. MIR2053 (rs10505168) and MIR323B (rs56103835) were associated with protection from gastrointestinal toxicity, while DROSHA (rs639174) increased the risk of development. The rs2043556 (MIR605) variant was related to protection from infectious toxicity. SNVs rs12904 (MIR200C), rs3746444 (MIR499A), and rs10739971 (MIRLET7A1) were associated with a lower risk for severe hematologic toxicity during ALL treatment. These findings reveal the potential for the use of these genetic variants to understand the development of toxicities related to the treatment of ALL in patients from the Brazilian Amazon region.

Influence of Genetic Variations in miRNA and Genes Encoding Proteins in the miRNA Synthesis Complex on Toxicity of the Treatment of Pediatric B-Cell ALL in the Brazilian Amazon Acute lymphoblastic leukemia (ALL) is the most common childhood cancer in the world. Single nucleotide variants (SNVs) in miRNA and genes encoding proteins of the miRNA synthesis complex (SC) may affect the processing of drugs used in the treatment of ALL, resulting in treatment-related toxicities (TRTs). We investigated the role of 25 SNVs in microRNA genes and genes encoding proteins of the miRNA SC, in 77 patients treated for ALL-B from the Brazilian Amazon. The 25 SNVs were investigated using the TaqMan® OpenArray™ Genotyping System. SNVs rs2292832 (MIR149), rs2043556 (MIR605), and rs10505168 (MIR2053) were associated with an increased risk of developing Neurological Toxicity, while rs2505901 (MIR938) was associated with protection from this toxicity. MIR2053 (rs10505168) and MIR323B (rs56103835) were associated with protection from gastrointestinal toxicity, while DROSHA (rs639174) increased the risk of development. The rs2043556 (MIR605) variant was related to protection from infectious toxicity. SNVs rs12904 (MIR200C), rs3746444 (MIR499A), and rs10739971 (MIRLET7A1) were associated with a lower risk for severe hematologic toxicity during ALL treatment. These findings reveal the potential for the use of these genetic variants to understand the development of toxicities related to the treatment of ALL in patients from the Brazilian Amazon region. Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, and B-cell acute lymphoblastic leukemia (B-ALL) accounts for 75–80% of all ALL cases [1]. This leukemic type is the cancer with the highest lethality from 0 to 19 years of age in Brazil [2]. Although the survival rate recorded in pediatric patients with ALL in developed countries such as Australia and Belgium is >90%, the treatment of this neoplasm is still challenging as serious toxic events continue to be present in about 20% of children treated for ALL [3,4]. Pharmacological therapy for ALL uses the European Group Berlin–Frankfurt–Münster (BFM) as its main protocol, which consists of a combination of chemotherapeutic agents according to the stage of treatment [1]. These chemotherapeutics have a narrow therapeutic window, which favors high toxicity in children treated for ALL, often generating changes or the interruption of therapy [4,5]. The response to treatment varies inter-individually among patients with the same protocol; this is partly due to pharmacogenomic variability, as already well established and recommended by international agencies (FDA and EMA) for the TPMT and NUDT15 genes [6]. The literature demonstrates that some factors influence the development of treatment-related toxicities (TRTs), including the patient’s ethnic origin, since the peculiarity of genetic signatures of mixed populations in the Brazilian Amazon, with different degrees of ancestry and with greater contribution of Amerindian descent, plays a significant role in modulating ALL chemotherapy susceptibility and toxicity [7]. Likewise, single nucleotide variants (SNVs) present in miRNA genes and in genes encoding proteins of the miRNA synthesis complex may affect the function of drugs used for treating ALL and contribute to the efficacy and development of toxicity [8]. Pharmacogenomics studies of ALL with mixed populations from the Brazilian Amazon have been published in the scientific literature, highlighting the significance of the regulatory role of genetic variants involved in the development of ALL and the impact of toxicities during pharmacological therapy in pediatric patients [4,7]. Therefore, our study investigated the role of 25 SNVs located in important miRNA genes and in genes encoding proteins of the miRNA synthesis complex, with the toxicity of pediatric patients from the Brazilian Amazon region treated for B-cell ALL. The clinical data of the 77 patients with ALL included in this study are presented in Table 1. The mean age of the patients was 4.8 ± 3.6 years, with the majority being male with 62.3%. Study participants had an average proportion of European ancestry of 42.7%, followed by Amerindians with 36.3% and Africans with 20.4%. Regarding the toxicity parameters, among the 77 patients, 90.9% had some type of toxicity, of which 78.5% had severe toxicities, with the most frequent being infectious toxicity (85.7%), followed by gastrointestinal toxicity present in 67.1% of patients, in addition to hematological (62.8%) and neurological (22.8%) toxicity. Because of important toxicity findings, we stratified the sample according to each outcome (Table 1). In the neurological-type toxicity results, four genetic variants located in MIR149, MIR605, SVIL, and MIR2053 showed statistical relevance with significant results (Table 2). The rs2292832 mutant homozygous TT genotype (MIR149) was associated with a 7-fold increased risk of developing neurological toxicity compared with patients with other genotypes (p = 0.016, OR = 7.26). The homozygous mutant TT genotype of rs2043556 (MIR605) also presented results with an association of risk in the development of neurological toxicity during the treatment of ALL, suggesting a 10-fold increase in relation to the other genotypes (p = 0.039, OR = 10.23). Thus, the homozygous mutant TT genotype of rs10505168 (MIR2053) was associated with a fourfold increased risk of developing neurological toxicity compared with the other genotypes (p = 0.025, OR = 4.61). In contrast, the homozygous mutant TT genotype of rs2505901 (SVIL) was significantly associated with a lower risk of developing neurological toxicity, suggesting a protective factor for patients with this genotype (p = 0.030, OR = 0.09). In the specific analyses for gastrointestinal toxicity, three polymorphisms with a significant association were identified (Table 3). The rs2505901 (SVIL) polymorphism was shown to be a protective factor for individuals with the CC genotype compared with patients with other genotypes (p = 0.045, OR = 0.20). The homozygous mutant rs639174 (CC) genotype in the DROSHA gene was significantly associated with an 11-fold increased risk of developing gastrointestinal toxicity during ALL treatment (p = 0.040, OR = 11.63). The wild-type homozygous TT variant of rs56103835 (MIR323B) was shown to be a protective factor for gastrointestinal toxicity in patients with this genotype compared with the others in this study. None of the genetic variants investigated demonstrated significance for levels of severe gastrointestinal toxicity. The logistic regression performed was adjusted for African ancestry (p = 0.026). One polymorphism showed a statistically significant result with infectious-type toxicity during ALL treatment (Table 4): rs2043556 of the MIR605 gene. The homozygous wild-type (CC) genotype of rs2043556 was associated with a reduced risk of developing infectious toxicity (p = 0.010, OR = 0.08), suggesting a protective effect. In Table 5, analyses of severe hematological toxicity revealed significant results for three variants: rs12904 of the MIR200C gene (p = 0.037, OR = 0.26), rs3746444 of the MIR499A gene (p = 0.025, OR = 0.23), and rs10739971 of the MIRLET7A1 gene (p = 0.040, OR = 0.18). Both variants were associated with a lower risk of developing severe hematologic toxicity during ALL treatment. Despite the clinical advances in the treatment of ALL, 65.3% of the mixed population with a high contribution of Amerindian ancestry still present grades 3 and 4 toxicities when submitted to the European Group Berlin–Frankfurt–Münster (BFM) protocol, data that present great difference when compared with the average of world populations (20%) [4,10]. Due to the high rate of miscegenation in poorly investigated populations, such as Brazilian, it is important to evaluate genetic variants that may be related to therapeutic failure. Some studies have sought to identify genetic variants that may be directly related to the high toxicities during the treatment of ALL found in the Brazilian Amazon; in this way, the present project intends to evaluate the effect of important genetic variants in miRNA genes for the toxicities generated in Amazonian populations [10]. In this study, significant relationships were found with the following variants: rs2292832 (MIR149), rs2043556 (MIR605), rs10505168 (MIR2053), and rs2505901 (MIR938), correlated with neurological toxicity during the ALL treatment. MIR149 has previously been linked to the risk of multiple cancers, including colorectal, liver, and breast cancer [11,12,13]. In our study, rs2292832 (MIR149) was statistically associated with an increased risk of central nervous system (CNS) toxic events during ALL treatment. The rs2043556 (MIR605) variant has also been linked to the development of a variety of cancers, including breast and gastrointestinal cancer; it may affect the functionality of the MIR605 processing gene [14,15]. The MDM2 gene is involved in different parts of the cancer signaling cascade, being a direct target of regulation by MIR605 [14,15]. This miRNA is considered an activator of the p53 signaling pathway, interrupting the p53-MDM2 interaction, resulting in an accumulation of p53 and consequently aiding its cellular functionality [15,16]. The G allele of rs2043556 was associated with its interference in platinum-based therapy, inducing the risk of severe hepatotoxicity in lung cancer patients during platinum-based treatment [17]. In this investigation, the MIR605 gene rs2043556 was significantly associated with the risk of developing neurological toxicity inherent to the use of MTX and 6-Mercaptopurine and also associated with a 92% protective factor in the risk of infectious toxicities in our patients. This variant has also been previously evidenced as a phenotype modeler in patients with Li-Fraumeni syndrome [18]. In this study, the rs10505168 of the MIR2053 gene was associated with the development of neurological toxicities during the treatment of ALL. This variant was identified and related to oral mucositis in the consolidation stage of ALL treatment [19]. In addition, another study analyzed the association of this variant with the risk of MTX-induced oral mucositis in Dutch children with ALL [20]. Statistically significant results were found in DROSHA (639174), MIR198 (2505901), and MIR323B (56103835), with the risk of developing gastrointestinal toxicities in our patients. DROSHA encodes double-stranded RNA-specific ribonuclease III (RNase III), an important enzyme for the production of pre-miRNA from pri-miRNAs. SNVs in this gene can cause changes in drug responses as a result of their expression variation. The first study to demonstrate the potential of variants in miRNA processing genes as a predictor of toxicity in the pharmacological management of ALL linked rs639174 in DROSHA to MTX-induced gastrointestinal toxicity in pediatric patients with B-cell ALL [19,21]. In our study, this result was confirmed, and the rs639174 variant was associated with an increased risk of developing gastrointestinal toxic effects. The rs56103835 variant in pre-MIR323B was previously associated with changes in plasma MTX levels and the occurrence of vomiting in patients with ALL; mature MIR453 may undergo alterations in its levels and biogenesis and, consequently, in its role in the regulation of target genes ABCC1, ABCB1, ABCC2, and ABCC4, included in the transport of the drug MTX. The rs56103835 variant was related to mature MIR functioning and plasma levels of this drug during pharmacological treatment, which supports a significant association with gastrointestinal toxicity [19]. The results of the present study indicate that the rs56103835 variant was associated with a lower risk of developing gastrointestinal toxicities. In our study, the rs2505901 variant of the MIR938 gene was significantly associated with protection from gastrointestinal and neurological toxicity. Another variant present in the MIR938 gene has been associated with decreased risk of gastric cancer [22]. In addition, rs2505901 has been previously described as a potential reduction in ALL susceptibility in populations from the Amazon region, which corroborates the protective effect of the rs2505901 variant [23]. Regarding severe hematologic toxicity, our results demonstrated significant data on the variants rs12904 (MIR200C), rs3746444 (MIR499A), and rs10739971 (MIRLET7A1) for hematologic toxicity arising from the treatment of ALL in our patients. In the present work, rs12904 was associated with a 74% decrease in the risk of hematologic toxicity. The same variant was previously related to colorectal cancer risk in the Chinese population and gastric adenocarcinoma risk [24,25]. Studies showed that MIR200C was expressed at significantly lower levels in children with relapsing ALL compared to those at primary diagnosis, i.e., the decreased expression of MIR200C can be considered as a prognostic factor for relapse in childhood ALL [26]. Another significant association for hematologic toxicity in our study involved rs3746444 (MIR499A). This variant was identified and associated with a 77% lower chance of developing toxic hematological events during the treatment of ALL in the present study. rs3746444 was recently implicated in ALL susceptibility in a study that relevantly associated this variant with a lower risk of developing ALL [20], while another demonstrated an association of rs3746444 with significantly increased risk of ALL [27]. In our study, the rs10739971 variant of the MIRLET7A1 gene was associated with a possible protective factor of 82% in the risk of developing toxic hematological events in pediatric patients undergoing ALL. The same variant has already been described as a potential gastric cancer biomarker [28]. Three variants in our study (rs10505168, rs639174, and rs56103835) were previously associated and described in the specialized literature as relevant to the pharmacogenomics of ALL treatment [19]. In addition, other new variants were identified and related for the first time to toxic events during chemotherapy for ALL. Therefore, we suggest that variants in the MIR149, MIR605, MIR938, MIR200C, MIR499A, and MIRLET7A1 genes, although not related in the specialized literature to the pharmacological pathways of the antineoplastics used in ALL, can still influence the toxicity in these patients since they play regulatory roles in the cellular environment aiding the survival of cancer cells, thus impairing the effectiveness of the treatment. It is important to highlight that the expression of variants in miRNAs can affect the function of drugs; however, they are still poorly understood in the involvement of different pathways that may be regulating the treatment of ALL [8]. Therefore, additional studies would be ideal to clarify the real potential of these variants in the pharmacological management of ALL. All precepts of the Declaration of Helsinki and the Nuremberg Code were followed, in addition to the Research Standards Involving Human Beings in Brazil (Res. 466/12 of the National Health Council). The study protocol was approved by the Research Ethics Committee of the Research Center of Oncology of the Federal University of Pará (CAAE number 11433019.5.0000.5634/2019). The study was performed with 77 patients diagnosed with B-cell ALL through immunophenotyping and/or molecular analysis, aged between 1 and 18 years. All of them received treatment at the Otávio Lobo Children’s Oncological Hospital, a reference center for childhood cancer treatment in the North region of Brazil. Patients with a history of relapses or with comorbidities were excluded from this study. Toxicity data were collected from patient charts and were classified based on common terminology criteria for adverse events v.5 [9]. The SNVs selected for the present study were chosen due to their participation in the pharmacokinetics and/or pharmacogenomics of one or both drugs (6-MP or MTX) used in the treatment of ALL and associated with adverse events, in addition to being involved in this carcinogenesis. A total of 25 variants were selected in miRNA genes and in genes encoding proteins essential for the synthesis of miRNAs contained in Supplementary Table S1. The selection was performed based on the inclusion of two criteria: (i) MAF ≥ 1% and (ii) genotyping rate ≥80. DNA was extracted from peripheral blood using the commercial BiopurKit Mini Spin Plus–250 Extraction Kit (Biopur, Pinhais, PR, Brazil), according to the manufacturer’s instructions. The concentration of genetic material was quantified using a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Genotyping of variants was performed by allelic discrimination using QuantStudio TaqMan® OpenArray technology (ThermoFisher, Carlsbad, CA, USA) with a set of 25 custom assays, which were run on a QuantStudio™ 12K Flex Real-Time PCR system (Applied Biosystem, Life Technologies, Carlsbad, CA, USA), according to the manufacturer’s protocol. The quality of genotype readings and other data were analyzed using the TaqMan® v1.2 Genotyper software (Thermo Fisher Scientific). The genomic ancestry of the participants was analyzed according to Santos et al. 2010) [29] and Ramos et al., 2016 [30], using a set of 61 Ancestry Informative Markers (AIMs). The individual and global proportions of European, Amerindian, and African genetic ancestry were estimated using STRUCTURE v.2.3.4. A descriptive analysis of the data referring to the characterization of the sample was carried out using the absolute frequency; percentage; mean; standard deviation; median; and interquartile range of 25% to 75%. Quantitative variables were first submitted to the Kolmogorov–Smirnvov test for normality distribution analysis. The individual proportions of European, African, and Amerindian genetic ancestry were estimated using Structure 2.3.3 software. The Chi-square test was applied to categorical variables and the Mann–Whitney test to continuous variables. To analyze the association of polymorphisms involved with the risk of toxicity in ALL, simple and multivariate logistic regression was performed. All statistical analyzes were performed using the SPSS 20.0 statistical package, considering a significance level of 5% (p-value ≤ 0.05). In the mixed population of the North region of Brazil, the average occurrence of toxicities is above the average of the rest of the population, and in part, the specialized literature has demonstrated the influence of Amerindian ancestry. Few studies describe data on miRNA variants and their influence on ALL therapy in mixed Brazilian populations. Therefore, the data presented are of great value for understanding the variability of response in the standard treatment of ALL in the investigated population, standing out among the other studies carried out in homogeneous populations, which were the focus of most previous research on this topic. Finally, we demonstrate that the investigated MIR149, MIR605, MIR938, DROSHA, MIR200C, MIR499A, MIRLET7A1, MIR323B, and MIR2053 could potentially modulate the therapeutic response of standard treatment for ALL.

PMC10003058

Yi-Lin Li,Xiu-Ying Gong,Zi-Ling Qu,Xiang Zhao,Cheng Dan,Hao-Yu Sun,Li-Li An,Jian-Fang Gui,Yi-Bing Zhang

Zebrafish HERC7c Acts as an Inhibitor of Fish IFN Response

27-02-2023

small HERC family,HERC7 subfamily,negative regulation,IFN response,protein attenuation

In humans, four small HERCs (HERC3-6) exhibit differential degrees of antiviral activity toward HIV-1. Recently we revealed a novel member HERC7 of small HERCs exclusively in non-mammalian vertebrates and varied copies of herc7 genes in distinct fish species, raising a question of what is the exact role for a certain fish herc7 gene. Here, a total of four herc7 genes (named HERC7a–d sequentially) are identified in the zebrafish genome. They are transcriptionally induced by a viral infection, and detailed promoter analyses indicate that zebrafish herc7c is a typical interferon (IFN)-stimulated gene. Overexpression of zebrafish HERC7c promotes SVCV (spring viremia of carp virus) replication in fish cells and concomitantly downregulates cellular IFN response. Mechanistically, zebrafish HERC7c targets STING, MAVS, and IRF7 for protein degradation, thus impairing cellular IFN response. Whereas the recently-identified crucian carp HERC7 has an E3 ligase activity for the conjugation of both ubiquitin and ISG15, zebrafish HERC7c only displays the potential to transfer ubiquitin. Considering the necessity for timely regulation of IFN expression during viral infection, these results together suggest that zebrafish HERC7c is a negative regulator of fish IFN antiviral response.

Zebrafish HERC7c Acts as an Inhibitor of Fish IFN Response In humans, four small HERCs (HERC3-6) exhibit differential degrees of antiviral activity toward HIV-1. Recently we revealed a novel member HERC7 of small HERCs exclusively in non-mammalian vertebrates and varied copies of herc7 genes in distinct fish species, raising a question of what is the exact role for a certain fish herc7 gene. Here, a total of four herc7 genes (named HERC7a–d sequentially) are identified in the zebrafish genome. They are transcriptionally induced by a viral infection, and detailed promoter analyses indicate that zebrafish herc7c is a typical interferon (IFN)-stimulated gene. Overexpression of zebrafish HERC7c promotes SVCV (spring viremia of carp virus) replication in fish cells and concomitantly downregulates cellular IFN response. Mechanistically, zebrafish HERC7c targets STING, MAVS, and IRF7 for protein degradation, thus impairing cellular IFN response. Whereas the recently-identified crucian carp HERC7 has an E3 ligase activity for the conjugation of both ubiquitin and ISG15, zebrafish HERC7c only displays the potential to transfer ubiquitin. Considering the necessity for timely regulation of IFN expression during viral infection, these results together suggest that zebrafish HERC7c is a negative regulator of fish IFN antiviral response. The HERC family proteins are E3 ubiquitin ligases that contain one C-terminal HECT (homologous to E6AP carboxyl terminus) domain and one or more N-terminal RCC1 (regulator of chromosome condensation 1)-like domains (RLD) [1]. In humans, the HERC family has six members that are traditionally classified into two subgroups: large HERCs (HERC1 and HERC2) and small HERCs (HERC3–6). Compared with large HERC proteins bearing one HECT domain, more than one RLD domain and multiple other conserved regions, small HERC proteins harbor a single HECT and a single RLD domain [2]. Such a structural difference supports the notion that large HERCs and small HERCs arise from convergent evolution of ancestors belonging to two distant families [3]. The E3 ubiquitin ligase activities of HERC proteins are ascribed to their C-terminal HECT domains that are capable of transferring ubiquitin to target proteins, a process of protein translational modification (PTM) termed ubiquitinylation, which has been verified in HERC1, HERC3, and HERC5 [4,5,6]. Apart from ubiquitinylation, human HERC5 and mouse HERC6 are also involved in a second PTM process, termed ISGylation, by utilizing the E3 ligases to catalyze the conjugation of ISG15, a ubiquitin-like protein induced by an antiviral cytokine interferon (IFN) [7,8]. Given the regulatory roles of HERCs-mediated ubiquitinylation and ISGylation in various physiological activities [9,10], four small HERCs exhibit differential potentials to inhibit HIV-1 particle production [1]. Notedly, HERC5 and HERC6 are transcriptionally induced in viral-infected cells [7,8,11]. These results highlight that small HERCs are involved in innate IFN antiviral immunity although the details are largely unknown. IFN response is believed to begin with a rapid recognition of viral products by host pattern recognition receptors (PRR) including retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), cGAS (cyclic GMP-AMP synthase), and TLRs (toll-like receptors) [12]. Such recognition initiates distinct signaling cascades through the recruitment of downstream adaptors MAVS (mitochondrial antiviral signaling protein), STING (stimulator of interferon response cGAMP interactor 1, also known as MITA), or TRIF (TIR domain-containing adaptor protein inducing interferon-β), but finally converges on activating the TBK1 (TANK-binding kinase 1)-IRF (IFN regulatory factor) 3/7 signaling axis to turn on cellular IFN expression. The produced IFNs in turn induce the expression of hundreds of ISGs (IFN-stimulated genes), thus constituting the first line of defense against viral replication [12]. Despite the necessity and relevance of cellular IFN response, unregulated IFN expression is pathogenic and often fatal in mammals [13]. Therefore, some ISGs are induced to fine-tune the IFN expression [14,15,16], such as human HERC5 which promotes, as a typical ISG, cellular IFN expression through sustaining IRF3 activation [17]. It is documented that small HERCs originate from a common ancestor by gene duplication and chromosomal rearrangement [1,2,18], as evidenced by the findings that HERC3 and HERC4 generally display a strict 1:1 orthologous relationship across vertebrates, and they both reside in 2 chromosomes bearing the highest homology to each other [1,19]. However, we have recently revealed that only mammalian species have the orthologs of human HERC5 and HERC6, and nonmammalian vertebrates harbor a novel HERC7 subfamily that does not exist in mammals [19]. A herc7 gene from crucian carp Carassius auratus is expressed as an ISG, and in viral-infected cells, it selectively targets three RLR signaling factors to alleviate IFN response by two distinct strategies [19]. Interestingly, varied copies of herc7 genes are present in different fish species, with some unique to fish species [19]. This means that functional characterization of a fish species-specific herc7 gene is of great significance for the delineation of fish species-specific antiviral immunity. In this study, we found four herc7 homologous genes (named HERC7a–d) in zebrafish Chromosome 1, which were transcriptionally induced in zebrafish tissues following SVCV (spring viremia of carp virus) infection. Phylogenetical analyses supported that the HERC7 subfamily has undergone species-specific expansion during the radiation of teleosts. We focused on zebrafish herc7c which was identified as an IFN-stimulated gene (ISG). Overexpression of zebrafish HERC7c promoted viral replication likely through the downregulation of fish IFN response. Mechanistically, zebrafish HERC7c targeted MAVS, STING, and IRF7 for protein degradation through the proteasomal-dependent pathway. Unlike the recently-identified crucian carp HERC7 showing the potential to conjugate ubiquitin and ISG15 to itself, zebrafish HERC7c has only E3 ubiquitin ligase activity, indicating function diversification of fish HERC7 family members in IFN antiviral response. Using crucian carp HERC7 as query, blast searches of zebrafish genome (GRCz11) identified four herc7 homologous genes, sequentially named HERC7a (XP_17211386.1), HERC7b (XP_005160175.1), HERC7c (XP_021330683.1), and HERC7d (XP_005160166.1), which reside near the herc3 gene locus in Chromosome 1 but not the herc4 gene locus in Chromosome 13 (Figure 1A). Considering that the recently identified crucian carp HERC7 is transcriptionally induced by viral infection [19], we determined the expression patterns of four zebrafish herc7 genes in response to SVCV infection. Intraperitoneal injection of SVCV into zebrafish resulted in increased mRNA expressions of zebrafish ifnφ1 and ifnφ3, as well as mxc genes, a typical IFN-stimulated gene [20] (Figure 1B). Consistently, four zebrafish herc7 genes were also transcriptionally induced by SVCV infection (Figure 1C). These results implied that SVCV infection activated a robust IFN response in all zebrafish tissues and also the expression of four zebrafish herc7 genes. We tried to clone the full-length cDNA sequences of four zebrafish herc7 genes. It was easy to obtain a single PCR band using a pair of primers designed against the 5′ UTR and 3′UTR sequences of the annotated herc7c in zebrafish genome data (left panel in Figure 2A). The cloned cDNA sequence contains the largest ORF of 2790bp, encoding a 929-aa HERC7c protein (Figure 2B). The annotated herc7c gene in zebrafish genome (GRCz11) was identified by automated computational analysis. Interestingly, it was annotated to contain 25 exons and was predicated to generate two transcript variants, encoding a 1002-aa protein and a 994-aa protein, respectively (Figure 2B). Sequence comparison revealed that our cloned herc7c cDNA sequence (OQ360721) does not contain the predicated 17th and 18th exons annotated in zebrafish genome (GRCz11) (Figure 2B). We repeated PCR experiments using different tissues samples; however, the same PCR product rather than both annotated transcript variants was cloned. Further, we designed a second pair of primes against sequences of the 16th and 19th exons (Figure 2B) to verify whether the 2 annotated variants were expressed. RT-PCR assays still obtained a single product with a predicated size of 199 bp representing our cloned herc7c cDNA sequence (OQ360721), without a larger product of 388 bp predicated from the 2 annotated transcription variants (right panel in Figure 2A). Thus, we thought that the cloned cDNA (OQ360721) might be the real transcript of the zebrafish herc7c gene. To characterize whether zebrafish HERC7c is induced by IFN stimuli, we further cloned an 888-bp-5′ flanking sequence relative to the transcription start site of zebrafish herc7c gene (Figure 2C). This sequence has two putative ISRE/IRF-E sites, and it was next used to construct an herc7c promoter-driven luciferase plasmid (HERC7cpro-luc) and several derived mutants by mutating two predicated ISRE motifs (Figure 2D). As expected, the 888-bp-promoter of herc7c (HERC7cpro-luc) was robustly activated in EPC (Epithelioma papulosum cyprini) cells when transfected with poly(I:C) (polyinosinic-polycytidylic acid) as intracellular poly(I:C), or each of RLR signaling molecules, including RIG-I, MDA5, MAVS, STING, TBK1, IRF3, and IRF7 (Figure 2E). Overexpression of IFN also effectively activated HERC7cpro-luc (Figure 2E), and this activation was seen by individual or collective overexpression of STAT1, STAT2, and IRF9 (Figure 2F), three pivotal molecules involved in the IFN-triggered JAK-STAT signaling pathway [21,22,23]. The RLR pathway-induced IFN response can be triggered in fish cells by poly(I:C) transfection and SVCV infection [24,25]. Subsequent assays showed that intra-poly(I:C)-triggered activation of HERC7cpro-luc was severely decreased by individual overexpression of dominant negative mutants of RLR signaling factors (TBK1-K38M, IRF3-DN, and IRF7-DN) as well as JAK-STAT signaling factors (STAT1-ΔC and IRF9-ΔC) (Figure 2G). Compared with the full-length HERC7c promoter sequence (WT, −888~−1) that could be activated by intra-poly(I:C), extra-poly(I:C), or SVCV, a truncated promoter sequence (−248~−1) containing 2 putative ISRE motifs (ISRE1 and ISRE2) retained the intact promoter activation, but a second truncated promoter sequence devoid of 2 ISRE motifs (−888~−249) failed to respond to 3 stimuli above (Figure 2H). Mutation of ISRE1 but not ISRE2 gave a weakened luciferase activity (Figure 2I), indicating that the proximal ISRE1 motif rather than the distant ISRE2 was responsible for the HERC7c promoter activation. These results together indicated that zebrafish herc7c is a typical ISG. Given that the recently identified crucian carp HERC7 is involved in downregulation of the fish IFN response [19], we next investigated whether zebrafish HERC7c played a similar role. Luciferase assays showed that, compared with the control cells transfected with pcDNA3.1, poly(I:C) transfection resulted in robust activation of crucian carp IFN promoter-driven luciferase plasmid (CaIFNpro-luc); however, this activation was severely impeded by overexpression of zebrafish HERC7c in a dose-dependent manner (Figure 3A). Consistently, overexpression of zebrafish HERC7c in EPC cells inhibited poly(I:C)-triggered mRNA expression of ifn and viperin (Figure 3B), which was seen in a time-dependent manner (Figure 3C). These results indicated that zebrafish HERC7c functions as an inhibitor of IFN response in fish. To determine the effect of zebrafish HERC7c on viral replication, EPC cells were transfected with zebrafish HERC7c or pcDNA3.1 as control, followed by infection of SVCV at different titers. SVCV incubation yielded broad CPEs in zebrafish HERC7c-overexpressing cells compared with control cells (Figure 4A). Consistently, a higher transcription level of three SVCV genes (L, N, and G) was detected in HERC7c-overexpressing cells than in control cells (Figure 4B). Under the same conditions, the increase in the expression of cellular ifn and viperin in the presence of HERC7c overexpression was less than in the case of its absence (Figure 4C). Subsequent assays showed that overexpression of zebrafish HERC7c inhibited SVCV-triggered mRNA expression of cellular ifn and viperin over infection time (Figure 4D) and, concomitantly, resulted in a transcription elevation of the three SVCV genes (Figure 4E). These results indicated that zebrafish HERC7c promotes virus replication in fish cells likely through downregulation of the fish IFN response. Luciferase assays showed that overexpression of STING stimulated the activation of zebrafish IFNφ1 promoter- or IFNφ3 promoter-driven luciferase plasmids (DrIFNφ1pro-luc, DrIFNφ3pro-luc); however, this activation was alleviated in the presence of zebrafish HERC7c (Figure 5A). Zebrafish HERC7c-mediated alleviation was seen when IFN promoter activation was stimulated by MAVS or IRF7 (Figure 5B), but not by TBK1 or IRF3 (Figure 5C). It was noteworthy that overexpression of zebrafish IRF3 just activated zebrafish IFNφ1 promoter but not zebrafish IFNφ3 promoter (Figure 5C), similar to our previous results [24]. These data indicated that zebrafish HERC7c targets STING, MAVS, and IRF7 to downregulate the IFN antiviral response. To further determine the mechanism of how zebrafish HERC7c downregulated the STING-mediated IFN response, the effect of zebrafish HERC7c on gene transcription of ifn and sting was initially investigated. As anticipated, zebrafish STING-induced transcription of cellular ifn and viperin genes was significantly attenuated by zebrafish HERC7c over infection time (Figure 6A). However, zebrafish HERC7c did not have influences on sting gene transcription because a nearly identical pattern was detected between the cells overexpressing STING alone and the cells overexpressing STING and HERC7c together; the detected pattern was a pair of primers that amplifies mRNAs only from the transfected STING plasmid (Figure 6B). Conversely, Western blots showed that simultaneous transfection of HERC7c and STING resulted in a decrease in STING proteins compared with the single transfection of STING (Figure 6C). Similar assays showed that overexpression of zebrafish HERC7c time-dependently alleviated mRNA expression of cellular ifn and viperin, which were triggered by MAVS or IRF7 (Figure 6D). Under the same conditions, zebrafish HERC7c did not make a difference on mRNA expression of the transfected mavs or irf7 (Figure 6E) but significantly attenuated their protein expressions (Figure 6F). Zebrafish HERC7c-mediated protein degradation of STING, MAVS, and IRF7 was blocked by the addition of MG132 (an inhibitor of the ubiquitin-proteasomal-dependent degradation pathway) but not of chloroquine (an inhibitor of the autophagy-lysosomal-dependent degradation pathway) (Figure 7A–C). These results indicated that zebrafish HERC7c facilitates STING, MAVS, and IRF7 protein degradation to downregulate the IFN response. Similar to the recently identified crucian carp HERC7 [19], zebrafish HERC7c contains an N-terminal RLD domain and a C-terminal HERC domain (Figure 8A). It is believed that the HECT domain entitles HERC proteins with the E3 ubiquitin ligase activity, and particularly, human HERC5 and mouse HERC6 are also responsible for protein ISGylation [9]. To this end, we investigated whether zebrafish HERC7c has a potential to transfer ubiquitin or ISG15. Similar to the recently-identified crucian carp HERC7 that can be ubiquitinated by itself [19], transfection of HEK293T cells with His-ubiquitin and HERC7c-Flag followed by affinity purification of His-ubiquitin using Ni2+-NTA resin revealed an enhanced level of ubiquitinated HERC7c proteins compared with overexpression of HERC7c alone (Figure 8B). Similar assays showed that crucian carp HERC7 rather than zebrafish HERC7c could be modified by ISG15 in cells when simultaneously transfected with ISG15 instead of ubiquitin (Figure 8C). These results indicated that zebrafish HERC7c is an E3 ligase responsible for ubiquitinylation but not for ISGylation. The HERC7 subfamily exists in non-mammalian vertebrates [19]. To determine the relationship of zebrafish HERC7c in the HERC7 subfamily, we collected a total of 40 small HERC homologs from elephant shark (C. milii) to birds. Apart from four HERC7 members in zebrafish, blast searches of genome data revealed three HERC7 members in grass carp, three in common carp, and two in goldfish. Phylogenetical tree analyses showed that all HERC7 members are clustered into a clad that is distinct from the HERC3, HERC4, HERC5, and HERC6 subfamilies. Four zebrafish HERC7s were divided into two branches and each has no “one to one” orthologs in other fish species (Figure 9). These results indicated the occurrence of the species-specific expansion of the HERC7 subfamily in zebrafish, thus implying that zebrafish HERC7c might be a species-specific gene. HERC1 is the founding member of the HERC family characterized in human breast cancer cells [26], followed by the identification of a total of six HERC members in human, which are phylogenetically divided into large HERCs (HERC1 and HERC2) and small HERCs (HERC3-6) [2,10]. By genome-wide search of small HERC homologs from elephant shark to mammals and subsequently comprehensive evolutionary analyses, we provide evidence showing that, whereas HERC3 and HERC4 are conserved across vertebrates, the orthologs of human HERC5 and HERC6 are only present in mammals with a definite orthologous relationship to each other, and importantly, non-mammalian vertebrates have a unique HERC7 subfamily that might have been lost in modern mammals [19]. In this study, we cloned zebrafish herc7c cDNA by nested PCR. Interestingly, the obtained sequence is different from the two “annotated” transcripts in the zebrafish genome (GRCz11) by automated computational analysis. To verify whether our cloned sequence is a novel splicing variant of zebrafish herc7c, we designed a second pair of primers based on our hypothesis that, if there is a splicing variation, two PCR products will be amplified. However, only one band corresponding to the cloned sequence was obtained. Therefore, we think that our cloned cDNA represents the real transcript of the zebrafish herc7c gene. Subsequently, we identified four herc7 homologs in zebrafish Chromosome 1, showing that they are adjacent to herc3. In mammals, small HERCs generally reside in two gene loci, one containing a single herc4 gene in one chromosome, and the other containing herc3 and other herc genes in a second chromosome [1,19]. The chromosomal location link of zebrafish herc3 and four herc7 genes indicate that they might originate from a common ancestry. In addition, different fish species have varied copies of herc7 genes, most of which seem not to exhibit a “one to one” orthologous relationship to each other. Given that teleost fish have additional whole-genome duplication [27,28,29], we propose that the varied herc7 copies in different fish species might arise from segmental duplication after the additional whole-genome duplication. These results support a notion that the small HERC family has experienced gene duplication, chromosomal rearrangement, and gene loss events during vertebrate evolution [1,2,3,18]. The results in the current study establish that zebrafish HERC7 destabilizes different signaling molecules at the protein level to downregulate the IFN response during viral infection. First, zebrafish HERC7c is transcriptionally expressed along the viral infection. Secondly, zebrafish HERC7c benefits SVCV replication and concomitantly alleviates the IFN response. Thirdly, zebrafish HERC7c markedly abrogates the IFN promoter activation and ifn gene transcription by RLR signaling molecules, including STING, MAVS, and IRF7. Mechanistically, zebrafish HERC7c targets STING, MAVS, and IRF7 for proteasome-dependent protein degradation, as evidenced by the findings that this degradation is blocked by MG132. An interesting question is that zebrafish HERC7c targets IRF7 but not IRF3 to attenuate IFN expression, although IRF3 is most homologous to IRF7 [24,30,31]. This means a possibility that zebrafish HERC7c can specifically select the substrates to exert inhibitory effects. The same is true for the differential function of zebrafish IRF3 and IRF7 because they are responsible for the transcription of the zebrafish ifnφ1 and ifnφ3 genes, respectively [23,24]. Although vertebrate IRF3s exhibit a “one to one” orthologous relationship to each other, fish IRF3 is a virus- and IFN-induced protein, and instead, mammalian IRF3 is constitutively expressed even under viral infection [31,32,33]. These results further suggest that the inhibitory effect of zebrafish HERC7c on the IFN response might be a consequence of selection pressures that are exerted by fish viruses. Given that zebrafish HERC7c is identified as an inhibitor of the fish IFN response, mammalian HERC5s play a positive role in limiting different virus replications [1]. In this paper, the authors present evidence that a coelacanth protein (XP_014354291.1) also displays a similar inhibitory effect on simian immunodeficiency virus replication [1]. However, subsequently we found that this coelacanth protein (XP_014354291.1) is indeed a HERC7 homolog although erroneously characterized as a coelacanth homolog of human HECR5 by comprehensive phylogenetic analyses [19]. Therefore, coelacanth does not contain an ortholog of human HERC5, and the coelacanth HERC7 protein (XP_014354291.1) acts as an intracellular viral inhibitor, similar to human HERC5 [1]. Moreover, the recently-identified crucian carp HERC7 attenuates the IFN response by utilizing two different mechanisms to degrade STING, MAVS, and IRF7 at the protein and mRNA levels [19]. These results indicate that the HERC7 subfamily members have undergone functional diversification, and thus they might play opposing roles in response to viral infection, such as the coelacanth protein (XP_014354291.1) as a positive regulator, and zebrafish HERC7c and crucian carp HERC7 as a negative regulator. Small HERCs possess E3 ligase activity as a result of their C-terminal HECT domains [34]. Interestingly, whereas crucian carp HERC7 participates in both ubiquitinylation and ISGylation, zebrafish HERC7c just bears the potential to transfer ubiquitin (ubiquitinylation), further indicating that fish HERC7 subfamily members have experienced function diversification. In the present study, we did not investigate whether the E3 ubiquitin ligase activity of zebrafish HERC7c is tightly related to its inhibitory role in fish antiviral response; however, our previous report has shown that the inherent E3 ligase activity seems to not be required for the crucian carp HERC7 downregulation of the IFN response because a mutant without E3 ligase activity displays a nearly intact ability to alleviate the fish IFN response [19]. Given that four zebrafish herc7 genes are generated by fish species-specific expansion of the HERC7 family, zebrafish herc7c might represent a zebrafish-specific gene, as evidenced by the fact that we failed to find a “one-to-one” ortholog of zebrafish HERC7c by comprehensive analyses of the available fish genome databases. Since zebrafish HERC7c expression is elevated along with viral infection, the data in the present study suggest that zebrafish HERC7c might mediate a fish species-specific regulation of the IFN response to avoid unregulated IFN production during viral infection. Further studies might focus on in vivo function clarification of zebrafish HERC7c. If the function blockade of zebrafish HERC7c were able to effectively improve zebrafish survival against viral infection, it would highlight a relevance of HERC7 subfamily genes, such as zebrafish HERC7c with an inhibitory role, in fish antiviral precision breeding by gene-editing technology [35]. Epithelioma papulosum cyprini cells (EPC) were cultured in medium 199 supplemented with 10% fetal bovine serum (FBS) at 28 °C in a humidified incubator containing 5% CO2. Human embryonic kidney 293T cells (HEK293T, ATCC (CRL-3216)) were cultured in DMEM supplemented with 10% FBS at 37 °C. Spring viremia of carp virus (SVCV) was propagated in EPC cells and tittered, according to the method of Reed and Muench, by a tissue culture ID50 assay. EPC cells were infected with SVCV at a final concentration of 5 × 103 TCID50/mL. Zebrafish adults (2-month-old), with similar sizes and weights (body length: 3 cm; weight: 0.4 g), were raised in a single batch according to standard protocol [36], which was approved by the Animal Care and Use Committee of Institute of Hydrobiology, Chinese Academy of Sciences. For viral infection, zebrafish were intraperitoneally injected with SVCV at 1 × 108 TCID50/mL (25 μL/fish). After injection, they were kept at 28 °C water for 48 h without feeding. The control group received the same dose of 0.9% normal saline. After 48 h, the zebrafish were euthanized by immersing in a mixture of ice water for 20 min, followed by sampling of tissues. Four immune tissues (spleen, liver, head kidney, and body kidney), from a zebrafish adult infected for 48 h with SVCV, were mixed to extract total RNA for cDNA synthesis by TRUEscript RT MasterMix (PC5801, Aidlab, Beijing, China). The mixed cDNA was used as a template to clone the ORF of zebrafish herc7c by nested PCR method. Zebrafish genome DNAs were extracted by the Wizard Genomic DNA Purification Kit (Promega) for PCR amplification of the herc7c promoter. The primers were designed against the computational annotated herc7c sequence in the zebrafish genome data (GRCz11) (Table 1). Using zebrafish HERC7c (GenBank accession no. OQ360721) protein sequence as a query, protein BLAST searches were performed on the genome databases of grass carp (Ctenopharyngodon idella), common carp (Cyprinus carpio), and goldfish (Carassius auratus). Three homologs of zebrafish HERC7 were found in grass carp (XP_051736083.1, XP_051739640.1, and XP_051731642.1) and common carp genomes (XP_042627096.1, XP_042617724.1, and XP_042617185.1), and two in goldfish genome (XP_026059385.1, XP_026059288.1). Meanwhile, 40 sequences of small HERC family members in other species, which were verified by evolutionary analysis in our previous study [19], were collected for subsequent evolutionary tree analysis. They include: HERC3 (pufferfish, elephant shark, and grass carp), HERC4 (mouse and zebrafish), HERC5 (hedgehog and bat), HERC6 (human and pika), HERC5/6 (striped catfish, coelacanth, elephant shark, frog, and green anole), and HERC7 (Atlantic salmon, river trout striped catfish, milkfish, zebrafish, common carp, grass carp, crucian carp, goldfish, elephant shark, coelacanth, green anole, and chicken). Multiple alignments were carried out with ClustalW2 to make a phylogenetic tree by neighbor-joining methods in Geneious. Transcription factor-binding sites were predicated using JASPAR database (http://jaspar.genereg.net/) accessed on 5 June 2022. For overexpression, the ORF of DrHERC7c was cloned into EcoR I and BamH I sites of pcDNA3.1/myc-His (-) A (Invitrogen). At the same time, different tags (HA, Flag) were added to the C-terminus of DrHERC7c by reverse amplification primers. For promoter analysis, 3 size-different 5′ flanking sequences of DrHERC7c including HERC7cpro-luc (−888–−1), HERC7cpro-luc (−888–−249), and HERC7cpro-luc (−248–−1) were cloned into Nhe I site of the pGL3-basic plasmid. The same method was carried out for three mutations plasmids (HERC7cpro-mut1, HERC7cpro-mut2, and HERC7cpro-mut1+2). Zebrafish plasmids DrMAVS/DrMAVS-Flag, DrSTING/DrSTING-HA, TBK1/TBK1-HA, IRF3/IRF3-HA, and IRF7/IRF7-HA were described in our previous reports [37,38]. Other plasmids including TBK1-K38M, IRF3-DN, IRF7-DN, IFNφ1pro-luc, IFNφ3pro-luc, STAT1-ΔC, and IRF9-ΔC were described previously [21,22,24,30]. Cell transfection assays were performed with polyethylenimine, Linear (PEI, MW 25,000) (Sigma-Aldrich, Shanghai, China) according to our previous reports [15,36]. Luciferase activity assays were performed by a Junior LB 9509 luminometer (Berthold, Pforzheim, Germany) using Dual-Luciferase Reporter Assay System (Promega), as described previously [15,16,33]. The results were the representative of at least three independent experiments, each performed in triplicate. Luciferase activities were normalized to the amounts of internal control Renilla luciferase activities. Cellular total RNAs were extracted by EASYspin Plus Kit (Aidlab, Beijing, China), followed by DNase treatment to remove residual DNA. First-strand cDNA was synthesized using MonScriptTM RTIII Super Mix with dsDNase Kit (Monad, Suzhou, China) according to the manufacturer’s protocol [36]. Real-time PCR (RT-qPCR) was performed with Hieff qPCR SYBR Green Master Mix (Yeasen, Shanghai, China) on the CFX96 real-time system (Bio-Rad). PCR condition was set by referring to the operation manual of the Hieff qPCR SYBR Green Master Mix. The relative expression was normalized to the expression of β-actin and represented as the fold induction relative to the expression level in the control cells that was set to 1. The primers used in this study are listed in Table 1. The primer designing principle follows a single amplification band and an amplification length between 100–250 bp. For ubiquitination assays, HEK293T cells seeded in 10 cm2 dishes were transfected with the indicated plasmids. After 30 h, the transfected cells were lysed, and the cell supernatant was incubated with Ni2+-NTA His. Bind Resin (Novagen) at 4 °C overnight, followed by Western blotting using tag-specific Abs [14]. For ISGylation assays, HEK293T cells were transfected with zebrafish HERC7c-HA together with or without 5 μg Flag-ISG15. After 30 h, the cells were collected for Western blotting with tag-specific antibodies. Student’s t-test is applied for statistical analysis of the data derived from luciferase assays and RT-PCR assays. All quantitative experiments were performed with at least three independent biological repeats. (* p < 0.05; ** p < 0.01; *** p < 0.001, ns: no significant.)

PMC10003061

Tonghao Miao,Huaxu Bao,Hui Ling,Pengwei Li,Yiling Zhang,Yan He,Xufan Hu,Chengcheng Ling,Yunyan Liu,Wei Tang,Yajing Liu,Songhu Wang

Comparative Transcriptomic Analysis Revealed the Suppression and Alternative Splicing of Kiwifruit (Actinidia latifolia) NAP1 Gene Mediating Trichome Development

24-02-2023

kiwifruit,trichome development,transcriptomic analysis,NAP1

Kiwifruit (Actinidia chinensis) is commonly covered by fruit hairs (trichomes) that affect kiwifruit popularity in the commercial market. However, it remains largely unknown which gene mediates trichome development in kiwifruit. In this study, we analyzed two kiwifruit species, A. eriantha (Ae) with long, straight, and bushy trichomes and A. latifolia (Al) with short, distorted, and spare trichomes, by second- and third-generation RNA sequencing. Transcriptomic analysis indicated that the expression of the NAP1 gene, a positive regulator of trichome development, was suppressed in Al compared with that in Ae. Additionally, the alternative splicing of AlNAP1 produced two short transcripts (AlNAP1-AS1 and AlNAP1-AS2) lacking multiple exons, in addition to a full-length transcript of AlNAP1-FL. The defects of trichome development (short and distorted trichome) in Arabidopsis nap1 mutant were rescued by AlNAP1-FL but not by AlNAP1-AS1. AlNAP1-FL gene does not affect trichome density in nap1 mutant. The qRT−PCR analysis indicated that the alternative splicing further reduces the level of functional transcripts. These results indicated that the short and distorted trichomes in Al might be caused by the suppression and alternative splicing of AlNAP1. Together, we revealed that AlNAP1 mediates trichome development and is a good candidate target for genetic modification of trichome length in kiwifruit.

Comparative Transcriptomic Analysis Revealed the Suppression and Alternative Splicing of Kiwifruit (Actinidia latifolia) NAP1 Gene Mediating Trichome Development Kiwifruit (Actinidia chinensis) is commonly covered by fruit hairs (trichomes) that affect kiwifruit popularity in the commercial market. However, it remains largely unknown which gene mediates trichome development in kiwifruit. In this study, we analyzed two kiwifruit species, A. eriantha (Ae) with long, straight, and bushy trichomes and A. latifolia (Al) with short, distorted, and spare trichomes, by second- and third-generation RNA sequencing. Transcriptomic analysis indicated that the expression of the NAP1 gene, a positive regulator of trichome development, was suppressed in Al compared with that in Ae. Additionally, the alternative splicing of AlNAP1 produced two short transcripts (AlNAP1-AS1 and AlNAP1-AS2) lacking multiple exons, in addition to a full-length transcript of AlNAP1-FL. The defects of trichome development (short and distorted trichome) in Arabidopsis nap1 mutant were rescued by AlNAP1-FL but not by AlNAP1-AS1. AlNAP1-FL gene does not affect trichome density in nap1 mutant. The qRT−PCR analysis indicated that the alternative splicing further reduces the level of functional transcripts. These results indicated that the short and distorted trichomes in Al might be caused by the suppression and alternative splicing of AlNAP1. Together, we revealed that AlNAP1 mediates trichome development and is a good candidate target for genetic modification of trichome length in kiwifruit. Kiwifruit (Actinidia chinensis) is a popular and health-beneficial fruit because of its high vitamin C content and balanced nutrients, including dietary fiber, various minerals, and other metabolites [1,2]. Kiwifruit consumption improves immune, digestive, and metabolic health and even provides anticancer effects [3,4]. Fruit hair (trichome) is an important appearance quality that affects kiwifruit popularity in the market [5]. Some cultivars, such as A. deliciosa ‘Hayward’, have long coarse trichomes, which are generally considered a commercial disadvantage [5]. The surface trichomes of ‘Hayward’ could be removed by brushing for customer favor, but brushing accelerates kiwifruit softening and reduces the shelf life [6]. A. deliciosa was crossed with A. arguta, which has hairless and edible fruit skins, in order to breed a new cultivar with hairless skins [7]. Although micromorphological characters of trichomes have been used to analyze phylogenetic relationships within the genus Actinidia [8], little is known about kiwifruit’s genes mediating trichome development. Trichomes are epidermal protrusions that developed from the surfaces of leaves, stems, flowers, seed coats, and fruits. Trichomes protect plants from insect predation, UV radiation, and excess transpiration [9]. In Arabidopsis, the genes mediating trichome development have been extensively identified [10,11,12]. The initiation and development of trichome are majorly regulated by the transcriptional complex involving three types of transcription factors (TFs): the R2R3 MYB, basic helix-loop-helix (bHLH), and WD40 repeat (WDR) protein. In the R2R3 MYB family, GLABROUS 1 (GL1) [13], MYB23 [14], and MYB82 [15] are involved in trichome development and differentiation. The bHLH TFs affecting trichome development include GLABROUS 3 (GL3) [16], ENHANCER OF GL3 (EGL3) [17], TRANSPARENT TESTA 8 (TT8) [18], and MYC1 [19]. TTG1, a WDR gene, mediates trichome differentiation [20]. Some R3 MYBs, which include TRIPTYCHON (TRY) [21], CAPRICE (CPC) [22], ENHANCER OF TRY AND CPC1 (ETC1, ETC2, and ETC3) [23,24], and TRICHOMELESS 1 (TCL1 and TCL2) [25,26], are negative regulators of trichome development. Additionally, phytohormones, miRNA, and ubiquitin/26S proteasome can affect trichome development by directly or indirectly targeting the TFs mediating trichome development [10,12,27,28,29,30]. For instance, the ubiquitin protein ligase 3 (UPL3) is involved in trichome development by mediating proteasomal degradation of GL3 and EGL3 [27]. The ARP2/3-mediated nucleation of actin filaments is involved in trichome development [31,32]. The SCAR/WAVE complex is the major activator of ARP2/3-mediated F-actin nucleating and branching [33]. A defect in Nck-associated protein 1 (NAP1), a subunit of the SCAR/WAVE complex, causes short and distorted trichomes in Arabidopsis [34,35]. In soybean, two mutants with shorter and distorted trichome were revealed by map-based cloning to be caused by loss-of-function mutations in Glycine max NAP1 (GmNAP1) [36,37]. These results indicated that NAP1 plays an important role in trichome development. Transcriptomic analysis has been widely used to discover the genes mediating trichome development in different species, such as tomato [38], cucumber [39], Lilium pumilum [40], and medicinal cannabis [41]. In this study, we analyzed two kiwifruit species (A. eriantha [42] with long bushy trichomes and A. latifolia [43] with short, sparse trichomes) by second- and third-generation transcriptome analysis. Our results indicated that the expression level of the NAP1 gene was much lower in A. latifolia than that in A. eriantha. Meanwhile, we discovered that there is alternative splicing of NAP1 mRNA in A. latifolia, which might be responsible for the shorter trichomes in A. latifolia. The fruits of A. latifolia (Al) are sparsely covered by short trichomes (Figure S1A), while A. eriantha (Ae) fruits are densely covered by long intertwining trichomes (Figure S1A), which is consistent with the previous observation [44]. The contrasting distribution patterns between Al and Ae trichomes were also observed in the petiole of mature leaves (Figure 1A–D). The epidermis of Al petiole is attached with short trichomes (Figure 1D,F), and the average length of trichomes is 100 μm (Figure 1G). The trichomes of Ae petioles are much longer than that in Al (Figure 1C,E,G). Additionally, the trichome density in Ae petioles is much higher than that in Al (Figure 1H). It is worth mentioning that Al trichomes are mildly distorted and brown (Figure 1F), while Ae trichomes are straight and colorless (Figure 1E). These observations indicated that the morphologic characterizations of Al and Ae trichomes are quite different. Since the time of flowering and fruit setting is quite different between these two species, the climatic conditions will dramatically affect the gene expression if we harvest the fruits at different times to perform the transcriptome analysis, which will obstruct our digging for the differentially expressed genes mediating trichome development. Considering that trichome distribution patterns on the fruits are similar to that on the petiole of mature leaves in two species (Figure 1), we used the petioles of mature leaves from the plants of two species grown in the same field for the RNA sequencing. Because the genome sequence of Al is lacking, the third-generation (full-length) RNA sequencing of mature leaves, including the petioles from Al and Ae, was performed to facilitate gene annotations. As shown in Table 1, we obtained 135,286 and 156,752 high-quality isoforms from third-generation RNA sequencing of Al and Ae, respectively. Among them, there are 126,102 and 93,226 non-redundant transcripts for Al and Ae, respectively (Table 1). These transcript sequences will contribute to gene annotations and further functional characterization. Meanwhile, three biological replicates of the epidermis of petioles samples from Al (Al-q1, -q2, and -q3) and Ae (Ae-q1, -q2, and -q3) were harvested for the second-generation RNA sequencing. The PCA analysis indicated that there is a high correlation among the three samples of each cultivar, suggesting a high repeatability of RNA sequencing results (Figure S2). Next, we discovered 88,270 differentially expressed transcripts (DETs) (listed in Table S1), including 39,879 up-regulated and 48,391 down-regulated transcripts between Al and Ae samples (Table 2). These DETs were also mapped to the genome of ‘White’ [42], which is provided by the kiwifruit genome database (http://kiwifruitgenome.org/, accessed on 3 October 2021) [45], and 12,950 differentially expressed genes (DEGs) were identified (Table 2). KEGG analysis of DEGs indicated that the pathways of RNA metabolisms, including RNA processing (spliceosome), transport, degradation, surveillance, and polymerase (synthesis), were enriched (Figure 2). No pathway of trichome development has been identified in KEGG enrichment. Next, we screened out the homologous genes of trichome development-regulating genes in Arabidopsis from all the DEGs and compared their expressions between Al and Ae (Figure 3A). Unexpectedly, the expression levels of most genes encoding a positive regulator of trichome development in Al, such as GL3, TTG1, TTG2, Constitutive Expressor of Pathogenesis-Related Genes5 (CPR5) [46], Zinc Finger Protein5 (ZFP5) [47], and GENERAL CONTROL NON-REPRESSED PROTEIN5 (GCN5) [48], are higher than that in Ae (Figure 3A) while most of the genes encoding negative regulators, such as CPC, SPINDLY (SPY) [28], Jasmonate ZIM (JAZ) [29], and SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 9 (SPL9) [30], are down-regulated in Al but up-regulated in Ae (Figure 3A). These results were opposite to our expectation since Al with fewer trichomes are supposed to down-regulate the positive regulators or up-regulate the negative regulators. The expression level of UPL3, a negative regulator, appeared to be lower in Ae than in Al (Figure 3A), which requires further verification. Only one positive regulator, NAP1, as highlighted in yellow in Figure 3A, showed low expression in Al but a high expression in Ae, which is consistent with the phenotypic observation. Our qRT-PCR analysis confirmed that the expression patterns of NAP1 and other regulators of trichome development are consistent with the results of RNA seq (Figure 3B). These results indicated that down-regulated NAP1 in Al might contribute to the phenotype that Al has short, sparse trichomes. To clone the NAP1 gene in kiwifruit, we used the samples for RNA-seq as a template and the same pair of primers targeting the 5′ and 3′ UTRs of both AeNAP1 (DTZ79_14g00610, accession number of Ae genome) and AlNAP1 to perform RT-PCR. The results showed that Ae has a clear band with the expected size (Figure 4A), while Al has two alternatively spliced bands, named AlNAP1-AS1 and AlNAP1-AS2, in addition to the full-length band AlNAP1-FL (Figure 4A). These bands were cloned and analyzed by Sanger sequencing. The results indicated that the encoding sequences of AeNAP1 and AlNAP1-FL are almost the same except for two SNPs causing the substitution of two amino acids (Figure S3). We identified the 23 exons of AlNAP1 by comparing its cDNA sequence with the genome sequence of AeNAP1 Locus (Figure 4B). The sequencing results of AlNAP1-AS1 and AlNAP1-AS2 indicated that AlNAP1-AS1 is short of the exons from 16th to 22nd, while AlNAP1-AS2 lacks most exons but remains the 1st and 23rd exons linked with two introns (Figure 4B). The motif-based sequence analysis [49] indicated that AeNAP1 and AlNAP1-FL contain 15 conserved motifs that are present in all NAP1 proteins from Arabidopsis, rice, and soybean (Figure 4C). AlNAP1-AS1 encodes a short protein lacking the conserved motif 1, 6, 11, 12, and 15 (Figure 4C), while AlNAP1-AS2 encodes a very short peptide having no similarity with NAP1, suggesting that AlNAP1-FL might have the conserved function in trichome development while the AlNAP1-AS1 and -AS2 should lose the function. The qRT−PCR indicated that the expression level of all transcripts of AlNAP1, including AlNAP1-FL, -AS1, and -AS2 is about 40% of that of AeNAP1 (Figure 4D). The expression of AlNAP1-FL is only 8% of that of AeNAP1 (Figure 4D). These results indicated that the alternative splice of AlNAP1 further decreases the level of functional proteins. Moreover, the alternatively spliced bands of NAP1 were also amplified by RT−PCR from the epidermal tissues of Al young fruits but not from that of Ae fruits (Figure S1B), suggesting that the alternative splice of AlNAP1 occurs in both leaves and fruits. To verify the function of AlNAP1 in trichome development, we tried to express AlNAP1-FL and AlNAP1-AS1 in the mutant nap1-2 (SALK_014298, nap1 for short) of Arabidopsis [34]. A his-tag was fused to the C terminus of AlNAP1-FL and AlNAP-AS1, respectively, and the fused genes were driven by the CaMV35S promoter (Figure 5A). The nap1 mutant was transformed by the agrobacteria containing the construct of 35S:: AlNAP1-FL-His and 35S::AlNAP1-AS1-His, respectively. Three independent transgenic lines for each construct were identified by Western blot analysis using anti-His antibodies (Figure 5B). The nap1 mutant showed shorter and distorted trichomes [34] compared with the Col-0 (Figure 5C,D). Three independent transgenic lines of nap1/AlNAP1-FL (−1, −2, and −3) showed similar phenotypes in that their trichomes are long and straight (Figure 5C just showed the trichomes of nap1/AlNAP1-FL-1). The trichomes of nap1/AlNAP1-FL-1 are much longer than that of nap1 and indistinguishable from that of Col-0 plants (Figure 5D). However, three transgenic lines of nap1/AlNAP1-AS1 (−1, −2, and −3) showed short and distorted trichomes (Figure 5C just showed the trichomes of nap1/AlNAP1-AS1-1), which are as short as that of nap1 mutant (Figure 5D). The trichome density of the nap1 mutant is not altered by AlNAP1-FL or AlNAP1-AS1 overexpression (Figure 5D). These results indicated that AlNAP1-FL, but not AlNAP1-AS1, rescued the defects of trichome development in the nap1 mutant. The trichomes protect plants from mechanical damage, insect predation, UV radiation, and excess transpiration [9]. In kiwifruit, trichomes might play a role in the resistance to bacterial canker caused by Pseudomonas syringae pv. Actinidiae [50]. Commercially, trichomes affect the kiwifruit popularity in the market [5]. Although brushing with commercial brushes has been practically used to remove the surface trichomes of kiwifruit, brushing promotes kiwifruit softening and reduces the shelf life [6]. Therefore, it is better to breed new kiwifruit cultivars with shorter and fewer trichomes or genetically modify the popular cultivar by targeting the key genes mediating trichome development. The genes regulating trichome development have been extensively identified in Arabidopsis [10,11,12]. To the best of our knowledge, no such gene has been characterized in kiwifruit. In this study, we observed that Al has short, mildly distorted, and brown trichomes (Figure 1F), while Ae has long, straight, and colorless ones (Figure 1E). The trichome density in Al petioles is much lower than that in Ae (Figure 1H). By the second- and third-generation transcriptome analysis, we revealed that the mRNA levels of most DEGs mediating trichome development are contrary to the observed phenotypes of trichome (Figure 3). Only NAP1 expression, which is lower in Al than in Ae, is consistent with the trichome phenotypes (Figure 3). NAP1, a subunit of the SCAR/WAVE complex, is required for the activation of the Arp2/3 complex, which is a crucial regulator of actin nucleation and branching. A defect on NAP1 gene causes short and distorted trichomes in both Arabidopsis [34,35] and soybean [36,37], although the underlying mechanisms of regulating trichome development remains largely unknown. In our study, the alternative splicing of AlNAP1 mRNA occurs in both leaves and fruits of Al but not in that of Ae (Figure 4 and Figure S1B). Sanger sequencing indicated that two spliced mRNA, AlNAP1-AS1 and AlNAP1-AS2, lost 7 exons and 21 exons, respectively (Figure 4B). AlNAP1-AS2 encodes a totally different protein that has no similarity with NAP1. AlNAP1-AS1 encodes a short protein lacking the conserved motif 1, 6, 11, 12, and 15 (Figure 4C) and cannot rescue the defects of trichome development in mutant nap1 of Arabidopsis (Figure 5), suggesting that AlNAP1-AS1 is not a functional protein. The alternative splicing further down-regulated the expression level of AlNAP1-FL (Figure 4D), which has been verified to have functions in regulating trichome development (Figure 5). Defects on NAP1 genes cause shorter and distorted trichome in Arabidopsis [34] and soybean [36,37]. Therefore, we speculate that the suppression and alternative splicing of AlNAP1 is responsible for the short, mildly distorted trichome of Al. Considering that the trichome densities in nap1 mutant and nap1/AlNAP1-FL plants are not altered compared to that of Col-0 (Figure 5), we believe that low trichome density in Al has nothing to do with the AlNAP1 gene. Of course, verification of our speculation requires further investigations, such as genetic modification of the NAP1 gene in Al, which is currently not practicable because the method of Al transformation is not established yet. As for the reason why alternative splicing of NAP1 exists in Al but not in Ae, we revealed that the genes belonging to spliceosome were most significantly enriched in our transcriptomic analysis (Figure 2). Differentially expressed spliceosome genes in Al might contribute to the alternative splicing of AlNAP1. To date, no spliceosome gene has been demonstrated to participate in trichome development. It will be interesting to figure out which spliceosome gene plays a key role in the processing of AlNAP1 in the future. Among the negative regulators identified by our transcriptome, UPL3 appeared to have lower levels in Ae than in Al (Figure 3A). UPL3 is an E3 ligase mediating ubiquitin/26S proteasome-dependent degradation of GL3 and EGL3 [27]. Overexpression of GL3 significantly increased the trichome number in Arabidopsis [16] and even had a stronger effect on trichome density in the upl3 mutant [27]. Therefore, we speculate that the lower expression of UPL3 in Ae might cause the increased protein abundance of GL3, which might be responsible for the high trichome density in Ae. Together, our results indicate that the shorter and distorted trichomes in Al might be caused by the suppression and alternative splicing of AlNAP1, which can be a potential target for genetic modification of trichome length in kiwifruit. The kiwi species “Actinidia eriantha” and “Actinidia latifolia” were grown on a kiwi plantation at Anhui Agricultural University. Hefei, China. The leaves and petioles of “Actinidia eriantha” and “Actinidia latifolia” with similar development periods and states were cut down and immediately frozen in liquid nitrogen and stored at −80 °C. The Arabidopsis nap1 mutant strain SALK_014298 was ordered from the AraShare Science website (www.arashare.cn, accessed on 10 November 2021). Homozygous plants were identified by the triple primer method, as described previously. Arabidopsis Columbia ecotype (Col-0) and nap1 mutant were sterilized and vernalized for 3 d at 4 °C and then were sown on MS medium for 10 d under 14 h light/10 h dark cycle at 22 °C. Then, Arabidopsis seedlings were transferred to a soil mixture of vegetative soil and vermiculite (3:1, v/v) and grown at a long-day condition (22 °C, 14/10-h light/dark). RNA was extracted from the leaves of “Actinidia eriantha” and “Actinidia latifolia” using an RNA plant plus Reagent kit (TianGen, Beijing, China) and transcribed into cDNA using the PrimeScript® RT reagent kit (Perfect Real Time, TaKaRa). Fluorescent quantitative primers were designed by Primer-BLAST in NCBI (www.ncbi.nlm.nih.gov/tools/primer-blast/, accessed on 25 November 2021). The qRT–PCR was carried out using the CFX connectTM Real-Time System (BIORAD, US), qRT–PCR reactions were as follows: pre-denaturation at 95 °C for 10 min, denaturation at 95 °C for 15 s, annealing at 56 °C for 15 s, extension at 65 °C for 10 s, 40 cycles, relative expression values were analyzed via the cycle threshold (Ct) 2−ΔΔCT method [51]. Three biological replicates for each sample and three technical replicates for each biological replicate. The qRT−PCR primers are listed in Supplemental Table S2. The full-length cDNA of AlNAP1 and AeNAP1 were amplified with the first strand cDNA using the forward primer 5′-TCCAACAATCGGCCTTCCCTAC-3′ and the reverse primer 5′-AGGACCAGACCTTGACACAGC-3′, respectively. The genes were amplified by PrimeSTAR® Max DNA Polymerase (Takara, Dalian, CN), and PCR reaction conditions were pre-incubation at 98 °C for 3 min, followed by 35 cycles of 98 °C (30 s), 55 °C (30 s), and 72 °C (5 min), with a final extension at 72 °C for 5 min. The PCR product was recovered, ligated to the pESI-Blunt simple vector, and then transferred into E. coli. Recombinant clones were identified by PCR and sequencing. A His-tag (6×His) was fused to the coding sequence of AlNAP1-FL and AlNAP1-AS1, respectively, by PCR. The fused genes AlNAP1-FL-His and AlNAP1-AS1-His were transformed into the expression vector pCAMBIA1302. The constructed vectors 35S::AlNAP1-FL-His and 35S::AlNAP1-AS1-His were transformed into Arabidopsis nap1 mutant strain using the floral dip transformation method as described previously [52]. Transgenic lines were then screened with 60 mg/L hygromycin. Two independent transgenic plants for each vector were identified and used for further experiments. Sequence alignments were performed using ApE software, a phylogenetic tree was performed using the neighbor-joining method by the MEGA (ver. 7.1), and protein domains were analyzed using the NCBI Conserved Domain Search website (www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 8 January 2022). The motifs of the NAP1 gene were further analyzed using the MEME—MEME Suite website (meme-suite.org, accessed on 10 January 2022) [49]. Since the time of flowering and fruit setting is quite different between these two species, the climatic conditions will dramatically affect the gene expression if we harvest the fruits at different times to perform the transcriptome analysis, which will obstruct our digging for the differentially expressed genes mediating trichome development. Considering that trichome distribution patterns on the fruits were similar to that on the petiole of mature leaves in two species, we used the mature leaves and the epidermal tissues of the petiole for third- and second-generation transcriptome analysis, respectively. For the third-generation transcriptome, we just had one sample, which is a mixture of three leaves from different trees. Total RNA was extracted from the mature leaves (including petioles) of “Actinidia eriantha” and “Actinidia latifolia” and used for third-generation transcriptome analysis. For the second-generation transcriptome, we have three samples (biological replicates) for each specie, which means that three petioles were detached from three different trees. Total RNA was also extracted from epidermal tissues of petioles and used for second-generation transcriptome analysis. The RNA sequencing and analysis were performed by Biomarker biotech Co., Ltd. (Qingdao, China). Briefly, after total RNA was extracted, eukaryotic mRNA was enriched by magnetic beads with Oligo (dT) and then was randomly interrupted by fragmentation buffer. One-stranded cDNA was synthesized from the interrupted mRNA template using six-base random primers. Then, the second cDNA strand was synthesized by adding buffer, dNTPs, RNase H, and DNA polymerase I. The resulting double-stranded cDNA was purified using AMPure XP beads, and the terminal was repaired, added with A tail, and connected with the sequencing connector, and then AMPure XP beads were used to select the fragment size, and the cDNA library was obtained by PCR enrichment. The constructed library was sequenced using the Illumina platform to generate 150 bp double-ended reads; the total read is above 6G bp. The RNA sequencing data were obtained from three biological replicates, and PCA analysis was used as an assessment indicator of biological repeat relevance. PCA analysis was performed using the base package stats in R (v3.1.1), and visualization was performed using the ggplot2 package (v1.0.1). The data were obtained from three biological replicates, use of Spearman’s correlation coefficient R as an assessment indicator of biological repeat relevance. The expressed genes were analyzed; log2 fold change values > 1 and log2 fold change values < −1 were considered significant. The significantly induced (>2-fold) and repressed (<0.5-fold) genes are listed in Supplemental Table S1. Approximately 500 mg of Arabidopsis seedlings were ground in a 2× Laemmli sample buffer containing 100 mM Tris-HCl (pH6.8), 4% SDS, 0.2% BPB (bromophenol blue), 2% beta-ME, and 20% glycerol. The samples were boiled at 100 °C for 15 min and then centrifuged for 10 min at 12,000 rpm. Protein extracts were separated on a 10% SDS-PAGE and transferred to PVDF blotting membranes as described previously [53]. The 35S::AlNAP1-FL-His and 35S::AlNAP1-AS1-His protein amounts were determined by protein gel blotting using anti-His antibodies. Epidermal samples were photographed under a microscope (E200MV; Nikon, Nanjing, China), and the length and density of epidermal fur were measured by ImageJ-Win64 software. The data were obtained from three biological replicates. SPSS v21 (Statistic Package for Social Science) software was used to analyze the significance of the differences. The mean values ± SD from three replicates are presented, and significant differences compared with the control were determined by Student’s t-test (* indicates p < 0.05; ** indicates p < 0.001). In this study, we observed that Ae has long, straight, and high-density trichomes, while Al has short, distorted, and low-density trichomes. The second- and third-generation transcriptomic analysis indicated that the expression of the NAP1 gene was suppressed in Al compared with that in Ae. Additionally, alternative splicing of AlNAP1 existed in both leaves and fruits of Al but not in that of Ae. The defects of trichome development in Arabidopsis nap1 mutant were rescued by full-length AlNAP1 but not by the spliced transcript of AlNAP1. AlNAP1 gene overexpression does not affect trichome density in nap1 mutant or wild-type plants. The alternative splicing further decreased the level of functional transcript AlNAP1-FL, which might cause the short and distorted trichomes in Al. Overall, we revealed that AlNAP1 mediates trichome development and is a good candidate target for genetic modification of trichome length in kiwifruit.

PMC10003063

Yumeng Jia,Xin Qi,Mei Ma,Shiqiang Cheng,Bolun Cheng,Chujun Liang,Xiong Guo,Feng Zhang

Integrating genome-wide association study with regulatory SNP annotations identified novel candidate genes for osteoporosis

20-02-2023

Osteoporosis,Bone mineral density,Regulatory single nucleotide polymorphism,Genome-wide association studies,Bone mineral density (BMD),single nucleotide polymorphisms,cartilage,chondrocyte,metabolic bone disease,mesenchymal stem cell (MSC),hip,osteoblasts,RNAs

Aims Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. Methods We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects. Results Through discovery and replication integrative analysis for BMD GWAS and rSNP annotation database, we identified 36 common BMD-associated genes for BMD irrespective of regulatory elements, such as FAM3C (pdiscovery GWAS = 1.21 × 10-25, preplication GWAS = 1.80 × 10-12), CCDC170 (pdiscovery GWAS = 1.23 × 10-11, preplication GWAS = 3.22 × 10-9), and SOX6 (pdiscovery GWAS = 4.41 × 10-15, preplication GWAS = 6.57 × 10-14). Then, for the 36 common target genes, multiple gene ontology (GO) terms were detected for BMD such as positive regulation of cartilage development (p = 9.27 × 10-3) and positive regulation of chondrocyte differentiation (p = 9.27 × 10-3). Conclusion We explored the potential roles of rSNP in the genetic mechanisms of BMD and identified multiple candidate genes. Our study results support the implication of regulatory genetic variants in the development of OP. Cite this article: Bone Joint Res 2023;12(2):147–154.

Integrating genome-wide association study with regulatory SNP annotations identified novel candidate genes for osteoporosis Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects. Through discovery and replication integrative analysis for BMD GWAS and rSNP annotation database, we identified 36 common BMD-associated genes for BMD irrespective of regulatory elements, such as FAM3C (pdiscovery GWAS = 1.21 × 10-25, preplication GWAS = 1.80 × 10-12), CCDC170 (pdiscovery GWAS = 1.23 × 10-11, preplication GWAS = 3.22 × 10-9), and SOX6 (pdiscovery GWAS = 4.41 × 10-15, preplication GWAS = 6.57 × 10-14). Then, for the 36 common target genes, multiple gene ontology (GO) terms were detected for BMD such as positive regulation of cartilage development (p = 9.27 × 10-3) and positive regulation of chondrocyte differentiation (p = 9.27 × 10-3). We explored the potential roles of rSNP in the genetic mechanisms of BMD and identified multiple candidate genes. Our study results support the implication of regulatory genetic variants in the development of OP. Cite this article: Bone Joint Res 2023;12(2):147–154. To access the genetic mechanism of osteoporosis (OP) using the integrative analysis of genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information of bone mineral density (BMD). We performed functional enrichment analysis of the common candidate genes associated with BMD. A total of 36 target regulatory genes were detected for BMD such as FAM3C, CCDC170, SOX6, and PLEKHM1. We detected 12 BMD-associated gene ontology terms such as muscle cell differentiation, positive regulation of cartilage development, and positive regulation of chondrocyte differentiation. Integrating analysis of GWAS and rSNP has a boosting power for regulatory genetic variant detection. One of the main limitations is that rSNP analysis could not take tissue or cell types into account. Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in the density of bone. Multiple risk factors contribute to the development of OP such as hormone changes, gut microbiome, the use of certain drugs, and cigarette smoking. In the USA, millions of people either already have OP or are at high risk due to low bone mass. OP is more common in postmenopausal women, which leads to heavy burden on the healthcare system and society. Bone mineral density (BMD) is one of the major diagnostic indexes of OP. A recent study suggested that bone density had a strong genetic determination, with an estimated heritability ranging from 61% to 83%. More than 50 susceptibility loci have been identified for BMD or OP, such as LRP5, MEPE, SPTBN1, and DKK1. For instance, genome-wide association studies (GWASs) have led to the identification of 100 loci associated with BMD and other bone traits related to risk of fracture. However, only a small percentage of the heritability of BMD can be explained by the susceptibility genetic variants discovered so far, suggesting the existence of undiscovered causal genetic factors for BMD. Although GWASs have achieved great success in identifying the susceptible loci of complex diseases, there are several issues and limitations associated with these genetic association studies. GWAS signals often lie in non-coding regions, which may harbour regulatory elements affecting gene expression, such as expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs). However, it is difficult to identify the precise causal SNP and causal gene for these noncoding variants. These causal genetic variants within non-coding regulatory regions are indistinguishable from the neighbouring markers. Regulatory single nucleotide polymorphisms (rSNPs) refer to the SNPs that are associated with the regulation of gene expression levels through transcription factor binding, chromatin interaction, circular RNA (circRNA)-mediated post-transcriptional regulation, and so on. Hindorff et al have illustrated that a lot of risk SNPs could affect phenotypes in a non-coding manner, for instance impacting gene regulation. Integrating GWAS datasets with rSNPs has the potential to reveal novel susceptibility genetic variants for human complex diseases. A previous study has shown that a rSNP in the Cx43 promoter region plays a critical role in Tetralogy of Fallot (TOF), by impacting the transcriptional activity. Furthermore, Yeo et al reported that low-effect chronic obstructive pulmonary disease (COPD) risk SNPs were identified through enrichment of cis-regulatory SNPs in genes. In this study, we conducted an integrative analysis of GWAS and large-scale rSNP annotation data for BMD, containing seven regulatory genetic elements. The significant loci identified by the GWAS of BMD were firstly annotated with the rSNP annotation database to obtain BMD-associated regulatory genetic elements and their target genes. To explore the functional relevance of identified candidate genes, the common candidate genes identified by both discovery and replication studies were further subjected to gene ontology (GO) functional enrichment analysis. The GWAS summary dataset of BMD was drawn from the GEnetic Factors for OSteoporosis (GEFOS) Consortium, containing a total of 52,236 individuals of European ancestry. Briefly, the GEFOS project used meta-analysis of whole genome sequencing, whole exome sequencing, and deep imputation of genotype data to identify candidate variants associated with the risk of BMD. Single variants with a minor allele frequency (MAF) > 0.5% were tested for an additive effect on femoral neck BMD (FN-BMD), lumbar spine BMD (LS-BMD), and forearm BMD (FA-BMD), adjusting for sex, age, age_squared, and weight as covariates. Detailed information of the subjects, genotyping, imputation, and quality control can be found in a previously published study. The replication GWAS summary dataset of BMD was drawn from the UK Biobank database. In summary, the UK Biobank BMD GWAS dataset contains 452,264 participants. The BMD values of bones and joints were measured using dual-energy X-ray absorptiometry in this study. DNA was extracted from stored blood samples and shipped to Affymetrix Research Services Laboratory for genotyping. SNP genotyping was performed using the UK Biobank Axiom array. Genotypes were imputed by IMPUTE4. Principal component analysis (PCA) was used to account for potential population structure in both marker- and sample-based quality control procedures. Detailed information of the subjects, genotyping, imputation, and quality control can be found in two previously published studies. The rSNP annotation data were collected from the rSNPBase 3.1 database. There are seven types of regulatory elements, including 7,562,592 annotation terms for transcription factor binding regions (TFBRs) from the Encyclopaedia of DNA Elements (ENCODE) project, 212,837 for chromatin interactive regions (CIRs) from the ENCODE project, 2,794 for mature microRNA (miRNA) regions from miRbase, 384,284 for predicted miRNA target sites from TargetScan and miRNAda, 211,749 for long non-coding RNA (lncRNA) regions from LNCipedia, 38,916 for topologically associated domains (TADs) from ENCODE-processed data, and 312,673 for circRNAs from CircNet. Except for circRNAs, target gene analyses were performed on the other six types of regulatory elements to get corresponding elements-gene (E-G) pairs. For regulatory E-G pairs of transcriptional regulation, chromosome location was acquired from ENCODE Consortium, among which TFBR information was acquired from proceeded ChIP-seq peak data, CIR information was acquired from Chromatin Interactions by 5 C and ChIA-PET, and TAD information was acquired from proceeded Hi-C data. Ensembl recorded genes on hg19 coordinate was used to analyze the genome locations of these three types of regulatory elements through the potential promoter region (from 2 k upstream to 1 k downstream of transcription). For E-G pairs of non-coding RNAs, miR2Disease, miRTarBase, and lncRNA2Target databases were integrated into rSNPBase for miRNA-gene and lncRNA-gene pairs with experimentally supported target relations through RT-PCR, microarray, or RNA-seq. Moreover, TargetScan and miRnada databases were used to obtain predicted miRNA target sites, which were mapped to human genome sequence (on hg 19 coordinate). The functional association between the included regulatory elements and target genes was analyzed with genomic proximity or by using widely used reference databases as mentioned above. Firstly, significant SNPs were selected from the discovery GWAS dataset with p-value < 5 × 10-8, and then were annotated in rSNPBase 3.1 to obtain BMD-associated SNP regulatory elements and E-G pairs. Then, the other GWAS replicate summary dataset of BMD was used to validate the integration results with p-value < 5 × 10-8. Finally, we selected the common genes between the discovery and replication analysis results. A flowchart for this study is depicted in Figure 1. For the BMD-associated genes overlapping in both discovery and replicate studies, GO enrichment analysis was conducted by HumanNet v2, a database of human gene networks. The network of HumanNet-XC (Functional gene network extended by Co-citation) and the network-based disease gene prediction of HumanNet were used in our study. The significant SNPs with GWAS p-value < 5 × 10-8 were selected from both the discovery and replication GWAS summary dataset of BMD. To explore the functional relevance of identified common genes shared by both the discovery and replicate studies, GO and pathway enrichment analyses were performed by HumanNet-XC and the network-based disease gene prediction of HumanNet. The significance threshold was set as p < 0.05. In discovery GWAS dataset study, for FA-BMD, we detected six rSNPs for TFBRs, 14 rSNPs for TADs, and 12 rSNPs for CIRs, corresponding to four, three, and six target regulatory genes, respectively. For circRNA region, 108 rSNPs were identified for FA-BMD, 16 of which have been demonstrated as eQTLs in a previous study by Guo et al (Supplementary Table i). For FN-BMD, we detected 20 rSNPs for TFBRs, 140 rSNPs for TADs, 53 rSNPs for CIRs, and 15 rSNPs for lncRNAs, corresponding to 19, 33, 49, and four target regulatory genes, respectively. For circRNA region, 135 rSNPs were identified for BMD, 100 of which have been demonstrated as eQTLs by Guo et al (Supplementary Table ii). For LS BMD, we detected 32 rSNPs for TFBRs, 268 rSNPs for TADs, 69 rSNPs for CIRs, and six rSNPs for lncRNAs, corresponding to 18, 31, 44, and four target regulatory genes, respectively. For circRNA region, 400 rSNPs were observed for BMD, 204 of which have been identified as eQTLs by Guo et al (Supplementary Table iii). For the replication results, we detected 533 rSNPs for TFBRs, 4298 rSNPs for TADs, 1336 rSNPs for CIRs, one rSNP for miRNA, six rSNPs for predicted miRNA target site, and 365 rSNPs for lncRNAs, corresponding to 1,136, 2,645, 2,275, four, 12, and 380 target regulatory genes, respectively. For circRNA region, 6,446 rSNPs were identified for BMD, 90 of which have been demonstrated as eQTLs by Guo et al (Supplementary Table iv). After comparing the discovery and replication study results, we identified four overlapped target regulatory genes for TFBRs, 30 overlapped target regulatory genes for TADs, and 14 overlapped target regulatory genes for CIRs, respectively (Table I). Irrespective of different regulatory genetic elements, 36 target regulatory genes were detected for BMD, such as FAM3C for TADs and CIRs (pdiscovery GWAS = 1.21 × 10-25, beta = 0.186, preplication GWAS = 1.80 × 10-12), CCDC170 for TADs (pdiscovery GWAS = 1.23 × 10-11, beta = -0.053, preplication GWAS = 3.22 × 10-9), SOX6 for TADs (pdiscovery GWAS = 4.41 × 10-15, beta = 0.080, preplication GWAS = 6.57 × 10-14), and PLEKHM1 for TADs (pdiscovery GWAS = 1.75 × 10-8, beta = 0.085, preplication GWAS = 1.56 × 10-15). For the 36 target genes shared by both discovery and replication study, GO enrichment analysis detected 12 GO terms with p < 0.01 for BMD, such as positive regulation of cartilage development (p = 9.27 × 10-3), positive regulation of chondrocyte differentiation (p = 9.27 × 10-3), muscle cell differentiation (p = 5.31 × 10-3), and regulation of p38 mitogen-activated protein kinase (p38MAPK) cascade (p = 5.31 × 10-3) (Table II). Recent studies have demonstrated the important roles of regulatory genetic variants in the genetic mechanism of human complex diseases. To explore the functional relevance of regulatory genetic variants with BMD and identified novel candidate genes for OP, we conducted an integrative analysis of GWAS with rSNP annotation information. We identified multiple rSNPs and their target genes for BMD. Further functional analysis of the identified target genes supports the important roles of rSNPs in the development of OP. One important finding of this study is FAM3C, which was detected between discovery and replication studies. FAM3C, a member of the family with sequence similarity 3 (FAM3), encodes a secreted protein with a GG domain. In a three-stage genome-wide association (GWA) meta-analysis study, FAM3C was confirmed to be associated with BMD. Additionally, a follow-up study in Caucasians observed that rs7776725 influenced BMD at multiple skeletal sites. Interestingly, the variant rs7776725 was located in the first intron of the FAM3C gene. Notably, several other SNPs identified in this gene were also associated with BMD at multiple sites, indicating that FAM3C may play a notable role in bone metabolism. Furthermore, the SNP rs7776725 in FAM3C was also proved to be associated with a genome-wide substantially increased risk of forearm fracture.FAM3C was demonstrated to play a functional role in the regulation of osteoblast differentiation. In differentiating osteoblasts, knockdown of FAM3C increased alkaline phosphatase expression and activity whereas overexpression of FAM3C reduced it. Furthermore, FAM3C and TGF-β1 were found to regulate each other reciprocally. Furthermore, our analysis found that rs7776725 targeted FAM3C and PTPRZ1 through regulating CIRs and TADs, which belong to transcriptional regulation. Previous studies have shown that FAM3C indeed has an effect on bone metabolism-related disease through transcriptional regulation, which was consistent with our analysis. SOX6 is another important gene, which encodes transcription factor SOX-6. It has been reported that the SOX6 gene is an essential transcription factor in chondrogenesis and cartilage formation. For example, SOX6 was discovered to have differential expression during osteoblast development. Homozygous Sox6 mutant (Sox6-/-) mice were born with relatively mild skeletal anomalies and mesenchymal condensations, but there was no overt chondrocyte differentiation. Moreover, expression of chondrocyte marker genes was severely reduced in Sox6 mutant mice. Sox5, Sox6, and Sox9 are necessary for chondrogenic differentiation at different steps, the combination of which provides a new in vitro chondrogenic differentiation model. In addition, several studies have identified that hip BMD was associated with rs7117858, which is located downstream of the SOX6 gene. Furthermore, multiple SNPs located in the SOX6 gene were identified to be associated with hip BMD in both Caucasian and Chinese populations, which further highlights the importance of the role of SOX6 in influencing BMD variation. Besides, Sox9/Sox6 and Sp1 are involved in the insulin-like growth factor-I-mediated upregulation of human type II collagen gene expression in articular chondrocytes, which is consistent with our findings that rs16931831 and rs138547759, as regulatory SNPs, target SOX6 through TADs. Additionally, we detected several novel candidate genes for BMD, such as PLEKHM1, PTPRZ1, CCDC122, and DCLK1. PLEKHM1 encodes pleckstrin homology domain-containing family M member 1, which is suggested to be involved in vesicular transport in osteoclasts.PLEKHM1 gene mutation results in osteopetrosis both in humans and rats, which is characterized by diminished bone resorption by osteoclasts. Mechanistically, loss of PLEKHM1 abrogates the peripheral distribution of lysosomes and bone resorption in osteoclasts through regulating lysosome positioning and secretion through RAB7. Rptpzeta, which is encoded by PTPRZ1, has been proved to play a physiological role in bone remodelling, and was thus identified as the first protein tyrosine phosphatase (PTP) regulating bone formation in vivo.CCDC122 was identified as a susceptibility gene for leprosy in 3,614 individuals, involving two family-based and three independent case-control samples. Moreover, a study for exploring the relationship of testicular atrophy to bone metabolism in 31 male leprosy patients and 31 healthy control men was conducted and identified that BMD of the forearm significantly correlated with free testosterone levels (r = 0.689, p < 0.001), which indicates that low BMD may be due to testicular atrophy in leprosy patients. In addition, DCLK1 is upregulated in osteoblast-prone clones compared with non-differentiating clones through transcriptome sequencing and confirmed by real-time quantitative PCR. rs7776725 targeting PTPRZ1, rs34814687 and rs144518135 targeting PLEKHM1, rs9533094 targeting CCDC122 and DCLK1, rs150081494 targeting CCDC122, and rs191115702 targeting DCLK1 are all regulated through TADs. Further biological studies are warranted to explore the potential roles of PLEKHM1, PTPRZ1, CCDC122, and DCLK1 in the development of BMD. We identified 12 GO terms enriched in the overlapped candidate genes identified by discovery and replication studies, such as positive regulation of mesenchymal stem cell (MSC) differentiation GO term (GO:2000741) and positive regulation of cartilage development (GO:0061036). Bone-forming osteoblasts are derived from MSCs. In a study of transcriptional profiling of human femoral MSCs in OP, some genetic changes in MSCs were found to be involved in the pathophysiology of OP. Research of mouse pathological models and patients with postmenopausal osteoporosis (PMOP) indicated that MEG3 regulates the expression of miR-133a-3p, and inhibits the osteogenic differentiation of bone marrow mesenchymal stem cell (BMSC)-induced PMOP. It has also been reported that cell-based arthroplasty therapy via the use of MSCs may become one of the strategies for OP treatment. Another interesting GO term is positive regulation of cartilage development. There is a growing amount of research focus on the relationship between systemic BMD and cartilage properties. For example, Zhu et al have demonstrated that low BMD, particularly at the hip, was positively associated with knee cartilage defects. In addition, it has been reported that longitudinal BMD loss is related to progressive cartilage loss in knees with osteoarthritis. Furthermore, a cross-sectional study demonstrated that systemic BMD is positively associated with knee cartilage volume in healthy, asymptomatic adult females. To the best of our knowledge, this study represents one of the larger studies to explore the roles of regulatory genetic variants in the genetic mechanism of BMD. The main advantage of this study is that rSNPBase 3.1 extends the scope of SNP-related annotations, the regulatory elements to SNP-related regulatory element target gene pairs, therefore it supports SNP-based gene regulatory network analysis. In addition, we further used the replication analysis to validate the discovery results, enhancing the reliability and persuasiveness of our study. However, there are several limitations in our study. First, although data used in our study were from a large sample and we performed a replication analysis, further studies need to be conducted using larger sample sizes, different genetic populations, and different gene variations. Additionally, the biological effect of target genes in different tissue or cell types was not considered in this functional annotation information of rSNP. Our rSNP analysis could not take tissue or cell types into account; therefore, the roles of different tissue and cell types should be warranted in further studies. Moreover, in this analysis, integrative analysis and functional analysis were performed, however some other regulatory elements are not included in the rSNPBase 3.1 database, for instance m6A. Finally, this study focused on rSNP, which occupies a small part of the whole genome. In conclusion, we identified SNP-related regulatory elements and regulatory element-target gene pairs associated with BMD by integrating rSNPBase 3.1 with both discovery and replication GWAS summary datasets of BMD. We anticipate that the findings of this investigation will bring new insights into the aetiology and treatment of OP. Further research is required to substantiate and elucidate the underlying mechanisms of the identified genes implicated in the development of OP.

PMC10003064

Nan-Nan Yu,Wirinthip Ketya,Gyungsoon Park

Intracellular Nitric Oxide and cAMP Are Involved in Cellulolytic Enzyme Production in Neurospora crassa

24-02-2023

Neurospora crassa,cellulase,enzyme production,nitric oxide,cyclic AMP,MAPK,filamentous fungi,enzyme activity,signaling pathways,reactive oxygen species

Although molecular regulation of cellulolytic enzyme production in filamentous fungi has been actively explored, the underlying signaling processes in fungal cells are still not clearly understood. In this study, the molecular signaling mechanism regulating cellulase production in Neurospora crassa was investigated. We found that the transcription and extracellular cellulolytic activity of four cellulolytic enzymes (cbh1, gh6-2, gh5-1, and gh3-4) increased in Avicel (microcrystalline cellulose) medium. Intracellular nitric oxide (NO) and reactive oxygen species (ROS) detected by fluorescent dyes were observed in larger areas of fungal hyphae grown in Avicel medium compared to those grown in glucose medium. The transcription of the four cellulolytic enzyme genes in fungal hyphae grown in Avicel medium was significantly decreased and increased after NO was intracellularly removed and extracellularly added, respectively. Furthermore, we found that the cyclic AMP (cAMP) level in fungal cells was significantly decreased after intracellular NO removal, and the addition of cAMP could enhance cellulolytic enzyme activity. Taken together, our data suggest that the increase in intracellular NO in response to cellulose in media may have promoted the transcription of cellulolytic enzymes and participated in the elevation of intracellular cAMP, eventually leading to improved extracellular cellulolytic enzyme activity.

Intracellular Nitric Oxide and cAMP Are Involved in Cellulolytic Enzyme Production in Neurospora crassa Although molecular regulation of cellulolytic enzyme production in filamentous fungi has been actively explored, the underlying signaling processes in fungal cells are still not clearly understood. In this study, the molecular signaling mechanism regulating cellulase production in Neurospora crassa was investigated. We found that the transcription and extracellular cellulolytic activity of four cellulolytic enzymes (cbh1, gh6-2, gh5-1, and gh3-4) increased in Avicel (microcrystalline cellulose) medium. Intracellular nitric oxide (NO) and reactive oxygen species (ROS) detected by fluorescent dyes were observed in larger areas of fungal hyphae grown in Avicel medium compared to those grown in glucose medium. The transcription of the four cellulolytic enzyme genes in fungal hyphae grown in Avicel medium was significantly decreased and increased after NO was intracellularly removed and extracellularly added, respectively. Furthermore, we found that the cyclic AMP (cAMP) level in fungal cells was significantly decreased after intracellular NO removal, and the addition of cAMP could enhance cellulolytic enzyme activity. Taken together, our data suggest that the increase in intracellular NO in response to cellulose in media may have promoted the transcription of cellulolytic enzymes and participated in the elevation of intracellular cAMP, eventually leading to improved extracellular cellulolytic enzyme activity. Cellulose is the most abundant renewable resource in nature and has broad application prospects [1]. The enzyme cellulase can decompose cellulose into soluble reducing sugars and is an essential component of cellulose industrial applications in diverse fields ranging from the pulp and paper industry to winemaking and renewable energy power generation [2]. According to reports of global enzyme market analyses, cellulases are the third most important industrial enzymes, with an exponentially increasing demand [3]. Filamentous fungi are widely used for producing cellulolytic enzymes [4]. Because filamentous fungi can secrete extracellular proteins with high efficiency, the extracellular activity of fungal cellulolytic enzymes tends to be higher than that of bacterial cellulolytic enzymes [5]. Fungi, as eukaryotic organisms, have advanced mechanisms for post-translational processing of proteins, such as glycosylation, protease cleavage, and disulfide bond formation, which are critical for conferring specific functions on cellulolytic enzymes [6]. Cellulolytic enzymes have been reported to be produced by many filamentous fungi, such as Penicillium oxalicum, Aspergillus niger, Trichoderma reesei and Neurospora crassa [7], among which T. reesei is the most actively studied and widely used fungal species in industrial cellulase production. Additionally, N. crassa has been actively explored for cellulolytic enzyme production [8,9]. Fungi secrete three main types of cellulolytic enzymes, namely endoglucanase (endo-1, 4-β-D-glucanase, EG, EC 3.2.1.4), cellobiohydrolase or exoglucanase (exo-1, 4-β-D-glucanase, CBH, EC 3.2.1.91), and β-glucosidase (1, 4-β-D-glucosidase, BG, EC 3.2.1.21), which generally act synergistically to degrade cellulose [5]. The content of these three cellulolytic enzymes has been shown to reach 69% of the total secreted protein under the induction of Avicel (microcrystalline cellulose) medium in N. crassa [10]. In addition, N. crassa can also secrete accessory proteins, such as GH61 family proteins (lytic polysaccharide monooxygenase) and CDH-1 (cellobiose dehydrogenase), which synergistically promote the hydrolysis of cellulose with cellulolytic enzymes [10]. Production of cellulolytic enzymes is regulated mostly at the transcription level in N. crassa, and a protein kinase, STK-12, is known to act as a transcriptional brake in the expression of cellulase-encoding genes [11]. Transcription factors such as cellulose degradation regulator 1/2 (Clr-1/2), activator of cellulase expression 1/2/3 (Ace 1/2/3), xylanase regulator 1 (Xyr1), carbon catabolite repressor (Cre1) and beta-glucosidase regulator (BglR) have been also identified as transcriptional regulators in the expression of cellulolytic enzymes in N. crassa [12]. Fungal cellulolytic enzyme production is regulated by complex molecular mechanisms. Studies have shown that N. crassa can sense the cellobiose concentration in its environment and transport cellobiose into cells through cellodextrin transporters (CDT) on the cell membrane, and finally activate the cellulase transcription factor to promote the expression of cellulolytic enzymes [8,13,14]. A recent study has reported a novel regulatory strategy for cellulase production, in which G-protein signaling activates the cellulase transcription factor by regulating cAMP levels [15]. In T. reesei, multiple signaling pathways, such as cAMP/PKA, calcium, and MAPK, are involved in the regulation of cellulase formation [16,17,18,19,20,21,22,23,24,25]. In addition, changes in components of signaling pathways, such as small GTPase, MAPK, Ca2+, and polyphosphoinositol, in the presence of cellulose were identified in N. crassa through sequencing and bioinformatics analysis [26]. Multiple signaling pathways may regulate the production of fungal cellulolytic enzymes, and there may be a tandem relationship between these pathways. Molecular regulatory networks for fungal cellulase production are not completely understood and still have many gaps that need to be elucidated. In this study, we investigated the molecular basis of the transcription and extracellular activity of cellulolytic enzymes, particularly focusing on clarifying the internal signaling pathways, in N. crassa. As a natural degrader of cellulose, N. crassa has been considered as a model organism in many studies to explore the regulatory mechanisms of cellulolytic genes [27]. We used Avicel® PH-101 (microcrystalline cellulose with a size of approximately 50 μm) as an inducer of cellulase production in this study. Avicel is often used to induce mRNA transcription and protein secretion of cellulolytic enzymes in N. crassa [8,10]. To explore the production mechanism of fungal cellulolytic enzymes, cellulose is usually added as the sole carbon source to induce the expression of cellulolytic enzymes. In the presence of glucose, a fungus preferentially uptakes glucose from the environment, and the production of cellulolytic enzymes is inhibited via carbon catabolite repression [28]. Media for cellulase induction (Avicel) or non-induction (glucose) may be quite different, even in their physicochemical properties, such as conductivity, acidity, alkalinity, and redox capacity, because of significantly different molecular weights and solubilities between cellulose and glucose. The changes in these physicochemical properties can act as signals for activating signaling pathways within fungal hyphae. In this study, we also analyzed the differences in the physicochemical properties of media and their relationship with the production of fungal cellulolytic enzymes. Cellulolytic enzymes in N. crassa are produced when celluloses are provided as the only carbon source [8]. We also confirmed this in our experimental conditions. The filter paper-degrading activity (FPase activity, total activity of cellulolytic enzymes) and total protein concentration were measured when Avicel or glucose (control; no induction of cellulases) was provided as the carbon source in media. The FPase activity increased significantly in the medium containing Avicel after 48 h (346.98 %) and 72 h (774.72 %), while no significant change in activity was observed in the medium containing glucose (Figure 1a). The total protein concentration in Avicel medium was significantly increased after 24 h (240.14 %), 48 h (288.26 %), and 72 h (361.47 %), compared to no significant change in glucose medium (Figure 1a). Specific enzyme activity (total enzyme activity divided by total protein) was increased in Avicel medium only after 72 h (94.36 %) (Figure 1a). High levels of extracellular enzymes may result from the increased intracellular expression of enzyme proteins. To test this hypothesis, we measured the mRNA levels of four cellulolytic enzymes, including two cellobiohydrolases (cbh1 and gh6-2), an endoglucanase (gh5-1), and a β-glucosidase (gh3-4), known to be abundantly secreted upon Avicel induction [10]. A significant increase in the mRNA levels of the four cellulolytic enzyme genes was observed in the hyphae grown in Avicel media after 2 h (at least 2.5 times higher compared to that at 0 h) and 4 h (at least 3 times higher compared to that at 0 h), compared to the uninduced hyphae (grown in glucose containing media) (Figure 1b). Furthermore, we estimated the protein levels of the four cellulolytic enzymes in media by analyzing their protein profiles using SDS (sodium dodecyl sulfate)–PAGE (polyacrylamide gel electrophoresis). Protein band intensity was generally higher in Avicel medium than in glucose medium (Figure 2a), and the four protein bands corresponding to each cellulolytic enzyme were identified according to their molecular weights as previously described [29]. Total intensity of the four enzyme bands estimated using the ImageJ software was significantly higher in the samples collected from Avicel medium than in those collected from glucose medium after 24 h, 48 h and 72 h (Figure 2b). Intensity of GH3-4 or GH5-1 was significantly higher in Avicel than in glucose media at all incubation times (Figure 2c,e). Because bands of GH6-2 and CBH1 proteins were not separated on the gel, the intensity of a band including both proteins was estimated. It was significantly greater in Avicel than in glucose media at all incubation times (Figure 2d). To find whether changes in the extracellular media environment affected the expression and secretion of cellulolytic enzymes in N. crassa, the physical and chemical properties of both glucose and Avicel media were analyzed during incubation. The white precipitate in Avicel medium (Avicel is a water-insoluble cellulose polymer) gradually disappeared as the incubation time increased (Figure 3a), indicating that celluloses were degraded into soluble sugars by cellulolytic enzymes before they could be used by cells. The pH of Avicel medium did not change dramatically during incubation, but remained significantly higher than that of glucose medium during 0–24 h incubation (5.52–5.66 vs. 4.59–5.55) (Figure 3b). At 48 h incubation time, the pH of Avicel medium was significantly lower than that of glucose medium (5.99 vs. 6.58) (Figure 3b). The oxidation–reduction potential (ORP) value of Avicel medium was lower than that of glucose medium during 0–4 h incubation (231.56–248.89 vs. 233.22–258.11 mV; significantly lower at 4 h incubation), and significantly higher than that of glucose medium at 48 h incubation (235.11 vs. 223.44 mV) (Figure 3b). Generally, the changes in pH values in both media were contrary to the changes in ORP values during incubation (Figure 3b). This accords with the previous findings that pH is an important factor causing the change in the ORP value: the higher the pH, the lower the ORP [30]. The electrical conductivity (EC) gradually decreased as the incubation time increased in both glucose and Avicel media, although no dramatic decrease was observed during 0–4 h incubation (Figure 3b). At all incubation times, including 0 h, the EC values were significantly higher in Avicel medium than in glucose medium (Figure 3b). Solvent concentration is positively related to the EC of the solution [31]. An ORP value represents the redox capacity of a solution, and the redox capacity of the culture environment may be related to the generation of intracellular reactive oxygen and nitrogen species (RONS) [32]. To test this, we detected the intracellular NO and ROS using fluorescent dyes in fungal hyphae grown in both media. The intensity of ROS and NO fluorescence was found to be stronger in fungal hyphae grown in Avicel medium (induced) than in those grown in glucose (non-induced) medium after 2 h and 4 h incubation (Figure 4 and Supplementary Figure S1). However, no significant change in ROS and NO production in fungal cells was observed between glucose and Avicel media after 24 and 48 h (Supplementary Figure S2). Fluorescence was hardly detected in most samples (Supplementary Figure S2). These results indicate that intracellular ROS and NO production significantly increased in medium containing Avicel only during the early incubation period (0–4 h). The elevated production of intracellular ROS and NO in fungal hyphae grown in Avicel medium during early incubation suggested their potential role in the production (mostly gene expression) of cellulolytic enzymes. To validate this, we first analyzed the role of intracellular NO in cellulolytic enzyme production in Avicel medium. This is because experimental tools, such as scavengers and donors, are available only for NO, and peroxynitrite anion (ONOO−), a highly reactive species formed by a rapid reaction between nitric oxide (NO) and superoxide anion, is highly sensitive to H2DCF-DA [33]. After the application of the NO scavenger, 2-4-carboxyphenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (cPTIO), the levels of cbh1, gh6-2, and gh5-1 mRNA significantly decreased in fungal hyphae cultured in Avicel medium, mostly after 4 h (Figure 5a). After 24–72 h, the total cellulolytic activity, total protein concentration, and specific cellulolytic activity were significantly reduced in Avicel medium containing cPTIO (Figure 5b). The highest decrease was observed after 24 h (Figure 5b). When the NO donor, sodium nitroprusside (SNP), was added to Avicel medium (0.01 mM), the mRNA levels of cbh1, gh6-2, gh5-1, and gh3-4 were significantly increased in fungal hyphae grown in this medium after 4 h (Figure 6a). Generally, no significant difference in total cellulolytic activity, protein concentration, and specific enzyme activity in media was observed between the control (no SNP) and SNP treatment after 24, 48, and 72 h; however, an approximately 24.59% increase in total enzyme activity was observed in the SNP-treated group after 24 h (Figure 6b). Notably, the transcription of gh6-2, gh5-1, and gh3-4 was significantly elevated in glucose medium after the addition of SNP, mainly after 2 h (Supplementary Figure S3a). The total cellulolytic activity (filter paper-degrading activity) of glucose medium was also slightly increased, mainly after 24 h in the SNP-treated sample (Supplementary Figure S3b). This result is quite intriguing and warrants further investigation because cellulolytic enzymes are generally not induced in glucose medium. We examined whether cPTIO and SNP treatments affected fungal growth. No significant change in the dry weight of the fungal mycelia grown in Avicel medium was observed after cPTIO or SNP treatment at all incubation times (Supplementary Figure S4a,b). In glucose medium, the dry weight of the harvested fungal mycelia was not significantly different between the control and SNP treatment at all incubation times (Supplementary Figure S4c). Thus, we concluded that cPTIO and SNP treatments may not affect the fungal growth. In filamentous fungi, cAMP is known to activate cAMP-dependent protein kinase A (PKA) and regulate cellulase gene transcription [15,18]. To clarify how intracellular NO can regulate the production of cellulolytic enzymes, we examined the possibility of the involvement of cAMP signaling. We first measured the cAMP concentration and PKA activity in fungal hyphae grown in Avicel medium for 4 h because intracellular NO was increased after 2–4 h as shown in Figure 4d. Intracellular cAMP concentration was slightly higher in fungal hyphae grown in Avicel medium than in glucose medium, significantly decreased with the addition of cPTIO (removal of intracellular NO), and not significantly changed with the addition of SNP (Figure 7a). When relative ratios were calculated and compared using the same data, the cAMP level in fungal hyphae grown in Avicel medium was increased by approximately 28% compared to that in glucose medium (Figure 7b). The cPTIO treatment caused an approximately 43.33% decrease in the intracellular level of cAMP in Avicel medium (Figure 7c). We assessed PKA activity in fungal hyphae grown in glucose or Avicel medium for 4 h by Western blot analysis of phosphorylated peptides or proteins (as a result of PKA action). No significant difference in band number and intensity (indication of PKA activity) was observed between glucose and Avicel media and between control and cPTIO and SNP treatments in Avicel medium (Figure 7d). To further analyze the roles of intracellular NO and cAMP in extracellular cellulase production, we added cPTIO and cAMP to fungal culture and measured the cellulolytic activity in media after 24–72 h. The results showed that cPTIO addition reduced the activity of cellulolytic enzymes in Avicel medium, and the addition of cAMP in the presence of cPTIO could slightly rescue cellulolytic activity after 48 h, but not after 24 and 72 h (Figure 7e). When cAMP was added to the fungal culture in Avicel medium, the activity of cellulolytic enzymes was significantly elevated after 48 and 72 h (Figure 7e), indicating that the intracellularly produced NO is likely to accelerate the intracellular production of cellulases, possibly by inducing cAMP production, which in turn may lead to the elevation of extracellular cellulolytic activity. Calcium signaling is known to promote cellulase mRNA transcription via crz1 (calcineurin-responsive zinc finger transcription factor 1) in T. reesei [17,34]. We stained Ca2+ using the fluorescent dye, Fluo-3 AM, after 2 and 4 h in N. crassa hyphae and found no significant difference in fluorescence between glucose and Avicel cultures (Supplementary Figure S5). This suggests that calcium signaling may not be related to Avicel-induced increase in NO. In addition, MAP kinases are known to be involved in cellulase formation in T. reesei [35]. We assessed the activation of these MAP kinases in N. crassa (Fus3 homolog; MAK-2, Slt2 homolog; MAK-1, Hog1 homolog; OS-2) during the elevation of intracellular NO in hyphae by examining the phosphorylation of MAP kinases. Our preliminary results showed no significant difference in phosphorylated OS-2 levels among glucose and Avicel media and with the addition of cPTIO and SNP (Supplementary Figure S6). Many bands were detected by anti-phospho-p44/42 antibody, and we estimated two bands corresponding to MAK-1 and MAK-2 by analyzing the molecular weights of these two MAP kinases. The phosphorylation levels of MAK-1 and MAK-2 seemed to increase slightly after the addition of cPTIO (Supplementary Figure S6), indicating a possibility of the negative role of MAK-1 and MAK-2 in the production of cellulases, as shown in T. reesei [35,36]. Regulatory networks involved in the production of fungal cellulases have been continuously studied and reported to include changes in multiple signals. However, the mechanisms by which these intracellular signaling pathways are activated and the tandem relationship among these signals are not completely understood. As frequently demonstrated in previous studies, our study verified that external signals, such as cellulose, initiated signal transduction, leading to the transcription of cellulolytic enzyme genes and further extracellular cellulolytic activity [13,24]. Notably, this initial cellulose signal seems to induce the generation of secondary intracellular signals, such as ROS and NO, in N. crassa cells, as shown by our data. We observed that the intracellular ROS and NO levels increased in response to the presence of cellulose in media. These signals seem to be involved in regulating the transcription of cellulolytic enzyme genes rather than the extracellular secretion of cellulolytic enzymes because intracellular ROS and NO levels were elevated only during early incubation (2–4 h), not during later incubation (24–48 h; secretion stage). We further analyzed the effect of NO in this study, just because NO scavenger and donor are available and can be easily used in experiments. Our results showed that the transcription of cellulolytic enzyme genes significantly changed with the addition of cPTIO (NO scavenger) or SNP (NO donor); the removal of intracellular NO significantly decreased the transcription of cellulolytic enzyme genes, leading to the decrease in extracellular cellulolytic enzyme activity, and the addition of NO extracellularly increased the expression of cellulolytic enzyme genes. This elucidated the positive regulatory role of intracellular NO in N. crassa cellulase production. Intracellular ROS and NO production during fungal cellulase production has been rarely observed. Hydrogen peroxide (H2O2) is generated in fungal co-cultures and is responsible for the increase in laccase and manganese peroxidase activities [37]. A recent study showed that the level of intracellular ROS detected using H2DCFDA in T. reesei increased after Sr2+ was supplemented in media, and the intracellular ROS was detrimental to cellulase production [38]. H2DCFDA used for detecting intracellular ROS in our study was more sensitive to peroxinitrite (ONOO−) and hydroxyl radical (OH·) than to other species, and peroxinitrite is formed by a rapid reaction between NO and superoxide anion (O2·−) [33]. This indicates that H2DCFDA-mediated detection indirectly reflects the presence of intracellular NO. Taken together, our results suggest a novel, hitherto unknown mechanism by which extracellular cellulose (Avicel) induces NO production within fungal cells and intracellular NO plays a positive regulatory role in the expression of fungal cellulase genes. Intracellular NO generated in response to Avicel seemed to be related to the elevation of cAMP, a well-known secondary messenger in fungal cells, in our study. The cAMP level significantly decreased together with extracellular specific cellulolytic enzyme activity when intracellular NO was removed in Avicel medium. Addition of cAMP into Avicel medium slightly increased the cellulolytic enzyme activity, and the addition of cAMP together with cPTIO (NO scavenger) slightly restored the reduced cellulase activity. Many studies reported the involvement of intracellular cAMP in fungal cellulase production [15,18,21]. Regarding signaling pathways regulated by cAMP or ROS/NO for cellulase production, the cAMP/PKA pathway, calcium signaling, and MAPK signaling can be considered because the involvement of these signaling pathways has been frequently reported in T. reesei. The cAMP/PKA pathway has been known to be essential for regulating the expression of cellulase-encoding genes through activation or inactivation of transcription factors CRE1, ACE1, CLR1/2, and HAP2/3/5 complex in T. reesei [18,21]. In N. crassa, cAMP signaling serves as a downstream target of G-protein GNA-3, regulating cellulose degradation [15]. In our study, we observed no significant change in substrate protein phosphorylation by cAMP-dependent PKA after NO removal or addition. This indicates that cAMP generation in response to the elevation of intracellular NO level may not lead to the activation of PKA but be involved in other cellular pathways to control cellulase production. Calcium and MAPK signaling pathways have been actively explored in the production of T. reesei cellulases [16,17,19,20,22,23,24,25]. Recently, cAMP was found to activate calcium signaling for regulating cellulase production in T. reesei [22]. MAPK signaling also regulates cellulase production, and Hog1-like MAPK plays a positive role in the transcription of cellulase-encoding genes [16]. Fus3- and Slt2-like MAP kinases negatively regulate cellulase formation indirectly by repressing growth and maintaining cell wall integrity [35]. In this study, several preliminary analyses were performed to determine if Ca2+ and MAPK signaling are associated with intracellular NO or cAMP levels that induce cellulase production. Our results showed that the Ca2+ level in Avicel medium was not significantly different from that in glucose medium, indicating that Ca2+ signaling may not be associated with cellulase production. In addition, no significant change was detected in the phosphorylation of Hog1-like MAPK (OS-2) in Avicel medium, and intracellular NO removal or addition did not seem to significantly affect the level of phosphorylation of this MAPK. Phosphorylation of Fus3- and SLt2-like MAPKs (MAK-1 and MAK-2) seemed to slightly increase after NO removal in Avicel medium, suggesting the suppression of MAK-1 and MAK-2 activities under the elevated intracellular NO condition in response to cellulose in media, which may possibly indicate the negative role of MAK-1 and MAK-2 in cellulase production in N. crassa, as shown in T. reesei. Further in-depth investigation of this issue may be needed. Interestingly, physical signals can play a major role in the induction of cellulase formation. Physical environmental signals, such as light and pH, have been suggested as induction signals for cellulase production besides cellulose in T. reesei [24]. The ORP, pH, and EC in the culture environment can affect various physiological activities of microorganisms [39,40]. Light-sensing photoreceptors activate cAMP and calcium signaling pathways, regulating cellulase expression [22,41]. The receptor PAC1 activates cellulase production through the pal signaling pathway in a neutral pH environment [42]. A decrease in intracellular pH stimulates Ca2+ input through the Ca2+ channel and increases cellulase transcription through the Ca2+ signaling pathway [17]. In our experiments, light was continuously applied to fungus, and pH was generally higher in Avicel than in glucose medium during incubation. Notably, the EC values were higher in Avicel than in glucose medium during all incubation times. Different electrical properties of media may affect the fungal cell membrane and membrane transport characteristics, such as opening of channel or transporter proteins on membrane. Studies in T. reesei have shown that cellobiose released from cellulose degradation may be a direct signal because cellobiose, not cellulose, can be transported into cells [24]. Cellobiose transport through a membrane transporter can be a limiting factor for the initiation of cellulase expression. Several sugar transporters involved in the regulation of cellulase production have been identified in T. reesei [24]. The transporter-mediated control of sugar transport is likely critical for inducing cellulase production. Change in membrane electrical properties caused by the electrical environment in media may possibly affect the efficiency of a transporter. Neurospora crassa (strain name: ORS-SL6a, mating type: mat a, FGSC number: 4200) was used in this study and obtained from the Fungal Genetics Stock Center (FGSC, Manhattan, KS, USA). The fungus was maintained on Vogel’s Minimal (VM) agar. Fungal culture in glucose and Avicel media was performed as follows: a piece of N. crassa mycelia was inoculated onto VM agar media in a flask and cultured at 30 °C in darkness for 2 d and then at 25 °C in light for 12 d. Sterile deionized (DI) water (approximately 50 mL) was added into the flask and then shaken vigorously. Fungal suspension was filtered through two layers of Miracloth (EMD Millipore, Burlington, MA, USA) and then centrifuged at 3134× g for 5 min to pellet down spores. The spore pellet was resuspended in fresh sterile DI water. Spores (3 × 107) were inoculated into 30 mL VM liquid with 2% (w/v) glucose and incubated at 25 °C under constant light with shaking (200 rpm) for 24 h. Fungal mycelia were then collected by filtration through two layers of Miracloth (EMD Millipore) and washed with DI water. The washed mycelia were resuspended in 30 mL of fresh VM containing 2% (w/v) glucose or 2% (w/v) Avicel (Avicel PH-101, Sigma-Aldrich, St. Louis, MI, USA) and incubated at 25 °C under constant light with shaking (200 rpm) for 24, 48, and 72 h. The culture medium was collected at different incubation time points and centrifuged at 2390× g for 10 min, and the supernatant was recovered for measuring EC, ORP, and pH. The ORP was measured using an ExStikTM Model RE300 waterproof ORP meter (Extech, Nashua, NH, USA), and the pH was measured using a portable pH meter (Oakton Instruments, Vernonb Hills, IL, USA). The EC was measured using a PCTSTestr™ 50 Waterproof Pocket pH/Cond/TDS/Salinity Tester (Oakton Instruments, Vernon Hills, IL, USA). All measurements were performed according to the manufacturer’s instructions. To measure protein concentration and cellulase activity in the medium, the culture medium was harvested at 24, 48, and 72 h after Avicel induction and then centrifuged at 2390× g for 10 min. The supernatant was collected and stored at 4 °C. Within 48 h, total protein concentration in the supernatant was determined using the Bradford protein assay kit (Bio-Rad, Hercules, CA, USA) according to the manufacturer’s protocol. Bradford solution (1×, 200 μL) was added into 10 μL culture supernatant, and then the mixture was incubated at 25 °C for 5 min in the dark. The absorbance of solution was measured at 595 nm using a microplate reader (Biotek, Winooski, VT, USA). Total activity of cellulolytic enzymes was determined by the rate of degradation of filter paper (FPase), as described previously [43]. Briefly, a reaction mixture containing Whatman filter paper no. 1. (substrate; Sigma-Aldrich, St. Louis, MI, USA), 30 μL 0.1 M acetate buffer (pH 5.6) and 30 μL culture supernatant was incubated at 50 °C for 30 min. Levels of liberated reducing sugars (product of the enzymatic reaction) were measured by adding 120 μL 3,5-dinitrosalicylic acid (DNS; Sigma-Aldrich, St. Louis, MI, USA) into the reaction mixture and then boiling for 10 min. After 720 μL of deionized water was added to the reaction mixture, the solution absorbance was measured at 540 nm using a microplate reader (Biotek). One unit of enzymatic activity was defined as the amount of enzyme capable of producing 1 μM of reducing sugars from the appropriate substrates per minute. Specific enzyme activity was estimated by dividing the total enzyme activity by the total protein amount. Culture media were collected at 24, 48, and 72 h after Avicel induction, and hyphae were removed by centrifugation at 2390× g for 10 min. The supernatant was mixed with sample buffer (5×), and the mixture was boiled for 5 min. A 20 μL solution (30 µg total protein) was applied to a sodium dodecyl sulfate -polyacrylamide (12%) gel, and the gel was electrophoresed. Gels were stained overnight with Coomassie Blue R-250 (Bio-Rad). The protein bands corresponding to relevant cellulolytic enzymes were determined according to their molecular weights [29]. Photography and analysis were performed using a ChemiDocTM MP imaging system (Bio-Rad) and ImageJ software version 1.52a (National Institute of Health). For Western blot analysis, mycelia were collected after Avicel induction for 4 h and ground with a mortar and pestle under liquid nitrogen. Protein concentration was determined using the Bradford protein assay kit (Bio-Rad). The same amount of protein (30 µg/20 μL) was subjected to SDS-polyacrylamide gel (12 %) electrophoresis and electro-transferred to a nitrocellulose membrane (Millipore, Bedford, MA, USA). The membrane was blocked with 5% milk, washed three times with 1× PBS, and then incubated with the primary antibody (1:1000 dilution) at 4 °C overnight. Primary antibodies used in the study were as follows: anti-Hog1 (D-3) (sc-165978; Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-p44/42 MAPK (#9102; Cell Signaling Technology, Danvers, MA, USA), anti-phospho-p38 MAPK (#9211; Cell Signaling), anti-phospho-p44/42 MAPK (#9101; Cell Signaling), anti-PKA substrate antibody (#9621; Cell Signaling), and anti-β-actin (#4967; Cell Signaling). After washing with 1× PBS, the membrane was incubated with anti-rabbit IgG, HRP-conjugated secondary antibody (1:2500 dilution; Thermo Fisher, Rockford, IL, USA) for 1 h at 25 °C. Finally, Clarity Western ECL Substrate (Bio-Rad) was added onto the washed membrane, and chemiluminescence was detected using a ChemiDocTM MP imaging system (Bio-Rad). Analysis was performed using ImageJ software version 1.52a (National Institute of Health). Quantitative real-time PCR was used to analyze the mRNA expression levels of the four cellulolytic enzymes. Fungal mycelia were collected by filtration through Miracloth (EMD Millipore) at 0, 2, and 4 h after Avicel induction and immediately frozen in liquid nitrogen and stored at −80 °C until analysis. RNAiso Plus (TaKaRa Bio, Shiga, Japan) was used to extract total RNA, and ReverTra Ace qPCR RT Master Mix with gDNA Remover (Toyobo, Osaka, Japan) was used to synthesize cDNA, according to the manufacturer’s instructions. Real-time PCR was performed using the iQ SYBR Green Supermix (Bio-Rad) and CFX 96TM real time Instrument (Bio-Rad), following the manufacturer’s instructions. The thermal cycling conditions were 95 °C for 3 min, 40 cycles at 95 °C for 10 s, and 60 °C for 30 s. Primer sequences are listed in Table 1. β-actin was used as a reference gene. Cycle threshold (Ct) values were determined, and the mRNA levels for each enzyme were normalized to the reference gene (β-actin). The relative mRNA level of enzyme gene in each incubation time was calculated based on the difference in Ct values compared to that of the glucose-treated sample at 0 h as follows: 2−∆∆Ct, where ∆∆Ct = (Cttarget − Ctreference) Avicel at all incubation times or glucose at 2 and 4 h—(Cttarget − Ctreference) glucose at 0 h [44]. To detect intracellular ROS and NO, fungal mycelia were harvested at 0, 2, 4, 24, 48 h after incubation in glucose or Avicel medium. The harvested mycelia were stained with 20 μM 2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA, Themo Fisher, Waltham, MA, USA) and 20 μM 4-amino-5-methylamino-2′,7′-difluorofluorescein diacetate (DAF-FM DA, Themo Fisher) for intracellular ROS and NO, respectively, at 25 °C in the dark for 1 h. Intracellular Ca2+ was detected using the fluorescent dye Fluo3-AM (Invitrogen, Carlsbad, CA, USA). Fungal mycelia were harvested at 0, 2, 4, 24, 48 h after incubation in glucose or Avicel medium and then stained with 5 μM of Fluo3-AM (Invitrogen) at 25 °C in the dark for 1 h. After incubation, all stained samples were washed with 1× PBS and then imaged using a FV-100 MPE spectral confocal laser scanning microscope (Olympus Corporation, Tokyo, Japan) under wavelengths corresponding to each fluorescent dye: 488/525 nm (excitation/emission) for H2DCFDA, 495/515 nm (ex./em.) for DAFFMDA, 506/526 nm (ex./em.) for Fluo3-AM. For cPTIO (2-(4-carboxyphenyl)-4,5-dihydro-4,4,5,5-tetramethyl-1 H-imidazolyl-1-oxy-3-oxide), SNP (sodium nitroprusside), or cAMP (adenosine 3′,5′-cyclic monophosphate sodium salt monohydrate) treatment, 1 × 106 spores of N. crassa were inoculated into 1 mL VM liquid with 2% (w/v) glucose in a 24-well plate. After being incubated at 25 °C for 24 h, the fungal mycelia were washed twice with DI water, and 1 mL of VM liquid with 2% (w/v) Avicel supplemented with 10 mM cPTIO (Calbiochem, San Diego, CA, USA), 0.01 mM SNP (Sigma-Aldrich), or 3 mM cAMP (Sigma-Aldrich) was added. The culture was incubated under constant light at 25 °C with shaking (200 rpm). cAMP concentrations were determined using a cAMP Competitive ELISA Kit (Invitrogen) according to the manufacturer’s protocol. Fungal mycelia were harvested at 4 h and immediately triturated with liquid nitrogen, and PBS was added into ground fungal powder. Subsequently, the mixture was centrifuged at 600× g for 10 min, and the supernatant was collected and stored at −80 °C until analysis. Neutralizing reagent was added into the supernatant, and then cyclic AMP antibody, cyclic AMP-AP conjugate solution, substrate solution, and stop solution were added in sequence according to the manufacturer’s instructions. Finally, the absorbance of the resulting solution was measured at 450 nm using a microplate reader (Biotek). All data are presented as the mean ± standard deviation (SD) from at least six replicates. Paired Student’s t-tests and two-way analysis of variance were performed, followed by Tukey’s post hoc test. A p-value < 0.05 was considered to reflect a statistically significant difference. SPSS Statistics Software, version 25 (IBM, Chicago, IL, USA) was used for statistical analysis. Our analysis of the molecular basis of cellulase production in N. crassa showed that the intracellular NO levels increased in response to extracellular cellulose, and increased NO levels might stimulate cAMP generation in cells, thereby promoting cellulolytic enzyme transcription (Figure 8). Our study, to the best of our knowledge, is the first to report the involvement of intracellular NO in fungal cellulase formation. Although the relationship between intracellular NO and downstream signaling pathways was not completely clarified in our study, our preliminary results suggest the potential involvement of the cAMP/PKA, calcium, and MAPK signaling pathways in the regulatory network of cellulolytic enzyme production in N. crassa and warrant further intensive investigation. Molecular regulation of fungal cellulase production has been most extensively studied in T. reesei. However, these molecular mechanisms are still not completely understood, and extensive studies including various fungal species should be conducted for elucidating the general regulatory network for cellulase production.

PMC10003068

Dagmar Heydeck,Christoph Ufer,Kumar R. Kakularam,Michael Rothe,Thomas Liehr,Philippe Poulain,Hartmut Kuhn

Functional Characterization of Transgenic Mice Overexpressing Human 15-Lipoxygenase-1 (ALOX15) under the Control of the aP2 Promoter

02-03-2023

eicosanoids,polyenoic fatty acids,inflammation,oxidative stress,inflammation,atherosclerosis

Arachidonic acid lipoxygenases (ALOX) have been implicated in the pathogenesis of inflammatory, hyperproliferative, neurodegenerative, and metabolic diseases, but the physiological function of ALOX15 still remains a matter of discussion. To contribute to this discussion, we created transgenic mice (aP2-ALOX15 mice) expressing human ALOX15 under the control of the aP2 (adipocyte fatty acid binding protein 2) promoter, which directs expression of the transgene to mesenchymal cells. Fluorescence in situ hybridization and whole-genome sequencing indicated transgene insertion into the E1-2 region of chromosome 2. The transgene was highly expressed in adipocytes, bone marrow cells, and peritoneal macrophages, and ex vivo activity assays proved the catalytic activity of the transgenic enzyme. LC-MS/MS-based plasma oxylipidome analyses of the aP2-ALOX15 mice suggested in vivo activity of the transgenic enzyme. The aP2-ALOX15 mice were viable, could reproduce normally, and did not show major phenotypic alterations when compared with wildtype control animals. However, they exhibited gender-specific differences with wildtype controls when their body-weight kinetics were evaluated during adolescence and early adulthood. The aP2-ALOX15 mice characterized here can now be used for gain-of-function studies evaluating the biological role of ALOX15 in adipose tissue and hematopoietic cells.

Functional Characterization of Transgenic Mice Overexpressing Human 15-Lipoxygenase-1 (ALOX15) under the Control of the aP2 Promoter Arachidonic acid lipoxygenases (ALOX) have been implicated in the pathogenesis of inflammatory, hyperproliferative, neurodegenerative, and metabolic diseases, but the physiological function of ALOX15 still remains a matter of discussion. To contribute to this discussion, we created transgenic mice (aP2-ALOX15 mice) expressing human ALOX15 under the control of the aP2 (adipocyte fatty acid binding protein 2) promoter, which directs expression of the transgene to mesenchymal cells. Fluorescence in situ hybridization and whole-genome sequencing indicated transgene insertion into the E1-2 region of chromosome 2. The transgene was highly expressed in adipocytes, bone marrow cells, and peritoneal macrophages, and ex vivo activity assays proved the catalytic activity of the transgenic enzyme. LC-MS/MS-based plasma oxylipidome analyses of the aP2-ALOX15 mice suggested in vivo activity of the transgenic enzyme. The aP2-ALOX15 mice were viable, could reproduce normally, and did not show major phenotypic alterations when compared with wildtype control animals. However, they exhibited gender-specific differences with wildtype controls when their body-weight kinetics were evaluated during adolescence and early adulthood. The aP2-ALOX15 mice characterized here can now be used for gain-of-function studies evaluating the biological role of ALOX15 in adipose tissue and hematopoietic cells. Lipoxygenases are fatty acid dioxygenases that oxygenate arachidonic acid and related polyenoic fatty acids to the corresponding hydroperoxy derivatives [1,2,3,4,5]. They have been implicated in the differentiation of mesenchymal [6,7,8,9] and ectodermic cells [10,11,12] but may also play a role in the pathogenesis of inflammatory [13,14], hyperproliferative [15,16,17,18], neurodegenerative [19,20,21], and metabolic [22,23,24,25] diseases. The human genome involves six functional ALOX genes (ALOX15 [26], ALOX15B [27], ALOX12 [28,29], ALOX12B [30], ALOX5 [31,32], ALOXE3 [12,33]), and each of the ALOX-isoforms exhibit distinct biological functions. In the mouse genome, a single-copy ortholog exists for each human ALOX gene, but in addition, an Aloxe12 gene exists that encodes for a functional epidermal Aloxe12 [34]. This enzyme shares a high degree of amino acid identity with Alox15, but in humans, the corresponding ortholog is a corrupted pseudogene [34]. Except for ALOXE12, knockout mice are available for each ALOX-isoform ([11,35,36,37,38,39,40]), but despite the availability of these tools, the biological relevance of the different ALOX-isoforms is still a matter of discussion. Together with ALOX5, ALOX15 is the most comprehensively characterized ALOX-isoform [26,41,42,43]. It was discovered in 1975 as a protein in immature red blood cells of rabbits that was capable of oxygenating mitochondrial membranes [44]. Because of this property, the enzyme has been implicated in the maturational breakdown of mitochondria during late erythropoiesis [45,46]. To explore the biological roles of Alox15 in vivo, ALOX15−/− mice have been generated [35], and these animals (loss-of-function strategy) have been tested in a large number of mouse models of human diseases [47,48,49,50,51,52,53,54]. In addition, a number of transgenic mouse lines have been created (gain-of-function strategy), in which mouse or human ALOX15 was overexpressed under the control of different regulatory elements, that exhibit interesting phenotypes. Moderate overexpression of the endogenous mouse Alox15 induced spontaneous formation of aortic fatty streaks, which was related to upregulated expression of endothelial cell-adhesion molecules [55]. Endothelium-specific overexpression of human ALOX15 [56] accelerated aortic lipid deposition in LDL-receptor deficient mice [57], but it also inhibited tumor growth and metastasis in two different mouse models of human cancer [58]. More recently, these authors showed that this protective effect may be related to the promotion of apoptosis and necrosis in primary and metastatic tumor cells [59]. In rabbits, overexpression of human ALOX15 under the control of the lysozyme promoter induced macrophage-specific expression of the transgene [60] and protected the animals from aortic lipid deposition when fed a lipid-rich Western-type diet [61]. Transgenic mice overexpressing human ALOX15 under the control of the scavenger receptor A promoter [62] were also protected from aortic lipid deposition, but here, the protective effect was related to the augmented biosynthesis of anti-inflammatory and pro-resolving lipid mediators such as lipoxin A4, resolvin D4, and protectin D1 [63]. Genetically modified mice overexpressing a transgenic version of the endogenous Alox15 under the control of the alpha-cardiac myosin heavy chain promoter developed heart failure and diabetic cardiomyopathy [64,65]. When human ALOX15 was overexpressed in the intestinal epithelium under the control of the villin promoter [66], the resulting transgenic mice were protected from the development of azoxymethane-induced colonic tumors, and expression of the ALOX15 transgene was always impaired in tumor cells when compared with non-tumor controls [67]. Additional mechanistic studies have suggested that expression of the transgene inhibited the expression of tumor necrosis factor alpha and its target, the inducible nitric-oxide synthase. Moreover, activation of nuclear factor kappa B was prevented [67]. More recently, a transgenic mouse line was created in which the expression of the human ALOX15 was controlled by the Cre-lox promoter [68]. The employed strategy ensured ubiquitous overexpression of the transgene, but when these mice and corresponding wildtype controls were used in a diabetic peripheral neuropathy model, the authors did not observe significant differences when compared with wildtype controls [68]. In most of these transgenic animals, tissue-specific expression of the transgene was explored. However, incorporation of the transgene into the host genome was controlled in neither of them, and thus, it is unclear how many copies of the transgene had been incorporated into the host genome and at which positions. Moreover, in many of these studies, activity assays were performed, and thus, it is unclear whether the transgenic enzyme was catalytically active. This is a serious limitation for some of these studies, since expression of a functional ALOX15 is strongly regulated on the translational level [69,70,71], and thus, detection of the transgenic mRNA is not sufficient to conclude the catalytic activity of the enzyme. In fact, in human umbilical vein endothelial cells, high levels of ALOX15 mRNA were detected, but the catalytically active enzyme was missing [72]. To contribute to the discussion on the biological role of Alox15, we here characterize transgenic mice expressing the human ALOX15 under the control of the aP2 (adipocyte fatty acid binding protein-2) promoter (aP2-Alox15 mice). In these mice, transgene expression is directed to mesenchymal cells, particularly to adipocytes, macrophages, and other cells of the myeloic linage. In the present paper we report the breeding of homozygous aP2-ALOX15 mice and found that the transgene was incorporated as single copy gene into the E1-2 region of chromosome 2. Ex vivo activity assays indicated expression of the functional transgene in adipocytes, spleen, bone marrow cells, and peritoneal macrophages. The in vivo activity of transgenic human ALOX15 was indicated by analysis of the plasma oxylipidomes. Because of the high expression levels of the transgene in adipose tissue and in the hematopoietic system, these mice can be used in the future to study the role of ALOX15 in adipocyte differentiation and hematopoiesis. Different ALOX-isoforms (ALOX5 [73], ALOX12 [74], ALOX12B [75], ALOXE3 [76] and ALOX15 [77]) have been implicated in adipocyte differentiation, in the energy metabolism of fat cells, and in adipose tissue remodeling. Moreover, supplementation studies with ALOX products suggested that several oxylipins activate adipogenesis of 3T3 cells in vitro, and these data support a possible role of ALOX15 in adipogenesis [9]. However, 15-HETE formation in mice is limited, since none of the seven functional Alox isoforms produce 15-HETE as a major arachidonic acid oxygenation product. Human ALOX15 effectively oxygenates arachidonic acid to 15-HETE [78,79], and thus, 15-HETE formation can be used as metabolic footprint for expression of the transgene. To test the impact of endogenous 15-HETE formation in mouse adipose tissue in vivo, a transgenic mouse line was created that overexpresses human ALOX15 under the control of the aP2 (adipocyte fatty acid binding protein 2) promoter. For this purpose, the cDNA of human ALOX15 was ligated behind the aP2 promoter (Figure 1), and this construct was microinjected into fertilized eggs. Cells were reimplanted into pseudo-pregnant mice, and individuals carrying the transgene in the germ line were crossed with wildtype C57BL/6 mice. Heterozygous allele carriers were intercrossed, and homozygous aP2-ALOX15 mice were selected. These animals were used to establish a colony of homozygous aP2-ALOX15 mice, and individuals of this colony were used for our characterization studies. Since our transgenic strategy involved coincidental incorporation of the transgene into the host genome, we next explored how many copies of the transgene were incorporated into the genome, and we also determined the site(s) of transgene insertion. For this purpose, we first performed fluorescence in situ hybridization (FISH) using the human ALOX15 cDNA as a probe. Figure 2A shows a representative FISH staining of a heterozygous founder. It can be seen that the transgene was inserted as a single-copy gene into the subband E1-2 on chromosome 2. No specific fluorescence signal was detected on any other chromosome. To describe the site of transgene incorporation more precisely and to exclude transgene insertion having disrupted a functional gene in this region, we carried out whole-genome sequencing. The obtained sequence data confirmed single incorporation of the transgene and also suggested that no functional gene was disrupted during transgene insertion. To explore the tissue-specific expression of both endogenous mouse Alox15 and the human ALOX15 transgene, we carried out qRT-PCR using isofom-specific primers. Human and mouse ALOX15 cDNA share a high degree of nucleotide sequence identity (85%), and thus, designing ortholog specific pPCR primers was somewhat difficult. However, we selected cDNA regions with relatively low degrees of nucleotide sequence conservation, and by using these ortholog specific primer pairs, we found (Figure 3A) that the endogenous arachidonic acid 12-lipoxygenating mouse Alox15 was expressed at relatively low levels in most cells and tissues. The highest expression levels were observed in the lung, but even in this organ, only about 20 copies of Alox15 mRNA were present per 1000 copies of Gapdh mRNA. Lower expression levels were observed in bone marrow cells and in peri-epididymal adipose tissue. In spleen, heart, liver, kidney, and brain, we did not see specific amplification signals. When similar analyses were carried out with the RNA extracts prepared from corresponding tissues of the transgenic aP2-ALOX15 mice, lower steady-state ALOX15 mRNA concentrations were detected in the lungs, but elevated levels were detected in the perirenal adipose tissue (Figure 3A). However, despite these differences, the expression levels of the endogenous mouse Alox15 mRNA were also low (1–5 Alox mRNA copies per 1000 copies of Gapdh) in all tested tissues of the transgenic aP2-ALOX15 mice. When we repeated these analyses with the human ALOX15-specific amplification primers (Figure 3A), we did not see specific amplification signals in the different tissues of wildtype mice. These results were expected, since wildtype mice do not express human ALOX15, and our primers do not pick up mouse Alox15 mRNA. In contrast, we detected the abundant expression of human ALOX15 in the three types of adipose tissue (peri-epididymal, subcutaneous, perirenal). We also detected high-level expression of the transgene in bone marrow cells, spleen, lungs, and testis. The most interesting outcome of our qRT-PCR data was that the steady state concentrations of the transgenic mRNA, which varied between 800 and 3,500 ALOX15 mRNA copies per 103 copies of Gapdh, were much higher than the mRNA copy numbers of the endogenous Alox15 in wildtype tissues. Taken together, these data indicate overexpression of the transgenic enzyme in adipose tissue, but also in hematopoietic cells (bone marrow), spleen, lung, and testis. Expression of ALOX15 orthologs is strongly regulated at transcriptional [80,81] and translational levels [69,70]. In fact, in young rabbit reticulocytes, large amounts of ALOX15 mRNA are present, but no functional protein can be detected [45]. Thus, in principle, there is the possibility that ALOX15 mRNA is present but no functional enzyme is expressed [72]. To explore whether a functional transgenic enzyme is expressed in different tissues of the transgenic aP2-ALOX15 mice, we carried out ex vivo activity assays using intact cell suspensions or tissue homogenate supernatants as enzyme source. In peritoneal lavage cells, mouse ALOX15 is highly expressed, and thus, these cells are well-suited to ex vivo activity assays. When we incubated these cells from wildtype mice with arachidonic acid (Figure 4A), large amounts of 12-HETE were detected. In addition, smaller amounts of 15-HETE were also identified as a minor side product. Interestingly, under these experimental conditions, we did not find any 5-HETE formation, although significant amounts of ALOX5 mRNA were detected in these cells by qRT-PCR. When these experiments were repeated with peritoneal macrophages prepared from ALOX15−/− mice, 12- and 15-HETE were no longer detectable. Instead, 5-HETE was identified as a major arachidonic acid oxygenation product (Figure 4B). Since ALOX5 is expressed in peritoneal macrophages, the formation of 5-HETE is plausible when the dominant ALOX15 pathway is genetically silenced. When we incubated peritoneal lavage cells from our transgenic aP2-ALOX15 mice with arachidonic acid, 12-HETE remained the major oxygenation product (Figure 4C). However, the relative share of 15-HETE was significantly increased when compared with wildtype cells (Table 1). The most plausible explanation for these data is that both endogenous ALOX15 (forming 12-HETE) and the transgenic ALOX15 (forming 15-HETE) were catalytically active. To provide more compelling evidence for this conclusion, we crossed ALOX15−/− mice with our transgenic aP2-ALOX15 animals, prepared peritoneal lavage cells from the animals, and carried out ex vivo activity assays. In these cells, endogenous Alox15 (forming 12-HETE) was absent, and thus, 15-HETE originating from the transgenic ALOX15 pathway was expected to be dominant. In fact, when we carried out such ex vivo activity assays, 15-HETE was the major arachidonic acid oxygenation product, and small amounts of 12-HETE were also detected (Figure 4D). Since human ALOX15 exhibits dual-reaction specificity [79], the formation of small amounts of 12-HETE by the transgenic enzyme is plausible. Similar ex vivo activity assays were carried out with three individuals of each genotype; the statistical evaluation of the experimental raw data is given in Table 1. In summary, these data confirm our hypothesis that the transgenic human ALOX15 is expressed as a catalytically active enzyme in peritoneal macrophages in addition to the endogenous mouse Alox15. Assuming a similar specific activity of mouse and human ALOX15, more endogenous Alox15 should be present in these cells when compared with the transgenic human ALOX15. Bone marrow cells are another rich source of endogenous Alox15. However, in these cell types, the arachidonic acid metabolism is somewhat more complex, since the arachidonic acid 12-lipoxygenating ALOX15, the arachidonic acid 12-lipoxygenating ALOX12, and the arachidonic acid 5-lipoxygenating ALOX5 are simultaneously expressed. When wildtype bone marrow cells are incubated with arachidonic acid, 12-HETE was identified as a major arachidonic acid oxygenation product (Table 2). 15-HETE and 5-HETE only contributed minor shares. When bone marrow cells of ALOX15−/− mice were used for the ex vivo activity assays, we did not see any 15-HETE formation (Table 2). These data suggest that the minor share of 15-HETE formation by wildtype bone marrow cells (4.9 ± 1.6%) may be related to the catalytic activity of the endogenous mouse Alox15. Although mouse Alox15 is dominantly arachidonic acid 12-lipoxygenating, 15-HETE is a minor side product [82]. The strong but incomplete reduction of 12-HETE formation by ALOX15−/− bone marrow cells suggests that the dominant 12-HETE formation by wildtype bone marrow cells (93.8 ± 3.6%) may be related to the mixed catalytic activity of the endogenous ALOX15 and ALOX12 isoforms. Interestingly, ALOX15−/− bone marrow cells produce large amounts of 5-HETE, and these data (Table 2) are consistent with the results of the ex vivo activity assays of peritoneal lavage cells (Figure 4B, Table 1). Expression of transgenic human ALOX15 completely altered the pattern of arachidonic acid oxygenation. In this case, 15-HETE was the major (55.5 ± 1.6%) arachidonic acid oxygenation product; these activity data suggest catalytic activity from the transgenic human ALOX15. When we crossed aP2-ALOX15 transgenic mice with ALOX15−/− animals, the relative share of 12-HETE was further reduced (from 44.4 ± 1.6% in aP2-ALOX15 mice to 10.9 ± 0.5% in aP2-ALOX15 + ALOX15−/−); these data suggest that more than 70% of the 12-HETE formed by aP2-ALOX15 bone marrow cells originated from the endogenous ALOX15 pathway. In these cells, ALOX12 may only contribute 30% to 12-HETE formation. As expected, formation of 15-HETE was strongly elevated by bone marrow cells of aP2-ALOX15 + ALOX15−/− mice. Taken together, our ex vivo activity experiments confirm that in peritoneal lavage cells, as well as in bone marrow cells, transgenic human ALOX15 is expressed and the transgenic enzyme is catalytically active. As indicated in Figure 3, the transgenic mRNA is expressed in different solid tissues such as adipose tissue, spleen, lungs, and testis. To explore whether the transgenic enzyme is also expressed in these tissues and whether the protein is catalytically active, we carried out similar ex vivo activity assays. For this purpose, we prepared tissue homogenates, and used the 20,000 g supernatants as enzyme source. After a 15 min incubation period of the homogenate supernatants with arachidonic acid, we quantified by RP-HPLC the formation of 12-HETE and 15-HETE as the major readout parameter. When homogenate supernatants of wildtype control mice were used for the ex vivo activity assays, only small amounts of 12-HETE and 15-HETE were formed. Only in lungs and spleen, we observed significant formation of 12-HETE, which exceeded the formation of 15-HETE. These data suggest that the endogenous arachidonic acid 12-lipoxygenating mouse Alox15 is expressed in these tissues, but that the enzyme may not be present in adipose tissue, testis, and heart. In contrast, activity assays with homogenate supernatants prepared from these tissues of aP2-ALOX15 mice indicated dominant 15-HETE formation by the homogenate supernatants of adipose tissue, spleen, and lungs, whereas only minor 15-HETE formation was observed in testis and heart. Taken together, our ex vivo activity data indicated that the transgenic human ALOX15 is expressed at high levels in adipose tissue but also in spleen and lungs. Our ex vivo activity assays indicated the expression of the catalytically active transgenic human ALOX15 in different tissues, but the data did not prove the in vivo activity of the enzyme. If the transgenic enzyme is catalytically active in vivo and if this in vivo activity is mirrored on blood plasma levels of 15-HETE and other omega-6 oxygenation products of polyenoic fatty acids, the plasma concentrations of 15-HETE, 15-HEPE, 17-HDHA, and 15-HETrE should be higher in aP2-ALOX15 mice when compared with wildtype controls. To test this hypothesis, we analyzed the plasma oxylipidomes of aP2-ALOX15 mice and corresponding wildtype controls and quantified the plasma concentrations of oxygenated polyenoic fatty acids, including the major ALOX15 products [83]. As negative controls, we also quantified the plasma concentrations of other oxylipins that are not formed from arachidonic acid, eicosapentaenoic acid, docosahexaenoic acid, nor 8,11,14-eicosatrienoic acid by human ALOX15 (8-HETE, 8-HEPE, 10-HDHA, 8-HETrE). First, we quantified the sum of all oxygenated polyenoic fatty acids present in the blood plasma of the two genotypes (Figure 5A). Here, we did not find a significant difference between the two genotypes. These data indicate that the degree of oxidative challenge is similar in both genotypes. In other words, overexpression of human ALOX15 did not lead to an increased oxidative stress in the aP2-ALOX15 mice. When we analyzed the major arachidonic acid oxygenation products, we found that the plasma concentrations of 15-HETE in transgenic aP2-ALOX15 mice were almost five-fold higher than those in wildtype control animals (C57BL/6). In contrast, there were no significant differences between the two genotypes when the plasma levels of 8-HETE (not an ALOX15 product) were compared. These data can be interpreted as an indication of the in vivo activity of the transgenic human ALOX15. Next, we analyzed the oxygenation products of three other polyenoic fatty acids. Human ALOX15 converts 5,8,11,14-eicosapentaenoic acid predominantly to 15-HEPE [83]. We found that the 15-HEPE plasma concentrations were more than five-fold higher in aP2-ALOX15 mice when compared with wildtype controls. Here again, we did not find any difference between the two genotypes for 8-HEPE, which is not formed by human ALOX15 (Figure 6C). Similar results were obtained for the major oxygenation products formed from 4,7,10,13,16,19-docosahexaenoic acid (Figure 6D) and 8,11,14-eicosatrienoic acid (Figure 6E). Here, the differences between aP2-ALOX15 mice and C57Bl/6 control animals were even more pronounced. In summary, our plasma oxilipidomes suggest the in vivo activity of the transgenic human ALOX15. Interestingly, the in vivo catalytic activity of the transgenic ALOX15 did not induce an elevated oxidative challenge in the transgenic animals. Obviously, the reductive capacity of the ALOX15-expressing cells is high enough to ensure the instantaneous reduction of the hydroperoxy fatty acids formed by the transgenic enzyme. ALOX15 has been implicated in spermatogenesis [84], and ALOX15−/− mice are sub-fertile [85,86]. Although we did not find dramatic overexpression of the catalytically active transgene in testis (Figure 7), we compared the reproduction statistics of the aP2-ALOX15 mice with those of wildtype controls. Here, we found that the frequency of pregnancy (litters per female and month) and the reproduction efficiency (litters per female and months) were significantly elevated in aP2-ALOX15 transgenic mice (Figure 7). For the other readout parameters, no significant differences were observed when the two genotypes were compared (Figure 7). In summary, one can conclude that the aP2-ALOX15 mice, which express human ALOX15 in addition to the endogenous mouse ALOX15, were slightly more fertile than wildtype controls, although the differences were rather subtle. To explore whether systemic overexpression of human ALOX15 impacts the development of mice during adolescence and adulthood, we next profiled the body-weight kinetics of aP2-ALOX15 mice and wildtype control animals starting at the age of 8 weeks. For female individuals, we found that at 8 weeks, aP2-ALOX15 mice were significantly leaner than wildtype controls (Figure 8A). In fact, between 8–30 weeks, the curve of the body-weight kinetics of aP2-ALOX15 mice was consistently below the curve of the wildtype controls, and this difference was statistically highly significant (Wilcoxon test, p < 0.0085). In contrast, between 31–38 weeks, no significant difference was observed between the two genotypes. These data suggest that female aP2-ALOX15 mice gained less body weight than wildtype controls during the early developmental period but that the transgenic individuals caught up with the wildtype controls at later developmental stages (Figure 8A). When the body weights of male individuals were profiled, an inverse situation was observed. Here, we did not find significant differences between the two genotypes in early developmental stages (Figure 8B). In fact, between 8 and 20 weeks, the curves of the body-weight kinetics were superimposable, and using the Wilcoxon test, we did not observe a significant difference between the two genotypes. However, at later developmental stages (20–38 weeks), aP2-ALOX15 mice gained significantly more body weight that wildtype controls (Figure 8B). Although the extent of this difference was rather subtle, it was statistically highly significant (p = 0.0005). When the Wilcoxon test was applied for the entire experimental timescale, highly significant differences between aP2-ALOX15 mice and wildtype controls were observed for either sex (p < 0.0001), but the net effects were opposite in males and females. In females, aP2-ALOX15 mice gained less body weight, whereas male aP2-ALOX15 individuals gained more. The mechanistic basis for the observed gender specific effects have not been explored. We speculate that the transgenic expression of the ALOX15 in adipose tissue might impact the production of sexual hormones and/or of leptin in the adipose tissue. To test this hypothesis, additional experiments must be carried out that exceed the frame of the present study. Mammalian ALOX15 orthologs have been implicated in the differentiation of adipocytes [87], in the oxidative metabolism of fat cells [88], and in the remodeling of the adipose tissue [77]. ALOX15 mRNA expression was dramatically upregulated in white epididymal adipocytes when wildtype mice were fed a high-fat diet [87]. In 3T3 preadipocytes, ALOX15 is virtually absent, but its expression is strongly upregulated when cells were differentiated into adipocytes [87]. When treated with the ALOX15 products, these cells adopt a proinflammatory phenotype and lose their insulin resistance [9,87]. ALOX15−/− mice are resistant to the induction of type-1 diabetes [89] and also to the inflammatory effects of obesity induced by a Western-type diet [90]. ALOX15-deficient nonobese diabetic mice developed diabetes at a markedly reduced rate, demonstrated improved glucose tolerance, reduced severity of insulitis, and improved beta-cell mass when compared with age-matched nondiabetic ALOX15-sufficient controls. These results suggest an important role for ALOX15 in the pathogenesis of autoimmune diabetes [91]. In most of these studies, loss-of-function strategies were employed to evaluate the role of ALOX15 in the pathogenesis of obesity and diabetes, but the application of gain-of-function strategies was rare. To address this problem, we here created transgenic mice that overexpress human ALOX15 under the control of the aP2 promoter. Our qRT-PCR studies (Figure 3) and our ex vivo activity data (Figure 5) indicate the expression of the transgene in different types of adipose tissue but also in other mesenchymal cells such as bone marrow, spleen, and peritoneal macrophages. Although our data indicate that transgene expression may not be specific for adipocytes, we did not detect transgene expression in other major organs of our aP2-ALOX15 mice, such as in liver, skin, bones, kidney, or skeleton muscles. If one compares the aP2-ALOX15 mice created in this study with previously described ALOX transgenic mouse lines, the advantages and disadvantages of the aP2-ALOX15 mice can be summarized as follows: (i) Expression of the transgene is limited to a small number of special cell types, and thus, these mice are particularly suited for further investigations into the role of the ALOX15 pathway in adipocytes (Figure 5) and in hematopoietic cells (Table 2). In other studies, expression of the ALOX transgenes was controlled by different promoters directing transgene expression to other cell types [56,59,62,63,66]. Thus, for studies on the potential role of the ALOX15 pathway in adipocytes and hematopoietic cells, the previously created ALOX15 transgenic mouse lines are less suitable. On the other hand, the aP2-ALOX15 mice may not be useful to study the metabolic role of this enzyme in endothelial cells, epithelial cells, and/or macrophages. For such experiments, transgenic ALOX15 mice should be used, in which transgene expression is controlled by the preproendothelin [56], the lysozyme [63], scavenger receptor A [62], or the villin [66] promoter. (ii) In all previously created ALOX15 transgenic mouse lines, incorporation of the transgene into the genome was not controlled. Thus, multiple copies of the transgene might have been inserted, and incorporation of the transgene might have disrupted other genes. For the aP2-ALOX15 mice, we characterized the site of transgene insertion and found that the ALOX15 transgene was incorporated as a single-copy gene into the E1-2 region of chromosome 2 (Figure 2). Moreover, complete genome sequencing suggested that transgene incorporation did not structurally disturb other genes. (iii) In most previously created ALOX15 transgenic mouse lines, the catalytic activity of the transgenic enzyme was not tested, and thus, it was unclear whether the transgenic enzyme was catalytically active. For the aP2-ALOX15 mice, we carried out ex vivo ALOX15 activity assays with different cells and tissues and showed catalytic activity of the transgene (Figure 4 and Figure 5, Table 2). Moreover, we found that the product pattern formed from exogenously added arachidonic acid was very similar to that formed by recombinant human ALOX15 [79]. (iv) Although our ex vivo activity assays indicated the principle catalytic activity of the transgenic enzyme, such assays do not prove the in vivo activity. To show the in vivo activity of the transgenic ALOX15, we analyzed the plasma oxylipidomes (Figure 6) and found that in the blood plasma of the aP2-ALOX15 mice, the classical ALOX15 products formed from different polyenoic fatty acid were elevated. In contrast, there was no difference between aP2-ALOX15 mice and wildtype controls when unrelated oxylipins (e.g., 8-HETE, 8-HEPE, 8-HeTrE) were compared. These data suggest the in vivo activity of the transgenic enzyme. Corresponding experiments have not been carried out with any of the other ALOX transgenic mouse lines. (v) ALOX15 has been implicated in spermatogenesis, and ALOX15−/− mice are sub-fertile [84]. Thus, there is the possibility that transgenic overexpression of ALOX15 might impact the reproduction behavior of aP2-ALOX15 mice. To test the fertility of these animals, we evaluated the reproduction statistics and found no dramatic difference with wildtype mice (Figure 7). Similar experiments have not been carried out for any of the other transgenic ALOX15 mice. (vi) aP2-ALOX15 mice showed gender-specific differences to wildtype controls when their body-weight kinetics were evaluated (Figure 8). This observation is not trivial and must be considered in the interpretation of future experimental data obtained with these mice in animal disease models. Here again, body-weight kinetics have not been reported for any of the other transgenic mouse lines. In summary, one can conclude that the aP2-ALOX15 mice created in this study constitute the most comprehensively characterized transgenic ALOX15 mouse line currently available. The aP2-ALOX15 mice may also be used for rescue experiments reversing the effects induced by systemic or tissue-specific ALOX15 knockout. We recently reported that systemic inactivation of the ALOX15 gene induced subtle defects in the erythropoietic systems in ALOX15−/− mice, as indicated by significantly reduced Hb, HK, and Ery counts [92]. When the ALOX15−/− mice were crossed with our aP2-ALOX15 mice, we found that this defective phenotype was rescued, since the above-mentioned erythropoietic parameters were normalized [92]. From these data, we concluded that overexpression of human ALOX15 in hematopoietic cells may compensate for ALOX15 deficiency. Originally, we created these mice in order to study the role of ALOX15 in adipocytes. In previous cellular studies, different ALOX-isoforms and their metabolites have been implicated in adipogenesis and in the pathogenesis of the metabolic syndrome [9,93,94,95], which is associated with hyperplasia of the adipose tissue. The aP2-ALOX15 mice appear to be a valuable research tool to test these hypotheses in vivo. The present paper describes the production and basic functional characterization of these mice, which can later be used in different animal disease models associated with adipocyte hyperplasia. Since our lab is not specialized in such diseases, and since we do not have the suitable model systems, the aP2-ALOX15 mice may be employed by interested scientists in the frame of scientific collaboration. When we started this project, we had a long discussion regarding whether we should use the endogenous mouse Alox15 or the corresponding human ortholog (ALOX15) as the transgene. This discussion was prompted by the catalytic differences of the two ALOX15 orthologs. Human ALOX15 converts arachidonic acid mainly to 15S-HETE (90%), and only about 10% is formed as 12S-HETE [79,96]. Under identical experimental conditions, mouse Alox15 exhibits an inverse product pattern. Here, 12S-HETE is dominant, whereas 15S-HETE is a minor side product [82]. The molecular basis for this difference in the reaction specificity has been explored [97,98,99,100], and the Triad Concept [26,101] has been developed as a mechanistic tool for predicting the reaction specificity of mammalian ALOX15 orthologs on the basis of their primary structures. Moreover, the evolutionary hypothesis of mammalian ALOX15 specificity [102,103] suggests that ALOX15 orthologs of those mammalian species ranked in evolution above gibbons, including humans, chimpanzees, and orangutans, express arachidonic acid 15-lipoxygenating ALOX15 orthologs. In mammals ranking in evolution below gibbons, arachidonic acid 12-lipoxygenating ALOX15 orthologs are present. Thus, the vast majority (<95%) of mammals express an arachidonic acid 12-lipoxygenating ALOX15 ortholog, despite their annotation as ALOX15. However, several mammals (about 5%) including rabbits [104], mountain hares [103], kangaroo rats [105], anteaters, and bamboo rats [103] violate this concept. Thus, because of the dominance of arachidonic acid 12-lipoxygenating ALOX15 orthologs in mammals, the endogenous mouse ALOX15 should be employed as the transgene. However, the advantage of using the human ALOX15 as transgene is that the catalytic activity of this transgene can easily be followed. In mice, there is no arachidonic acid 15-lipoxygenating ALOX-isoform and thus, 15-HETE formation can be considered as a metabolic footprint of the transgene. In contrast, several mouse ALOX-isoforms, including the endogenous ALOX15, convert arachidonic acid to 12-HETE, and thus, profiling 12-HETE formation does not allow metabolic profiling of the transgene. Thus, we decided to use human ALOX15 as the transgene. Despite their different reaction specificity with arachidonic acid and 4,7,10,13,16,19-docosahexaenoic acid [83], mouse Alox15 and its human ortholog are very similar. They share a high degree (>85%) of amino acid sequence identity, and both enzymes are capable of oxygenating linoleic acid. For both enzymes, 13-H(p)ODE was identified as the dominant linoleic acid oxygenation product. Similarly, from 5,8,11,14,17-eicosapentaenoic acid, 15-H(p)EPE is formed as the major oxygenation product by the two ALOX15 orthologs [83]. Moreover, both ALOX15 orthologs are capable of oxygenating biomembranes, although human ALOX15 is somewhat more efficient. If ALOX15 orthologs fulfill their biological functions via the formation of specific oxygenation products from arachidonic acid or docosahexaenoic acid, there must be a functional difference between mouse and human ALOX15. In contrast, when product formation from linoleic acid and/or 5,8,11,14,17-eicosapentaenoic acid is more important, both enzymes should induce similar biological effects. If the biological functions of the ALOX15 orthologs are related to their ability to oxygenate complex substrates, there may not be major differences between mouse and human ALOX15. For clarity, we would like to discuss the following example. Rabbit ALOX15 has been implicated in late erythropoiesis [46]. When synthesized, the enzyme oxygenates mitochondrial membrane lipids, which initiates the maturational proteolytic breakdown of the mitochondria in mature reticulocytes. If this concept is transferred to other mammals, there should not be a major impact whether the ALOX15 ortholog is an arachidonic acid 12-lipoxygenating or an arachidonic acid 15-lipoxygenating enzyme. As long as the enzyme is capable of oxygenating the membrane lipids it will fulfill its biological function. Thus, in this case, the ability of the enzyme to oxygenate complex substrates is more important for the biological function than the reaction specificity with arachidonic acid. Moreover, linoleic acid is the major polyenoic fatty acid of mitochondrial membranes. Thus, the ability of mouse and human ALOX15 to oxygenate this substrate may be more important for the biological role of the enzyme than their reaction specificity with free arachidonic acid. In mouse bone marrow cells, several ALOX-isoforms (ALOX15, ALOX12, ALOX5) are constitutively expressed, and thus, these cells may be good models for the exploration of functional ALOX interaction. When these cells were incubated ex vivo with arachidonic acid (Table 2), we found that 12-HETE was dominant. In addition, small amounts of 15-HETE were also detected, whereas 5-HETE formation was minimal. The most plausible explanation for this product pattern was that 12-HETE formation may be due to the catalytic activity of both endogenous ALOX12 and ALOX15. Mouse ALOX12 exclusively produces 12-HETE, whereas the endogenous ALOX15 forms 15-HETE as a minor side product. When we knocked out ALOX15 expression, the relative share of 12-HETE formation was strongly reduced, and 15-HETE formation completely disappeared. Thus, in mouse bone marrow cells, endogenous ALOX15 is responsible for the formation of 15-HETE and parts of 12-HETE. Most interestingly, however, was the observation that functional inactivation of the ALOX15 pathway strongly upregulated the catalytic activity of endogenous ALOX5 (Table 2). In fact, 5-HETE was the dominant arachidonic acid oxygenation product when bone marrow cells of ALOX15−/− mice were incubated ex vivo with arachidonic acid. In peritoneal macrophages (Table 1), this effect was even more pronounced. Here, ALOX15-derived 12-HETE was dominant when ALOX15-sufficient cells were employed. In contrast, exclusive 5-HETE formation was observed with ALOX15-deficient macrophages. These data suggest that at least in bone marrow cells and in peritoneal macrophages, a catalytically active ALOX15 suppresses the ALOX5 pathway. Expression of the human ALOX15 transgene induced a similar repressive effect as the endogenous ALOX15 (Table 1 and Table 2). The most straightforward explanation for this observation is that endogenous and transgenic ALOX15 orthologs compete with endogenous ALOX5 for the exogenous substrate. However, there are two lines of experimental evidence arguing against this explanation: (i) the affinity of human ALOX15 [79] and human ALOX5 [106] for arachidonic acid is comparable, and thus, the suppressive effect cannot be related to competition of the two enzymes for the joint substrate; (ii) when we analyzed the free arachidonic acid, which was left over after the ex vivo incubation period, we found that about half of the substrate was not converted. These data suggest suppression of the ALOX5 pathway, even though plenty of exogenous arachidonic acid was present as ALOX5 substrate. Thus, simple substrate competition may not be the major reason for the suppression of the ALOX5 pathway by ALOX15 expression. The molecular basis for the suppressive effect of ALOX15 expression on ALOX5 has not been explored in detail, but it may be possible that primary and/or secondary products of the ALOX15 pathway directly inhibit ALOX5. This effect may be of biological relevance, since it may explain, at least in part, the anti-inflammatory role of ALOX15 in different mouse inflammation models [63,107,108], in addition to the ALOX15-dependent formation of special pro-resolving mediators [109,110] As indicated in Table 2, transgenic expression of human ALOX15 in bone marrow cells suppressed the catalytic activity of ALOX5 in our ex vivo activity assays. Unfortunately, we did not quantify the expression levels of endogenous ALOX5 or other ALOX-isoforms such as ALOX15b. In humans, ALOX15B converts AA to the same oxygenation product (15-HETE) as ALOX15, but its mouse ortholog exhibits a different product specificity [111] with free AA (8-HETE formation). Since we did not see major amounts of 8-HETE formation in our ex vivo activity assays using peritoneal lavage and bone marrow cells (Table 2), it may be concluded that ALOX15b expression in these cells may not be very pronounced. Moreover, analyses of the plasma oxylipidomes did not reveal significant differences between aP2-ALOX15 mice and wildtype controls; these data suggest that the endogenous ALOX15b pathway may have minimally altered by our genetic manipulation. For complex substrates, the situation is somewhat different. When nanodiscs involving AA-containing phospholipids were used as substrate for recombinant mouse and human ALOX15B orthologs, 15S-HETE-containing phospholipids were detected as major reaction products [112]. In other words, with phospholipids as substrate, mouse and human ALOX15B orthologs exhibit similar reaction specificities. Because of these observations, we cannot completely exclude, on the basis of our experimental data, the modification of ALOX15b expression in the aP2-ALOX15 mice. The biological role of ALOX15B has not been well-defined, neither in mice nor in humans. In a recent review [113], the different hypotheses on the putative physiological and pathophysiological functions of mammalian ALOX15B orthologs were summarized, but because of the lack of systemic ALOX15b−/− mice, most of these hypotheses have not been confirmed under in vivo conditions. The chemicals used for the different experiments were obtained from the following sources: phosphate-buffered saline without calcium and magnesium (PBS) from PAN Biotech (Aidenbach, Germany); EDTA from Merck KG (Darmstadt, Germany); arachidonic acid (AA) and authentic HPLC standards of HETE-isomers (15R/S-HETE, 12S/R-HETE, 8R/S-HETE, 5S-HETE) from Cayman Chem (distributed by Biomol GmbH, Hamburg, Germany); acetic acid from Carl Roth GmbH (Karlsruhe, Germany); sodium borohydride from Life Technologies, Inc (Eggenstein, Germany); restriction enzymes from ThermoFisher (Schwerte, Germany). Oligonucleotide synthesis was performed at BioTez Berlin Buch GmbH (Berlin, Germany). Nucleic acid sequencing was carried out at Eurofins MWG Operon (Ebersberg, Germany). HPLC-grade methanol, acetonitrile, n-hexane, 2-propanol, ethanol, and water were from Fisher Scientific (Schwerte, Germany). A colony of homozygous ALOX15−/− mice [35] that was provided years ago by Dr. C. Funk is kept in our animal house. These mice have been back-crossed into a C57BL/6J background several times [92] and were crossed with homozygous aP2-ALOX15 mice for ex vivo activity assays using peritoneal lavage cells (Figure 4). aP2-ALOX15 transgenic mice expressing human ALOX15 under the control of the aP2 promoter were created as described in Section 2.2. A total of 10–30 mg (wet weight) of different tissues were stored in RNAlater solution (Sigma-Aldrich/Merck, Taufkirchen, Germany), after which they were cut into small pieces using a scalpel and then homogenized in 400 µL of LBP buffer (Nucleospin RNA plus kit, Macherey-Nagel, Düren, Germany) using a FastPrep24 homogenizer. Cell debris was spun down, and from the homogenate supernatant, total RNA was extracted following the instructions of the vendor of the Nucleospin RNA plus kit (Macherey-Nagel, Düren, Germany). Subsequently, 500 ng of RNA was reversely transcribed using the Tetro Reverse Transcriptase kit (Meridian Bioscience, Memphis, TN, USA, distributed by BioCat GmbH, Heidelberg, Germany) and Oligo dT18 reagents as recommended by the vendor. qRT-PCR was performed as described before [114]. Briefly, for each target gene, specific intron-spanning amplification primer combinations were synthesized (BioTez GmbH, Berlin, Germany), and external amplification standards were prepared. The following primer combinations were used: mouse ALOX15, 5′-GTACGCGGGCTCCAACAACGA-3′ and 3′-TCTCCGGGGCCCTTCACAGAA-5′; human ALOX15, 5′-ACTGAAATCGGGCTGCAAGGGG-3′ and 3′-TGGCCCACAGCCACCATAACGG-5′. Expression of target genes was quantified using standard curves (known copy numbers of the external amplification standards) and was normalized to GAPDH expression. qRT-PCR was performed on a Rotor Gene 3000 device (Corbett Research, Mortlake, Australia). Amplification products were generated, and the progress of the amplification process was followed using the SensiMixTM SYBR PCR Kit (Meridian Bioscience, Memphis, TN, USA, distributed by BioCat GmbH, Heidelberg, Germany). Prometaphase chromosomes were prepared from three 8-week-old male aP2-15LOX1 mice. Spleen tissue was disrupted in 3 mL of RPMI 1640 medium using a dounce homogenizer. Six cell-culture flasks (75 cm2) containing 20 mL of RPMI 1640 medium, supplemented with 10% FCS, 7.5 µg/mL concanavalin A, and 5 µg/mL LPS (both from Sigma-Aldrich/Merck, Taufkirchen, Germany) were prepared. Then, 500 µL of homogenate was added to each flask and cultured for 48 h at 37 °C under 5% CO2-containing atmosphere. The cultured cells were harvested, and the cell suspension was filled into four 50 mL blue-cap tubes. Cells were pelleted by centrifugation for 10 min at 1000 rpm. Each cell pellet was resuspended in 10 mL of RPMI 1640 containing 10% FCS, and the two suspensions were combined. Then, 120 µL of Colcemid was added (Karyomax stock 10 µg/mL, ThermoFisher Scientific, Schwerte, Germany), and the cell suspensions were transferred to 15 cm Petri dishes. The dishes were incubated for 10 min at 37 °C, and then the cell suspensions were transferred into 50 mL blue-cap tubes. After centrifugation for 10 min at 1000 rpm, the supernatant was discarded, 10 mL of 75 mM KCl (37 °C) was added, and the samples were incubated for 15 min at 37 °C. Afterwards, 10 droplets of ice-cold fixative (20 mL of acetic acid + 60 mL of methanol) was added to each tube, and cells were pelleted by centrifugation (10 min at 1200 rpm, 4 °C). The supernatant was discarded and all cell pellets were combined and washed three times with 20 mL of fresh fixative at 4 °C. Finally, the cells, which were effectively reduced by the previous preparation to nuclei, were resuspended in 1 mL of fixative and kept at −20 °C until further use. For FISH, ~0.1–0.2 mL of fixative (with cells/nuclei) were applied to clean and humid slides and air-dried. During this step, spread metaphases were formed by sequential evaporation of methanol and acetic acid. Before vanishing from the slide surface, acetic acid attracts atmospheric water, and the nucleic material spreads, leading to enlarged interphase nuclei and well-spread metaphase chromosomes [115]. Slides were processed using a standard FISH procedure as previously reported [116]. For mapping of the ALOX15, cDNA was used as probe. ALOX15 cDNA was labelled by degenerate oligonucleotide primed polymerase chain reaction (DOP-PCR), incorporating biotin-dUTPs during the reaction. The ALOX15 cDNA probe was applied in a one-color FISH experiment, and the probe was either detected by avidin-tagged Spectrum Orange or Spectrum Green. Then, 20 metaphases were acquired on a Zeiss Axioplan microscope (Carl Zeiss, Jena, Germany) equipped with corresponding filters and ISIS software (MetaSystems, Altlussheim, Germany). The positions of the acquired metaphases were registered; thus, the same 20 metaphases could be evaluated again after a second FISH was conducted on the same slide using a commercial multicolor FISH probe (M-FISH) set staining all 21 different murine chromosomes in specific color combinations (“SkyPaintTM DNA Kit M-10 for Mouse Chromosomes”, Applied Spectral Imaging, Edingen-Neckarhausen, Germany). Accordingly, the chromosome in which the human ALOX15 cDNA was inserted could be identified. Genomic DNA was prepared from 58 mg of liver tissue using the Invisorb® Spin Tissue Mini Kit (Invitek Molecular GmbH, Berlin, Germany). An additional RNAse treatment was performed, and the RNA-free DNA preparation was quality-checked with agarose gel electrophoresis. The DNA was sequenced using the shot-gun technology (ATLAS Biolabs GmbH, Berlin, Germany). The whole genome sequence data can be obtained by interested scientists upon request from Dr. K.R. Kakularam For preparation of peritoneal macrophages, 10 mL of PBS was injected into the peritoneal cavity of sacrificed mice. The belly was gently massaged for 2 min and the fluid was removed by puncturing the peritoneal cavity. Usually, about 8–9 mL of cell suspension was recovered. Cells were spun down for 15 min at 800 g and were washed twice with PBS. Finally, the cells were reconstituted in 0.5 mL of PBS and were used for ex vivo ALOX activity assays. To prepare bone marrow cells, mice were sacrificed under anesthesia by cervical dislocation, and the two femur bones were prepared. The ends of the bones were cut off, and the bone marrow cavity was rinsed with 10 mL PBS. The cell suspensions were combined, and cells were pelleted (15 min, 800 g), washed twice with PBS, and reconstituted in 1 mL of PBS. Aliquots of this cell suspension were used for ex vivo ALOX activity assays quantifying the formation of oxygenated AA derivatives. To explore whether the transgenic human ALOX15 is expressed in different cells and tissues as a catalytically active enzyme, we carried out ex vivo activity assays using tissue homogenate or cell suspensions (peritoneal macrophages, bone marrow cells) as enzyme source. For the activity assays of solid tissues, 200 mg (wet weight) of tissue were homogenized in 2 mL of PBS using the Fast Prep-24 homogenizer (MP Biomedicals, Eschwege, Germany). The tissue homogenates were centrifuged for 10 min at 15,000× g (4 °C), and the homogenate supernatants were used as enzyme source. Aliquots (20–200 µL depending on the protein content) of the homogenate supernatants were incubated at room temperature in 1 mL of PBS containing 100 µM of arachidonic acid for 15 min. The reaction was terminated by the addition of 1 mg of solid sodium borohydride. After the addition of 35 µL of acetic acid, the lipids were extracted twice with 1 mL of ethyl acetate. Then, 1 mL of 2-propanol was added, and the solvents were evaporated in a rotatory evaporator. The remaining lipids were reconstituted in 0.5 mL of RP-HPLC column solvent (acetonitrile:water:acetic acid, 70:30:0.1, by vol.), the sample was sonicated, debris was spun down, and aliquots were injected for RP-HPLC quantification of the ALOX15 products. A similar method was employed for the ex vivo activity assays of the cell suspensions. For these assays, 1–10 × 106 cells were incubated at room temperature in 0.5 mL of PBS containing 100 µM of arachidonic acid. After 10 min, the hydroperoxy fatty acids that formed were reduced by the addition of 1 mg of solid sodium borohydride, the sample was acidified, and 0.5 mL of ice-cold acetonitrile was added. The protein precipitate was spun down, and aliquots of the protein-free supernatant were injected to RP-HPLC for quantification of the hydroxy fatty acids. To quantify the amounts of ALOX products formed during the incubation period of the ex vivo activity assays, a Shimadzu instrument (LC20 AD) equipped with a diode array detector (SPD M20A) was used, and the hydroxy fatty acids were separated on a Nucleodur C18 Gravity column (Macherey-Nagel, Düren, Germany; 250 × 4 mm, 5 μm particle size), which was coupled with a guard column (8 × 4 mm, 5 μm particle size). The analytes were eluted isocratically using a solvent system consisting of acetonitrile:water:acetic acid (70:30:0.1, by vol) with a flow rate of 1 mL/min at 25 °C. The absorbance at 235 nm (absorbance maximum of the conjugated dienes) was recorded, and the UV spectra of the dominant peaks that were recorded during the chromatographic runs were evaluated. Mouse Alox15 is an arachidonic acid 12-lipoxygenating enzyme [82], whereas the human ortholog oxygenates the same substrate predominantly to 15-H(p)ETE [78]. If aP2-ALOX15 transgenic mice have significantly elevated 15-HETE plasma levels, these data may be interpreted as an indication of the in vivo activity of the transgenic enzyme. To explore whether the pattern of the plasma oxylipins was impacted by in vivo expression of the transgenic human ALOX15, we quantified the amounts of more than 40 different free-oxygenated PUFAs in the blood plasma [117]. For this purpose, EDTA blood was drawn from sacrificed mice, and after a 15 min incubation period, the blood plasma was prepared by centrifugation. Then, 10 µL of blood plasma was mixed with 450 µL of water and 10 µL of a mixture of internal standards (LTB4-d4, 20-HETE-d6, 15-HETE-d8, 13-HODE-d4, 14,15-DHET-d11, 9,10-DiHOME-d4, 12,13-EpOME-d4, 8,9-EET-d11, PGE2-d4; 10 ng/mL each). Next, 5 µL of a butylhydroxytoluene (BHT) solution were added to prevent PUFA autooxidation during sample workup and storage. Plasma proteins were precipitated by the addition of 100 µL of a 1:4 mixture (by vol.) of glycerol/water and 500 µL of acetonitrile. The pH was adjusted to 6.0 by the addition of 2 mL of phosphate buffer (0.15 M), the precipitated proteins were removed by centrifugation, and the clear supernatant was used for solid-phase lipid extraction on a 200 mg Agilent Bond Elut Certify II cartridge (Agilent Technologies, Santa Clara, USA). Before sample application, the cartridge was conditioned with 3 mL of methanol and 3 mL of phosphate buffer (0.15 M, pH 6.0). After the sample was applied, the column was washed with 3 mL of a 1:1 mixture (by vol.) of methanol: water, and the oxygenated fatty acids were eluted with a 74:25:1 mixture (by vol.) of ethyl acetate: n-hexane:acetic acid. The solvents were evaporated in a stream of nitrogen, and the remaining lipids were reconstituted in 100 µL of a 6:4 mixture (by vol.) of methanol: water and used for LC-MS/MS analysis. The chemical identity of the different analytes was concluded from co-chromatography with authentic standards, and for each of the quantified metabolites, a calibration curve was established. LC-MS/MS was carried out on an Agilent 1290/II LC-MS system consisting of a binary pump system, an autosampler, and a column oven (Agilent Technologies, Waldbronn, Germany). As a stationary phase, we employed an Agilent Zorbax Eclipse C18 UPLC column (150 × 2.1 mm, 1.8 µm particle size). The column temperature was set at 30 °C. As a mobile phase, we used a solvent gradient that was mixed from two stock solutions. Stock A: water containing 0.05% acetic acid. Stock B: 1:1 mixture (by vol.) of methanol: acetonitrile. The HPLC system was connected to a triple-quadrupole MS system (Agilent 6495 System, Agilent Technologies, Santa Clara, CA, USA). Negative electrospray ionization was carried out. The mass spectrometer was run in dynamic MRM mode, and each metabolite was detected simultaneously by two independent mass transitions that are characteristic for the different analytes. Experimental raw data were evaluated with the Agilent Mass-Hunter software package, version B10.0. For all metabolites analyzed in this study, individual calibration curves were established, and the lower detection limits were also determined. More detailed information on this analytical procedure is given in [117]. Nineteen breeding pairs (1 male, 2 females/cage) were investigated in a time frame of 4–6 months, and the following reproduction parameters were determined: litters/month, pups/litter, male/female ratio, dead pups before weaning. The body weights of 5 males and 5 females (aP2-ALOX15 and C57BL/6 as controls) were determined once a week between 8 and 34 weeks of age. Statistical calculations and figure design were performed using GraphPad prism version 8.00 for Windows (GraphPad Software, La Jolla, CA, USA, (license obtained on 8 January 2021). Transgenic mice expressing human ALOX15 under the control of the aP2 (activating protein 2) promoter in addition to the endogenous ALOX15 are viable and reproduce normally, but exhibited gender-specific differences with wildtype controls when their body-weight kinetics were evaluated. These mice can now be used in whole-animal disease models associated with adipose tissue hyperplasia, such as adipositas, diabetes, and metabolic syndrome.

PMC10003073

36861685

Steffen Witte,Angela Boshnakovska,Metin Özdemir,Arpita Chowdhury,Peter Rehling,Abhishek Aich

Defective COX1 expression in aging mice liver

02-03-2023

Ageing,Mitochondria,Nanopore,Transcriptomics

ABSTRACT Mitochondrial defects are associated with aging processes and age-related diseases, including cardiovascular diseases, neurodegenerative diseases and cancer. In addition, some recent studies suggest mild mitochondrial dysfunctions appear to be associated with longer lifespans. In this context, liver tissue is considered to be largely resilient to aging and mitochondrial dysfunction. Yet, in recent years studies report dysregulation of mitochondrial function and nutrient sensing pathways in ageing livers. Therefore, we analyzed the effects of the aging process on mitochondrial gene expression in liver using wildtype C57BL/6N mice. In our analyses, we observed alteration in mitochondrial energy metabolism with age. To assess if defects in mitochondrial gene expression are linked to this decline, we applied a Nanopore sequencing based approach for mitochondrial transcriptomics. Our analyses show that a decrease of the Cox1 transcript correlates with reduced respiratory complex IV activity in older mice livers.

Defective COX1 expression in aging mice liver Mitochondrial defects are associated with aging processes and age-related diseases, including cardiovascular diseases, neurodegenerative diseases and cancer. In addition, some recent studies suggest mild mitochondrial dysfunctions appear to be associated with longer lifespans. In this context, liver tissue is considered to be largely resilient to aging and mitochondrial dysfunction. Yet, in recent years studies report dysregulation of mitochondrial function and nutrient sensing pathways in ageing livers. Therefore, we analyzed the effects of the aging process on mitochondrial gene expression in liver using wildtype C57BL/6N mice. In our analyses, we observed alteration in mitochondrial energy metabolism with age. To assess if defects in mitochondrial gene expression are linked to this decline, we applied a Nanopore sequencing based approach for mitochondrial transcriptomics. Our analyses show that a decrease of the Cox1 transcript correlates with reduced respiratory complex IV activity in older mice livers. Mitochondria play a key role in cellular energy metabolism by providing the bulk of ATP to drive cellular activities. Moreover, they carry out additional important metabolic tasks such as the tricarboxylic acid cycle (TCA), β-oxidation of fatty acids, and ketogenesis. Due to their prokaryotic origin, mitochondria contain their own genome and a perfectly adapted transcriptomic machinery that differs substantially from those used to express the nuclear genome. The circular mitochondrial DNA (mtDNA) encodes 2 rRNAs, 22 tRNAs, and 11 mRNAs encoding 13 polypeptides that are core subunits of the oxidative phosphorylation (OXPHOS) complexes in the inner membrane (Anderson et al., 1981). Mitochondrial transcription, translation, and assembly of the OXPHOS complexes are highly complex processes. The mitochondrial gene expression process is coordinated by numerous nuclear-encoded, imported regulatory factors (D'Souza and Minczuk, 2018; Basu et al., 2020; Barshad et al., 2018). Since each mitochondrial-encoded polypeptide is part of an OXPHOS complex, mutations in mitochondrial DNA cause severe disease phenotypes (Taylor and Turnbull, 2005). In addition, accumulating mitochondrial DNA mutations have been linked to cellular aging processes (Münscher et al., 1993; Zhang et al., 1993; Nekhaeva et al., 2002; Taylor et al., 2003; McDonald et al., 2008). However, these dysfunction influence aging is highly controversial and not yet fully elucidated (Kauppila et al., 2018; Wolf, 2021; Vermulst et al., 2007). Cellular senescence is considered as the process of general decline in cellular physiology leading to morbidity and mortality. Exploring further the connection between cellular aging and mitochondria, one finds that multifaceted pathways are linked with a mitochondrial contribution to aging (Sun et al., 2016). Conversely, age-related changes in the cell contribute to a severe decline in mitochondrial function as well (Chistiakov et al., 2014). The liver shows remarkable resilience to aging, but it is becoming increasingly clear that the liver mitochondria undergo similar cellular changes associated with aging as other tissues (Łysek-Gładysińska et al., 2021; Barazzoni et al., 2000). Aging causes changes to both the nuclear and mitochondrial genomes and the epigenome in liver (Hunt et al., 2019). Yet, also in hepatocytes, mitochondria fulfill crucial metabolic roles. In aged hepatocytes, mitochondria increase in size, show decreased membrane potential, and increased ROS production (Sugrue and Tatton, 2001; Sastre et al., 1996). Increased cell stress due to ROS production as a result of dysfunction of the OXPHOS system could also contribute to cellular aging. Because mitochondrial DNA, unlike nuclear DNA, lacks important repair and quality control mechanisms, mtDNA has been shown to be more susceptible to ROS (Miquel et al., 1980; Huang et al., 2020). However, it is not clear whether mtDNA mutations and mitochondrial malfunction are a cause, side effect, or consequence of aging. Therefore, more detailed insights into the role of mitochondrial DNA maintenance and transcription, and its adaptation to aging processes remain to be obtained. Analyses of the nuclear transcriptome provided new insights into a variety of molecular pathways and cell type-specific aging markers (The Tabula Muris Consortium, 2020; Zhang et al., 2021). Gene expression studies in aging mouse liver revealed pathways of fibrosis and immune response to be upregulated while those of metabolism and cell cycle appear to be downregulated (Pibiri et al., 2015; White et al., 2015). Furthermore, multi-time-point transcriptomics in rats showed that the most prominent pathway downregulated with aging was oxidative phosphorylation and respiratory electron transport (Shavlakadze et al., 2019). Considering the importance of mitochondrial gene expression for the biogenesis of the OXPHOS system, it is important to examine the effect of ageing on this process. New technologies, such as the recent development of Nanopore sequencing, allow for fast genome- and transcriptome sequencing in a wide range of research areas (Wang et al., 2021). Especially, for future analyses of mitochondrial dysfunction, its adaptation to changing metabolic conditions, and involvement in human disease pathogenesis, a reliable and fast approach for monitoring of the mitochondrial transcriptome would represent a key technical asset. Therefore, we established a method for transcriptome analysis of mitochondrial mRNAs. Together with functional analyses of mitochondria, this approach provides new insights into mitochondrial changes during aging in healthy hepatocytes. Considering a key role of mitochondria in aging and pathology, we investigated mitochondrial function in 12- and 65-week-old mice. For this, we established a Nanopore sequencing based method for mitochondrial transcriptome analyses. Our analyses revealed a robust decrease of mt-COX1 transcript abundance resulting in reduced protein levels. Loss of the core subunit COX1 is in agreement with reduced complex IV activity in aged mice samples. Our findings provide new insights into how altered gene expression contributes to the functional decline of hepatic mitochondria. Considering that hepatic cells are claimed to display to a certain extend resilience towards aging processes, we analyzed the correlation between different key parameters of mitochondrial physiology and age in the livers of young and aged mice 12 week (12 W) and 65 week (65 W), respectively (Fig. 1A). Livers excised from the 65 W mice showed a pale appearance. During the mitochondrial isolation the older livers also displayed a higher degree of fat layer abundance. The mitochondrial respiratory chain establishes a proton gradient across the inner membrane that drives ATP production by the F1Fo ATP synthase. To assess the mitochondrial membrane potential (Δσ), the isolated mitochondria from both experimental cohorts were stained with the membrane potential sensitive dye tetramethylrhodamin-methylester-perchlorat (TMRM). Applying the samples to flow cytometric analyses, we observed that the membrane potential was significantly reduced in the 65 W mice compared with that measured for the 12 W mice mitochondria (Fig. 1B). Similarly, when the isolated mitochondria were stained for superoxide production with fluorescent indicator MitoSOX, we found that superoxide levels were significantly increased in mitochondria from the 65 W mice compared to that of the 12 W mice (Fig. 1C). Based on these observations, we concluded that a decrease in the mitochondrial health parameters were apparent with increasing age. A reduction in the mitochondrial membrane potential with increased superoxide production are indicative of dysfunction of the respiratory chain and concomitantly the oxidative phosphorylation process. Therefore, we assessed mitochondrial oxygen consumption by real time respirometry to determine if a decline in oxidative phosphorylation was apparent with age. In the presence of non-limiting amounts of ADP and substrate (state 3) actively respiring mitochondria reach a maximal physiological respiration. We found that state 3 respiration was lower in 65 W liver mitochondria as compared to those from 12 W old mice (Fig. 2A). The addition of oligomycin and CCCP to measure the uncoupled maximal respiration showed a similar difference. When we quantified averages obtained from three measurements in each case, we observed that the rate of oxygen consumption was significantly reduced under all conditions (Fig. 2B). Subsequently, we measured the NADH and NAD+ levels in liver tissue lysates. Interestingly, both metabolites were increased in the 65 W mitochondria (Fig. 2C). However, the NAD+/NADH ratio was similar in both age groups. Surprisingly, quantification of the ATP levels in the experimental cohort liver lysates showed a significantly higher levels of ATP in the 65 W mice samples (Fig. 2D). To assess if the increased amounts of ATP at steady state were the result of increased glycolysis, we also measured the lactate levels in the same samples and found them to be increased in the 65 W mice samples (Fig. 2E). Accordingly, our results indicated that in the liver samples from older mice the activity of the respiratory chain is decreased and cells display a highly glycolytic metabolism. The reduced respiration observed in the mitochondria of 65 W mice led us to examine the amounts of mtDNA in the isolated mitochondria of the different mice. For this, we used equal amounts of purified mitochondria and treated the obtained DNA with RNAse to deplete mitochondrial RNA. Subsequently, we used real time PCR for a quantitative assessment of mtDNA. For complete coverage of mtDNA we used primers designed for several mitochondrial genes. These analyses showed that the mtDNA copy numbers were similar in both 12 W and 65 W mice (Fig. 3A). Next, we analyzed the protein levels of selected subunits of the mitochondrial OXPHOS complexes. Of the mitochondrial proteins addressed, only COX1 showed a reduction in the aged experimental cohort (Fig. 3B). Quantification of the blots confirmed a statistically significant reduction only in the levels of COX1 in the 65 W cohort (Fig. 3C). These findings suggested a selective effect on the cytochrome c oxidase (complex IV) of the respiratory chain. Accordingly, we assessed the activity of complex IV in the isolated mitochondrial. As expected from the steady state protein analyses, we found that the activity of complex IV was significantly reduced in the 65 week mitochondria samples, with a pronounced degree of variability compared to the 12 week samples (Fig. 3D). These findings on the activity of complex IV are in agreement with the reduced steady state levels of COX1. To address as to why COX1 levels were reduced in liver mitochondria of 65 week old mice, we decided to assess mitochondrial RNA levels. Since the isolated crude mitochondrial fraction used for our analyses also contained microsomal membranes, we further enriched mitochondria by sucrose density centrifugations. Gradient-purified mitochondria were processed for RNA isolation and subsequent DNAse digestion was performed to avoid mtDNA contamination. The purified RNA was subjected to library preparation and Nanopore sequencing (Fig. 4A). The use of PCR barcoding allowed us to pool all samples and to analyze these together. Although we used a poly dT primer annealing approach for library generation, we were able to obtain sequencing reads for mitochondrial ribosomal RNAs, Rnr1 and Rnr2. A detailed analysis of the reads showed that both RNAs contain a short internal stretch of poly A (Fig. 4B). Thus, the presence of an internal A-rich sequence enables poly dT primer annealing and subsequent recovery of Rnr1 and Rnr2. Subsequently, the Nanopore sequencing results were analyzed using the Epi2me Labs differential gene expression pipeline (Oxford Nanopore Technologies). Normalization of the data to Rnr2 was carried out and results displayed in a heatmap visualization (Table S2 for Mapped Trancript Counts). Interestingly, these analyses revealed that the Cox1 transcript was strongly decreased in all the 65 W samples (Fig. 5A). Further statistical analysis showed that Cox1 was the only transcript that was significantly different between mitochondria of the 65 W samples and those from the 12 W ones (Fig. 5B). Considering that we had incorporated barcodes using PCR in the experimental setup in order to multiplex the analysis, we decided to further exclude a PCR bias and inaccurate transcript number estimation. Therefore, we carried out qPCR analyses to confirm the reduction of the Cox1 transcript by an alternative approach. Using this second strategy, we were able to confirm the reduction the Cox1 transcript in liver mitochondria of 65 W samples (Fig. 5C). In conclusion, we observed a reduction of complex IV activity due to decrease in the levels of Cox1 mRNA and protein. This finding agrees with the observed decline in OXPHOS activity and changes of mitochondrial health parameters that we observe in the liver mitochondria from mice samples with age. Cellular functions decline with age. In addition to DNA damage and increased ROS production, aging has been found to be associated with metabolic dysfunction (Houtkooper et al., 2011). During the aging process, energy demands, lipid metabolism and reaction conditions change. The adaptation of the OXPHOS system to these changing conditions appears to be a highly dynamic process that can be influenced by a variety of (external) factors such as diet or exercise (Perelló-Amorós et al., 2021; Chen et al., 2018; McCoin et al., 2019; Han et al., 2012). In this context, the liver represents a critical organ for energy and lipid metabolism and hepatic mitochondria are a central hub for oxidative phosphorylation, fatty acid metabolism, and ketogenesis. Therefore, to study the effects of adaptation of metabolic pathways to changing conditions hepatocytes represent a suitable cellular system. Moreover, the liver is the only visceral organ that can regenerate and is exposed to a high degree to changing metabolic conditions (Michalopoulos and Bhushan, 2021). Therefore, mitochondria need to adapt to metabolic challenges. They proliferate in a process of mitochondrial biogenesis through fusion and fission from pre-existing mitochondria (Ploumi et al., 2017). Thus, the transcription and translation of nuclear genes coding for mitochondrial proteins appears to be critical for many aspects of cellular physiology (Kotrys and Szczesny, 2020). Here, we compared mitochondrial functions in the livers of young and old mice. Our analyses find that both ATP and lactate levels are significantly increased in liver in the aged group. This, in conjunction with the reduced oxygen consumption rates, indicates that the livers become increasingly glycolytic with age. Our finding is in line with previous studies which reported increased lactate levels and reduced glycolytic intermediates indicative of elevated anaerobic glycolysis (Houtkooper et al., 2011). Surprisingly, the NAD+ levels were found to be increased in this study. In contrast, other studies report a hepatic NAD+ deficiency in aged mice and humans (Zhou et al., 2016). However, in our analyses we found that the NAD+/NADH ratio remains unaffected in 65 W mice compared to the 12 W age cohort. In addition, we found a decrease in oxidative phosphorylation capacity of the mitochondria that are linked to a loss in COX1, the mitochondrial-encoded core subunit of the cytochrome c oxidase. Third-generation sequencing has revolutionized many aspects of biology from genome assemblies, metagenomics, epigenetics and transcriptomics (Kraft and Kurth, 2019). Additionally, the use of the MinION sequencer (Oxford Nanopore Technologies) allows rapid, sensitive and real time long read sequencing of nucleic acids (Player et al., 2020; Tyler et al., 2018). Coupled with barcoding, it possible to further reduce the machine run time by pooling all the samples and replicates in a single run. Here we applied this experimental approach to address if a loss COX1 was linked to the availability of the corresponding transcript. For this, we purified mitochondria to eliminate cytosolic RNAs from the samples to be analyzed. This enrichment allowed for extensive sequencing of the mitochondrial transcripts alone. However, on the downside this approach reduced the number of housekeeping genes that could be used for normalizing the data during analysis. Therefore, we started with equal amounts of purified mitochondria for RNA extraction and subsequently used equal amounts of RNA for cDNA preparations and library generation. We chose to base our analyses on polyadenylated RNAs for the initiation for cDNA and library preparation. The presence of an internal poly A stretch, long enough for the oligo dT primer to bind, enabled the analysis of the mitochondrial Rnr1 and Rnr2. Regarding the Cox1 transcript, the analyses revealed that in aged mitochondria the amount of the mRNA was specifically reduced in liver mitochondria of the 65 W mice while other transcripts were not affected. This reduction agrees with the observed decline in the respiratory activity. Key resources are specified in table S1. Maintenance of all mice and their study were performed according to the guidelines from the German Animal Welfare Act and approved by the Landesamt für Verbraucherschutz und Lebensmittelsicherheit, Niedersachsen, Germany (AZ: 33.9-42502-04-14/1720). The animals were kept either in high barrier (SPF-specified pathogen free) areas in IVC (individually ventilated caging) on standard rodent chow to WT C57BL/6N mice, with restricted access for animal care staff only. The WT C57BL/6N mice were historically acquired from Charles River Laboratories, Research Models and Services, Germany GmbH, Sulzfeld. They were subsequently maintained at the animal facility at Max Planck Institute for Multidisciplinary Sciences, Göttingen till they reached appropriate age for experimentation. The animals were sacrificed at the respective ages to isolate the liver. These were then homogenized using glass potters in 15 ml of Isolation Buffer (IB), containing 10 mM Tris-MOPS pH 7.4, 1 mM EGTA/Tris and 200 mM Sucrose. Nuclei, debris and unlyzed cells were removed by centrifugation at 700×g, 10 min, 4°C. Mitochondria were further pelleted at 7000×g, 10 min, 4°C. They were then washed and resuspended in Isolation Buffer and their protein concentration was determined using Bradford assay. To remove extramitochondrial nucleic acids from the isolated mitochondria, samples were first treated with 50 U Benzonase for 30 min, at 4°. Centrifugation (2×, 14,000×g, 10 min, 4°C) and resuspension in IB (composition as described in mitochondrial isolation, containing 2.5 mM EDTA) stopped the Benzonase activity. A sucrose gradient was prepared by placing 1 volume of isolation buffer containing 1.7 M sucrose into a centrifuge tube and overlaying this with 2 volumes of isolation buffer containing 1 M sucrose. Mitochondria were finally resuspended in 1 M sucrose isolation buffer and carefully loaded onto the gradient. After centrifugation for 25 min, 25,000 rpm (SW41Ti, Beckman Coulter) at 4°C, mitochondria were isolated from the interphase. Membrane potential measurement was conducted on isolated liver mitochondria (as described above) using a Flow Cytometer (FACSCanto, BD Biosciences). The mitochondria were resuspended in freshly prepared Analysis buffer (pH 7.0; 250 mM Sucrose, 20 mM Tris-MOPS, 100 µM Pi(K), 0.5 mM MgCl2, 5 mM Succinate, 2 µM Rotenone). 100 µM Tetramethylrhodamin-methylester-perchlorat, TMRM (Life Tech; T668) was added to all samples except the unstained control and the samples were incubated for 10 min at room temperature, protected from light. The measurement was done at Ex488/Em590 nm. Oxygen Consumption Rate (OCR) of freshly isolated liver mitochondria (isolation as described above) was obtained via respirometry on a Seahorse XFe96 analyzer (Agilent; S7894-10000). The mitochondria were resuspended in Mitochondrial Assay (MAS) Buffer (pH 7.4; 70 mM Sucrose, 210 mM Mannitol, 5 mM HEPES, 1 mM EGTA, 10 mM KH2PO4, 5 mM MgCl2, 0.5% BSA(w/v) to a concentration of 0.1 mg/ml. The mitochondria were aliquoted in the Seahorse XF96 Cell Culture Microplate (Agilent; 101085-004) and the plate was centrifuged at 2000×g for 5 min at room temperature. In port A of the Seahorse XFe96 Sensor Cartridge (Agilent; 101085-004) either a Pyruvate (0.1 M Pyruvate, 40 mM Succinate, 40 mM ADP in MAS buffer) or Succinate (100 µM Succinate, 40 µM ADP in MAS buffer) mix was provided as substrate for the mitochondria. 30 µM of Oligomycin, 40 µM of CCCP, 10 µM of Antimycin and Rotenone dissolved in MAS buffer were added in ports B, C, and D of the Sensor Cartridge respectively. A modified Mito Stress Test protocol was used for the measurement. The modifications were the removal of the Equilibration step for the Cell Plate to minimize the stress time on the isolated mitochondria and the addition of another Port injection to accommodate for the substrate. Quantification of NAD+/NADH ratio in mouse liver tissue samples was done using a NAD+/NADH Quantification Kit (Sigma-Aldrich; MAK037). The protocol provided by the supplier was followed. NADtotal as well as NADH were detected measuring absorbance at 450 nm on a microplate reader (Synergy H1; BioTek; 8041000) following mechanical lysis and deproteination of the lysates. In order to measure NADH separately from the NADtotal, NAD+ was thermally decomposed by a 30 min incubation at 60°C. Measurement of total tissue ATP content was done using the ATP Assay Kit (Colorimetric/Fluorometric) (Abcam; ab83355) and as specified by the protocol from the supplier. In order to determine total ATP mouse liver tissue was lysed mechanically and deproteinized. Samples were incubated for 30 min at room temperature with the reaction mix in triplicates. The phosphorylation of glycerol resulting in a product detectable at 570 nm was measured using a microplate reader (Synergy H1; BioTek; 8041000). L-Lactate Assay Kit (Colorimetric/Fluorometric) (Abcam; ab65330) was used in order to detect lactate in mouse liver tissue lysate. The experiment was performed as instructed in the protocol provided by the supplier. Following mechanical lysis, the samples were deproteinized and assayed for 30 min. Lactate was detected calorimetrically at 570 nm. The measurement was done in triplicate and visualized using a microplate reader (Synergy H1; BioTek; 8041000). The QIAamp® DNA Blood Mini Kit was used to isolate mitochondrial DNA from mitochondria. The isolated mitochondria (see above) were diluted 1:50 in the provided sample buffer and the manufacturer's protocol was executed. The isolated and purified mitochondria were lysed in 1 ml TRIzol using the vendor's protocol. The samples were then treated with DNase I (ThermoFisher Scientific) following the manufacturer's instructions. For purification of the sample, the RNA Clean and Concentrator Kit (R1013, Zymo Research) was used. The RNA quality and concentration were measured using a Nanodrop 2000. cDNA was synthesized using the RevertAid First Strand cDNA Synthesis Kit (K1621; ThermoFisher Scientific), specifically using the Random Hexamer primers from the isolated RNA (described in the previous section) in a thermocycler (Labcycler Gradient, SensoQuest GmbH). The cDNA was used in quadruplicates for a Real Time PCR reaction with Sensi Mix SYBR Low-ROX Kit (QT625-05; Bioline) on a Quant Studio 6 Flex Real-Time PCR system (4485691; ThermoFisher Scientific). All the primer sequences of the primers used are available upon request. Tricine-SDS PAGE was performed using standard methods. The samples were lysed in T-PER Tissue Protein Extraction Buffer (ThermoFisher Scientific; 78510). The gels used were gradient 10-18% gels. Western blotting was preformed using standard semi-dry transfer. The Complex IV Rodent Enzyme Activity Microplate Assay Kit (Abcam; ab109911) was used to assess the activity of the Cytochrome c Oxidase in isolated mouse liver mitochondria. The procedure was performed as instructed by the provider. The principle of the assay is the use of immunoprecipitated mitochondrial complex IV, whose activity gets determined by the oxidation of Cytochrome c. A microplate reader (Synergy H1; BioTek; 8041000) was used to measure the absorbance of cytochrome c, which turns colorless due to its oxidation and is detectable at 550 nm. Total mitochondrial RNA was purified and concentrated on an RNA Clean Concentrator™-5 column (Zymo Research, Irvine, CA, USA). cDNA libraries were prepared from a mix of 50 ng RNA according to the Oxford Nanopore Technologies (Oxford Nanopore Technologies Ltd, Oxford, UK) protocol ‘DNA-PCR Sequencing’ with a 14 cycles PCR (8 min for elongation time). ONT adapters were ligated to 650 ng of cDNA. Nanopore libraries were sequenced using a MinION Mk1b with R9.4.1 flowcells. The data were generated and basedcalled using MinKNOW (Version 21.11.9). The fastq files were then uploaded to and analyzed using the Epi2Me Labs (Version 1.1) Differential Gene Expression workflow. Transcript counts obtained were processed for heatmap and volcano plot generation using Prism 9 software (GraphPad Software, San Diego, CA, USA). Significant differences between means of two (or more) sets of data were analyzed using either unpaired t-tests or ANOVA tests in Prism 9 software (GraphPad Software, San Diego, CA, USA, unless otherwise noted. Maintenance of all mice and their study were performed according to the guidelines from the German Animal Welfare Act and approved by the Lower Saxony government office ethic committee, Landesamt für Verbraucherschutz und Lebensmittelsicherheit, Niedersachsen, Germany (AZ: 33.9-42502-04-14/1720). All methods are reported in accordance with ARRIVE guidelines for the reporting of animal experiments. 10.1242/biolopen.059844_sup1 Click here for additional data file.

PMC10003075

Ulrich Wirth,Tianxiao Jiang,Josefine Schardey,Katharina Kratz,Mingming Li,Malte Schirren,Florian Kühn,Alexandr Bazhin,Jens Werner,Markus Guba,Christian Schulz,Joachim Andrassy

The Role of Microbiota in Liver Transplantation and Liver Transplantation-Related Biliary Complications

02-03-2023

liver transplantation,biliary microbiome,biliary complications,multi-drug resistant microbiota,ischemic-type biliary lesions

Liver transplantation as a treatment option for end-stage liver diseases is associated with a relevant risk for complications. On the one hand, immunological factors and associated chronic graft rejection are major causes of morbidity and carry an increased risk of mortality due to liver graft failure. On the other hand, infectious complications have a major impact on patient outcomes. In addition, abdominal or pulmonary infections, and biliary complications, including cholangitis, are common complications in patients after liver transplantation and can also be associated with a risk for mortality. Thereby, these patients already suffer from gut dysbiosis at the time of liver transplantation due to their severe underlying disease, causing end-stage liver failure. Despite an impaired gut-liver axis, repeated antibiotic therapies can cause major changes in the gut microbiome. Due to repeated biliary interventions, the biliary tract is often colonized by several bacteria with a high risk for multi-drug resistant germs causing local and systemic infections before and after liver transplantation. Growing evidence about the role of gut microbiota in the perioperative course and their impact on patient outcomes in liver transplantation is available. However, data about biliary microbiota and their impact on infectious and biliary complications are still sparse. In this comprehensive review, we compile the current evidence for the role of microbiome research in liver transplantation with a focus on biliary complications and infections due to multi-drug resistant germs.

The Role of Microbiota in Liver Transplantation and Liver Transplantation-Related Biliary Complications Liver transplantation as a treatment option for end-stage liver diseases is associated with a relevant risk for complications. On the one hand, immunological factors and associated chronic graft rejection are major causes of morbidity and carry an increased risk of mortality due to liver graft failure. On the other hand, infectious complications have a major impact on patient outcomes. In addition, abdominal or pulmonary infections, and biliary complications, including cholangitis, are common complications in patients after liver transplantation and can also be associated with a risk for mortality. Thereby, these patients already suffer from gut dysbiosis at the time of liver transplantation due to their severe underlying disease, causing end-stage liver failure. Despite an impaired gut-liver axis, repeated antibiotic therapies can cause major changes in the gut microbiome. Due to repeated biliary interventions, the biliary tract is often colonized by several bacteria with a high risk for multi-drug resistant germs causing local and systemic infections before and after liver transplantation. Growing evidence about the role of gut microbiota in the perioperative course and their impact on patient outcomes in liver transplantation is available. However, data about biliary microbiota and their impact on infectious and biliary complications are still sparse. In this comprehensive review, we compile the current evidence for the role of microbiome research in liver transplantation with a focus on biliary complications and infections due to multi-drug resistant germs. Liver transplantation (LT) is the only available treatment for patients with end-stage liver disease and acute liver failure with a definite long-term survival benefit since the 1960s [1]. Despite significant improvements both in surgical techniques as well as in postoperative medical care [2], biliary tract reconstruction remains a major source of short- and long-term morbidity. Biliary complications occur in up to 40% of patients after orthotopic liver transplantation [3,4]. Biliary leakage and bile duct strictures are the most common biliary complications [5,6,7,8]. Strictures can be classified as anastomotic or non-anastomotic according to their localization. Non-anastomotic intrahepatic strictures (NAS) are the most troublesome biliary complication and are either associated with hepatic artery thrombosis or can be referred to as “ischemic-type biliary lesions (ITBL)” [9]. Furthermore, biliary tract infections can occur due to ascending infections or due to microbial colonization already present at the time of transplantation [10]. Especially in patients with repeated biliary interventions and antibiotic therapies, the biliary tract can be colonized by a wide spectrum of potential pathogen microbiota [11,12,13]. However, despite pure colonization, infections, especially with multi-drug resistant microbiota, play a crucial role, as they can cause severe morbidity and are associated with an increased risk for mortality [14,15,16]. All these biliary complications chronically impair liver graft function and can lead to graft failure and the need for re-transplantation in some of the cases [9,17,18]. The human gastrointestinal tract harbors a complex and diverse population of microorganisms known as the gut microbiome. Given its anatomical position, the liver has a bidirectional relationship with the intestine and its microbiota, known as the “gut-liver axis,” which exhibits circular causality [19]. The liver thus represents the first line of defense against gut-derived antigens and toxicity factors. End-stage liver disease, as well as LT, is often associated with changes in the composition of the gut microbiome due to antibiotic therapy, interventions, altered anatomy from surgery, biliary complications, and the use of immunosuppression [20,21,22]. Available studies on humans have shown that LT can improve gut microbiota diversity in patients with end-stage liver diseases, accompanied by a higher relative abundance of beneficial bacteria and suppression of pathogenic Gram-negative bacteria [22], even with the use of immunosuppressants [23]. For a long time, the biliary tract has been considered a hostile territory for microbiota because bile acids, cholesterol, phospholipids, and biliverdin within the bile act as a biological detergent that emulsifies lipids and thus dissolves bacterial membranes. Various works on animal models and humans could disprove that the biliary tract is sterile [24,25,26,27]. Furthermore, a recent study on humans showed that the biliary tract seems to have a complex microbiota, even in healthy individuals [28]. Wu et al. even proposed that in humans, the bacterial diversity is higher in the biliary tract than in the intestine [29]. Due to bacterial colonization and immunosuppression, biliary infections are a frequent cause of biliary complications in liver transplant recipients [30,31]. Results from previous clinical studies have shown that pathogenic bacteria can be detected in specimens of bile or bile ducts in patients with biliary complications after liver transplantation [13,32]. In this review, we want to elucidate the role of microbiota in the context of liver transplantation, with a specific focus on the growing issue of multi-drug resistant microbiota. Finally, the biliary complications of LT are discussed in terms of the underlying role of the local microbial niche. The gut-liver axis refers to the bidirectional relationship between the intestine and the liver, in which they communicate and interact with each other through various pathways, including the portal venous and biliary systems (Figure 1). The liver plays a crucial role in detoxifying substances such as bacterial toxins from gut microbiota [19]. One of the major components of the gut-liver axis are bile acids, which serve as pleiotropic signaling molecules [33]. Primary bile acids are synthesized from cholesterol, which is later conjugated with glycine or taurine in the liver and released into the duodenum as primary bile salts. Bacteria in the gut will first deconjugate the primary bile salts into primary bile acids by removing the glycine or taurine and then modify the primary bile acids into secondary bile acids by 7α-dehydroxylation. Both primary and secondary bile acids could be further oxidized into less toxic oxo-bile acids or epimerized into non-toxic iso-bile acids by gut microbiota. While most bacteria can perform oxidization and synthesize oxo-bile acids, only some of the microbes are able to perform dehydroxylation and epimerization and synthesize iso-bile acids [33]. In patients with end-stage liver diseases, there is often a low bile acid secretion into the intestine as a result of cholestatic conditions [34]. Furthermore, there is a reduction in secondary bile acids due to reduced colonization by beneficial bacteria that perform the 7α-dehydroxylation [35]. The increase in secondary iso and oxo-bile acids in patients after LT serves as a biomarker of the proliferation in Firmicutes and reduction in Proteobacteria, which can be referred to as a reconstitution of a regular gut microbiome. Moreover, this provides better protection against opportunistic nosocomial bacterial overgrowth, such as Clostridium difficile, which are inhibited mainly by the secondary rather than the primary bile acids [36]. In healthy individuals, the gastrointestinal tract prevents bacterial translocation towards the liver through the intestinal barrier, mucus layer, and various antimicrobial proteins. A small amount of gut bacterial components could enter the portal blood circulation without triggering an immunological response due to the immune tolerance of the liver [37]. However, in conditions such as gut dysbiosis, inflammation, and loss of those barriers, an increased number of bacterial components enter the portal blood circulation, thereby triggering hepatic inflammation and fibrotic remodeling [38]. Seventy-five percent of primary sclerosing cholangitis (PSC) cases are associated with gut dysbiosis [39,40]. Furthermore, data demonstrate that colectomy due to various factors, including associated ulcerative colitis and colorectal cancer, can reduce PSC relapse in 37% of patients, reflecting the role of gut microbiota in inflammation-related liver diseases [41,42]. Not only for PSC but in other biliary diseases such as primary biliary cholangitis and biliary atresia, recent studies have demonstrated the essential role of innate immune responses [43,44]. These responses are triggered by microbial patterns, highlighting the importance of host-microbe interaction in the development of these conditions [37,38]. Overall, the gut-liver axis is important for the maintenance of immune function as well as metabolism and depends on the homeostasis of the gut microbiota. Therefore, it can be severely compromised in end-stage liver disease and associated gut dysbiosis. Gut microbial dysbiosis is associated with various liver diseases, including liver cirrhosis, hepatocellular carcinoma, and non-alcoholic fatty liver disease [45]. Therefore, LT is often associated with changes in the composition of the gut microbiome with possible restitution over time. At the time of LT, donor microbiota can be transferred to the recipient via the liver allograft [45]. Furthermore, increased intestinal permeability caused by surgery will allow certain pathogens to enter the portal or systemic circulation, and donor immune cells of the liver graft can interact with the recipient’s gut microbiome via the gut-liver axis [20,21,22]. A qPCR-based analysis of samples from 111 LT patients showed a decrease in Bifidobacterium, Lactobacillus, and Faecalibacterum and an increase in Enterobacteriaceae and Enterococcus in the gut microbiota of post-LT patients [46]. It is noteworthy that the indicators for the severity of liver cirrhosis, including a model for end-stage liver disease (MELD), Child-Pugh score, total bilirubin, pro-thrombin time test, international normalized ratio, creatinine level, and albumin level, were associated with higher amounts of a certain genus of bacteria, such as Streptococcus, Veillonella and Clostridium [47]. Patients with a higher amount of these bacteria had a significantly more severe illness compared to those with a low amount [47]. Another human study also showed a positive association between the severity of cirrhosis, as measured by Child-Pugh scores, and the presence of Streptococcus spp. [48]. These findings suggest that certain bacteria may play an active role in liver cirrhosis, as the correlation follows a “dose-response” pattern [47]. In another study, including 177 patients undergoing liver transplantation, Annavajhala et al. could demonstrate a correlation between disease etiology and gut microbiome diversity [16]. Especially patients with alcohol-related liver cirrhosis had significantly lower α-diversity measures compared to other diagnoses, whereas patients suffering from hepato-cellular carcinomas had significantly higher α-diversity measures [16]. Furthermore, the relative abundance of specific microbiota such as Enterococcus casseliflavus, Veillonella dispar, Faecalibacterium prausnitzii, or Bifidobacterium bifidum was different depending on disease etiology [16]. In their data, the microbial communities clustered differential for Child-Pugh A vs. Child-Pugh C patients as well as for patients with high or low MELD scores [16]. Specific changes in the gut microbiome could be detected in the post-LT phase, as in the first weeks following LT; usually, the diversity is reduced due to perioperative broad-spectrum antibiotic therapy [16]. In the perioperative phase, an enrichment in Clostridiales, Streptococcus, and Enterococcus spp. could be detected [16]. In the further months after LT, there was an increasing α-diversity, and distinct microbial patterns were identified in early (1–3 months) vs. late (6–12 months) post-LT phases [16]. Yet, there is not enough data that the gut or biliary microbiome is reliably able to predict outcomes or prognosis in LT patients [45]. Notably, LT and the administration of antibiotics can disrupt the microbial balance in the intestines of patients, leading to decreased beneficial and increased pathogenic bacteria [49]. Several studies on both animal models and humans report a beneficial effect of pro- and prebiotics on the outcome of liver transplantation regarding infectious complications, but no microbiome analysis has been included in these studies [50]. Taking into account that pre- and probiotics are proven to have beneficial effects on the gut microbiome, can enhance immune responses, and may have anti-inflammatory effects [51], probiotics and prebiotics may help reduce post-LT complications, including severe infections and liver injury, by altering the gut microbiome [50,52]. In general, moderate alterations of the gut microbiome after LT contribute to an increased tolerance of the liver allograft. Regulatory T cells (Tregs) secrete inhibitory cytokines and interact with CD80 that downregulates T cell activation, thereby inhibiting effector T cells [52]. Therefore, Tregs prevent the development of acute cellular rejection (ACR) by inducing a tolerogenic environment with an intact immune system in LT patients. Gut dysbiosis in post-LT patients increases abnormal portal circulation of bacterial products like LPS. Kupffer cells respond to such change by increasing concentrations of IL-10 with an anti-inflammatory effect [53]. In addition, such change also induces type 1 interferon and stimulates myeloid cell IL-10 production, thereby further increasing IL-10 concentrations in the liver [54]. Other research showed that LPS-induced local inflammation upregulates CD80 in a murine model [55]. If this finding is applicable to humans, post-LT dysbiosis could increase the apoptosis of CD8+ T cells and increase the tolerance of the liver allograft [56]. An increase in gut Bacteroides fragilis and Bacteroides thetaiotaomicron was found to drive regulatory T cell induction and differentiation in post-LT patients, which is correlated with a more tolerant alloimmune response [57]. However, excessive upregulation of Tregs could lead to reduced alloreactive T cell proliferation, thereby increasing the risk of post-LT malignancies and infections [45]. Gut dysbiosis can also affect the balance of CD4+ T cell subsets in mesenteric lymph nodes [58], and migrations of such altered T cells will promote hepatic injury or ACR [59]. In terms of post-LT hepatic ischemia-reperfusion (I/R) injury, several animal studies suggested that gut dysbiosis could exacerbate I/R injury-mediated development of early ACR in the post-LT patients because increased segmented filamentous bacteria could aid in IL-17 expression [60,61]. However, alterations in gut microbiota could potentially improve early ACR outcomes by alleviating hepatic I/R injury. It has been demonstrated that butyrate-altered gut microbiota can prevent NF-κB activation and upregulate 3,4-dihydroxy phenyl propionic acid, thereby mitigating macrophage pro-inflammatory activity and increasing the protective effect of nucleotide-biding oligomerization domain-containing protein 2 (NOD2) [62]. This effect is associated with decreased I/R injury, thus improving the early LT outcome. Gut dysbiosis can result in increased bacterial translocation from the gut into the liver allograft, thereby increasing antigen exposure. This can have a dual effect: low-dose antigen exposure in the liver can increase tolerance of the liver towards the allograft, while high-dose antigen exposure can stimulate an enhanced immune response, thereby promoting ACR [63]. Patients with gut dysbiosis are more susceptible to negative outcomes, including acute-on-chronic liver failure and advanced cirrhosis in the pre-LT period [64,65]. The impaired microbial functionality in end-stage liver disease is reflected by a lower conversion of bile acids, changes in ammonia metabolism, as well as changes in microbial-mammalian co-metabolites such as trimethylamine-N-oxide (TMAO) [34,66]. Since converted bile acid can suppress pathogens, their reduction becomes worrisome in the pre-LT period [36]. Consequences of exacerbated gut microbial production include hyperammonemia, which can result in the development of hepatic encephalopathy [67]. Studies in animals and cell cultures have shown that TMAO can stimulate the production of various pro-inflammatory molecules, including IL-1β, IL-6, TNF-α, NF-κB, and MMP9, thereby inducing inflammatory responses in the liver and other organs, such as the aortic root [68]. Additionally, TMAO has been shown to link gut microbiota with the development of atherosclerosis and cardiovascular changes [66]. Given the pro-atherogenic profile post-LT, the role of TMAO needs to be further investigated. There is evidence especially based on animal trials in rodents, that the immunosuppressive therapy itself induces changes in the gut microbiome [23,69]. Ling et al. report specific alterations in the relative abundance of Firmicutes and Bacteroides due to tacrolimus treatment in mice [23]. Different effects have been observed for tacrolimus regarding microbial diversity and richness as well the relative abundance of, e.g., Clostridium, Ruminococcaceae, Bifidobacterium, Bacteroides, and Lactobacillus [69]. Overall, tacrolimus induces a gut dysbiosis comparable to metabolic diseases and alters microbiome-associated metabolic functions such as carbohydrate and lipid metabolism [69]. Mycophenolate Mofetil (MMF), another immunosuppressive drug used in LT, not only causes dysbiosis, which can lead to colitis, but endotoxemia due to an increase in Gram-negative bacteria as well as an impairment of the mucosa barrier and therefore increased gut permeability [69]. Taken together, there are many effects of different used immunosuppressive drugs on the gut microbiome based on animal trials, which may have an impact on LT patients’ outcomes [69]. Only sparse data are available at present, and all these effects are not taken into account in routine clinical practice and treatment of LT patients yet. While the current literature on the role of gut microbiota in post-liver transplantation outcomes is limited, studying the role of gut microbiota is crucial. Previous studies have demonstrated a potentially beneficial effect of pre- and probiotics to improve outcomes of post-LT course [70], despite the observed beneficial change in the gut microbiota composition and functionality after successful LT [22]. The effects of necessary immunosuppressive therapy on the gut microbiome and the intestinal barrier have been insufficiently studied to date [69]. Infections are a major cause of morbidity and even mortality after LT. Despite advances in surgical technique, strategies to prevent infections, and modern immunosuppression regimens, infections still occur in up to 40–50% during short-term and in up to 80% during long-term follow-up after LT [14,15,16]. LT recipients are susceptible to infection due to the technical complexity of the surgical procedure, contamination of the abdominal cavity, and the usually poor medical condition of LT recipients [14,71]. In addition, underlying end-stage liver diseases are related to intestinal and biliary tract dysbiosis; the latter caused by repeated biliary tract interventions [16,72,73]. Recently published data show that end-stage liver disease is associated with immune dysfunction, changes in the local microbial milieu, and an increase in bacterial translocation due to an impaired mucosal barrier [16,72]. Annavajhala et al. demonstrated an inverse correlation of the microbial diversity with MELD- or Child-Pugh score values at the time of transplantation, indicating significant gut dysbiosis at the time of transplantation [16]. The risk for infection is considered to be highest in the first month after transplantation and decreases steadily thereafter [14,71]. Some data report risk factors for post-LT infections, such as patient condition at LT, length of stay in the intensive care unit, prolonged need for catheters, blood transfusions, and duration of surgery [14,15,74,75,76,77]. The most common sites of infection are the abdomen, lungs, bloodstream, and urinary tract [14,15,71,75]. While abdominal infections predominate in the first month in terms of surgical site infections and early bile duct complications, the rate of pulmonary and bloodstream infections increases over time [15,71,75,78]. Most notably, biliary tract infections or cholangitis occur due to leakage and strictures in the bile ducts and are associated with repeated procedures such as Endoscopic Retrograde Cholangiopancreatography (ERCP) [73]. This favors colonization of the bile ducts with various potentially pathogenic germs from the intestine [13,73]. In an analysis by Kabar et al. of bile duct samples from ERCP in LT recipients, 86.6% of samples tested positive for at least potential pathogenic bacteria, and nearly 80% were polymicrobial [73]. Overall, most infections after LT are primarily caused by bacteria, followed by viral and fungal causes [14,15,71,78]. For bacterial infections, in the Gram-negative spectrum, E. coli, Klebsiella spp., and other Enterobacteriaceae are the most important germs, whereas, for Gram-positive germs, Enterococcus spp. and Staphylococcus spp. are the most common infectious agents [14,15,75,78]. Several studies have reported that especially Enterococcus spp. are the predominant pathogens found in LT-related infections [75,76,77]. Kim et al. reported 112 episodes of bloodstream infections in 64 LT recipients with Enterobacteriaceae spp. (32.5%), Enterococci spp. (17.8%), Staphylococci spp. (10.3%), and Acinetobacter baumanii (10.3%) being the most common germs due to biliary tract and other abdominal or catheter infections [15]. They also note that most germs showed resistance to major antibiotics [15]. Infections caused by multidrug-resistant (MDR) germs are a major problem and are associated with an increased risk for mortality [16,74,79,80]. Several data show that infections with vancomycin-resistant Enterococcus spp. (VRE) in particular, are associated with prior antibiotic use, higher rates of biliary complications, more abdominal surgeries, and, most importantly, lower survival [80]. In contrast, colonization with VRE was associated with only a small 1-year mortality risk of about 7% [79]. On the other hand, there is an increasing number of Gram-negative multidrug-resistant germs such as E. coli, Klebsiella spp., Citrobacter spp., and other Enterobacteriaceae [74]. Especially in biliary tract and pulmonary infections, these Gram-negative MDR bacteria play an important role by increasing mortality and days in the intensive care unit compared to “normal” non-MDR infections [74]. On the other hand, the risk for infections after LT is determined by the intensity of immunosuppression [31,81]. Especially in the first months after LT, the intensity of immunosuppressive therapy is much more intensive compared to the later immunologically stable course, associated with a correspondingly higher risk of infection [81,82]. Overall, there is a higher susceptibility to bacterial infections due to colonizing potential pathogen germs and opportunistic infections related to immunosuppressive therapy, which can cause serious morbidity [14,81]. Usually, the risk for at least opportunistic infections is addressed by antibiotic prophylaxis in immunosuppressed patients [14,81]. Specifically, for pulses of steroids in acute graft rejection, there seems to be no elevated risk for infections [14]. A recent analysis of the gut microbiome in LT recipients showed that 65% of patients developed colonization with MDR bacteria, e.g., VRE, carbapenem-resistant Enterobacteriaceae, or Enterobacteriaceae resistant to third generation cephalosporins, within 1 year of LT [16]. Patients colonized with MDR bacteria presented a lower α-diversity throughout the study period, and additional antibiotic exposure significantly decreased gut microbial diversity [16]. However, although most MDR bacterial colonization is known in LT candidates, there are currently no clinical data on the adaption of perioperative antibiotics to the screening results in LT. Adjusting perioperative antibiotic therapy in LT patients for colonization with MDR bacteria could improve perioperative outcomes in terms of severe abdominal, biliary tract, and pulmonary infections. Given the high rate of infectious complications in LT patients and the associated morbidity and mortality, a better understanding of microbial niches as potential sources of these infections is needed. MDR germs remain a relevant problem, and only homeostasis of the microbial environment and immune function could potentially prevent MDR colonization and associated severe morbidity and mortality. Biliary complications remain to be the Achilles heel of LT, owing to both surgical and non-surgical factors. Surgical factors include anatomical factors like small bile duct diameter in the graft [83], multiple bile duct orifices [84], intimal damage to the duct, scar formation as a healing process, and compromised blood supply to the bile duct [7,85]. Non-surgical risk factors include increased cold ischemic time [86], arterial hypoperfusion caused by portal hypertension [87], and immunological factors [88]. The overall incidence of biliary complication in LT recipients ranges from 7.4% to 39%; biliary leakage occurs in 5.1–23.4%, and biliary strictures occur in 6.5–21.5% [5,6,7,8]. Biliary complications affect the quality of life in the recipient, leading to significant morbidity and mortality. To minimize the risk of biliary complication in LT, the maintenance of fundamental principles of surgical anastomoses, such as minimal tension, regular intervals between suture bites, sufficient blood supply, and avoidance of injury to bile duct epithelium is of utmost importance [89]. The two most commonly used techniques are the choledocho-choledochostomy or duct-to-duct anastomosis and the choledocho-jejunostomy or Roux-en-Y hepaticojejunostomy. Roux-en-Y hepaticojejunostomy has the ability to maintain good blood supply and obtain tension-free anastomosis, which is why it has been promoted in the past [90]. However, duct-to-duct anastomosis is considered more favorable generally because it most closely resembles normal anatomy, thereby eliminating bowel manipulation and preserving the physiological bilio-enteric continuity [91]. Additionally, shorter operation time and easier endoscopic access to the biliary tract in case of biliary complications also make duct-to-duct anastomosis a preferred technique [92]. The rate of biliary complications is either similar between duct-to-duct and Roux-en-Y hepaticojejunostomy or slightly increased for the latter [93]. Colonization of the biliary tract and severe bile leakage and bleeding are more common in Roux-en-Y hepaticojejunostomy [93]. In addition, the infection rate is much higher in Roux-en-Y hepaticojejunostomy (65.9% vs. 22.8%) due to the absence of the sphincter of Oddi, which facilitates ascending bacterial migration and recurrent cholangitis [93,94,95]. Biliary leakage and strictures are the most common complications after LT. Leakage mostly occurs from the site of anastomosis and seldom from the T-tube exit side [96]. Anastomotic leaks usually occur within 1 month after LT [97,98]. In other gastrointestinal surgeries, the impact of local microbiota causing anastomotic leakage has been unraveled recently [99,100,101]. Despite ischemia and tension at the anastomotic site, bacteria-induced local protease activity can impair anastomotic healing by breaking down newly synthesized collagen [99,101]. Alverdy et al. could prove this impact of certain bacterial strains on enhancing the activity of tissue proteases, e.g., for enterococci spp. [100]. In the local microenvironment, commensal bacteria physiologically take part in the modulation of host genes and maintaining the mucosal barrier integrity [99,100]. Surgical trauma, antibiotic use, and states of disease can alter this commensal microbial niche with an increase of at least potential pathogen germs [99,100]. Therefore, the local microbiota might play an important role in the molecular process of anastomotic healing, even in the biliary tract. Strictures at the site of the biliary anastomosis are relatively frequent and occur in 5% to 10% of patients after LT [102]. The majority of anastomotic strictures happen within the first year after LT [95]. A slight and temporary narrowing at the site of biliary anastomosis after LT is considered normal due to postoperative edema; however, it could further develop into significant anastomotic stricture with relevant cholestasis and cholangitis [103]. The causes of an anastomotic stricture include surgical technique, inadequate mucosa-to-mucosa anastomosis, local ischemia, and fibrotic healing [97]. Generalized ischemia and bile leakage also increase the risk of anastomotic structuring. Most anastomotic strictures are treatable with endoscopic procedures with high success rates. Non-anastomotic strictures (NAS) occurring after hepatic artery thrombosis has been well-known since the beginning of liver transplantation [104]. NAS occurring with a preserved arterial blood supply has been described as ischemic-type biliary lesions (ITBL) in the 1990s and represents a major therapeutic problem [105]. ITBL is associated with the destruction of the non-anastomotic parts of the biliary tract, including segmental stenosis and expansion, resulting in biliary sludge, biliary casts, and filling defects [9]. The development of ITBL is associated with significant morbidity due to the need for multiple biliary interventions, and approximately 65% of patients with ITBL require re-LT [18]. In general, rates of NAS are up to 19%, and rates of ITBL range from 3% to 16% following LT [17]. An ischemic/immune-mediated injury is the most straightforward pathogenesis of NAS; in addition, surgical factors and cytotoxicity of bile salts may also play a role in the development of NAS [88,106]. Damage of the bile duct epithelium or injury to the microvasculature of the bile duct arteriolar plexus due to fibrotic healing could lead to these strictures [107]. Identified risk factors for the development of NAS include macro-angiopathic (hepatic artery thrombosis or stenosis), microangiopathic (prolonged ischemia times, preservation solution, cardiac death donor, donor dopamine use), and immunogenetic (ABO incompatibility, rejection, auto-immune disease, CMV infection, chemokine polymorphisms) injury [108]. Another potential factor in the pathogenesis of bile duct injury after LT is the local microbiota, as a biliary infection is a frequent cause of biliary complications in patients after LT [30,31]. Recently, a study suggested enteric bacteria to be significantly associated with the clinical signs of cholangitis after LT, a condition that lowers survival rates in patients with biliary tract injury [32]. Microbiome research of the gut, but especially the biliary microbiome, might contribute to a deeper understanding of the pathomechanisms of biliary complications, especially biliary leak and anastomotic and non-anastomotic strictures. By influencing microbial niches, new therapeutic and even prophylactic options may become available in the future. The physiologic colonization of the gut and the biliary tract changes with the occurrence of liver diseases. In these instances, pathogenic potentially harmful bacteria can be found, which are then summarized under the term “pathobiome” [26], whereas some microbes might exhibit beneficial effects against the development of liver diseases [22]. Table 1 provides an overview of these relevant microbiota. A growing number of studies have begun to elucidate the role of the microbiota, its metabolites, and its influence on host immune responses after LT in general and specifically in the development of biliary complications. Various factors from microbiota potentially contributing to the development of biliary complications are summarized in Figure 2. Gut bacteria have a significant impact on human metabolic activity, barrier function, and immunity development. Dysbiosis of gut bacteria is associated with various conditions, including obesity, diabetes, nonalcoholic fatty liver diseases, and autoimmune disorders [121,122], and even plays a significant role in I/R injury [123]. For LT patients, portal vein blocking, I/R injury, antibiotics, or immunosuppression use can seriously impair the recipient’s immune function, and destroy the intestinal barrier, thereby increasing the risk of dysbiosis of gut microbiota. These changes in gut bacteria may lead to direct injury to the host liver through the “gut-liver axis” [124]. The relationship between gut microbiota dysbiosis and postoperative complications, including acute rejection, early-stage infection, and graft loss due to biliary complications, has been discussed in the previous sections. Based on the sparse available data, one can hypothesize that alterations of gut microbiota may be responsible for the graft’s I/R injury to some extent. Compared to patients without complications after LT, patients diagnosed with NAS showed a decreased abundance of Bacteroidetes and an increase of Proteobacteria, which usually amounts to a very small part of human gut microbiota [113,125]. Bacteroides, together with Firmicutes, are predominant bacteria within the human intestine; a decrease of either always indicates an impairment of intestinal barrier function and an increased risk of bacterial translocation [126]. Similar changes have also been reported in cirrhosis patients [47]. At the family level, higher proportions of Enterococcaceae, Streptococcaceae, Enterobacteriaceae, and Pseudomonadaceae were observed among patients with NAS in comparison with patients without biliary complications of LT [113]. These families of bacteria are commonly regarded as pathogenic bacteria, and their overgrowth will lead to a release of LPS and peptidoglycan. When recognized by the human immune system via Toll-like receptors or nucleotide-binding oligomerization domain-like receptors, LPS, and peptidoglycan would trigger the pro-inflammatory NF-κB cascade and directly stimulate hepatic stellate cells, which finally lead to liver damage and liver disease progression [124]. As bile ducts are susceptible to inflammatory damage, serious gut microbiota dysbiosis may exacerbate cholangiocyte apoptosis and eventually lead to bile duct strictures or ITBL [108]. In addition, cholangiocytes are also susceptible to ischemic injury and oxygen-free radicals, and microcirculatory disturbances can lead to insufficient biliary tract preservation as it is caused by I/R injury, which involves inflammation, oxidative stress, apoptosis, and necrosis [127]. The production of reactive oxygen species influenced by microbiota could further induce cholangiocyte-related damage [128,129]. The biliary tract is not sterile despite the anti-microbial activity of bile acids, even in healthy individuals [26,27]. In certain diseases or infectious conditions, reduced bile acid secretion can increase bacterial biliary colonization [130]. Especially in diseases of the biliary tract, e.g., PSC, studies revealed an altered microbial niche [11]. This dysbiosis is associated with an increased pro-inflammatory and even carcinogenic milieu [11,12,131]. Especially, Proteobacteria and Enterococci spp. are enriched in PSC and other end-stage liver diseases [11,131]. Furthermore, endoscopic interventions, biliary stents, and recurrent antibiotic therapy could alter the microbiota within the biliary tract, including ascending bacteria from the upper intestines [132]. Only sparse data are available on the biliary microbiome in different diseases and especially in LT patients [10,11,12,13]. Despite the study of D’Amico et al., who could not detect any biliary microbiome in a small series of six patients [133], data are mostly available for bile samples of patients suffering from biliary complications. Liu et al. analyzed bile samples from liver transplant recipients with routine use of biliary drains [10]. The predominant bacterial phyla were Firmicutes, Proteobacteria, and Actinobacteria, with differences in relative abundance between patients with and without biliary complications such as cholangitis or stenosis [10]. Recently, Klein et al. reported on a large series of patients using 16S rRNA-based microbiome analysis on bile samples [13]. They compared the biliary microbiome of patients with non-anastomotic vs. anastomotic strictures as controls. They detected a diverse biliary microbiome consisting mainly of the phyla Firmicutes, Proteobacteria, Fusobacteria, Bacteroidetes, and Actinobacteria, with differences in relative abundance between the groups [13]. On the Genus level, especially Enterococci spp. and Streptococci spp. have been found in all samples [13]. The microbial community structures were different between groups with biliary stents and recent antibiotic therapies [13]. Whereas biliary stenting did not result in different abundance in the anastomotic stricture group, the biliary microbiome differed in the non-anastomotic stricture group: they detected differences in the relative abundance of 27 genera in the microbial community of samples with and without biliary stents [13]. Despite an increase of biofilm-forming bacteria over time with the use of biliary stents, e.g., Streptococci spp. and Fusobacteria spp., the analysis revealed no relevant difference in diversity and similarity in the non-anastomotic stricture group due to antibiotic therapy [13]. Overall, the sparse available data demonstrates an increase of Proteobacteria in bile samples of patients with biliary complications, indicating an increase in potentially pathogen germs like E. coli, Klebsiella, and other Gram-negative germs. This was consistent with the gut microbiome in NAS discussed before, suggesting that Proteobacteria may play a significant role in the occurrence and development of biliary tract injury after LT. If the increase of Proteobacteria and these differences in relative abundance are causes or consequences of the biliary complications still remains unclear. However, unlike the gut microbiome, in patients with NAS, the proportion of Enterococcus spp. in bile was lower than in patients without complications [10]. This bacterium can regulate the balance of intestinal flora and process certain immune regulatory and anti-allergic effects [134]. Reduction in the biliary abundance of Enterococcus spp. in NAS patients suggests that Enterococcus spp. may play an important role in maintaining the stability and balance of bile microecology. The impact of biliary microbiota on biliary complications like anastomotic strictures or ITBL cannot be proven in prospective sampling studies, but at least due to cholestasis-related cholangitis and especially repeated endoscopic interventions like ERC and application of biliary drainages, there is an increase in potentially pathogen microbiota like Proteobacteria and Enterococci spp. [10,13,32]. Due to repeated interventions in patients suffering from biliary complications and the need for antibiotic therapy even before LT, the colonization and associated complications due to multi-drug resistant microbiota are increased [13,16,32]. In the available data, there were some significant differences in the metabolic pathways of bile samples between patients with and without biliary complications [10,13]; however, there are limited data on metabolic pathways in bile samples from patients after LT, and therefore further data are required. There are complex interactions between the gut microbiome and liver function as well as immune regulation with a significant impact on outcome in liver transplantation. Notably, there are only sparse data on the microbial niche of the biliary tract in LT. A more detailed description of the biliary microbiome is required both in the physiological state and in various biliary and immunological complications of liver transplantation. Table 1 provides an overview of the current knowledge of various microbiota detected in gut and biliary samples from patients with (end-stage) liver diseases or after LT. Biliary complications, as well as graft function in LT, are influenced by many different factors. The microbiome within the human gut and biliary tract plays an important role in the pathogenesis and development of complications after LT. Hence, microbiota presents itself as a very useful predictive tool for post-LT outcomes in data from animal experiments. For example, a murine model could differentiate the cause of liver dysfunction by using gut microbial profiling. As such, fecal microbiota sampling can serve as a potentially better biomarker for early detection of the various post-LT complications due to its non-invasive nature [135]. Data regarding the role of the microbiome in hepatobiliary disease and LT mostly aim at the human gut and fecal microbiome profiling, showing specific pathogenic alterations in the feces [26,113,136]. In terms of biliary microbiota, the data is scarce, and the only study related to biliary complications in LT patients showed there were significant differences in species composition within the bile samples between patients with and without biliary complications after LT [10]. It is highly advantageous if the rise of certain species or pathways within biliary and fecal samples could be associated with certain complications. This prompts the consideration of therapeutic alteration of microbiota composition. Since the liver is an immunotolerant organ, the discontinuation of the immunosuppression may be capable [137]. Therapeutic alteration of the microbiome could be considered, thereby preventing or improving post-LT complications. Such therapeutic alteration can be achieved through the administration of probiotics or fecal microbiota transplant. Existing literature on probiotic usage in patients after LT suggests efficacy in reducing post-LT infection [138], and fecal microbiota transplants have been demonstrated to be beneficial toward alcohol-related liver disease and hepatic encephalopathy [139,140]. However, there is no data available at present regarding biliary complications after LT. Microbiome research can be a useful aid in LT patient care; however, the current understanding of the roles of microbiota in biliary complications and graft functions in LT is inadequate for clinical application due to small sample sizes and the limited data from human studies. Future studies should not only focus on the composition and diversity of microbiota. Specific microbial characteristics such as metabolomics and transcriptomics should also be taken into consideration. The same microbiota may exhibit different behaviors in different contexts. Especially data on the biliary microbiome is still sparse, and their impact on infectious and especially biliary complications is mainly speculative. The effects of immunosuppressive therapy following LT on the gut and even biliary microbiome have not been sufficiently analyzed yet; in particular, this aspect does not currently play a role in the daily clinical care of our LT patients. Further data from prospective clinical trials are necessary for a better understanding of these complex interrelationships. Since most LT complications could be acute or chronic, an adequate follow-up period with a collection of bio-samples is also required.

PMC10003079

Niklas S. Jensen,Markus Wehland,Petra M. Wise,Daniela Grimm

Latest Knowledge on the Role of Vitamin D in Hypertension

28-02-2023

vitamin D,vitamin D deficiency,hypertension,antihypertensive treatment,supplement,clinical trials,molecular mechanisms

Hypertension is the third leading cause of the global disease burden, and while populations live longer, adopt more sedentary lifestyles, and become less economically concerned, the prevalence of hypertension is expected to increase. Pathologically elevated blood pressure (BP) is the strongest risk factor for cardiovascular disease (CVD) and related disability, thus making it imperative to treat this disease. Effective standard pharmacological treatments, i.e., diuretics, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blocker (ARBs), beta-adrenergic receptor blockers (BARBs), and calcium channel blockers (CCBs), are available. Vitamin D (vitD) is known best for its role in bone and mineral homeostasis. Studies with vitamin D receptor (VDR) knockout mice show an increased renin–angiotensin–aldosterone system (RAAS) activity and increased hypertension, suggesting a key role for vitD as a potential antihypertensive agent. Similar studies in humans displayed ambiguous and mixed results. No direct antihypertensive effect was shown, nor a significant impact on the human RAAS. Interestingly, human studies supplementing vitD with other antihypertensive agents reported more promising results. VitD is considered a safe supplement, proposing its great potential as antihypertensive supplement. The aim of this review is to examine the current knowledge about vitD and its role in the treatment of hypertension.

Latest Knowledge on the Role of Vitamin D in Hypertension Hypertension is the third leading cause of the global disease burden, and while populations live longer, adopt more sedentary lifestyles, and become less economically concerned, the prevalence of hypertension is expected to increase. Pathologically elevated blood pressure (BP) is the strongest risk factor for cardiovascular disease (CVD) and related disability, thus making it imperative to treat this disease. Effective standard pharmacological treatments, i.e., diuretics, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blocker (ARBs), beta-adrenergic receptor blockers (BARBs), and calcium channel blockers (CCBs), are available. Vitamin D (vitD) is known best for its role in bone and mineral homeostasis. Studies with vitamin D receptor (VDR) knockout mice show an increased renin–angiotensin–aldosterone system (RAAS) activity and increased hypertension, suggesting a key role for vitD as a potential antihypertensive agent. Similar studies in humans displayed ambiguous and mixed results. No direct antihypertensive effect was shown, nor a significant impact on the human RAAS. Interestingly, human studies supplementing vitD with other antihypertensive agents reported more promising results. VitD is considered a safe supplement, proposing its great potential as antihypertensive supplement. The aim of this review is to examine the current knowledge about vitD and its role in the treatment of hypertension. High blood pressure (hypertension) is a serious risk factor for cardiovascular diseases, such as coronary artery disease, myocardial infarction, or stroke, if untreated [1]. Study results revealed that vitamin D deficiency ameliorates the development of hypertension (HT) [1,2]. Vitamin D deficiency (25-OH-D < 30 ng/mL) is an independent risk factor for high blood pressure and is involved in the promotion of cardiovascular mortality [3]. In autumn and winter, until the beginning of April, the sunlight intensity in Europe is not sufficient for our body to synthesize sufficient vitamin D, which results in vitamin D deficiency (Figure 1). It is well known that vitamin D is involved in calcium homeostasis and bone metabolism, and that supplementation in the elderly can reducing the fracture risk [4]. Epidemiological and clinical studies demonstrated an association between inadequate exposure to sunlight, vitamin D deficiency, and hypertension or increased plasma renin activity [1,2,3]. On average, blood pressure values are lower in the summer than in winter [5,6,7]. This concise review summarizes the latest knowledge about vitamin D deficiency and arterial hypertension. The available literature published from 2017–2022 is evaluated and reviewed in the following chapters. The literature searched for this review was found through online databases, clinical trials, and very few online webpages. The online databases include PubMed (https://pubmed.ncbi.nlm.nih.gov/, accessed on 11 December 2022), Scopus (https://www.scopus.com/search/form.uri?display=basic#basic, accessed on 11 December 2022), and Clinical Trials (https://clinicaltrials.gov/, accessed on 11 December 2022). Original papers were found from a systematic literature search using several different databases, and from written reviews. The searches were (if possible) restricted to be from 2017–2022, ensuring the most recent trials would be found; however, earlier trials have also been included. The search terms were ((“vitamin D”) OR (cholecalciferol)) AND (hypertension). Clinical trials in this review are included to assess the efficacy of vitD supplementation on hypertension. The search process is outlined in the PRISMA flow diagram (Figure 2). Arterial hypertension (AH) is a common condition involving the arterial blood pressure (BP) being too high. This means that the force of blood pushing against the walls of the arteries is constantly elevated. This change affects the heart, which needs to work hard to pump sufficient amounts of blood in the body [8]. HT is traditionally defined as a persistent BP measured as 140/90 mmHg [9]. Maintenance of a normal BP is dependent on the balance between the cardiac output and the vascular resistance throughout the organism. Furthermore, the cardiac output is dependent on the stroke volume and heart rate (HR) [10]. Even though it is fairly impossible to find a clear underlying cause for most HT cases, there are still various risk factors that can lead to HT. Age, family history, obesity, lack of exercise, smoking, excessive salt diet, high alcohol consumption, and even pregnancy, are a few among the known risk factors responsible for the development of HT [8]. Besides lifestyle risk factors, prescribed drugs, such as oral contraceptives, non-steroidal anti-inflammatory drugs, ciclosporin, erythropoietin (EPO), and glucocorticoids (steroid hormones), may also raise the BP and induce HT [11]. Physiological maintenance of a normal BP is dependent on the balance between cardiac output and the vascular resistance of the system. There is an interchange between electrical, biochemical, and mechanical forces to control the BP. The electrical component is the sympathetic nervous system; the biochemical component is the renin–angiotensin–aldosterone system (RAAS), neurotransmitters (e.g., norepinephrine (noradrenaline)), or cytokines; and the mechanical component is the HR and the vasodilation/vasoconstriction of the arterioles. Thus, HT occurs when vascular regulation results from malfunctioning in the arterial BP control mechanisms of the body [10]. BP levels measured in the clinic may differ significantly when measured in an out-of-clinic setting by ambulatory BP monitoring (ABPM) or home BP monitoring [12]. White coat HT describes elevated clinical BP present in untreated individuals, but their out-of-office values are normal [13]. Masked HT is the inverse occurrence, characterized by an elevated out-of-clinic BP despite a normal clinic BP. The term masked HT can also be used as a term for people being treated for HT [12]. Resistant HT appoints to part of the population whose BP cannot be controlled. This means that despite treatment with the combination of three or more antihypertensive drugs at an adequate or full dosage, their BP values still remain above the therapeutic goals [14]. Table 1 gives an overview on the office BP classification and the definitions of the HT grade. HT is the third leading cause of the global burden of disease with 64 million disability-adjusted life years [16]. As populations live longer, adopt more inactive lifestyles, and become less economically burdened, it is estimated that the number of people with HT will increase by 15–20% by the year of 2025, reaching 1.56 billion hypertensive cases [17]. The overall prevalence of HT in adults globally is around 30–45% [18], which is an estimated 1.28 billion adults, with two-thirds living in low- and middle-income countries [19]. Pathologically increased BP is globally the strongest risk factor for cardiovascular disease (CVD) and related disability, despite extensive knowledge on the strategies to prevent and treat HT [20]. This becomes clearer with the fact that over the past 30 years, the disability-adjusted life caused by HT have increased by 40% since 1990 [21]. The largest number of systolic blood pressure (SBP)-related deaths are caused by ischemic heart disease (4.9 million), hemorrhagic stroke (2.0 million), and ischemic stroke (1.5 million) [21]. There are two well-established strategies to lower BP: lifestyle interventions and antihypertensive drug treatment [22]. The modifiable factors of HT include diets with excess salt consumption, high intake of saturated and trans fats, low intake of fruits and vegetables, physical inactivity, smoking, alcohol consumption, and being overweight or obese [19]. The Dietary Approaches to Stop Hypertension (DASH) trial proposes a diet that emphasizes fruit, vegetables, and low-fat diet products and is recommended in national guidelines [23]. It proved to lower BP substantially both in people without HT and with HT [23]. Exercise reduces the rate of progression from pre-hypertension to HT. Fitness in general reduces the risk of developing HT regardless of age, body mass index (BMI), and other traditional risk factors [24]. It is recommended to prescribe antihypertensive drugs in all patients with an SBP 140 mmHg or diastolic blood pressure (DBP) 90 mmHg, when the lifestyle adjustments are unsuccessful [25]. Referencing recent guidelines, five major drugs classes are recommended for the treatment of hypertension: angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), beta-adrenergic receptor blockers (BARBs), calcium channel blockers (CCBs), and diuretics [22]. Their mechanisms of actions are described in Table 2. In human skin, vitD is synthesized by photoconversion of 7-dehydrocholesterol (7-DHC) to pre-vitamin D3 (Pre-D3). Pre-D3 then isomerizes to vitamin D3 (VD3) [36]. First, the B ring is broken by UV-light (280–320 nm) radiation from the sun, forming the Pre-D3. The isomerization to VD3 happens in a noncatalytic, thermo-sensitive process [37]. Once VD3 is formed, it is translocated into the circulation by the vitamin D-binding protein (VDBP). Thus, the VDBP ensures the efficient conversion of the quantitatively smaller amounts of Pre-D3 to VD3 by shifting the Pre-D3 ⇋ VD3 reaction to the right [37]. VitD is available in two distinct forms, cholecalciferol (D3) from animal sources and ergocalciferol (D2) from plant sources [38]. Studies show that cholecalciferol is much more effective than ergocalciferol in humans, because it appears that cholecalciferol raises and maintains 25-hydroxycholecalciferol levels to a substantially greater degree than ergocalciferol [39]. VitD is transported either within chylomicrons or bound to VDBP to the liver or is stored into body fat [40]. The hepatic entry of vitD is modulated by its plasma carriers, and when vitD enters the liver, it is hydroxylated into 25-hydroxycholecalciferol by the enzyme 25-hydroxylase [40,41]; 25-hydroxycholecalciferol is considered the most reliable marker of an individual’s vitD status [41]. After the hydroxylation, 25-hydroxycholecalciferol is transported from the liver to target tissues, primarily the kidney, where it is converted into 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) by the enzyme 25-hydroxyvitamin D3-1α-hydroxylase, a mitochondrial P450 enzyme [40,42]. Cholecalciferol must be metabolized prior to initiation of its characteristic physiological response to the biologically active form 1,25(OH)2D3 [43]. 1,25(OH)2D3 plays an essential role in calcium and phosphate homeostasis, bone growth, and cellular differentiation [42]. The VDR was first discovered as binding protein in the intestine [44]. Later, it was revealed to be active in the parathyroid gland, bone, pancreas, and kidney [45]. The hormone 1,25(OH)2D3 evokes both genomic and nongenomic responses [46]. In the genomic response, the VDR acts jointly with other nuclear hormone receptors, in particular the retinoid X receptor (RXR) [47]. During the hormone-induced receptor activation, the VDR translocates into the cell nucleus in a ligand-dependent fashion [48] and generates an active signal transduction complex consisting of a heterodimer of the 1,25(OH)2D3-liganded VDR and the RXR. This VDR–RXR heterodimer recognizes the vitD response elements in the DNA sequence of the vitD-regulated genes [46]. Transactivation by the liganded VDR/RXR is furthermore reliant upon the binding of one or more co-activator complexes, which permit the bridging to the RNA polymerase II machinery [49]. The mechanistic range of 1,25(OH)2D involves gene expression regulation in specific tissues, which is mediated by the nuclear VDR. The VDR is a DNA-binding protein that interacts directly with regulatory sequences near the target genes. It functions by recruiting chromatin-active complexes that participate in modification of both genetic and epigenetic transcriptional outputs [44,45,50]. An overview of the genomic and non-genomic pathways is given in Figure 3. The non-genomic response to 1,25(OH)2D3 starts with the binding of calcitriol to its membrane VDR, and the 1,25D-membrane-associated rapid response steroid-binding protein (1,25-D-MARRS). This interaction between 1,25(OH)2D3 and 1,25-D-MARRS affects numerous cell signaling pathways via direct protein–protein interactions [51]. Examples of signaling pathways are the MAP kinases ERK1/ERK2/ERK5 and JNK MAP kinase modules [49,53]. Other studies also show that the rapid action of 1,25(OH)2D3 in intestinal epithelial cells is mediated by the activation of protein kinase C (PKC) [54]. Several other signaling molecules are also activated by the non-genomic response, such as phospholipase A2, phosphatidylinositol-3-kinase, and p21ras, as well as the rapid generation of second messengers, such as calcium, cyclic AMP, fatty acids, and 3-phosphoinositides [52]. Further downstream targets include transcription factors SP1, SP3, and RXR that bind to response elements on the promoters of vitD-responsive genes [52]. 1,25(OH)2D3 circulates to various target tissues to exert its actions, which are largely mediated by the nuclear VDR/RXR genomic actions [55]. The 1,25(OH)2D3 and VDR interaction regulates the expression of at least eleven genes encoding bone and mineral homeostasis effectors [56]. 1,25(OH)2D3 actively regulates at the transcriptional level the expression of calbindin, the calcium ATPase PMCA1b, and the renal TRPV5 and intestinal TRPV5 and TRPV6 calcium channels. These gene products all promote calcium absorption in the intestine and reabsorption in the kidney and thus enhance skeleton mineralization [56,57]. The homeostasis of serum inorganic phosphorus (Pi) is primarily regulated by parathyroid hormone (PTH) and 1,25(OH)2D3 [58]; however, 1,25(OH)2D3 inhibits PTH release [59]. The intestinal phosphate absorption requires the Na+/phosphate cotransporter NaPi-2b/Slc34a2, and the expression of this channel is stimulated by 1,25(OH)2D3 [60]. Fibroblast growth factor (FGF23) also plays a role in phosphate homeostasis, a phosphaturic peptide which is expressed in the bone via stimulation of 1,25(OH)2D3 and inhibits renal Npt2a and Npt2c similar to PTH, eliciting phosphaturia [61]. In terms of bone homeostasis, 1,25(OH)2D3 possesses both bone-resorbing and bone-remodeling properties. The bone-resorbing effect of 1,25(OH)2D3 is the ability to support osteoclastogenesis by upregulating the RANKL expression on osteoblasts/stromal cells [62]. In order for osteoclasts to differentiate into bone-resorbing osteoclasts, the RANKL/RANK signal also requires ligand binding of c-fms, an osteoclast precursor surface receptor present on the macrophage colony stimulating factor [55]. The bone-remodeling properties of 1,25(OH)2D3 is the synthesis of the bone matrix proteins osteopontin, collagen, and osteocalcin through transcriptional control in osteoblasts [56,63]. Figure 4 gives an overview of the functions of vitD in calcium homeostasis, bone metabolism, and the immune system. 1,25(OH)2D3 plays several roles outside of mineral and bone homeostasis. Moreover, the hormone is involved in modulating the immune response. Both the VDR and vitD-metabolizing enzymes are present in immune cells, monocytes, macrophages, dendritic cells, and activated B and T cells, which indicates that vitD exerts immunoregulatory effects on the innate and adaptive immune response [65]. Finally, the physiological effects of VDR activation in experimental studies include the suppression of neurohormonal activity and improvements in endothelial and vascular function [66]. In 1986 a study described a continuous relationship between 1,25(OH)2D3 levels and plasma renin activity (PRA) [67]. Another publication [68] reported a pronounced increase in ang II and renin in VDR-null mice. This suggests an interplay between the RAAS and VDR activation, which suggests that 1,25(OH)2D3 is directly involved in AH. As already mentioned earlier, HT has many etiological factors, vitD deficiency being one of them. The vitD level is inversely related to BP and incident HT [69]. Animal and human studies have suggested that the development of HT in individuals with lower levels of 1,25(OH)2D3 is due to the fact that the 1,25(OH)2D3 deficiency may increase activity of the RAAS, both systemically and in the kidney [70]. An increased plasma renin concentration (PRC) in a low 1,25(OH)2D3 setting may elevate sympathetic activity and enhance intra-glomerular pressure, predisposing to AH, a decline in GFR, and subsequent cardiovascular damage [71]. Knocking out of either the VDR or the 1-hydroxylase gene in mice upregulates RAAS activity and induces HT [72,73], while treatment of these animals with 1,25(OH)2D3 suppresses the RAAS activity [73]. Additionally, the VDR is expressed in vascular tissues, including the myocardium, renin-producing juxtaglomerular cells, and vascular smooth muscle, where it directly influences calcium influx, muscle relaxation, and diastolic function [74,75]. Aside from the RAAS, vitamin D can exert its influence on hypertension through several other ways. As stated in 3.7, vitamin D is involved in calcium homeostasis by stimulating the production of calcium transporters, increasing calcium reabsorption in the kidney, and inducing the osteoclastic calcium release in bones [76,77]. Therefore, a vitamin D deficiency can result in a decreased concentration of Ca2+ in the plasma, which will lead to the secretion of parathyroid hormone (PTH) from the chief cells in the parathyroid gland to counteract this. Several epidemiological studies have shown that elevated PTH levels were associated with higher SBP and DBP values and a higher prevalence of HT in general [78,79,80]. These results were validated by the observation that PTH administration could induce elevated BP values in healthy subjects [81,82]. So far, the underlying mechanism has no yet been fully understood, and it is hypothesized that PTH-induced hypercalcemia might impair endothelial function [83]. Furthermore, vitamin D might have a direct effect on vascular stiffness. Both endothelial and vascular smooth muscle cells (VSMCs) express 1α-hydrolase, which is involved in the conversion of 25(OH)D to calcitriol [84]. It has been shown that this enzyme is activated in HUVECs by inflammatory molecules such as TNF-α and lipopolysaccharide [85]. In addition, exogenously added 1,25(OH)2D3 and 25(OH)D3 attracted monocytes and increased their binding to HUVECs [85]. In addition, it was found that vitamin D has a direct effect on vascular tone by reducing calcium influx [86]. Lastly, Richart et al. [87] proposed extrarenal activation of vitamin D as a possible contributor to hypertension and arterial stiffness. Macrophage vitamin D activation is much less tightly controlled than renal activation. In atherosclerotic lesions, they penetrate the arterial wall, and the activated vitamin can directly act on VSMCs. There, it can enhance the response to vasopressors [88], promote calcification [89], and induce cell dedifferentiation and oxidative stress [90]. Several observational studies have suggested a direct correlation of low plasma 25(OH)D concentrations and the risk of developing hypertension and hypertension-related complications [91,92,93,94,95,96,97,98,99,100,101,102,103]. Therefore, a supplementation with vitamin D seems a promising therapeutic option for these patients. Table 3 provides an outline of recent completed clinical trials treating participants with vitD either as a supplement to another antihypertensive agent or as an antihypertensive agent on its own. In addition, three trials studying vitamin D and immune mechanisms of hypertension in type II diabetics (VDIM, NCT03348280), fibroblast growth factor 23 and hypertensive disorders complicating pregnancy (NCT03821922), and vitamin D in pregnancy (GRAVITD. NCT04291313) are currently recruiting but have no results yet. Several other studies without NCT numbers have also been included in the discussion to broaden the amount of scientific evidence to give the best possible assessment of vitD as a potential antihypertensive supplement. Overall, the effects of vitamin D supplementation on hypertension in the studies listed in Table 3 were negligible. They found no tangible evidence for an antihypertensive action of vitamin D alone. The recommended daily uptake of vitamin D lies between 200 and 600 UI/d [110], with 600 UI/d being advocated by most newer guidelines in order to achieve 25(OH)D serum concentrations of about 50 nmol/L [111]. No definitive recommendation exists for the upper limit of vitamin D supplementation; however, both the Institute of Medicine of the National Academies (IOM) as well as the European Food Safety Authority (EFSA) advise against doses exceeding 4000 UI/d to avoid hypercalcemia [112,113]. The dosages of the listed studies lay well within this range, some even at the higher limit, so the lack of effect cannot be attributed to underdosage. These findings are in accordance with a recent post-hoc analysis of the data from the Styrian Vitamin D Hypertension Trial of 2011–2014, where the authors also found no evidence of an antihypertensive effect of vitamin D supplementation [114]. It is possible that the underlying mechanisms of the association of low vitamin D plasma levels and hypertension are far more complicated as to be directly mediated by a vitamin D supplementation. Recent genetic studies showed that certain polymorphisms of the vitamin D receptor gene (VDR) and its downstream pathway genes were associated with the risk for HT. Caccamo et al. demonstrated an association between the Fok I and Bsm I SNPs with gestational hypertension [115]. Fok I was also associated with a higher incidence of heart failure and hypertension in patients with cardiovascular disease [116] and with the risk of developing essential hypertension [117], while Bsm I was closely linked to a higher predisposition to hypertension in pregnant women [118]. Vitamin D deficiency and the AA + AG genotype of the Taq-I SNP were linked to stage 2 hypertension in postmenopausal women [119]. In a study including 3699 pregnant women, polymorphisms in CYP24A1, GC, and LRP2 genes were associated with blood pressure and hypertensive disorders of pregnancy [120]. So far, these studies were merely observational, and further research is warranted to elucidate possible mechanistic implications. Despite the numerous scientific correlations between vitD, RAAS activity, PRC, and HT, the BP-lowering effects of vitD replacement have not been observed in most studies, and only found to be effective in a few studies [69]. A randomized, double-blind, placebo-controlled trial involving 84 vitD-deficient, overweight participants without HT, treated the participants with 50.000 IU/week ergocalciferol for 8 weeks. This treatment showed no effect of vitD supplementation on RAAS activity or BP when compared to placebo [70]. Pilz et al. tested the effect of vitD supplementation on 188 hypertensive and viD-deficient patients by treating them with 2800 IU of VD3 per day for 8 weeks, also without any significant effect on BP and several CVD risk factors [107]. It was proposed that longer treatment periods might be necessary to observe a potential long-term effect of vitD supplementation on BP or RAAS activity [70,107], which was studied by Arora et al. They tested individuals with low vitD status and SBP of 120–159 mmHg. Participants were randomized to either high dose (4000 IU/d) or low-dose (400 IU/d) oral VD3 for 6 months. Still, no association between the change in vitD and the primary 24-h BP end point was found [108]. Even among individuals with larger increases in 25-hydroxyvitamin D, no noticeable trend towards a lower 24-h BP was observed [108]. Beveridge et al. performed a vitD supplementation meta-analysis, in which BP was reported. They included 46 clinical trials (4541 participants) in the trial-level meta-analysis, whereas individual patient data were obtained for 27 trials (3092 participants). At the trial level, no effect of vitD supplementation was seen on BP or SBP and DBP alone, thus leading to the conclusion that vitD supplementation is ineffective as an intervention for lowering BP [121]. Earlier trials have succeeded in showing the antihypertensive effects of vitD [122,123]. Panahi et al. conducted an open-label clinical trial involving 173 patients with essential hypertension, administering 50.000 IU/week vitD, and 1000 IU/day in patients with serum vitD levels < 20 ng/mL and 20–30 ng/mL, respectively, for 8 weeks. Eight weeks of supplementation with conventional antihypertensive drug regimens evoked a 5.5 16.2 mmHg, 1.4 12.6 mmHg, and 3.7 9.2 mmHg decrease in the overall SBP, DBP, and MAP, respectively [124]. A single-center, double-blind, placebo-controlled trial by Chen et al. administered a conventional antihypertensive drug (nifedipine, 30 mg/d) to all participants. In total, 126 participants with graded 1–2 essential hypertension were randomly assigned to receive either vitD (63 participants, 2000 IU/d) or placebo (63 participants) for 6 months. The mean reductions in 24-h, daytime, and night-time mean SBP and DBP during ABPM were all significantly greater in the vitD supplementation group than in the control group after 6 months [125]. Another double-blind randomized clinical trial by Sheikh et al. administered conventional antihypertensive agents alongside vitD or placebo and showed similar antihypertensive effects of vitD [126]. The effect of vitD on the RAAS in mice showed promising results [72,73]. However, some human studies provided different results. A study involving 18 participants with type 2 diabetes (T2DM) administered calcitriol, a VDR agonist, or placebo for three weeks. No effects of calcitriol in terms of reducing RAAS activity or any significant altering of hemodynamic parameters, such as BP or renal plasma flow, was found [109]. Similarly, Bernini et al. showed that neither calcitriol nor VD3 therapy altered renin activity, circulating ang II, or aldosterone in hypertensives with vitD deficiency [127]. In contrast to these findings [109,127], Vaidya et al. showed a renal-vascular tissue RAAS-lowering effect when administering high dose cholecalciferol in non-diabetic, obese individuals with HT and vitD deficiency [128]. Other studies have been successful in showing the effects of cholecalciferol in lowering renin [105,129], and improving endothelial function [130] and plasma aldosterone [66]. Neither Pilz et al. nor Arora et al. [107,108] found any antihypertensive effects of vitD; however, they both agreed that vitD supplementation could be beneficial for other cardiovascular end points. This was tested in a double-blind, placebo-controlled trial involving 44 hypertensive patients by Qasemi et al. It aimed to examine the effect of vitD supplementation on flow mediated dilatation (FMD), oxidized LDL (O-LDL), and intracellular adhesion molecule 1 (ICAM1) [131]. These are inflammatory factors associated with CVD. In the vitD group, O-LDL and ICAM1 significantly decreased, while FMD increased in both groups. However, FMD was significantly higher in the vitD group [131], thus showing beneficial results for other cardiovascular end points than BP. Bislev et al. treated 81 postmenopausal women with both ARBs with adjuvant vitD supplementation and with vitD alone for 2 weeks. ARBs proved to be BP reducing, while vitD supplementation alone did not affect BP, cardiac conductivity, or renin and aldosterone measurements [106]. Even though vitD might not currently be able to replace standard pharmacological treatment, according to recent trials and meta-analyses [70,107,108,121], it has proven to be a promising adjunct therapeutic agent, showing better antihypertensive results when administered alongside an antihypertensive medication [124,125,126,132,133]. Other positive effects of vitD include the correction of typical tissue sensitization to ang II induced by ACE-inhibitors, which was reported by one study [128]. Another study found that VD3 supplementation in patients with stable chronic heart failure may have additional benefits over direct renin inhibitors because renin inhibitors block the PRA, but it is at the expense of an increase in PRC, while VD3 may reduce both [105]. Concerning safety and potential adverse effects (AEs) of vitD supplementation, missing effects of most of their outcome variables show that vitD supplementation is relatively safe regarding many cardiovascular risk factors. VitD was safe concerning parameters of mineral/calcium metabolism [107]. The only statistically significant AE of vitD was an increase in triglycerides. However, considering that several previous RCTs did not measure increased triglycerides with vitD supplementation, Pilz et al. hypothesized that this elevation is not necessarily reflecting a true effect [107]. The DAYLIGHT study did not report any serious AEs during the 6 months of vitD supplementation, and none of the reported AEs were considered likely to be related to vitD supplementation [108]. The challenge remaining for the causal effects of vitD supplementation is acknowledging HT as a multifactorial disease, and that some individuals with other comorbidities, such as smoking, obesity, sedentary lifestyles, and metabolic syndromes, may have a lower threshold for vitD deficiency-induced HT compared to those without these comorbidities [134]. Further studies with larger study populations and a more granular stratification should be performed to further evaluate the role of vitD in HT [69]. HT is a multifactorial global disease that continues to grow in terms of the disease burden and prevalence. Both animal and human studies strongly support the hypothesis that vitD levels are inversely proportional to BP and incident HT, suggesting a potential role for vitD as an antihypertensive agent. However, studies examining this suggestion have produced mixed results. Most of the studies examining a direct effect of vitD on HT alone fail to show any significant BP decreasing effects, while supplementing vitD with another standard antihypertensive agent to potentiate the BP reduction showed promising results. Challenges remain in terms of proving a direct antihypertensive effect of vitD on its own, and further studies with higher doses, larger populations, and longer treatment periods are required to further evaluate the role of vitD in arterial hypertension.

PMC10003080

Pavel Burko,Giuseppa D’Amico,Ilia Miltykh,Federica Scalia,Everly Conway de Macario,Alberto J. L. Macario,Giuseppe Giglia,Francesco Cappello,Celeste Caruso Bavisotto

Molecular Pathways Implicated in Radioresistance of Glioblastoma Multiforme: What Is the Role of Extracellular Vesicles?

02-03-2023

glioblastoma multiforme,radioresistance,extracellular vesicles,intercellular communication,stem cells,tumor heterogeneity,tumor microenvironment,hypoxia,metabolic reprogramming,chaperone system,non-coding RNA,DNA repair,theranostics,personalized medicine

Glioblastoma multiforme (GBM) is a primary brain tumor that is very aggressive, resistant to treatment, and characterized by a high degree of anaplasia and proliferation. Routine treatment includes ablative surgery, chemotherapy, and radiotherapy. However, GMB rapidly relapses and develops radioresistance. Here, we briefly review the mechanisms underpinning radioresistance and discuss research to stop it and install anti-tumor defenses. Factors that participate in radioresistance are varied and include stem cells, tumor heterogeneity, tumor microenvironment, hypoxia, metabolic reprogramming, the chaperone system, non-coding RNAs, DNA repair, and extracellular vesicles (EVs). We direct our attention toward EVs because they are emerging as promising candidates as diagnostic and prognostication tools and as the basis for developing nanodevices for delivering anti-cancer agents directly into the tumor mass. EVs are relatively easy to obtain and manipulate to endow them with the desired anti-cancer properties and to administer them using minimally invasive procedures. Thus, isolating EVs from a GBM patient, supplying them with the necessary anti-cancer agent and the capability of recognizing a specified tissue-cell target, and reinjecting them into the original donor appears, at this time, as a reachable objective of personalized medicine.

Molecular Pathways Implicated in Radioresistance of Glioblastoma Multiforme: What Is the Role of Extracellular Vesicles? Glioblastoma multiforme (GBM) is a primary brain tumor that is very aggressive, resistant to treatment, and characterized by a high degree of anaplasia and proliferation. Routine treatment includes ablative surgery, chemotherapy, and radiotherapy. However, GMB rapidly relapses and develops radioresistance. Here, we briefly review the mechanisms underpinning radioresistance and discuss research to stop it and install anti-tumor defenses. Factors that participate in radioresistance are varied and include stem cells, tumor heterogeneity, tumor microenvironment, hypoxia, metabolic reprogramming, the chaperone system, non-coding RNAs, DNA repair, and extracellular vesicles (EVs). We direct our attention toward EVs because they are emerging as promising candidates as diagnostic and prognostication tools and as the basis for developing nanodevices for delivering anti-cancer agents directly into the tumor mass. EVs are relatively easy to obtain and manipulate to endow them with the desired anti-cancer properties and to administer them using minimally invasive procedures. Thus, isolating EVs from a GBM patient, supplying them with the necessary anti-cancer agent and the capability of recognizing a specified tissue-cell target, and reinjecting them into the original donor appears, at this time, as a reachable objective of personalized medicine. Glioblastoma multiforme (GBM) is one of the most common primary malignant brain tumors and is characterized by cells with astrocyte differentiation. According to the World Health Organization (WHO), it has an incidence between 0.59 and 3.69 per 100,000 people worldwide and accounts for over 60% of all adult brain tumors [1]. Despite being rare, because of its poor prognosis, GBM contributes to 2.5% of all cancer mortality, and the median overall survival is approximately 14–17 months [2]. As in most cancers, age is a factor contributing to GBM incidence [3,4,5], and, on average, it is diagnosed at the age of 65 years [5], with a peak age of 75–79 years [6]. The older age of diagnosis usually means a worse prognosis. Elderly GMB patients have significantly shorter survival times than younger adults [7,8]. Therapy for GBM patients includes surgical resection of the tumor and fractionated radiation therapy concurrent with Temozolomide chemotherapy. However, other approaches to GBM treatment have been developed, as discussed below. The drugs often used to treat GBM are Temozolomide, intravenous Carmustine, Carmustine wafer implants, Bevacizumab, Vorinostat, Olaparib, Lomustine, and Valproic acid. The principal features of drugs currently used in chemotherapy for GBM are reported in Table 1. Radiotherapy is based on the effects of ionizing radiation on tumor cells. It causes direct and indirect damage to the DNA due to the water radiolysis that results in peroxide ions and radicals. The conventional regimen (dose per fraction 1.8–2.0 Gray over 30 days) remains the therapy of choice in glioblastoma. The hypofractionation regimen significantly delays tumor growth and rarely causes side effects [38,39]. Hypofractionation radiotherapy with Temozolomide can achieve 9–20 months of survival in elderly patients (compared to 6–8 months with standard radiotherapy). However, more research is required to adjust the fractionation regimen and increase the survival rate and quality of life of patients. Brachytherapy uses radioactive I-125 and Ir-192 isotopes to deliver ionizing radiation directly into the tumor [40,41,42,43,44]. Ir-192 is used in high-dose brachytherapy; it is removed after a certain period [42,43]. I-125 is used primarily for low-dose brachytherapy, and its capsules often remain in the body as their radiation intensity does not cause significant side effects [41,43]. Standard treatments combined with high-dose brachytherapy between surgery and external radiotherapy have been evaluated [40]. The study showed an increase in overall survival and survival without tumor progression. Furthermore, brachytherapy for inoperable patients can significantly increase their overall survival compared to life-sustaining treatment [42,43]. The main advantage of brachytherapy is its localized action and reduced distance between the radiation source and the tumor, which can lead to a reduced rate of tumor recurrence. However, inadequately high doses cause a high rate of radionecrosis in some patients. Radiosurgery has the most remarkable efficacy during tumor progression or tumor recurrence [45]. The average survival rate in patients with glioblastoma recurrence after radiosurgery is 9 months. There is an improved survival rate in recurrent glioblastoma patients, as well as a reduction in the side effects of radiosurgery and Bevacizumab, which limit tumor growth by inhibiting angiogenesis [46]. The response to radiotherapy is not consistent for all patients. The high genetic and molecular variability of GBM makes it difficult to predict the patient’s response to therapy. Radioresistance in some GBMs leads to poorer outcomes following radiotherapy. Aggressive growth, early and almost inevitable recurrence, and a poor prognosis require novel studies on radioresistance to improve the survival rate and quality of life [47]. Despite extensive research on GBM resistance, its mechanisms are still poorly understood. Replication stress (RS) is a critical mechanism of DNA damage in GBM stem cells [48]. RS is an inefficient DNA replication mode in which replication forks move slowly or terminate. RS activates specific molecular processes to stabilize replication forks and prevent DNA damage. Radioresistance is associated with artificially induced RS in GBM cells. The rate of RS in glioblastoma stem cells (GSCs) is higher, as indicated by higher levels of the following parameters: replication protein A, single-stranded DNA binding protein, and DNA damage markers [48,49]. Tyrosine kinase MET is involved in the signaling cascade of DNA damage repair under ionizing radiation and is required for proper cell migration during embryonic development [50]. It enhances cell survival, angiogenesis, invasion, and metastasis in cancer [51]. The main mechanisms induced by MET are (1) activation of AKT kinase and the subsequent downstream DNA repair effectors; and (2) phosphorylation and cytoplasmic retention of the p21 protein, which has an anti-apoptotic impact. Radioresistance is much more than a handful of surviving cells; it is a crucial mechanism in establishing the therapy resistance of the whole tumor. Remarkably, isolated glioblastoma cell lines do not show as much resistance due to the lack of cell interactions required for the development of radioresistance [52]. Radiotherapy is the most effective treatment method for most primary tumors of the central nervous system. However, its efficacy is limited by the phenomenon of tolerance to radiation therapy, characterized by uninterrupted tumor growth after radiation exposure and being a risk factor for metastatic disease, which requires a change in the standard patient management protocol [53]. Radioresistance is a process in which the tumor cells or tissues adapt to the radiotherapy-induced changes and develop resistance to the radiotherapy [54]. The factors involved in this phenomenon include cancer stem cells (CSCs), the chaperone system, tumor cell plasticity and heterogeneity, microenvironment, hypoxia, metabolic reprogramming, gene regulation, microRNAs (miRNAs), DNA repair, and the cell cycle (Figure 1), which are discussed in the following subsections. The tumor tissue consists of two types of cells: cancer stem cells (CSCs) (0.01–5%) and non-CSCs (99.9–95%). The former have the capabilities of proliferation, differentiation, and self-renewal and constitute the source of cancer persistence. The non-CSCs constitute the bulk of the tumor mass, along with the differentiated and death-committed cells [55]. The presence of CSCs in the tumor mass partially explains the phenomenon of cell resistance to ionizing radiation [56]. CSCs are a tumor cell population with properties that distinguish them from other malignant cells, namely the ability to initiate carcinogenesis, sustain tumor proliferation, differentiate into all cellular subpopulations present in the primary tumor, and engage in unlimited self-renewal [57,58]. There are two main ways to explain the origin of CSCs. One postulates their establishment from postnatal stem cells, whereas the other proposes that CSCs originate by reprogramming differentiated tumor cells [59]. In addition, epigenetic reprogramming mechanisms, like those in embryonic stem cells, also play a role in the formation of CSCs [57]. Some reports describe the existence of self-renewing tumor-forming cells in glioblastoma and other types of gliomas capable of multilinear differentiation with stem cell-typical markers, according to which they are considered GSCs [60,61,62,63,64,65]. These may be critical factors in treatment failure and poor patient outcomes [66]. These GSCs, along with other indicators, express the special marker CD133 (prominin-1) that participates in the differentiation of GSCs and their self-renewal, which has a key role in carcinogenesis [55] and in the development of resistance to radiotherapy [67]. CD133-positive cells can survive high-dose radiotherapy and favor tumor relapse, despite the concomitant damage to tumor blood vessels [68], which increases after radiation exposure [67]. CD133 antigen expression is considerably higher in regrowing glioma tissue than in primary tumor tissue obtained from recently diagnosed patients [55]. The proportion of CD133-positive cells is an independent factor important for tumor regrowth and patients’ survival [67]. CD133-positive tumor cells enable the DNA damage checkpoint in feedback to radiation and a more effective fix for radiation-induced DNA damage, which may cause, at least in part, the radioresistance of CD133-positive glioma-initiating cells (GICs) [69,70]. Additionally, they show resistance to apoptosis [71]. The proliferating cell nuclear antigen (PCNA)-associated factor (PAF) plays an essential role in GSC’s self-renewal, radioresistance, and tumorigenicity [72]. PAF is predominantly overexpressed in GSCs, controls the sliding of PCNA along the DNA, and facilitates the switch from error-free to error-prone DNA synthesis [72]. A negative correlation between PAF and overall survival was observed [72]. GSCs with high Cathepsin L co-expression also have extraordinarily low radiosensitivity [70]. Tumor heterogeneity is one of the tenets of tumor progression, metastasization, development of resistance to therapy, and recurrence [73,74]. Two types of heterogeneity, intra-tumoral and inter-tumoral, cause difficulties in managing GBM [75,76,77,78]. Heterogeneity includes various alterations at the transcriptional, methylation, and mutational levels [79]. Single-cell-derived subclones can be a source of phenotypically heterogeneous progenies [80]. In GBM, inter-tumoral heterogeneity contributes more than intra-tumoral one to overall tumor heterogeneity [81]. In GBM, tumor cells from different locations in the same tumor mass will develop different extra mutations and show diverse epigenetic or phenotypic variants [75]. Intra-tumoral heterogeneity is thought to contribute to disease progression and, at least partially, to the different responses and resistance to treatment [82,83]. A fluorescence-guided multiple sampling approach with integrated genomic analysis of GBM tissues identified the various phenotypic profiles of tumor clones present in the same malignancy and established that each fragment of the tumor includes a complicated hierarchy of the clone members [84]. Furthermore, it was shown by a single-cell RNA sequencing assay that GBM has numerous cell states with different transcriptional programs and dynamic transitions [85]. Molecular and cytogenetic analyses demonstrated that the GSCs, or typical ancestor cells, bear distinctive genetic anomalies and various tumorigenic potentials [64]. Variable stem cell or regenerative activity was reported for subclones in each GBM [86]. Due to the different reactions to genotoxic damage by GSCs, the response to radiation therapy may also differ in radioresistance. Another critical point is that tumor-cell plasticity allows for adaptation to intra- and extracellular changes. For example, bidirectional plasticity by epigenetic reprogramming is possible via a set of neuro-developmental transcription factors, with the possibility of completely reprogramming differentiated cells of GBMs to GICs [87]. CSCs encompass two types of the hierarchical model of cerebral cell differentiation: symmetric subdivision to support a pool of CSCs and asymmetric subdivision to give rise to the various populations that form GBM. Differentiated tumor cells can reverse their directionality and modify their hierarchy to form CSCs and non-CSCs progeny [88,89]. The effectiveness of radiation therapy also depends on the microenvironment of the tumor, in addition to factors inside the body that affect radioresistance. The tumor microenvironment is the result of interactions between the tumor cells and surrounding cells and molecules and contributes to GBM tumorigenesis and regrowth [90,91]. The GBM microenvironment includes blood vessels, glioma stem cells, astrocytes, fibroblasts, neural precursor cells, extracellular and vascular pericytes, different types of non-neoplastic stromal cells, and immune cells [90,91]. It also includes signaling molecules (e.g., cytokines, chemokines, and growth factors) and the extracellular matrix, all of which generate a hypoxic, inflammatory, and immunosuppressive milieu [57,90,91]. Various biomolecules are derived from cells within the tumor mass to support its progression and growth. All these cells and molecules in the tumor microenvironment most likely participate in the radiation-induced response along with the changes in phenotype, gene expression, and functions, mechanisms that cause the release of growth factors, activation of tumor-associated fibroblasts, induction of inflammation, and hypoxia [57,92]. Thus, the cellular radioresistance of GBM depends on the tumor microenvironment. This is supported by the fact that CD133-positive cells are comparatively more radioresistant in intracerebral growth conditions than in vitro [93]. CSCs are clustered in some regions of the microenvironment called niches, which make available autocrine signaling and signals outgoing from tumor-associated fibroblasts, immune and endothelial cells, and extracellular matrix components [94,95]. Even though accurate data on the structure of niches and their signaling interaction with the tumor are scarce, it is accepted that the microenvironment supplies CSCs with oxygen and nutrients, supports their functions, and protects them against radiation [96]. The concept of a perivascular niche for GSCs was advanced in 2007 [97] and that of a periarteriolar niche was proposed in 2015 [98], which pointed to the type of vessels walled by GSCs. This distinction of the niches into “perivascular” and “periarteriolar” is essential because, in most cases, “perivascular” implies capillaries [97,99]. However, it is necessary to bear in mind that while arterioles are transport vessels, capillaries are exchange vessels [100]. This means that there is no release of oxygen from the lumen of the arterioles into the surrounding tissues, explaining the occurrence of hypoxic areas. Thus, the place for the residence of GSCs is the hypoxic periarteriolar niches. It has been established that oxygen concentration affects the reaction of mammalian cells to radiation [101]. Hypoxia is a key condition for the CSCs to maintain their stemness [102]. Oxygen is a strong radiosensitizer, and its presence is necessary for forming radiation-induced reactive oxygen species (ROS), thus contributing to cell death. Therefore, a shortage of oxygen increases radiation resistance [103,104,105]. Additionally, hypoxic niches up-regulate ROS scavenging, thus decreasing ROS levels [57,106]. Hypoxia is a cause of increased expression of VEGF and hypoxia-inducible factor (HIF)-1α, which were identified in periarteriolar niches adjacent to necrotic areas [98,107]. HIFs are significant regulators that increase the radioresistance level by activating the transcription of hypoxia response elements and activating the Hedgehog, Notch, wingless, and INT-1 (WNT) pathways. These pathways contribute to CSC maintenance [108,109]. Hypoxia mediates the functional regulation of DNA-dependent protein kinase catalytic subunit (DNA-PKcs), extracellular signal-related kinases, and HIF-1α, which causes radioresistance in GBM [110]. In turn, the increased transcription of HIF-2α provoked by hypoxia is a cause of octamer-binding transcription factor 4 (OCT-4) activation, which regulates the differentiation and self-renewal CSCs [111,112]. Another additional factor is cycling hypoxia, which means irregular and unstable perfusion of tumor tissue due to a poorly structured network of blood vessels. It leads to good and poor oxygenation periods, thereby exposing the cells to hypoxia, followed by cyclic periods of reoxygenation [113,114]. Thus, hypoxia maintains the undifferentiated state of GSCs, intensifies the colony-forming effectiveness and glioma cell migration, and activates the expression of stem cell markers [102]. Cancer is tightly related to metabolic disorders [115,116]. Metabolic reprogramming has been recognized as one of the ten distinctive features of tumor cells. Metabolic reprogramming is needed for both malignant transformation and tumor development, including metastasization and invasion [117]. This special type of cell-energy metabolism reprogramming is required to maintain continuing proliferation and cell growth, substituting the cellular metabolic homeostasis generally presented in normal cells [83]. It was found that several metabolic characteristics differ in almost all gliomas from normal brain tissues, including surplus production of lactate and acetate and an increase in glucose oxidation to generate macromolecular precursors and energy [118,119]. Those metabolic changes also contribute to resistance to standard treatments in GBM [120,121,122,123,124]. For instance, GBM radioresistance correlates with high rates of glycolysis and suppression of the glycolytic pathway [125,126]. The Warburg effect is seen in most tumor cells in which aerobic glycolysis occurs despite the oxygen milieu [127,128]. Tumor cells use more glucose than cells in a normal physiological state. When cancer cells uptake more glucose, the pentose phosphate pathway dominates and is a source of excess nicotinamide adenine dinucleotide phosphate (NADPH) [129]. This co-factor is a crucial player in the function of redox homeostasis and cellular antioxidant systems, protecting the cell from oxidative stress, including radiation injury [129,130]. The IDH1 gene has the most expressed regulatory NADPH-producing activity in patient-derived GBM tissue [131]. Moreover, it is the most pronounced NADPH-producing gene in GBM compared to normal brain tissue [132]. The wild-type IDH1 drives NADPH production as a reaction to radiation, contributing to radioresistance. On the contrary, the inhibition of wild-type IDH1 diminishes the NADPH level, making GBM cells radiosensitive in vivo and in vitro [132,133]. The p53 tumor-suppressor protein plays a vital role in inhibiting malignant development and cellular stress [134]. The TP53-induced glycolysis and apoptosis regulator(TIGAR) is a p53-inducible protein that defends against oxidative stress and regulates glycolysis. TIGAR can decrease ROS levels and lower sensitivity to other ROS-associated apoptotic signals and p53 [135]. Knockdown of TIGAR intensifies DNA damage by overwhelming the pentose phosphate pathway, thereby reducing the radioresistance of glioma cells to radiation exposure [136,137]. The ATPase family AAA domain-containing 3A (ATAD3A) is a mitochondrial enzyme that has a role in the interaction between mitochondria and the endoplasmic reticulum (ER) [138,139]. Endogenic expression of ATAD3A correlates with radiosensitivity in cells of GBM. Forced ATAD3A expression considerably increased radiation resistance [140]. The chaperone system (CS) includes all the molecular chaperones, co-chaperones, chaperone co-factors, and chaperone interactors and receptors of an organism [141]. The CS components are distributed throughout the body with presence and function in all cells and tissues. The canonical functions pertain to the maintenance of protein homeostasis, and, thus, the CS plays a role in metabolism by keeping all enzymes and functionally related proteins in their native conformation in the place where they are needed. This applies to normal and tumor cells; thus, in the latter, the CS may contribute to carcinogenesis, including the development of resistance to radiotherapy. Likewise, the non-canonical functions of CS, which affect many key cellular and extracellular processes, can also play a role in carcinogenesis and pro- and anti-cancer [142]. The molecular chaperones are the chief components of the CS, and the role of some of them in carcinogenesis has been investigated. For example, Hsp60, Hsp70, and Hsp90 are released by tumor cells via extracellular vesicles (EVs) [143,144,145]. In the pathogenesis of gliomas, molecular chaperones play different roles. Hsp90 and Hsp47 favor angiogenesis, and Hsp70, Hsp40, and Hsp27 assist the survival pathway, promoting cancer survivability [146,147,148,149]. Hsp90 is involved in the rewiring of the metabolism and the transcription of several of the key genes that are responsible for tumorigenesis and cancer progression. Hsp90 can control metabolic rewiring, either directly by controlling the sustainability, structure, and functional activity of several metabolic enzymes or indirectly by amending the Hsp90-dependent signaling pathways involved in the expression of some proteins implicated in metabolic networks [150]. Thus, Hsp90 contributes to the radioprotective mechanisms [151,152]. Hsp70 can protect against radiation-induced apoptosis, thereby favoring glioblastoma resistance to radiation therapy [153]. Non-coding RNAs (ncRNAs), such as long non-coding RNAs (lncRNAs) and miRNAs, may be aberrantly expressed in many tumors, indicating potential implications for cancer pathogenesis. They can play an essential role in regulating tumor radioresistance\sensitivity, and chemoresistance by controlling cell proliferation, apoptosis, DNA damage checkpoints, and other critical signaling pathways [154,155,156,157]. miRNAs are short RNA molecules that control target genes by post-transcriptional silencing; a single miRNA can influence hundreds of mRNAs and regulate the expression of many genes [158]. Abnormal levels of expression of numerous miRNAs occur in GBM tumors compared with normal brain tissue [159]. For example, overexpression of 256 miRNAs and downregulation of 95 miRNAs have been found in GBM [160]. Aberrant expression of miRNAs (miR-1 [161], miR-21 [162], miR-125a [161], miR-135b [163], miR-150 [161], miR-210 [164], miR-212 [164], and miR-425 [161]) is associated with resistance to radiation therapy. lncRNAs participate in different cellular processes and can be implicated in the development of diseases [165], including oncogenesis [166]. Additionally, they contribute to tumor radioresistance\sensitivity by controlling signal pathways, including cell apoptosis, proliferation, and metabolism; DNA damage checkpoints; and autophagy [167]. lncRNAs can regulate radiotherapy response in three ways: by acting on miRNAs, interacting with proteins to influence the cell cycle and autophagy, and operating as transcription factors to trigger downstream signaling pathways [155]. In glioblastoma, lncRNAs play a role in the establishment of radioresistance. For instance, lncRNA HMMR-AS1 is implicated in radioresistance via upregulation of irradiation-induced phosphorylation of ATM and of the levels of DNA repair proteins like RAD51 and BMI1 [168]; lncRNA HOTAIRM1 via upregulation of mitochondrial function and ROS levels in cells of GBM by controlling the expression of TGM2 [168]; lncRNA RBPMS-AS1 via downregulation of radioresistance through the miR-301a-3p/CAMTA1 axis [169]; miR-146b-5p/HuR/lncRNA-p21 axis via upregulation of β-catenin signaling pathway [170]; lncRNA SNHG18 via upregulation of suppression of semaphorin-5A [171]; lncRNA NCK1-AS1 via upregulation of the miR-22-3p/IGF1R ceRNA pathway [172]; lncRNA XIST via upregulation of the miR-329-3p/CREB1 axis [173]; lncRNA TPTEP1 via downregulation of the P38 MAPK signaling by interacting with miR-106a-5p [174]; and lncRNA linc-RA1 via upregulation of the prevention H2Bub1/USP44 combination [175]. CSCs are radiation-resistant and have peculiar molecular properties that defend them against radiation-induced damage. The precise mechanisms of this resistance to radiation are still not completely understood, but it is believed that they depend on an increased DNA repair potential [176]. An essential part of the cell’s response to DNA damage caused by radiation is the activation of cell cycle checkpoints, which temporarily cause it to stop correcting defects in the nucleotide sequence [177]. Increased replication after radiation therapy is an adaptive response to replication stress, which includes base damage and single- and double-strand DNA breaks (DSBs). Homologous recombination repair (HRR), non-homologous end-joining (NHEJ), and alternative NHEJ, which work as backups, are the main pathways used by cells to repair the DSBs and participate in mechanisms of radioresistance in tumor cells [178]. HRR occurs preferably in the cell cycle’s late S, G2, and M-phases when a sister chromatid is present [179]. NHEJ does not need a homologous DNA template. For this reason, it can be activated at any point in the cell cycle, but it is the predominant repair pathway in G1 and G2, even when both repair pathways are working [180,181]. Maximal radioresistance is observed in the late S-phase and is explained by the increased replication level, which contributes to the process of homologous recombination [181]. Histone deacetylase (HDAC)-4 and -6 contribute to radiation tolerance in GBM by inducing DSB repair [182]. HDAC increases NHEJ editing efficiency due to the considerable HDAC inhibitor-mediated increase in Cas9 and sgRNA expression [183]. Moreover, hyperexpression of epidermal growth factor receptor (EGFR) and EGFRvIII causes radioresistance in GBM by activating both HRR and NHEJ. EGFRvIII promotes the activation of a key enzyme, DNA-PKcs, implicated in the repair of DSBs [184,185]. BMI 1 (a core component of the polycomb repressive complex 1) pairs with DNA DSB response and NHEJ in cells of GBM, which contributes to the radioresistance of GBM by recruiting DNA damage repair machinery [186]. Summing up all the pathways described above that contribute to the support and development of GBM radioresistance (summarized in Table 2), we can conclude that the diversity of the factors underlying this phenomenon requires a multipronged approach for elucidating the mechanisms involved. A continuous exchange of information involving molecules such as lipids, proteins, carbohydrates, and nucleic acids occurs in the human body. These molecules move to their destination in EVs, which are small vesicles coated with a phospholipid bilayer and a cargo of bioactive molecules that represents the contents of the cell in which the vesicle originated [194,195,196]. EVs are released into the extracellular space by all cell types and, consequently, are ubiquitously present in biological fluids, for example, blood [197], urine [198], saliva [199], cerebrospinal fluid [200], and breast milk [201]. EV biogenesis represents an important evolutionary advancement because the cargo is protected from degradation by ribonucleases, deoxyribonucleases, and proteases present in the extracellular space. These enzymes cannot traverse the EV’s lipid bilayer. Based on their size, density, and mechanism of biogenesis, EVs can be sorted into three main types: exosomes, microvesicles, and apoptotic bodies [202]. Based on their size, EVs can be distinguished into small (diameter < 100 nm), medium (diameter 100–200 nm), and large (diameter > 200 nm) [203]. The main characteristics that distinguish the different subtypes of EVs are summarized in Table 3. Today, the International Society for Extracellular Vesicles encourages the use of the term “extracellular vesicles” as a generic term for all secreted vesicles, considering the lack of consensus for the identification of specific markers to distinguish between the different subtypes of EVs [203]. There is an increasing interest in studying EVs because they are involved in communication among cells in normal physiological and pathological processes [217]. EVs and their content play an important role in tumor initiation, progression, and diagnosis [218]. GBM-derived EVs are involved in tumorigenesis, tumor microenvironment formation, angiogenesis, immune response, invasion, metastasization, and chemotherapy resistance [143,219,220,221,222]. In normal conditions, EVs play an important role in sustaining diverse physiological processes, such as cell growth, development, differentiation, and apoptosis, through the interchange of genetic information and biomolecules in cell-to-cell communications [223]. In the brain, the EVs are released by neurons and different types of glial cells. Under physiological conditions, EVs transport molecules between the neurons and the glia, with consequent involvement in synaptic activity, neuronal plasticity, maintenance of myelination, and neurovascular integrity. EVs have a substantial impact on neural development and genetic variety because of their ability to transfer various cargoes, such as protein and lipid components, signaling molecules, transcription factors, and DNA and RNA. Another potential role for EVs in developing the central nervous system (CNS) is the regulation of myelin membrane formation: the formation of the myelin membrane is downregulated by EVs released from oligodendrocytes [224]. EVs can also cross the blood–brain barrier (BBB), adding a communication channel through which systemic inflammation can modulate physiological processes in the CNS. For example, after neuronal injury, astroglial and microglial cells are activated and release exosomes that contain misfolded and inflammatory proteins and miRNAs involved in a neuroinflammatory response that affects the vitality of neurons [224]. The neuroinflammatory response can reach the periphery through the passage of exosomes through the BBB. These peripheral exosomes can be used as biomarkers for the pathogenesis of neuroinflammation and neurodegenerative disorders [224]. They act as bidirectional vehicles in brain-periphery communication, especially in neuroinflammation and aging. EVs also play a neuroprotective role and promote neuronal regeneration in the event of injury [225,226]. EVs derived from oligodendrocytes and microglia can increase neuronal firing [227]. EVs released by neurons during neuronal remodeling are involved in synapse elimination and stimulate microglial phagocytosis. The first line of defense against pathogens in the CNS is microglia. These cells are one of the protagonists of the immune response as they express immune receptors such as toll-like receptors and produce soluble factors such as cytokines, chemokines, free radicals, and reactive oxygen species, which mediate the inflammatory response [227]. Microglia-derived EVs regulate synaptic transmission by promoting the neuronal production of ceramide and sphingosine to enhance excitatory neurotransmission [224]. Excitatory neurotransmitters, e.g., glutamate, increase the release of small EVs from neurons, oligodendrocytes, and microglia and are associated with an increase in intracellular calcium levels [228,229]. The composition of EVs differs between healthy and cancer cells because the content of the EVs reflects the state of the secreting cell, and oncogenic processes increase the release of EVs [207]. In tumors, EVs play a key role because they can determine the fate of adjacent cells, leading to the formation of an environment that favors tumor growth [187]. Tumor-derived EVs are carriers of oncogenic factors involved in the development of GBM, and they are also responsible for their ability to infiltrate healthy brain parenchyma, which starts the formation of satellite tumors [187,220]. The vesicles produced by GBM cause suppression of the immune response against the tumor and favor the formation of new blood vessels to feed the tumor mass and the invasion of malignant cells [230]. Furthermore, GBM-derived EVs affect M2 macrophage polarization under hypoxia, thus promoting the formation of an immunosuppressive microenvironment [230]. Simultaneous injection of EVs isolated from the serum of patients with GBM and normal epithelial cells in mice caused the formation of gliomas in these mice, which confirmed the EVs’ involvement in GBM tumorigenesis [231]. The identification of transforming growth factor (TGF)-β1 in EVs isolated from the serum of patients with high-grade glioma supported the hypothesis of the involvement of GBM-derived EVs in the systemic immune response [232]. Conversely, TGF-β1 was not detected in EVs from healthy controls. TGF-β1 has pleiotropic effects, including the stimulation and activation of T cells and monocytes, but in neoplasms, the effect is mainly immunosuppressive [232]. In this regard, EVs from human GBM cell lines were studied. They carried immunosuppressive markers, including CD39, CD73, FasL, CTLA-4, and TRAIL [233]. Co-culture experiments with NK cells, CD4+T cells, and CD8+ cells revealed a downregulation of the activation state, reduced cytokine production, and increased apoptosis of CD8+T cells. Other upregulated markers in this population were CD39, PD-1, and EGFR [233]. It was found that 90% of all GBM patients showed aberrant expression of at least one of the following EV-markers: EGFR, EGRRvIII, podoplanin, and IDH1 [234]. Other EV components, such as mRNA and miRNA, also have the potential as tumor diagnostic markers. miRNAs can be exchanged between cells via exosomes and their detection and analysis provides information about the parental cell [143,223,235,236,237]. The diversity of transcriptomic profiles observed in glioma cells is mirrored in EVs derived from these cells. The expression levels of one small non-coding RNA (RNU6-1) and two miRNAs (miR-320 and miR-574-3p) are useful parameters for diagnosing GBM [238]. Exosomal miR-21 is also a useful marker for the diagnosis and assessing the prognosis of GMB because its levels are correlated with tumor recurrence and metastasis [239]. The surrounding tumor microenvironment (TME) in glioblastoma is highly heterogeneous. It consists of cancerous and non-cancerous cells, including endothelial cells (ECs), immune cells, glioma stem cells (GSCs), and astrocytes, as well as non-cellular components, such as the extracellular matrix [240]. TME is considered a crucial supporter of GBM progression, and EVs have recently been identified as an essential means of bidirectional communication between tumors and TME [241]. Rapidly growing GBM is accompanied by the formation of hypoxic areas [242]. Lack of oxygen is the cause of the formation of new blood vessels to supply oxygen and nutrients to the tumor. GBM-derived EVs have been implicated in vascular endothelial cell proliferation, migration, and tubulogenesis by releasing angiogenic proteins [243]. Mainly released by hypoxic GBM cells, vascular endothelial growth factor (VEGF)-A promotes the proliferation and migration of ECs toward hypoxic regions of GBM [244]. The result of neoangiogenesis in GBM is a highly disorganized and leaky network of vessels within areas of extreme chronic hypoxia. GBM-derived EVs, grown under hypoxic conditions, alter the phenotype of ECs to induce angiogenesis ex vivo and in vitro [245,246]. Other intercellular communication alterations occur in astrocytes, the most abundant glial cells, representing about 50% of the volume of the human brain [247]. EV-mediated crosstalk between glioblastoma cells and astrocytes supports tumor growth. Consequently, GBM-derived EVs have been implicated in altering the phenotype of normal astrocytes. Normal astrocytes exposed to GBM-derived EVs produce a tumor growth-stimulating secretome that includes VEGF; epidermal-growth, fibroblast-growth, and colony-stimulating factors; and Interleukins 10 and 19 (IL-10 and IL-19). GBM-derived EVs can be involved in the remodeling of astrocytic projections and disruption of the BBB in patients, favoring tumor invasiveness [248]. Astrocytic end feet are directly involved in the structure of the BBB. They are displaced during the development of the GBM, causing the loss of astrocyte-vascular coupling and the formation of openings in the BBB [249]. In addition, the remarkable proliferation of ECs in the GBM areas with increased hypoxia, disrupts tight junctions, leading to the loss of integrity of the BBB [250]. GBM initiation and growth are attributed to its ability to evade the immune response. EVs derived from GBM cells regulate the immune response to tumor growth via PD-L1/PD1 signaling [251]. PD-L1 associated with the EVs can directly bind the PD1 receptor on the surface of infiltrating T cells in the brain, inhibiting their activation and consequently promoting immunosuppression [251]. Therapeutic resistance remains a major obstacle to successful cancer treatment. Multiple mechanisms of resistance to therapy mediated by EVs have been described for various tumors, including breast, prostate, lung, kidney, ovarian, hematological, pancreatic, stomach, and brain cancers [252]. Diverse resistance mechanisms have been discovered in which EVs are involved. For example, EVs derived from resistant tumor cells and tumor support cells transfer the genomic and proteomic cargo (mRNA, miRNA, lncRNA, spliceosomes, and proteins) to the glioma treatment-sensitive cells, which improves their acquisition of a resistant phenotype and, by doing so, facilitates chemo- and radioresistance in GBM [187,188,189,190,191,192]. Transferring transcripts of DNA repair enzymes, such as alkylpurine-DNA-N-glycosylase and MGMT, results in increased DNA repair capacity in recipient cells [193]. GSCs-derived EVs enhance radiation resistance in GBM [191]. The regulation of DNA repair pathways and the CSCs’ state are coordinated by EV-mediated secretion of miR-603, leading to acquired radioresistance and cross-resistance to DNA alkylating agents and producing the treatment-resistant CSC phenotype [191]. EVs have an impact on the biological properties of GSCs, such as cell viability, invasion, and radioresistance. In this regard, the contribution of the hypoxia-inducible factor-1α (AHIF), transported by EVs, to the upregulation of radioresistant GBM cells was studied [192]. It was found that the expression of AHIF is highly represented in GBMs in response to radiation therapy, and suppression of AHIF in GBMs decreases cell radioresistance. Furthermore, EVs derived from AHIF-knockdown cells inhibited GBM radioresistance. GBM remains cancer with a high mortality rate, notwithstanding numerous research efforts and clinical trials using a variety of drugs and radiation. Despite the technological progress that has improved medical equipment and methods of radiation therapy, patient survival is still low. The development of resistance to radiation therapy by tumor cells is a frequent obstacle to therapy. Some progress has been made in the understanding of radioresistance mechanisms, as discussed in this brief review, but much needs to be elucidated at the molecular level to facilitate the development of efficacious treatments. EVs are involved in different ways in the onset and rapid growth of GBM. Tumor-derived EVs are oncogenic factor carriers involved in the initiation, progression, and formation of a resistant phenotype in GBM. Additionally, EVs reflect the transcriptomic profiles of the GBM cells that secret them. Therefore, EVs offer a means for diagnosis, prognostication, patient monitoring, and treatment, representing a promising theranostics tool. EVs can be used to deliver drugs directly to the tumor. In the literature, attention is directed to therapeutic agents such as radiolabeled compounds, quantum dots, plasmonic nanobubbles, liposomes, magnetic nanoparticles, polymer-conjugates, and nanovesicles, dendrimers linked with targeting agents or antitumor molecules and imaging substances [253,254,255,256,257,258,259,260,261,262]. However, there is still a need for useful tools, particularly regarding tumors of the nervous system, and EVs provide an alternative. One crucial point is that EVs can overcome the BBB. Consequently, efforts have been dedicated to developing nanomaterials, including EVs, that can penetrate the BBB [263,264]. The nanomaterials used in the treatment of GBM must meet several criteria. For example, the EVs with the active molecules must be: (1) exclusively released by the tumor cells; (2) produced by viable cells in the tumor mass rather than only loose cells undergoing necrosis or apoptosis; (3) represent the biomolecular diversity, i.e., heterogeneity, of the entire tumor; (4) penetrate through the BBB; (5) effective for specific interaction with, and penetration into the diseased regions of the brain; (6) endowed with a long-term half-life and long preserved delivery capability while in circulation; (7) capable of protecting the cargo from degradation; (8) easily detectable in tissues and fluids and (9) amenable to quantification and manipulation without major technical difficulties [265,266,267,268,269,270,271]. Most of these conditions are met by EVs, making them promising theranostics tools for studying and developing efficacious, personalized GBM treatment [269,270,271].

PMC10003082

Benedetta Fibbi,Giada Marroncini,Laura Naldi,Alessandro Peri

The Yin and Yang Effect of the Apelinergic System in Oxidative Stress

01-03-2023

apelin,APJ,apelinergic system,oxidative stress

Apelin is an endogenous ligand for the G protein-coupled receptor APJ and has multiple biological activities in human tissues and organs, including the heart, blood vessels, adipose tissue, central nervous system, lungs, kidneys, and liver. This article reviews the crucial role of apelin in regulating oxidative stress-related processes by promoting prooxidant or antioxidant mechanisms. Following the binding of APJ to different active apelin isoforms and the interaction with several G proteins according to cell types, the apelin/APJ system is able to modulate different intracellular signaling pathways and biological functions, such as vascular tone, platelet aggregation and leukocytes adhesion, myocardial activity, ischemia/reperfusion injury, insulin resistance, inflammation, and cell proliferation and invasion. As a consequence of these multifaceted properties, the role of the apelinergic axis in the pathogenesis of degenerative and proliferative conditions (e.g., Alzheimer’s and Parkinson’s diseases, osteoporosis, and cancer) is currently investigated. In this view, the dual effect of the apelin/APJ system in the regulation of oxidative stress needs to be more extensively clarified, in order to identify new potential strategies and tools able to selectively modulate this axis according to the tissue-specific profile.

The Yin and Yang Effect of the Apelinergic System in Oxidative Stress Apelin is an endogenous ligand for the G protein-coupled receptor APJ and has multiple biological activities in human tissues and organs, including the heart, blood vessels, adipose tissue, central nervous system, lungs, kidneys, and liver. This article reviews the crucial role of apelin in regulating oxidative stress-related processes by promoting prooxidant or antioxidant mechanisms. Following the binding of APJ to different active apelin isoforms and the interaction with several G proteins according to cell types, the apelin/APJ system is able to modulate different intracellular signaling pathways and biological functions, such as vascular tone, platelet aggregation and leukocytes adhesion, myocardial activity, ischemia/reperfusion injury, insulin resistance, inflammation, and cell proliferation and invasion. As a consequence of these multifaceted properties, the role of the apelinergic axis in the pathogenesis of degenerative and proliferative conditions (e.g., Alzheimer’s and Parkinson’s diseases, osteoporosis, and cancer) is currently investigated. In this view, the dual effect of the apelin/APJ system in the regulation of oxidative stress needs to be more extensively clarified, in order to identify new potential strategies and tools able to selectively modulate this axis according to the tissue-specific profile. Apelin is a biologically active neuropeptide that was first isolated in 1998 from bovine stomach extracts [1,2] and identified as the endogenous ligand for the orphan receptor APJ, which was characterized in 1993 as a seven transmembrane G-protein coupled receptor (GPCR) with high affinity (homology of 40–50% in the hydrophobic transmembrane region) with the angiotensin II receptor type 1a [3,4,5]. In humans, apelin is encoded by the APLN gene, which is located on the long arm of X chromosome (Xq25-q26.1) and encodes the 77-aminoacid precursor peptide pre-pro-apelin [2], whose enzymatic hydrolysis originates several active peptide fragments able to activate APJ by their common C-terminal sequence [6]. Apelin isoforms have 12, 13, 15, 16, 17, 19, 28, 31, 36, or 55 aminoacids and display a distinct receptor binding affinity [6], with apelin-13 representing the most effective activator of APJ [7], followed by apelin-17 and apelin-36 [8]. As a GPCR, APJ interacts with G proteins (mainly Gi/o and Gq/11), leading to the modulation of several different signaling pathways after ligand binding. Specifically, via Gi/o, the apelin/APJ system activates the phospho-inositide 3-kinase (PI3K)/AKT (also named protein kinase B, PKB) and protein kinase C (PKC)/extracellular signal-regulated kinase 1/2 (ERK 1/2) pathways, thereby being involved in the regulation of apoptosis, cell proliferation, neuroinflammation, and oxidative stress [9,10]. Moreover, Gi/o is implicated in the downregulation of protein kinase A (PKA) by inhibiting cAMP production [10]. Upregulation of phospholipase C beta (PLCβ) by Gq/11 triggers the generation of diacylglycerol (DAG) and inositol 1,4,5-triphosphate (IP3), which lead to the initiation of the PKC cascade and the intracellular release of Ca2+, respectively [10]. Both AKT activation and increase of intracellular Ca2+ induces nitric oxide synthase (NOS), thus promoting vasodilation. Binding of apelin to APJ can also result in the autophosphorylation of the receptor through G protein-coupled receptor kinase (GRK). This event initiates a β-arrestin-mediated response involving the desensitization and clathrin-dependent internalization of APJ, which can activate G protein-independent signaling pathways [10,11]. Finally, APJ has also been shown to activate G13 in human umbilical vein endothelial cells, leading to histone deacetylases (HDAC) type 4 and 5 inactivation, activation of myocyte enhancer factor-2 (MEF2) and expression of MEF2 target gene Kruppel-like factor 2 (KLF2) [12] (Figure 1). APJ and apelin are both highly conserved among species and widely expressed in rodents and human tissues, including lung, heart, spinal cord, brain, placenta, endocrine (thyroid, parathyroid, adrenal, pituitary), gastrointestinal and urinary apparatuses, bone marrow, skeletal and smooth muscles, and adipose tissue, among others [13]. The capability of APJ to interact with several G proteins according to cell types (i.e., heterologous signaling) and stimulate different intracellular pathways explains the variety of biological effects potentially mediated by the apelin/APJ system: vasodilation and lowering of blood pressure [14], increase of cardiac contractility and heart rate [15,16], control of pituitary hormone release, drinking behavior and body fluid homeostasis [17], neuroendocrine stress response [18], food intake and appetite regulation [17,19], glucose metabolism and insulin sensitivity [20], promotion of cell proliferation, migration and angiogenesis, and regulation of gastrointestinal and immune functions [21]. The type and magnitude of downstream events may be cell type- and context-dependent, since apelin isoforms induce different APJ trafficking [22,23]. It is worth noting that although apelin-13 and apelin-36 are able to promote the internalization of APJ, only apelin-13-internalized receptors can be rapidly recovered to the cell surface [24]. Conversely, apelin receptors internalized after binding to apelin-36 represent a target for lysosomal degradation [25]. Elabela is a micropeptide recognized as the second endogenous ligand for APJ [26]. Its involvement in physiological and pathological conditions will not be discussed in this review. Oxidative stress is a condition characterized by an excessive accumulation of reactive oxygen species (ROS) in cells and tissues, which overwhelms the normal dynamic homeostasis and the ability of a biological system to detoxify them. The imbalance between ROS and antioxidants exerts harmful effects on several cellular structures (proteins, lipids, and nucleic acids) [27] and processes (protein phosphorylation, transcriptional factors activation, apoptosis, differentiation, and immunity) [28], thus leading to cell and tissue damage. In this view, oxidative stress is considered as one of the underlying mechanisms of the onset and/or progression of several diseases (i.e., cancer, diabetes, metabolic disorders, atherosclerosis, and cardiovascular diseases) [29]. Mitochondria are the major intracellular site of energy metabolism regulation and therefore they are heavily involved in ROS production [30]. Both enzymatic and non-enzymatic (oxygen reaction with organic compounds, cell exposure to ionizing radiations, mitochondrial respiration) reactions participate in ROS generation from both endogenous (inflammation, ischemia, immune cell activation, infections, cancer, aging) and exogenous (chemical drugs and solvents, smoke, radiations, alcohol) sources [31,32]. As a consequence of apelin/APJ system characterization and evidence of its involvement in the regulation of many intracellular pathways and cell functions, it was not long before there was a demonstration of a close link between this axis and oxidative stress. In fact, not only the myocardial APLN gene expression and protein secretion have been shown to be upregulated by hypoxia via activation of hypoxia-inducible factor (HIF) [33], but the crucial role of apelin in regulating oxidative stress-related processes was also revealed in many tissues and pathological conditions. Although the activation of apelin/APJ-associated signaling pathways is secondary to both ROS-dependent and ROS-independent stimuli, this review focused on the role of the apelinergic system in oxidative stress-mediated pathologic conditions. In the vascular system, apelin and APJ are expressed by endothelial and vascular smooth muscle cells (VSMCs), where they are implicated in a complex regulation of blood vessels’ function [34]. Under physiologic conditions, apelin binding to APJ results in vasodilation and transient hypotension by modulating both NO synthesis (via PI3K/Akt and IP3/Ca2+ pathways) and the renin–angiotensin–aldosterone system (RAAS). Indeed, its counterregulatory role against angiotensin II-dependent vasopressor stimulation [35,36,37,38] is at least in part secondary to the upregulation of angiotensin converting enzyme 2 (ACE2), which is a negative modulator of RAAS [39,40]. Oxidative stress and vascular NO bioavailability imbalance represent the major etiopathogenetic factors of vascular injury and hypertension [41], with angiotensin II and RAAS acting as crucial triggers of ROS production (e.g., by angiotensin II-induced activity of mitochondrial NADPH oxidase 4, NOX4, which is the upstream signaling molecule of ERK) and endothelial NOS (eNOS) inhibition [42,43,44]. As expected, based on the endothelium-dependent vasodilative properties of apelin, different isoforms of this peptide were demonstrated to mitigate hypertension in in vivo models, with apelin-12 exhibiting the greater effect on blood pressure lowering after intraperitoneal injection of apelin-12, apelin-13, and apelin-36 in anesthetized rats. The absence of a significant antihypertensive effect in APJ-deficient mice suggests that apelin binding to an intact endothelial APJ is required for its vasodilative action [45]. Oxidative stress is the major trigger in the initiation and progression of atherosclerosis. Through the upregulation of selected genes [46], ROS promote mitogenicity and inhibit apoptosis of VSMCs, which contributes to the recruitment of circulant inflammatory cells and the production of extracellular matrix and cytokines, thus participating both in early- and late-stage atherogenesis [47]. Apelin/APJ has been demonstrated to be involved in the development of hypercholesterolemia-associated atherosclerosis similarly to angiotensin II/AT1, which promotes endothelial dysfunction and myosin light chain phosphorylation in VSMCs [48,49,50,51]. By exerting an opposite role on RAAS function to that previously described, apelin-13 is able to activate the ERK-Jagged-1/Notch3-cyclin D1 pathway [52], NOX4 expression and NOX4-derived ROS generation, and oxidative stress-linked proliferation in VSMCs [53]. Accordingly, APJ deficiency can prevent oxidative stress-induced atherosclerosis and protect blood vessels from atherosclerotic plaques [53,54]. In parallel, apelin/APJ-dependent activation of ERK increases the endothelial expression of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), and the release of monocyte chemoattractant protein-1 (MCP-1) through the NF-κB/JNK signaling pathway, thus leading to monocyte recruitment and adhesion to endothelial cells [55,56]. Hence, apelin/APJ and oxidative stress seem to be involved in early atherogenesis via the activation of the NOX4-ROS-NF-κB/ERK signaling pathway in VSMCs and in the endothelium. Abnormal proliferation and migration of VSMCs results in a large number of cells able to penetrate the endothelial layer, deposit in the arterial intima, and secrete bone morphogenetic proteins, which can promote the spontaneous calcification of plaques in late-staged atherosclerosis [57,58,59]. Abnormal apoptosis of mouse aortic vascular smooth muscle cells (MOVAS) secondary to intracellular oxidative stress has been closely related to vascular calcifications through ERK and PI3K/AKT pathways, which both affect MOVAS osteogenic differentiation and calcium deposition [5,60,61]. Zhang et al. have recently reported that apelin-13 significantly reduced high glucose-induced proliferation, invasion, and osteoblastic differentiation of MOVAS—therefore suppressing vascular calcification processes—by inhibiting ROS-mediated DNA damage and regulating ERK and PI3K/AKT pathways [62]. However, apelin’s ability to abrogate the development of atherosclerosis by increasing NO bioavailability and antagonizing angiotensin II cellular signaling was also described [63]. The exact pathophysiological mechanism of pre-eclampsia (PE) is not clearly defined, but abnormal placentation with angiogenic factors levels disproportion and placental insufficiency, increased inflammation, and oxidative stress are known to exert critical roles [64,65]. Adipokines including resistin, adiponectin, and apelin are released even from the placenta during pregnancy [66], and a significant decrease in circulating apelin levels has been demonstrated in PE women compared to normal pregnancies [67,68,69,70]. Circulating apelin decreases in the middle of pregnancy and rises again in the third trimester in healthy pregnancy [71]. Hence, maternal concentrations of apelin lower than expected may play a key role in the etiology of PE. Circulating apelin concentrations showed a significant negative correlation with mean arterial blood pressure, proteinuria, serum soluble fms-like tyrosine kinase-1 (sFlt-1, a soluble form of VEGF/PLGF receptors which acts as an effective scavenger of VEGF and PLGF and sensitizes maternal endothelium to proinflammatory cytokines, thus inducing endothelial dysfunction and multiorgan damage), soluble endoglin (sEng, that acts as a limiting factor for eNOS activity), and IFN-γ levels in PE compared to control women [72]. Furthermore, a positive correlation of apelin levels with serum placental growth factor (PLGF), VEGF and IL-10 levels, and superoxide dismutase (SOD) and catalase activities was also recognized [72]. However, apelin administration significantly improved sFlt-1 and sEng values in the treated group. These results, which are in line with previous reports stating that inflammation is one of the mechanisms of PE by inducing placental ischemia and endothelial dysfunction [73,74], also strengthen the effect of apelin in the pathogenesis of PE. The role of the apelinergic system on the endothelial function accounts for its close association with diabetic microvascular complications, which have, in oxidative stress, one of the underlying pathogenetic mechanisms [75]. In the kidney of diabetic mice, apelin was able to restore antioxidant enzymes’ activity and reduce oxidative stress, thus preventing chronic injury [76] and progression of diabetic nephropathy [77]. Moreover, the evidence of apelin-induced inhibition of ROS generation in an in vitro model of cortical neurons supports the hypothesis of its positive effect in preventing the occurrence of diabetic neuropathy [78]. Nevertheless, the mRNA levels of APJ, apelin, and VEGF are all upregulated in the vascular tissue membrane in proliferative diabetic retinopathy [79], and apelin/APJ was demonstrated to be involved in retinal neoangiogenesis by promoting the expression of VEGF [80,81]. Hence, apelin is supposed to exert a pathogenetic effect in the onset of diabetic retinopathy, and the inhibition of the apelinergic system has been proposed as an effective tool to prevent it. The role of apelin/APJ in myocardial homeostasis and pathology is uncertain and data from literature are conflicting. On the one hand, it was linked to a protecting effect against ventricular hypertrophy in murine models, where apelin was reported to reduce oxidative stress induced by hydrogen peroxide or 5-hydroxytryptamine [82], and endoplasmic reticulum stress [83]. Similarly, in a model of ischemia-induced heart failure, apelin was proved to reduce ROS production and to ameliorate cardiac dysfunction and RAAS hyperactivation-associated fibrosis, via inhibiting the PI3K/Akt signaling pathway [84]. Peripheral and coronary vasodilatation and improved cardiac output were observed even in patients affected by chronic heart failure after apelin injection [85]. Contrastingly, an increased expression of cardiac myosin and β-MHC (β-myosin heavy chain) mRNA was observed in normotensive rats 15 days after chronic infusion of apelin-13 into the paraventricular nucleus, thus indicating a role of the peptide in the induction of cardiac hypertrophy [86]. Ischemia/reperfusion (I/R) injury (IRI) consists of the paradoxical exacerbation of cellular dysfunction and death after restoration of blood flow to previously ischemic tissues. Oxidative stress and inflammation secondary to hypoxia-induced production of ROS are the main determinants of cellular and tissue damage [87], which are sustained by activation of matrix metalloproteinase enzymes and degradation of the extracellular matrix and tight junction proteins around endothelial vascular cells [88]. During I/R in in vivo models, apelin is able to protect myocardiocytes against oxidative stress and inhibit mitochondrial oxidative damage and lipid peroxidation by activating eNOS and reperfusion injury salvage kinase (RISK) [89,90]. Hemodynamically, it results in reduced left ventricular preload and afterload, improved cardiac contractility [91], and reduced infarct size [92]. The effect of apelin-13 on post-myocardial infarction repair is partially mediated by an increase of myocardial progenitor cells in the infarcted hearts [93]. Epidemiological data show that diabetes is the most important risk factor for cardiovascular diseases and IRI, with a 2–6-fold increased mortality compared to non-diabetic conditions [94]. Results from animal models showed that heart failure was more severe in diabetic IRI rats compared to non-diabetic IRI rats, and that apelin overexpression significantly decreased injury size and heart weight index and improved cardiac function [95]. Upregulation of PPARα (a well-known modulator of lipid metabolism, antioxidant defense, mitochondrial and endothelial functions, atherosclerosis, and inflammation) and inhibition of apoptosis (enhanced Bcl-2 levels and decreased Bax and cleaved caspase-3 levels) and oxidative stress via the PI3K and p38MAPK pathways has been characterized as the major determinant of apelin’s cardio-protective effects [96,97]. In lungs, IRI often occurs after pulmonary oedema or acute respiratory distress syndrome [98]. Apelin-13 administration to lung IRI rats resulted in a mild damage of alveolar structures, a reduced number of erythrocytes and inflammatory cells, and lower inflammatory cytokines (IL-1β, IL-6 and TNF-α) expression levels [99]. These morphological and molecular changes observed in tissues were associated with an increase of PaO2 and a decrease of PaCO2 compared to non-apelin-treated IRI rats, thus suggesting that apelin/APJ could minimize IRI by improving lung oxygenation and peroxidation. Finally, apelin-induced expression of uncoupling protein 2 (UCP2), an anionic carrier located on mitochondria which increases SOD activity and improves cell survival in a reduced ROS environment [100], could imply a direct effect of apelin/APJ in ameliorating mitochondrial damage [99]. In the brain, ischemia-induced injury is not only considered as an outcome of inadequate oxygen supply, but it has also been related to an excessive amount of ROS, which lead to cellular and protein dysfunction [101,102,103] and tissue disruption [104]. The degradation of the extracellular matrix secondary to IRI-associated oxidative stress leads to blood–brain barrier (BBB) destruction and vasogenic edema [105], which is a severe consequence of ischemic brain stroke, resulting in a 5% mortality rate [106,107,108]. The subsequent reperfusion contributes to cerebral oedema by initiating the activation of several destructing signaling pathways, including inflammatory responses, alteration of cellular receptors, ion imbalance, oxidative stress, changes in water channel expression, activation of proteinase enzymes, as well as changing tight junction proteins expression [109,110,111,112]. Apelin-13’s ability to significantly decrease brain IRI is mediated by different mechanisms. Gholamzadeh et al. showed that, in mice, oxidative stress markers increased due to ischemia, and that the injection of apelin-13 only 5 min before the onset of reperfusion could significantly reduce vasogenic cerebral oedema and protect BBB integrity [113]. Apelin-13 administration also decreased the expression of endothelin-1 receptor type B [113], whose up-regulation in astrocytes and endothelial cells is associated with metalloproteinase activation [114]. By the activation of ERK1/2 intracellular pathway, the apelinergic system inhibited the production of ROS and increased SOD activity [115]. In parallel, apelin-13 was able to inhibit the ROS-mediated inflammatory response of ischemic stroke by activating the phosphorylation level of AMP-activated protein kinase (AMPK) and the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) [116]. AMPK signaling was also reported to participate in the antiapoptotic role of apelin-13 in ischemic stroke [117]. Conversely, apelin-36-mediated decrease of Bax and caspase-3 levels associated with IRI was related to the PI3K/Akt pathway [118], inhibition of ER stress/unfolded protein response (UPR) activation induced by brain I/R injury [119], and SK1/JNK/caspase-3 apoptotic pathway [120], whereas apelin-12 neuroprotection after ischemia was associated with restrainment of the c-Jun N-terminal kinase (JNK) and p38MAPK signaling pathways of apoptosis-related MAPKs family [121]. Autophagy is a homeostatic process involved in the lysosomal-dependent degradation and elimination of damaged and/or misfolded proteins and organelles. It is negatively modulated by the AMPK/mammalian target of the rapamycin (mTOR) axis [122], and apelin-13 was suggested to attenuate traumatic brain-associated IRI by suppressing autophagy [123]. Finally, apelin/APJ reduced renal IRI by promoting the activity of the mitochondrial enzymes SOD, catalase, and glutathione peroxidase, and decreasing the formation of hydroxyl radicals and malondialdehyde [124]. Data from in vivo obesity models suggest that apelin may function as an adipokine [125,126,127]. Serum levels of this neuropeptide positively correlate with insulin resistance and obesity [125,126,127], and inflammation (particularly by TNF-α production) and oxidative stress have been proposed as the link between apelin/APJ and insulin resistance [128]. In skeletal muscle, apelin enhances the expression of mitochondrial biogenesis markers and enzymes (e.g., citrate synthase, β-hydroxyacyl-CoA dehydrogenase, cytochrome c oxidase) and the content of proteins involved in the assembly of mitochondrial respiratory chain complexes [129,130]. In adipocytes, the apelin/APJ axis prevents the generation of ROS by stimulating the expression of antioxidant enzymes (through MAPK/ERK and AMPK pathways) and inhibiting the expression of pro-oxidant enzymes [131]. The direct effect of insulin on the adipocytic production of apelin is supported by the statistical association among different markers of adiposity, related risk factors, and apelin expression from rat subcutaneous and retroperitoneal adipose tissue [132]. On the other hand, the correlation between apelin mRNA levels and markers of hepatic oxidative stress highlighted a possible role of the apelinergic system in obesity-induced liver oxidative steatosis and dysfunction [132]. Accordingly, exogenous apelin injection restored glucose tolerance and increased glucose utilization in peripheral tissues in high fat diet mice with hyperinsulinemia, hyperglycemia, and obesity [133]. Apelin has been reported to be downregulated with age in different tissues, and its absence accelerates the onset and progression of aging. Again, oxidative stress is considered to be the link between apelin and the aging process [134]. Specifically, increasing evidence has shown that the apelinergic system participates in autophagy [135,136] and alleviates oxidative stress [82,131,137], which contributes to the development of aging. Apelin and APJ mRNAs are widely expressed in neuronal cell bodies and fibers throughout the entire central nervous system (CNS), such as in the thalamus, subthalamic nucleus, pituitary gland, hippocampus, basal forebrain, frontal and piriform cortex, striatum, corpus callosum, substantia nigra, olfactory tract, amygdala, central gray matter, spinal cord, and cerebellum [34,138,139]. This broad localization fits with the huge impact of the apelinergic system in neuroprotection, which goes through several mechanisms: suppression of oxidative stress, inhibition of apoptosis and excitotoxicity, and modulation of inflammatory responses and autophagy. Interestingly, these different processes are frequently interconnected and regulated by the same intracellular pathways [45]. Indeed, apelin’s beneficial properties on ethanol-induced memory impairment and neuronal injury of rats are sustained by inhibitory effects on hippocampal oxidative stress, apoptosis, and neuroinflammation [140]. Specifically, the administration of apelin-13 was observed to increase antioxidant enzymes’ activity and glutathione concentration, reduce lipid peroxidation and the number of active caspase-3 positive cells, and attenuate TNF-α production and glial fibrillary acidic protein (GFAP) as a neuroinflammation mediators [140]. The regulatory role of apelin/APJ in neuroinflammation is exerted by suppressing the activity of microglia, astrocytes, and other inflammatory cells [141,142]. Microglia are the innate immune cells of the CNS, able to both eliminate pathogens and cell debris and contribute to neuronal regeneration after tissue damage through the acquisition of different activated phenotypes: M1 cells produce pro-inflammatory cytokines and ROS, causing cytotoxic effects, whereas M2 cells synthetize anti-inflammatory cytokines and stimulate tissue repair [143]. In an in vivo model of ischemic stroke, apelin-13 reduced the expression of pro-inflammatory cytokines and chemokines (IL-1β, TNF-α, macrophage inflammatory protein 1α or MIP-1α, monocyte chemoattractant protein 1 or MCP-1) produced by M1 microglia and increased the expression of the M2-derived anti-inflammatory cytokine IL-10 [144]. The shift of microglial M1 polarization toward the M2 phenotype may be sustained by the blockage of STAT3 signal [145]. The activation of the brain-derived neurotrophic factor (BDNF)-Tyrosine Kinase receptor B (TrkB) signaling pathway, and the inhibition of the NF-κB pathway and endoplasmic reticulum (ER) stress-associated AMPK/TXNIP/NLRP3 inflammasome are other targets of apelin-mediated suppression of neuroinflammation, resulting in improvement of cognitive dysfunction, depressive-like behavior, and early brain injury subarachnoid hemorrhage [142,146,147]. The overactivation of ER stress induced by ROS, with the aim to remove the damaged elements, induces calcium release and reinforces oxidative stress, which promote further microglia activation and leukocyte infiltration into the brain, which subsequently trap in a vicious circle to exacerbate brain injury after stroke [148,149]. In this view, apelin-13 activates AMPK and degradation of TXNIP, which suppresses the overactivation of ER stress and reduces the level of NLRP3 [150]. Excitotoxicity is a complex process of neuronal sufferance and death triggered by the excessive levels of neurotransmitters, which result in a pathologic stimulation of specific receptors. Glutamate neurotoxicity (GNT) is a condition characterized by time-dependent damage of several cell components driven by a massive cell influx of calcium ions and activation of enzymes, including phospholipases, endonucleases, and proteases such as calpain [151,152]. Among the neuroprotective effects of the apelinergic system, the inhibition of excitotoxicity by the activation of pro-survival pathways (i.e., PI3K/Akt and PKC/ERK1/2) and the regulation of N-Methyl-D-aspartic acid (NMDA) receptor activity [153,154,155,156] have also been described. Patients who have undergone thoracic and abdominal aortic surgery are frequently faced with nerve injury induced by spinal cord ischemia, which is driven by ROS-induced neuronal apoptosis, neuroinflammation, and autophagy [157]. The intraperitoneal injection of apelin-13 exerted spinal cord protection and recovery of motor function in rats by suppressing autophagy, oxidative stress, and mitochondrial dysfunction [158]. Recent evidence suggests that GnRH neurons are targets of apelin-associated neuroprotection. APJ signaling pathway activation via either apelin-13 or transient overexpression is able to increase GnRH neurons proliferation after H2O2 exposure and hypoxia, and to stimulate the conversion of G0/G1 to S phase through AKT and ERK-1/2 kinase pathways activation [159]. Therefore, the expression and activation of the apelin/APJ system in GnRH neurons might support a protective mechanism against oxidative stress-induced cell death. Furthermore, the observation of a promoting effect of the apelinergic system on GnRH release in embryonic stem cell-derived GnRH neurons supports the hypothesis of its pro-differentiating role during developmental stages [159]. The antioxidative stress effects of apelin/APJ prompted the research to evaluate its potential correlation with neurodegenerative diseases. Alzheimer’s disease (AD) is the most prevalent form of dementia in the elderly, characterized by intracellular neurofibrillary tangles (NFTs) and extracellular amyloid beta (Aβ) protein deposits that contribute to senile plaques and progressive neurodegeneration [160]. The neuronal loss that appears in the cerebral cortex and in the hippocampus as a consequence of mitochondrial dysfunction and ROS production is an early event in AD and anticipates senile plaques appearance [161,162]. By activating glycogen synthase kinase-3 (GSK-3) and c-Jun N-terminal kinase (JNK)/p38MAPK, oxidative stress induces Tau phosphorylation and beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) expression, and therefore promotes the production of NFTs and Aβ [163,164,165]. Moreover, dysregulation of intracellular calcium exerts a crucial role in the regulation of familial Alzheimer’s proteins (PSEN1 and PSEN2) and Aβ, which results in altered calcium signaling, loss of synapses, and memory impairment [166]. In this scenario, serum apelin-13 has been shown to be lower in AD patients compared to control subjects [167] and its exogenous administration attenuates Aβ-induced memory deficit in Aβ-treated animals [168]. Subsequent molecular studies revealed that the apelinergic system participates in the pathophysiology of AD via regulating Tau and Aβ [146]. Again, the intracellular mechanisms involved in this complex regulation are multiple: (i) activation of PI3K/AKT phosphorylates and inactivates GSK3β, thus suppressing Tau hyperphosphorylation and Aβ accumulation [169]; (ii) inhibition of Aβ-induced autophagy through mTOR signaling pathway [168]; (iii) inhibition of the synthesis of inflammatory mediators, especially TNF-α and IL-1β [170]; (iv) improvement of cell survival and inhibition of neuronal apoptosis through reduction of cytochrome c, increase of caspase-3, and suppression of intracellular calcium release [170,171]; (v) modulation of excitotoxicity [153]. The effects of the apelinergic system on multiple mechanisms involved in AD pathogenesis make apelin a potential therapeutic agent in AD. In Parkinson’s Disease (PD), the progressive loss of dopaminergic neurons in the substantia nigra is secondary to the accumulation of misfolded α-synuclein (α-Syn) in cytoplasmic inclusions named Lewy bodies [172,173]. Dysfunction of parkin, a key part of a multiprotein E3 ubiquitin ligase complex which destroys malformed proteins in neurons, is associated with the pathogenesis of PD [174], which is sustained by oxidative stress, microglia activation, and excessive neuroinflammation [175]. The dysregulation of PI3K/Akt and MAPKs cascades is implicated in the imbalance between cellular anti-apoptotic and pro-apoptotic pathways [175]. As in AD, apelin/APJ axis activation was linked to inhibition of apoptosis and dopaminergic neuronal loss, activation of antioxidants and autophagy, prevention of excessive neuroinflammation, suppression of endoplasmic reticulum stress, and glutamate-induced excitotoxicity. In in vitro models of SH-SY5Y cells, apelin-13 pre-treatment preserved the mitochondrial membrane potential, inhibited the release of cytochrome c and cleaved-caspase 3, and reduced ROS production, thus improving cell viability via PI3K-induced Akt activation [8,22]. AMPK/mTOR-dependent activation of autophagy [22] and ERK1/2-mediated attenuation of ER stress [176] contribute to apelin-13 protection against dopaminergic neurodegeneration. Downregulation of ROS and prevention of SH-SY5Y apoptosis was also described for apelin-36 [120]. In agreement with in vitro observations, different in vivo studies confirmed the neuroprotective role of apelin isoforms. Apelin-36 was able to prevent dopamine depletion in the striatum, at least partially via improving antioxidant cellular mechanisms (including SOD and glutathione) and downregulating inducible NOS and nitrated α-Syn expression [120], whereas apelin-13 markedly improved cognitive impairments in 6-OHDA-treated animals [177]. High levels of oxidative stress and mitochondrial dysfunction are key regulators of bone marrow mesenchymal stem cells (BMSCs) survival and bone formation [178]. ROS overproduction associated with aging and estrogen deficiency determines the establishment of a “pro-osteoporotic” microenvironment, which alters the commitment of BMSCs and shifts their differentiation from the osteogenic to the adipogenic line [179]. Furthermore, intracellular ROS accumulation promotes BMSCs apoptosis [180,181], induces loss of function and apoptosis in osteoblasts [182], and increases osteoclastic bone resorption [183], thus contributing to the development of osteoporosis. Upon mitochondrial damage, mitophagy (a unique form of autophagy) selectively removes damaged mitochondria and prevents their accumulation and oxidative stress aggravation [184]. Hence, its activation in BMSCs contributes to promoting osteogenic function at the expense of adipogenic commitment [185,186,187,188,189,190]. As expected, based on the essential role of adipokines in bone homeostasis, the apelin/APJ system is a potential therapeutic tool in the treatment of osteoporosis. Endogenous apelin is highly expressed during osteogenesis in human BMSCs [191], whereas both apelin and APJ are downregulated in distal femurs of ovariectomy-induced osteoporotic rats [192]. Accordingly, serum apelin-13 in osteoporotic patients was significantly lower than in osteopenia and normal subjects [193]. Molecular and cellular studies demonstrated that apelin is able to stimulate proliferation and to suppress apoptosis of the osteoblastic cell line MC3T3-E1 [194] and to prevent mitochondrial ROS accumulation [195] and mitophagy [192] in BMSCs via the AMPK pathway [196]. Cisplatin, a broad-spectrum chemotherapeutic drug which affects DNA replication and inhibits cell division, is burdened by cardio- and ototoxicity [197,198]. Oxidative stress-dependent apoptosis of cardiomyocytes, which are limitedly able to regenerate, results in irreversible cisplatin-induced cardiomyopathy [199,200]. Oxidation resistance is recognized as a key cellular event in the protective effects of apelin-13 in cisplatin-exposed cardiomyocytes, where it efficaciously blocks the mitochondrial apoptosis pathway by inhibiting ROS-mediated DNA damage and p53 phosphorylation and regulating MAPKs and AKT pathways [201]. In the cochlea, excessive ROS production and mitochondrial dysfunction induced by cisplatin are key contributors of cochlear hair cells (HCs) [202,203,204]. Downregulation of apelin expression has been related to cisplatin-induced damage to HCs, and exogenous apelin’s otoprotective effect against cisplatin-induced injury is closely associated with its ability to inhibit ROS production and mitochondrial dysfunction, which are known to potentiate cisplatin-induced apoptosis, via deregulation of JNK signaling [205]. Most recently, apelin-13 administration was demonstrated to reduce nephrotoxicity induced by cisplatin by triggering oxidative stress and inflammation [206]. Bupivacaine is a commonly used local anesthetic which may cause cardiotoxicity via inhibition of PI3K/AKT signaling [207], respiratory chain complexes I, III, and IV [208], and carnitine palmitoyl transferase [209]. As a result, cardiac energy metabolism is altered, and cardiac arrest may occur. In a rat model, apelin-13 treatment reduced bupivacaine-induced oxidative stress, attenuated mitochondrial morphological change and DNA damage, and enhanced mitochondrial energy metabolism through modulation of AMPK cascade, ultimately reversing bupivacaine-induced cardiotoxicity [210]. Cancer cells show a great ability to adapt their functions to perturbation of cellular homeostasis, particularly the imbalanced redox status secondary to local hypoxia and high metabolism. The theory of ROS rheostat predicts a fine regulation of ROS production and scavenging pathways to potentiate the antioxidant capacity of neoplastic cells and allow oxidative stress levels compatible with intracellular activities, even if higher than in normal cells [211]. Accordingly, an increased expression of ROS scavengers and low oxidative stress levels were described as crucial for the survival of pre-neoplastic foci in breast and liver cancer stem cells [212,213]. Indeed, oxidative stress is involved in the regulation of several cell functions, which are deregulated in cancer (i.e., cell growth, excitability, cytoskeleton remodeling and migration, autophagy, exocytosis and endocytosis, hormone signaling, necrosis, and apoptosis) [214,215], in the promotion of genomic instability and/or transcriptional errors [216], and in the activation of pro-survival and pro-metastatic pathways [215]. Consequently, the three steps of carcinogenesis (initiation, promotion, progression), local invasiveness and metastatization, and the resistance to treatment are strongly conditioned by the imbalance between ROS and antioxidant production [217]. As strong inducers of ROS generation, chemotherapy and radiotherapy are often unable to definitivly cure cancer: antineoplastic drugs and radiations may eliminate the bulk of cancer cells, but the upregulation of antioxidants in the presence of high ROS levels and ROS-dependent accumulation of DNA mutations are mechanisms that spare cancer stem cells and lead to therapeutic failure [211]. In this very complex scenario, antioxidant inhibitors (e.g., glutathione, HSP90, thioredoxin, enzyme poly-ADP-ribose polymerase or PARP) are considered a promising therapeutic tool in cancer treatment in association with radiotherapy or chemotherapy [211]. In the last 15 years, the role of the apelinergic system in tumorigenesis and cancer progression emerged from several studies and it has been proposed as a novel therapeutic target for different malignant tumors [218]. The apelin/APJ axis is upregulated in glioblastoma, esophageal squamous cell carcinoma, cholangiocarcinoma, and lymphoma, and it has been associated with carcinogenesis [218,219,220,221]. Furthermore, serum apelin levels were correlated with shorter survival, higher incidence of cancer recurrence and resistance to anticancer drugs in some human solid tumors, such as gastric cancer, lung adenocarcinoma, and breast cancer [222]. Hypoxia caused by the hypermorphosis of tumor cells was shown to promote apelin expression [223] via increased ROS-dependent hypoxia inducible factors (HIFs) activation [224], even in cancer stem cells [225]. The promoting effect of apelin/APJ in oxidative stress-associated cancer proliferation was reported in gastric adenocarcinoma cells [160] and melanoma [219], where apelin stimulated cancer cells survival and accelerated tumor growth in addition to allowing intratumoral lymphatic capillary and lymphnode metastatization. In several cancers, apelin may also protect cancer cells from apoptosis [226,227] and may play a role in mediating differentiation of mesenchymal stem cells into cancer stem cells, whose self-renewal is facilitated by activating signaling pathways such as wnt/β-catenin and Jagged/Notch [222]. In breast cancer, increased apelin levels were found to be an independent predictor of HER-2/neu expression and breast cancer phenotype, which accounts for 30% of breast carcinomas and is associated with a more aggressive tumor behavior [228]. The role of apelin/APJ signaling in angiogenesis is also well recognized in different cancers [222]. Growing evidence has suggested that apelin induces the maturation of tumor blood capillaries [229] and stimulates the proliferation of smooth muscle cells by modifying cyclin D1 expression and favoring the progression of cell cycle [230]. The apelin/APJ system may exert opposite effects on oxidative stress-mediated processes in different tissues and pathologic conditions (Table 1) by promoting prooxidant or antioxidant mechanisms (Figure 2). These contradictory functions, which can be explained by the existence of multiple isoforms of apelin, the activation of different APJ-coupled G proteins and signaling pathways, and context-dependent APJ trafficking, make the apelinergic axis a double-edged sword in regulating oxidative stress-associated diseases. In this view, a full comprehension of the complex role of apelin/APJ in ROS-related physiologic and pathologic processes is crucial, as well as to identify innovative therapeutic tools based on APJ inhibition or activation.

PMC10003083

Chiara Della Peruta,Biliana Lozanoska-Ochser,Alessandra Renzini,Viviana Moresi,Carles Sanchez Riera,Marina Bouché,Dario Coletti

Sex Differences in Inflammation and Muscle Wasting in Aging and Disease

28-02-2023

sarcopenia,aging,bed rest,microgravity,cachexia,inflammation,sex differences

Only in recent years, thanks to a precision medicine-based approach, have treatments tailored to the sex of each patient emerged in clinical trials. In this regard, both striated muscle tissues present significant differences between the two sexes, which may have important consequences for diagnosis and therapy in aging and chronic illness. In fact, preservation of muscle mass in disease conditions correlates with survival; however, sex should be considered when protocols for the maintenance of muscle mass are designed. One obvious difference is that men have more muscle than women. Moreover, the two sexes differ in inflammation parameters, particularly in response to infection and disease. Therefore, unsurprisingly, men and women respond differently to therapies. In this review, we present an up-to-date overview on what is known about sex differences in skeletal muscle physiology and disfunction, such as disuse atrophy, age-related sarcopenia, and cachexia. In addition, we summarize sex differences in inflammation which may underly the aforementioned conditions because pro-inflammatory cytokines deeply affect muscle homeostasis. The comparison of these three conditions and their sex-related bases is interesting because different forms of muscle atrophy share common mechanisms; for instance, those responsible for protein dismantling are similar although differing in terms of kinetics, severity, and regulatory mechanisms. In pre-clinical research, exploring sexual dimorphism in disease conditions could highlight new efficacious treatments or recommend implementation of an existing one. Any protective factors discovered in one sex could be exploited to achieve lower morbidity, reduce the severity of the disease, or avoid mortality in the opposite sex. Thus, the understanding of sex-dependent responses to different forms of muscle atrophy and inflammation is of pivotal importance to design innovative, tailored, and efficient interventions.

Sex Differences in Inflammation and Muscle Wasting in Aging and Disease Only in recent years, thanks to a precision medicine-based approach, have treatments tailored to the sex of each patient emerged in clinical trials. In this regard, both striated muscle tissues present significant differences between the two sexes, which may have important consequences for diagnosis and therapy in aging and chronic illness. In fact, preservation of muscle mass in disease conditions correlates with survival; however, sex should be considered when protocols for the maintenance of muscle mass are designed. One obvious difference is that men have more muscle than women. Moreover, the two sexes differ in inflammation parameters, particularly in response to infection and disease. Therefore, unsurprisingly, men and women respond differently to therapies. In this review, we present an up-to-date overview on what is known about sex differences in skeletal muscle physiology and disfunction, such as disuse atrophy, age-related sarcopenia, and cachexia. In addition, we summarize sex differences in inflammation which may underly the aforementioned conditions because pro-inflammatory cytokines deeply affect muscle homeostasis. The comparison of these three conditions and their sex-related bases is interesting because different forms of muscle atrophy share common mechanisms; for instance, those responsible for protein dismantling are similar although differing in terms of kinetics, severity, and regulatory mechanisms. In pre-clinical research, exploring sexual dimorphism in disease conditions could highlight new efficacious treatments or recommend implementation of an existing one. Any protective factors discovered in one sex could be exploited to achieve lower morbidity, reduce the severity of the disease, or avoid mortality in the opposite sex. Thus, the understanding of sex-dependent responses to different forms of muscle atrophy and inflammation is of pivotal importance to design innovative, tailored, and efficient interventions. In medicine and in clinical practice, sex differences comprise sex-specific and sex-related diseases, i.e., disease states exclusively or prevalently occurring in people of one sex. Obvious examples of sex-related diseases are genetic diseases linked to sexual chromosomes [1,2,3]. In addition, an impressive list of pathologies includes diseases that display different outcomes in the two sexes, ranging from depression and epilepsy [4,5] to autoimmune diseases [6], and also ranging from myopathies [7] to organ failure or dysfunction [8,9,10]. Many illnesses are characterized by sex-specific differences in severity [11], natural history [12], or disease mechanisms [13]. Only in recent years, thanks to a precision medicine approach, have treatments tailored to the sex of each patient emerged in clinical trials [14]. As an example, the treatment with the common immunosuppressant rapamycin in mice has sex-specific effects, such as extending the life-span in female mice more than in male mice, whereas the combination with the anti-hyperglycemic drug metformin levels these differences [15]. Indeed, finding sex differences in responses to disease or treatment may lead to implemented or totally new treatments [16,17,18,19]. In this review, we focus on sex differences in skeletal muscle. Indeed, significant differences between the two sexes concern both sexes’ striated muscle tissues with important consequences for diagnosis and therapy [20,21]. However, the preference given to the musculature, which prominently characterizes sexual dimorphism, is based on the fact that the amount of lean mass is directly associated with survival in both healthy and disease conditions [22]. In this review we analyze the most significant papers reporting on sex differences in skeletal muscle physiological conditions as well as in three different pathological states characterized by marked sarcopenia and muscle dysfunction: disuse atrophy due to immobilization or microgravity [23], age-related sarcopenia [24], and muscle wasting in cachexia [25,26]. We also discuss sex differences in inflammation which may underly the conditions above; indeed, pro-inflammatory cytokines deeply affect muscle homeostasis. The rationale of comparing these three conditions is based on the fact that different forms of muscle atrophy share common mechanisms—for instance, those responsible for protein dismantling [27]—although differing in terms of kinetics, severity, and regulatory mechanisms [28,29]. Whether these differences can arise differently on a sex-related basis is of particular interest for a precision medicine-based approach. Men have a remarkably different muscle phenotype compared to females, besides having greater muscle mass tout court. The major differences between the two sexes in muscle metabolism and homeostasis were extensively reviewed by Rosa-Caldwell and Greene [30]. In both rodents and humans, sex differences are observed in muscle fiber type, capillarity, and transcriptomes [31]. Indeed, glycolytic fibers are more abundant in men than in women [32], which has a direct consequence on the glucose metabolism [33] and respiratory capacity [34] of the musculature. This difference could account for the differential sensitivity to the diverse forms of muscle atrophy among sexes. Indeed, the fact that cachexia affects glycolytic fibers to a greater extent than oxidative ones [35], whereas disuse muscle atrophy affects predominantly oxidative fibers [36], is consistent with the fact that cachexia is more severe in men than in women [37] and that the opposite is observed in disuse muscle atrophy [38]. The mechanisms underpinning sex differences in fiber type composition remain to be determined: indeed, although the expression levels of several genes related to muscle fiber type phenotype (such as myosin heavy chain I, MyHC, and peroxisome proliferator-activated receptor delta, PPARδ) are higher in women compared to men, there are no significant sex-based differences in the levels of the corresponding proteins [39]. However, higher mitochondria biogenesis and content was reported in female muscle compared to male muscle [40], which corelates with the higher number of oxidative fibers in females and with the prominent role of fat oxidation to produce adenosine triphosphate (ATP) [41]. Although it is recognized that women differ from men in their mitochondria features and activity, both in health and in disease [42], it is not clear how these differences may affect overall phenotypic and clinical outcomes [43]. Indeed, no differences in the respiration of gastrocnemius mitochondria between men and women have been observed [44]. Moreover, sex does not influence the expression of the creatine transporter or the content of creatine in the human skeletal muscle [45], which suggests that the major source of ATP for immediate use is equally available in the muscle tissue of both sexes. Sex differences were also observed for lipid [46] and protein [47] metabolism and turnover. Different patterns of proteome regulation, including proteins involved in muscle contraction and metabolism as well as in detoxification and antioxidant systems, were observed in rats between sexes [48]. In addition, human women have a higher protein turnover rate than men at all ages considered [49]. As expected, these differences in protein turnover are accounted for by hormones [50], which is reported in detail in this review. Nonetheless, the mechanisms underlying these differences between female and male muscles must be brought to light. Indeed, a major player in the balance of protein synthesis is mTOR (mammalian Target of Rapamycin), which, surprisingly, is similarly activated in the two sexes in response to well-known anabolic stimuli, such as exercise and food intake [51,52], with notable exceptions [53]. Satellite cells (SC) are important players in muscle regeneration following acute or chronic injury [54,55,56,57,58]. In addition to fiber hypertrophy, SC contribute to muscle growth in early postnatal life and following muscle damage due to exercise [59,60]. Overall, men have more SC and show greater SC proliferation compared to women [61,62], which is likely linked to the different availability of humoral factors [63]. Interestingly, sex-based differences in SC content are specific to type II fibers without any correlation with fiber size [64]. It is not surprising, then, that skeletal muscle regeneration exhibits sex differences in mice [65]. Sexually dimorphic growth is attributed to the growth hormone (GH)/insulin-like growth factor 1 (IGF1) axis. In women, the expressions of growth factor receptor-bound 10 (GRB10), which is inhibitory for IGF-1 signaling, and activin receptor IIB (ActR-IIB), which mediates a pathway leading to muscle atrophy, are higher than in men [66]. The expression and activity of some myokines appear to be different among sexes. As an example, the brain-derived neurotrophic factor (BDNF), a muscle-generated myokine that controls metabolic reprograming upon fasting in a similar manner as physical exercise, displays sexual dimorphism [67,68]. In addition, the effects of interleukin 6 (IL-6) and myostatin, whose expressions are influenced by fasting, are fiber type-dependent and sex-dependent [69]; IL-6 plays different roles in muscle metabolism in female and male mice [70], and the effects of myostatin on muscle tissue are dose-, sex-, and muscle type-dependent [71]. GH regulates the abundance of mature myostatin by acting not only via the activator of transcription 5B (STAT5B) but also via a non- STAT5B pathway to regulate myostatin mRNA expression [72]. This double signaling pathway could explain why, in response to GH, the intracellular signal transducer STAT5B is dispensable, as shown in STAT5B -/- mice [73]. The expressions of other growth factors, such as FGFs, vary not only with the type of skeletal muscle fibers but also according to sex in mice [74], extending the paradigm of sex differences in the autocrine, paracrine, and endocrine control of muscle growth to other factors. All of these findings also show that humoral factors affect muscle mass in a complex and interdependent fashion. Sex-specific involvement of the neurohypophyseal peptides oxytocin (OXT) and vasopressin (AVP) in human behavior is well-established [75]. Less known is the fact that these two hormones can also be considered myokines [76], as they have profound effects on muscle homeostasis and development [77,78,79]. An additional, major endocrine difference between men and women is the axis from the anterior pituitary gland—via gonadotrophs—to sex organs, leading to the production of estrogen and progesterone, which are both associated with muscle growth and health in humans [80,81,82]. The role of estrogens in sexual dimorphism was comprehensively reviewed by McMillin et al. [83]. Estrogens (produced by granulosa and Sertoli cells in female and male individuals, respectively) vary in their circulating concentrations during the menstrual cycle in humans or the estrous cycle in mice; therefore, their level and activity should be considered when dealing with women of reproductive age. A meta-analysis addressing the effects of estradiol-based hormone replacement therapy on muscle mass clearly indicates that estradiol is beneficial for muscle maintenance [84]. On the other hand, androgens are chiefly responsible for the male phenotype [85], and circulating testosterone is one of the major factors responsible for sex differences in athletic performance due to the well-known dose–response relationship between its levels and those of muscle mass and strength [86]. Sex hormones appear to be responsible for greater fat oxidation in women during endurance exercise compared to men [87]. Recently, an interplay between female sex hormones and IL18 was reported with important, sex-specific consequences on glucose intolerance and insulin signaling [88]. Based on all of these findings, skeletal muscle growth, metabolism, and homeostasis are sexually dimorphic (Figure 1). This suggests that women and men suffer from sarcopenia to a very different extent, possibly with distinctive mechanisms of disease. In the following paragraphs, we will highlight the major sexually dimorphic features of muscle atrophy in various conditions. Muscle atrophy is associated with disuse, a condition due to prolonged bed rest or joint immobilization, resulting in the loss of skeletal muscle mass [43,89]. Similar to bed rest, the unloading condition due to microgravity, as in space flights, has multiple consequences, including a decrease in muscle mass [90]. Although disuse-induced muscle atrophy occurs in both men and women, many differences were observed between the sexes in both humans and animal models. Women suffer from greater muscle loss in intensive care units [38] and experience a higher risk of mortality compared to men [91]. Interestingly, a greater loss of knee extensor muscle strength (KES), despite a similar extent of atrophy, was observed in women compared to men following immobilization-induced disuse [92]. Conversely, following arm suspension, men displayed a significant decrease in the volume of flexor muscle that was not observed in women [93]. In another study, following hip fracture, men experienced a higher prevalence of sarcopenia than women [94]. Lastly, the mean thickness of the rectus femoris, although significantly different between male and female patients before surgery for femoral fractures, reached the same value in both sexes after a traction period of a few days [95]. Interestingly, patients of the two sexes may also differ in recovery capacity: men perform better than women after cast removal, as women require a more intense rehabilitation program [96]. During space flights, men and women show sex-specific adaptations with differences in immunity and metabolism, including compounds important for bone and muscle homeostasis and function [97]. Muscle atrophy is also associated with diseases such as osteoarthritis (OA), which is a frequent cause of disability due to lack of or poor joint mobility, ultimately resulting in disuse/reduced use of the muscle [98]. Sexual dimorphism was observed in OA; male patients display higher type IIa muscle fiber power and velocity compared to female patients. At the molecular level, this can be due to the slower kinetics of myosin–actin cross-bridge in women compared to men [99]. In addition, the reduction of subsarcolemmal mitochondria observed in women with OA may also contribute to poorer muscle performance compared to men because mitochondrial fission and remodeling are involved in disuse muscle atrophy [100]. Taken together, these studies suggest that women are more susceptible to disuse muscle atrophy than men and display functional alterations different from men upon atrophying conditions. However, the results can be inconsistent or even entirely different depending on the conditions. For instance, cast immobilization (limited to a few muscles of one arm) in a subject capable to move and use other muscles is not comparable with almost total immobilization due to bed rest for a patient of the same or the opposite sex. A more correct view is probably that features other than sex (muscle type, immobilization length and extent, etc.) interact with sex to trigger muscle atrophy upon immobilization or to unload in various ways and to different extents. It is worth noting that denervation [18,29,101] achieved by various means differs from casting [102], hindlimb suspension [103], or tenotomy [104] insomuch as muscle atrophy occurs in the absence of the neurotrophic affects deriving from innervation (i.e., the maintenance of neuromuscular junctions). Nonetheless, we report here the few studies on sex differences in this condition due to its clinical relevance. By exploiting a novel murine model of mild spinal muscular atrophy, Kothari and coworkers demonstrated that men are slightly more susceptible than women to neuromuscular junction (NMJ) transmission defects and muscle fiber atrophy [105]; similarly, sex differences were observed in a mouse model of amyotrophic lateral sclerosis [106] and in humans with milder types of spinal muscular atrophy [107]. In xenopus, denervation induces muscle fiber atrophy in the muscles of the larynx, whereas androgen treatment induces muscle fiber hypertrophy; no sex differences were observed in fiber size modification due to innervation or androgen treatment but in the control of the number of muscle fibers [108]. Consistently, crush-induced nerve injury negatively affected the isometric contractile capacity of muscle EDL in mice regardless of sex [109]. These interesting, albeit sparse, findings are relevant because, taken together, they suggest that men could be more heavily affected than women following nerve rescission or damages of motor neurons, whereas muscle atrophy is aggravated in women in innervated, unloaded muscles. Because age-related sarcopenia is partially due to a progressive and selective denervation of the fast-twitch fibers, denervation will be further discussed in Section 4, which is dedicated to aging. To address the molecular mechanisms underlying disuse-induced atrophy, several animal models are available, which were reviewed by Musacchia [110]. Disuse muscle atrophy generally encompasses categories such as tenotomy, unloading, immobilization, and denervation. However, all of them are fundamentally unique. Rotator cuff tenotomy-induced muscle atrophy is sex-specific (exacerbated in male mice) and regulated by autophagy independently of Nuclear factor-κB (NF-κB) [104], which we and others have shown controls muscle wasting in other conditions [111,112]. In rats subjected to hindlimb unloading, there is a greater reduction in soleus muscle mass and fiber cross-sectional area (CSA) in women than in men due to a different activation of the FoxO3a/ubiquitin-proteasome pathway [113]. These results were confirmed in mice: upregulation of ubiquitin-ligases expression was observed in women, but not in men, as early as 24–48 h after hindlimb unloading together with the upregulation of Deptor and Redd1, two inhibitors of mTOR Complex 1 (mTORC1) [43]. In a model of hindlimb unloading, damage to mitochondrial functions were also investigated [114,115]: whereas mitochondrial degeneration was evident in male mice before the onset of muscle atrophy, the opposite occurred in women despite massive ROS production followed by degradative pathways and mitophagy [116]. Thus, oxidative stress may play a pivotal role in disuse-induced muscle atrophy [117]. Age-related sarcopenia is a condition characterized by a reduction in muscle mass, strength, and function with increasing age, with a relevant burden on global health and the management of elderly people [118]. The definition of sarcopenia evolved over the last 25 years thanks to discussion groups, such as EWGSOP, giving rising importance to the functional deficit, which is characteristic of sarcopenic muscle, in the diagnosis and management of sarcopenia [119,120,121,122]. Currently, recommendations exist for the treatment of sarcopenia, which include exercise and nutritional supplementation, e.g., vitamin D [25,123]; nonetheless, sex differences remain a neglected aspect for both primary (age-related) and secondary (disease-related) sarcopenia [118]. Indeed, sex differences can influence how men and women respond to aging, as discussed by Anderson et al. [124]. The risk factors for the development of age-related sarcopenia are different for men and women, and they were identified by Hwang and Park [125]. Both men and women manifest loss of skeletal muscle mass and function with increasing age, but men have a greater loss than women, even though this gross difference can be partly explained by the greater initial muscle mass that men have compared to women [126]. However, a different study showed that the quadriceps muscle cross-sectional area decreases with age, especially in women [127]. When assessing age-related strength loss, the abrupt age-related decline measured (KES) occurs earlier in women than men, whereas the corresponding isometric strength loss is similar between sexes [128]. Indeed, the differences in KES are accounted for by sex differences in the kinetics of the muscles contributing to this measurement, i.e., the rectus femoris, quadriceps, etc. [129]. Consistently, single fibers show sex-dependent alterations in size and a decrease in intermyofibrillar mitochondrial size with age, primarily in women [34]. Consistently, the typical slowing of myosin cross-bridge kinetics is particularly evident in elderly women, and this may account for the increased disability and contractile dysfunction of skeletal muscle [130]. Aging is also associated with progressive denervation, a phenomenon that can be reversed by exercise [131]. The effects of aging on the regulation of muscle contraction by neurons were studied [132], but, to our knowledge, most studies have not examined denervation in a sex-stratified manner or addressed the sex-dependent mechanisms underlying this phenomenon. The lower appendicular mass of the skeletal muscle is associated with the increased risk of falls observed among elderly women compared to men [133,134], suggesting that differences in sarcopenia between the two sexes account for additional issues associated with aging, such as risk of morbidities and incidents. Certainly, frailty as a clinical condition, defined as an increased susceptibility to unfavorable health outcomes [135], contributes to aging-associated sarcopenia. Indeed, in the elderly, frailty represents the link between a healthy status and a poor outcome, including death, in people of the same chronological age. Some conflicting data were collected in the last 20 years regarding the sex differences in frailty [136], mainly because of the lack of a consensus in its definition and assessment or due to discrepancies in the study samples’ characteristics or ethnicities. However, by using phenotypic and accumulated deficits as a frailty index, two systematic reviews found the prevalence of frailty to be higher in older women than men [137,138], which was also confirmed in a recent metanalysis [136]. These conclusions are in alignment with, and may contribute to, an overall aging-associated sarcopenia that is particularly evident in elderly women compared to men. During aging, several factors underpinning muscle quality come into play, including muscle composition, aerobic capacity and metabolism, fatty infiltration, insulin resistance, fibrosis, and neural activation [139]. Looking for mechanisms responsible for sarcopenia in a sex-dependent fashion, it was proposed that a decrease in IGF1 contributes to the development of sarcopenia only in women [140]. In rats, soleus and extensor digitorum longus (EDL) muscle to body weight ratios steadily decrease with age in men but not in women up to 26 months of age; these sex-dependent differences were associated with differences in the regulation of IGF-1 downstream effectors, such as protein kinase B (Akt), mTOR, and p70s6k, in the slow-twitch soleus and with the regulation of AMP activated protein kinase (AMPK), Eukaryotic translation initiation factor 4E-binding protein 1 (4EBP1), p70s6k, and rpS6 in the fast-twitch EDL [141]. By contrast, sex-related differences in the serum levels of the other major regulator of muscle mass, myostatin, with aging is unclear, and further investigations are needed. In men, serum levels of myostatin slightly increase with age up to around 57 years and then decrease [142], and low serum levels of myostatin were associated with low skeletal muscle mass in older adult men, but not in women. According to these findings, serum levels of myostatin cannot be used to diagnose sarcopenia or to monitor how sarcopenic muscles respond to treatments [143]. On the other hand, a different study showed that serum concentrations of myostatin and myostatin-interacting proteins do not differ between young and sarcopenic elderly men [144]. In addition, a strong negative association between circulating myostatin, follistatin, and muscle power in women but not in men was described [145]. The decrease of sex hormones that occurs with increasing age was also proposed to be responsible for sarcopenia. Indeed, the loss of skeletal muscle associated with the perimenopausal stage may be potentially related to increased levels in FSH [146]. In parallel, the deficit of hormones, such as testosterone and 17 β estradiol, associated with aging would be the cause of the altered activation of SC, which are critical for muscle repair and regeneration processes [147]. Malnutrition also plays an important role in muscle homeostasis, and because it is often associated with aging [148], it might be responsible for age-related sarcopenia [149]. Malnutrition leads to an increased risk of sarcopenia in women [140]. In addition, low levels of vitamin D are associated with muscle loss in elderly Chinese individuals [150] and lower appendicular skeletal muscle mass index scores in Korean women, for whom it is also associated with a greater proportion of hypovitaminosis [151] that, again, highlights the importance of vitamin D balance to counteract sarcopenia associated with aging. Cachexia is a wasting syndrome associated with chronic illnesses, including cancer, and characterized by weight loss and skeletal muscle wasting [152]. The consensus definition of cancer cachexia [153] boosted the recognition of its clinical relevance [154]. The prevalence of cachexia is very high (50–80%) in advanced malignant cancer [155]. Due to severe muscle wasting, cancer patients experience weakness and fatigue, which significantly lower their quality of life [26]. The onset of cachexia has a predictive value of poor survival and response to therapy [156], and it affects 20% of cancer patients [157]. Although the mechanisms of cachexia receive increasing attention, sex differences in this syndrome are far less appreciated. Biological differences between men and women may account for different responses to cachexia at multiple levels: susceptibility, progression, and response to treatment [158]. The diagnostic and prognostic assessment of cachexia relies on both the body mass index (BMI) and the rate of ongoing weight loss [153,159]. The fact that men and women have different BMI immediately suggests that the susceptibility to cachexia and its severity are different between the two sexes. Moreover, men and women differ in the relative amount of fiber types, with women generally having mitochondria-enriched, more oxidative muscles. This fact results in an intrinsic higher respiratory capacity in mitochondria from women with respect to men [42,160] as well as differences in the metabolism of malonyl-CoA [161], which may account for the sex differences in cancer cachexia. Two studies on hundreds of cancer patients revealed that men showed muscle wasting two times more frequently than women [162,163]. Quite consistently, sexual dimorphism was observed in cachexia, including different decreases of muscle fiber cross-sectional area, expressions of atrogenes (Foxo, Ub-ligases, etc.), or expressions of genes responsible for muscle growth (AKT1, MSTN, etc.), apoptosis (CASP9), and inflammation (TNF and STAT3) [164]. All of these findings result in a greater reduction of force in men than women [37]. Among patients with lymphoma, both progression-free survival and overall survival were decreased in men with sarcopenia and not significantly affected in sarcopenic women [165], confirming the importance of muscle wasting for prognosis. Consistent with the clinical observations described previously, the mechanisms underlying cachexia appear to be different for the two sexes. As a caveat, it is worth noting that, although they confirm the existence of sex differences, animal models do not always mirror the prevalent human condition in cancer cachexia. Indeed, in a tumor-bearing mouse model, female mice developed body and limb muscle weight loss at early stages of cachexia but maintained their protein amounts and specific force, whereas the opposite was observed in male mice [166]. Alterations of mitochondria were widely reported in cachexia, suggesting a new avenue of investigation [167,168]. Nonetheless, no studies so far have been dedicated to identifying sex differences regarding mitochondria’s role in cachexia. Similarly, the role of microRNAs in cachexia is a growing field of investigation [169]; however, the characterization of their differential modulation in the two sexes during cachexia is still missing today. More significant progress was done on sexual dimorphism related to humoral factors as triggers of muscle atrophy in cachexia. The ligands of the activin receptor IIB (ActR-IIB), such as myostatin, activin, and other members of the TGFβ superfamily, were identified as major players in muscle wasting and proposed as therapeutic targets [170]. In pancreatic ductal adenocarcinoma patients, activin is a preferential driver of muscle wasting in men [171]. Altered levels of GDF15 associated with aging in humans—higher in older men than in age-matching women [172]—were proposed as causative of both sarcopenia and the low physical performance of the muscle [173,174]. Therefore, GDF15 is now heavily investigated in cachexia because blocking GDF15 signaling may have the potential to counteract cachexia [175]. However, to the best of our knowledge, the impact of sex on GDF15’s effects have not been carefully investigated yet. Whereas IL-6 levels inversely correlate with BMI in cancer patients [176], the samples were not stratified according to the sex of the patient. However, in animal models, female animals are more resistant to high levels of pro-inflammatory cytokines, such as IL-6 [177], which is probably due to a reduced catabolic response in muscle tissue [178]; in addition, a sex-dependent genetic predisposition to produce high levels of IL-6 exists due to polymorphism in the promoter of this gene [179]. The role of sex hormones was addressed in animal models of cancer, revealing that cachexia is associated with the cessation of estrous cycling [180]. The expression of estrogen receptors in muscle cells is not clear due to conflicting results [83], and additional research is required to fully elucidate the cellular and molecular mechanisms underlying 17-β estradiol-mediated effects. However, the effort will be rewarding because 17-β estradiol deficiency is shared by several conditions of skeletal muscle wasting, such as disuse, injury, cachexia, and sarcopenia, and any progress in this query will lead to applications for multiple conditions. There is now ample evidence that sex is an important determinant of the immune response in the context of inflammation in various disease settings, including infection, autoimmunity, and cancer, and that sex differences strongly influence disease symptoms’ severity and mortality. Existing epidemiological data reveal a critical role for sex differences in the immune response against viral, self, and tumor antigens, with women generally showing more robust innate and adaptive immune responses [181,182,183]. These differences are largely driven by differences in sex chromosome gene expression and in circulating levels of sex hormones including estrogens, progesterone, and androgens [181,182,183,184,185]. Estrogen and progesterone receptors are expressed by most immune cells, and 17-β estradiol boosts both cell-mediated and humoral immune responses [184,185], whereas progesterone has anti-inflammatory effects [186]. By contrast, androgens generally dampen the immune response [181,183]. Moreover, a number of genes on the X chromosome code for immune response-related proteins such as Toll-like receptors (TLRs) (in particular TLR7 and TLR8), interleukin 2 receptors (IL2R), and transcriptional factors (such as FOXP3), which regulate the immune response, and therefore, they contribute towards sex differences in the development of inflammatory diseases [187]. Circulating levels of estrogen were associated with more severe symptoms in a mouse model of systemic lupus erythematosus (SLE), and the removal of estrogen improves disease prognosis [188]. On the other hand, lower serum levels of androgens in elderly men is associated with an increased incidence of rheumatoid arthritis (RA) [189]. Although elevated innate and adaptive immunity in women may drive the progression of autoimmune diseases, such as Systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), it is advantageous in anti-tumor responses. Aging is typically associated with a moderately, albeit relevant, increased level of inflammation, even though it is not clear whether the so-called “inflammaging” is a cause or an effect of aging [190]. Some chronic conditions that present as age-associated comorbidities can definitely accelerate aging due to increased inflammation mediated by immune dysfunction [191]. Bed rest induces a small rise in pro-inflammatory cytokines, which can reach a statistically significant increase for specific ones, such as IL-6 [192,193]. Microgravity determines aging-like phenomena mediated by chronic low-grade inflammation as well [194]. On the contrary, systemic inflammation accompanied by increased circulation of proinflammatory cytokines is an important feature of cancer and contributes significantly to loss of muscle mass and the development of cancer cachexia [195]. Based on all of these findings, the changes in levels of pro-inflammatory cytokines seem to be abrupt and much more pronounced in cancer cachexia compared to other forms of muscle atrophy, such as those following unloading/disuse or associated with aging. Interestingly, men respond differently than women to these forms of muscle atrophy. All of the information about the differences between the two sexes and the corresponding references cited in this review are summarized in Table 1. Here we have presented, in a comparative way, sex differences in three forms of sarcopenia (Figure 2). Aging seems to affect men more severely in terms of muscle mass loss, but it affects women more insofar as muscle function is preferably considered. Disuse affects muscle atrophy in women more than men [38], whereas cancer cachexia is the opposite [98,162]. One difference between disuse and cachexia is the absence or presence of a significant degree of inflammation due, in the latter, to tumor–host interactions [196,197]. Inflammatory cells deeply affect SC behavior and muscle homeostasis [198,199] and are promising new targets to treat muscle diseases [200]. Even though inflammation does not necessarily correspond to an increased presence of inflammatory cells in muscle infiltrates [201], pro-inflammatory cytokines directly target striated muscles, triggering muscle wasting [202] and inhibiting muscle regeneration [60,203]. In addition to the cytokines released by the immune system, the levels of circulating myokines are strongly dependent on the amount of muscle mass present, which is overtly different between sexes. Based on the above, we propose that, in addition to obvious differences in hormone and growth factors, differences in myokines and cytokines must be taken into account when considering the mechanisms of differential muscle atrophy observed in the two sexes in different forms of muscle atrophy. The US NIH already requires taking into account sex as a biological variable in preclinical studies [204]. However, we propose a step forward in this direction: comparisons based on the sex of the organism should be systematically planned in both clinical and experimental studies dealing with muscle atrophy from now on. Remarkably, there is an issue even with studies addressing sex differences in a variety of biological disciplines; as beautifully demonstrated by Garcia-Sifuentes and Maney, often when a sex-specific effect is claimed based on experimental data, the authors do not actually statistically test the differences [204]. This often makes it difficult to actually state if and to what extent sex differences exist, and it calls for further investigation on this important aspect of biology. In clinical trials, the study groups are not systemically stratified by the sex of the patients, which is often due to the small size of the cohort studied. Nonetheless, it was already reported that the results may change significantly depending on the sex of the patient. For instance, the treatment with the common immunosuppressant rapamycin has sex-specific effects [15], highlighting the importance of taking into account sex differences for precision medicine. The same is true for physical exercise [205] as an intervention against cancer. The conclusion of a ponderous survey on the effectiveness, acceptability, and safety of exercise for cancer cachexia in adults is that “further high-quality randomized controlled trials are still required to test exercise alone or as part of a multimodal intervention to improve people’s well-being throughout all phases of cancer care”, suggesting that additional clinical and basic studies are needed to implement exercise efficacy [206]. Because men and women respond differently to both endurance and resistance exercise training [207,208]—which seems obvious based on the profound differences in their musculature, which are summarized in the first section of this review—the sex of the patient represents a major variable to be taken into account for future studies. The challenges and opportunities for future research on sex differences have been discussed [209]. In addition, guidelines and methods to test sex differences were recently published [210]. Furthermore, an effort should be made to clarify the role of inflammation in different conditions as opposed to that of reduced mechanical, contraction-mediated stimuli. Indeed, depending on the specific condition, muscle wasting may be due to the inflammatory factors present at high levels in a given disease state plus the secondary sarcopenia due to other factors, likely leading to a positive feedback loop [211]. For instance, in intensive care units (ICU), patients experience high inflammation typical of critical illness combined with bed rest, both contributing to inflammatory disequilibrium; similarly, the elderly may show chronic inflammation combined with reduced activity due to poor muscle performance. To better address the relative contribution of each of these factors to muscle wasting, it will be interesting to compare similar conditions, ideally differing in one variable. For instance, is the amount of muscle wasting in space flights (i.e., a “purely” microgravity condition) the same as in bed rest in an ICU (which is characterized by inflammation induced by injury or a severe disease)? Only in recent years has the importance of personalized medicine, also known as precision medicine, gained momentum [212], and tailored treatments have emerged in clinical trials [14]. In pre-clinical research, exploring sex differences in various disease conditions may be the gateway to successful treatments [16]. For example, any protective factors discovered in one sex could be exploited to lower disease morbidity and severity or avoid mortality in the opposite sex [158]. In particular, the understanding of sex-dependent responses to different forms of muscle atrophy and inflammation is of pivotal importance for the design of innovative, tailored, and efficient interventions.

PMC10003087

Eva Monte-Serrano,Pedro A. Lazo

VRK1 Kinase Activity Modulating Histone H4K16 Acetylation Inhibited by SIRT2 and VRK-IN-1

03-03-2023

VRK1,VRK-IN-1,SIRT2,DNA damage response,histone H4,acetylation,Tip60,KAT5

The accessibility of DNA to different cellular functions requires a dynamic regulation of chromatin organization that is mediated by different epigenetic modifications, which regulate chromatin accessibility and degree of compaction. These epigenetic modifications, particularly the acetylation of histone H4 in lysine 14 (H4K16ac), determine the degree of chromatin accessibility to different nuclear functions, as well as to DNA damage drugs. H4K16ac is regulated by the balance between two alternative histone modifications, acetylation and deacetylation, which are mediated by acetylases and deacetylases. Tip60/KAT5 acetylates, and SIRT2 deacetylates histone H4K16. However, the balance between these two epigenetic enzymes is unknown. VRK1 regulates the level of H4K16 acetylation by activating Tip60. We have shown that the VRK1 and SIRT2 are able to form a stable protein complex. For this work, we used in vitro interaction, pull-down and in vitro kinase assays. In cells, their interaction and colocalization were detected by immunoprecipitation and immunofluorescence. The kinase activity of VRK1 is inhibited by a direct interaction of its N-terminal kinase domain with SIRT2 in vitro. This interaction causes a loss of H4K16ac similarly to the effect of a novel VRK1 inhibitor (VRK-IN-1) or VRK1 depletion. The use of specific SIRT2 inhibitors in lung adenocarcinoma cells induces H4K16ac, contrary to the novel VRK-IN-1 inhibitor, which prevents H4K16ac and a correct DNA damage response. Therefore, the inhibition of SIRT2 can cooperate with VRK1 in the accessibility of drugs to chromatin in response to DNA damage caused by doxorubicin.

VRK1 Kinase Activity Modulating Histone H4K16 Acetylation Inhibited by SIRT2 and VRK-IN-1 The accessibility of DNA to different cellular functions requires a dynamic regulation of chromatin organization that is mediated by different epigenetic modifications, which regulate chromatin accessibility and degree of compaction. These epigenetic modifications, particularly the acetylation of histone H4 in lysine 14 (H4K16ac), determine the degree of chromatin accessibility to different nuclear functions, as well as to DNA damage drugs. H4K16ac is regulated by the balance between two alternative histone modifications, acetylation and deacetylation, which are mediated by acetylases and deacetylases. Tip60/KAT5 acetylates, and SIRT2 deacetylates histone H4K16. However, the balance between these two epigenetic enzymes is unknown. VRK1 regulates the level of H4K16 acetylation by activating Tip60. We have shown that the VRK1 and SIRT2 are able to form a stable protein complex. For this work, we used in vitro interaction, pull-down and in vitro kinase assays. In cells, their interaction and colocalization were detected by immunoprecipitation and immunofluorescence. The kinase activity of VRK1 is inhibited by a direct interaction of its N-terminal kinase domain with SIRT2 in vitro. This interaction causes a loss of H4K16ac similarly to the effect of a novel VRK1 inhibitor (VRK-IN-1) or VRK1 depletion. The use of specific SIRT2 inhibitors in lung adenocarcinoma cells induces H4K16ac, contrary to the novel VRK-IN-1 inhibitor, which prevents H4K16ac and a correct DNA damage response. Therefore, the inhibition of SIRT2 can cooperate with VRK1 in the accessibility of drugs to chromatin in response to DNA damage caused by doxorubicin. Dynamic chromatin relaxation and remodeling are associated with basic nuclear functions, normal or pathological. The epigenetic modification of histones and its patterns determine the roles chromatin remodeling plays. A specific histone epigenetic mark underlying chromatin relaxation is the acetylation of histone H4 in K16 (H4K16ac), which is essential for chromatin protein interactions in different pathways [1]. H4K16ac can facilitate DNA damage because of the DNA accessibility to oxidative stress or other genotoxic agents. Additionally, this epigenetic modification participates in the initial recruitment of sequential DNA repair proteins. H4K16ac is associated with several processes that require a dynamic local relaxation and opening of chromatin, such as gene transcription [2], recombination [3,4] or DNA damage responses [5,6], as well as differentiation and cell death [7], which reflects the complexity of its regulation. The enzymes performing histone epigenetic modifications can be potentially targeted as part of a therapeutic strategy [8,9,10], particularly if they can be used in synthetic lethality strategies [11]. The balance between acetylated and deacetylated H4 in K16 is regulated by the coordination between histone acetyl transferases (HAT/KAT), such as Tip60/KAT5 [12], and histone deacetylases (HDAC), such as SIRT2 [13,14,15]. However, the mechanism by which these two types of histone-modifying epigenetic enzymes and their coordination are regulated is unknown. One potential mechanism is that KAT5 and HDACs, SIRT1 and SIRT2 (sirtuins 1 and 2) are coordinated by members of other enzyme families, such as kinases, or alternatively by specific protein interactions that regulate the balance of local histone acetylation and their functional roles, like transcription, replication or pathological roles, such as DNA damage responses (DDR). In this context, the chromatin kinase VRK1 is a potential coordinating protein that regulates chromatin relaxation and accessibility [16]. Histone deacetylases (HDAC) are dysregulated in many cancer types, and their inhibition is a potential candidate for a novel therapeutic strategy [17,18]. Inhibition of HDAC will cause an accumulation of histone acetylation that is associated with a more relaxed and accessible chromatin to DNA damage. For this reason, the accumulation of this histone mark sensitizes cells to radiotherapy or genotoxic drugs used in cancer treatments [19,20], since its irreversibility can prevent progression of the repair process. SIRT2 is an HDAC that regulates cell cycle progression and genome stability [21]. Similarly, the nuclear and chromatin kinase VRK1 regulates cell cycle progression [22,23] and genome stability [24,25]. Moreover, it has been shown that VRK1 directly interacts and phosphorylates Tip60/KAT5, leading to its stabilization and translocation to chromatin where acetylates H4 in K16 [26,27]. Furthermore, VRK1 also plays several roles in the response to gene transcription [28,29] and DNA damage responses, processes which require a local and dynamic coordination of chromatin reorganization [30,31,32]. For this reason, the levels of H4K16 acetylation regulate chromatin accessibility as a result of the balance between the chromatin kinase VRK1 and SIRT2. Chromatin relaxation is associated with H4K16 acetylation and facilitates the access of proteins participating in DNA damage response to chromatin. SIRT2 (sirtuin 2) and Tip60/KAT5 have opposite roles in histone H4 acetylation, and the balance between these two enzymes determines the acetylation state of genomic regions, and their accessibility to DNA. Initially, the effect of three SIRT2 inhibitors, thiomyristoyl (TM), AGK2 and AK7 that block histone deacetylation, were tested individually on the basal levels of H4K16ac. Individually, each of these inhibitors caused a very significant increase in the levels of H4K16ac in A549 cells (Figure 1A). The opposite effect, a reduction in H4K16ac levels, was detected by the inhibition of Tip60/KAT5 with MG149, which inhibits its acetyltransferase activity (Figure 1B). The treatment of cells with doxorubicin, an intercalating DNA drug, caused an increase in histone H4K16 acetylation due to the activation of Tip60/KAT5 by VRK1 [26,27]. When doxorubicin was combined with any of the three SIRT2 inhibitors, it resulted in a higher accumulation of this histone mark because of the inhibition of SIRT2 deacetylase activity [26,27] (Figure 1C, Supplementary Figure S1). The increase in H4K16ac in response to doxorubicin treatment was impaired by either the inhibition of Tip60 with MG149 or by VRK1 depletion that prevents the activation of Tip60/KAT5 (Supplementary Figure S2) [26,27]. Thus, the three SIRT2 inhibitors (TM, AGK2, AK7) cause a strong increase in H4K16ac, which are even higher than those of doxorubicin treatment by itself. Acetylation of histone H4K16 is reversible. Therefore, it is likely that an unidentified mechanism might regulate the coordination and balance between HDAC and Tip60/KAT5 enzymes, which have opposite activities. In this context, a kinase, such as the chromatin kinase VRK1, is a likely candidate. H4K16 acetylation is mediated by Tip60/KAT5, which is regulated by VRK1 though a specific activating phosphorylation of Tip60 in T158 [26,27]. SIRT1 and SIRT2 deacetylate H4K16ac [13,15]. Therefore, it was studied whether VRK1 and SIRT2 are able to form a stable protein complex. For this aim, we first determined the in vitro interaction between tagged GST-VRK1, and SIRT2-his, using bacterially expressed and purified proteins, which can detect a direct and stable protein interaction. SIRT2 directly and stably interacted with VRK1 in a dose-dependent manner (Figure 2A). Next, to identify the VRK1 region of interaction, several GST-VRK1 constructs spanning different regions of VRK1 were expressed in bacteria, and purified fusion proteins were used in pull-down assays with SIRT2-his as the target (Figure 2B). The common VRK1 region of interaction corresponds to residues 1–262, which comprise the kinase domain, and includes both the ATP binding site and the catalytic site. However, SIRT2 did not interact with the low complexity C-terminal VRK1 regulatory domain (residues 267–396) (Figure 2B). To confirm the VRK1-SIRT2 interaction in vivo, HEK293T cells were transfected with tagged SIRT2-Flag, which was able to interact with the endogenous VRK1 in reciprocal immunoprecipitation experiments (Figure 2C, top panel). The immunoprecipitation of the endogenous VRK1 protein with an antibody targeting its C-terminus [33] confirmed that the VRK1 C-terminus is not involved in the interaction, and thus the N-terminus is available for recognition and interaction with SIRT2-Flag (Figure 2C, center panel). The colocalization of VRK1 and SIRT2 in nuclei was confirmed by immunofluorescence in A549 cells (Supplementary Figure S3). This VRK1-SIRT2 interaction was further confirmed when cells were transfected with both tagged proteins and detected in reciprocal immunoprecipitation experiments (Figure 2D). Furthermore, the VRK1-SIRT2 interaction is independent of the SIRT2-S368 mutation to either Ala or Glu (Figure 2E), a known phosphorylation site of SIRT2 in cell cycle progression [34,35]. Because VRK1 and SIRT2 have opposite roles on the acetylation of histone H4 in K16, it is likely that there is between these two enzyme activities. Therefore, we tested whether, as a result of the VRK1-SIRT2 interaction, the VRK1 activity could be altered, and thus permit the deacetylation of H4K16 mediated by SIRT2. This is a likely possibility since SIRT2 interacts with the catalytic domain of VRK1. For this aim, we performed an initial in vitro experiment with both proteins expressed and purified in bacteria. VRK1 by itself has a strong autophosphorylation activity that was inhibited in the presence of SIRT2 (Figure 3A). Next, we tested different concentrations to detect both the inhibitory effect of SIRT2 on VRK1 autophosphorylation, and on H3 phosphorylation, which is a direct target of VRK1 [24,36,37,38]. SIRT2 inhibited both the VRK1 autophosphorylation as well as the phosphorylation of histone H3 in a dose-dependent manner with an IC50 of 190 nM and 150 nM, respectively (Figure 3B). The levels of H4K16 acetylation are regulated by VRK1 [26,27]. In order to manipulate the activity of VRK1 function, the development of specific inhibitors is necessary. VRK1, because of its structural characteristics, is not inhibited by current inhibitors targeting different kinase families of the human kinome [39,40]. VRK-IN-1 is a novel inhibitor recently developed with a structure based on an aminopyridine scaffold that has a high affinity for VRK1, and to a lesser extent for VRK2 [41,42]. First, we tested the effect of the VRK1-IN-1 inhibitor in an in vitro kinase assay using two of the known protein phosphorylation targets of VRK1, histone H3 [38] and p53 [43,44]. The VRK1-IN-1 inhibitor blocked the specific phosphorylation of histone H3 in Thr3 (Figure 4A) and of p53 in Thr18 (Figure 4B) with an IC50 of 250 and 340 nM, respectively. These data indicated that this novel VRK-IN-1 inhibitor has potential for its pharmacological development and improvement. Most of the endogenous DNA damage is the result of oxidative stress, which is very effectively repaired by OGG1 [45]. In these endogenous oxidative DNA lesions that are not repaired, there is an increase in single-strand breaks, which can be detected by labelling the free 3′-DNA ends in broken strands with TdT using TUNEL assays. VRK1 depletion causes an increase in free DNA-ends [46]. Therefore, we tested whether the VRK-IN-1 inhibitor could have the same effect on the level of DNA damage cause by doxorubicin (Figure 5). A549 cells treated with doxorubicin showed an increase of free DNA-ends, and the VRK-IN-1 inhibitor cause similar level of DNA damage. Moreover, the combination of doxorubicin and VRK-IN-1 caused a significant increment in the levels of free-DNA ends (Figure 5). This result suggested that the inhibition of VRK1 combined with DNA damaging agents can promote tumor cell death. VRK1 controls the acetylation of H4K16 by regulating the translocation of Tip60 from the nucleoplasm to chromatin and activating the Tip60 trans-acetylase activity in non-dividing cells [26,27]. Therefore, we tested the effect of different concentrations of the VRK-IN-1 inhibitor on the endogenous basal levels of H4K16 acetylation. For this aim, serum-deprived A549 cells were incubated in the presence of different concentrations of the VRK-IN-1 inhibitor for twenty-four hours, and the levels of H4K16ac was determined by immunofluorescence and immunoblots. The VRK-IN-1 inhibitor resulted in the loss of H4K16 acetylation (Figure 6). This effect of the VRK-IN1 inhibitor mimics the effect of VRK1 depletion on H4K16 acetylation (Supplementary Figure S1) [26]. The use of VRK1 inhibitors, which should prevent the activation of Tip60 by VRK1 and avoid the recruitment of DNA repair proteins, should cause an increase in the accumulation of DNA damage, by maintaining a local open chromatin organization and impairing DDR progression. Therefore, we studied the effect of the VRK-IN-1 inhibitor to determine its effect on the accumulation of DNA damage induced by doxorubicin, which was determined by the level of H4K16ac reflecting the early response to damage mediated by Tip60, and γH2AX and 53BP1 foci that reflect DNA damage. The VRK-IN1 inhibitor reduced the level of H4K16ac (Figure 7A), which indicates that the activation of Tip60 was impaired, and thus unable to recruit repair proteins. Next, we determined that VRK-IN-1 reduced both the formation of γH2AX and 53BP1 foci induced in response to doxorubicin (Figure 7B), indicating that the activation of the NHEJ repair pathway was defective. The control of chromatin relaxation is necessary to facilitate different processes that require very specific and sequential regulatory mechanisms, which will be adapted to the specific need of a particular chromatin region. These local chromatin relaxations are critical for the correct functioning of the cellular processes requiring a dynamic chromatin remodeling, transcription, replication or DNA repair, in this latter case from DNA damage that locally alters chromatin. However, this relaxation is selective and transient for its specific temporal function. Thus, it requires a very tight regulation, and coordination, of the histones posttranslational modifications that are implicated, as is the case of H4K16 acetylation. H4K16ac is required for the recruitment of different proteins involved in the sequential specific steps in DDR pathways. An excess of H4K16 acetylation or its persistence in time will facilitate the chromatin accessibility to genotoxic agents, and if it is not removed, it might interfere with the progression and recruitment of other proteins in the DNA repair process. Therefore, this H4 epigenetic modification requires a precise regulation of its levels in time and space, which implicates several types of enzymes, including an acetyl transferase, such as Tip60/KAT5, and a histone deacetylase such as SIRT2, or another HDAC member. Moreover, the balance between these two enzyme activities, with opposite effects, requires a coordinator. The most suitable candidate for such coordination is a nuclear kinase, such as VRK1, which is also known as nucleosomal kinase-1 (NHK-1) in Drosophila melanogaster [47]. We have identified a mechanism in which there can be a crosstalk between the two activities, acetylase and deacetylase. VRK1 activates Tip60 that acetylates H4 in K16 [26,27], but when SIRT2 interacts with VRK1, its kinase activity is inhibited, and permits the histone deacetylation mediated by SIRT2. The kinase activity of VRK1 can be manipulated by novel inhibitors, such as VRK-IN-1 [41,42], the first inhibitor in its class, and can inhibit VRK1 kinase activity at nanomolar concentrations, and thus can be the base for future pharmacological development. We have shown that this inhibitor impairs the activity of VRK1 on two of its known substrates in vitro, histone H3 and p53. Additionally, this inhibitor impairs the acetylation of H4K16, and thus DNA repair enzymes cannot be recruited, facilitating the accumulation of DNA damage. In this report we have identified a novel mechanism coordinating the level of H4K16ac. This mechanism (Figure 8) implicates the nuclear VRK1 chromatin kinase [26]. This kinase modulates the activity of the Tip60/KAT5 acetylase as well as that of the SIRT2 histone deacetylase. However, the mechanisms are different depending on the enzyme. VRK1 directly phosphorylates Tip60, leading to its translocation to chromatin and activating its acetylase activity [26,27]. Nevertheless, the switch off is mediated, not by a phosphorylation, but by a direct protein interaction with the SIRT2 deacetylase. When VRK1 interacts with SIRT2, the kinase activity of VRK1 is inhibited, and consequently SIRT2 can perform the deacetylation at the same time that acetylation is suppressed. Functionally, the loss of Tip60/KAT5 activation by VRK1 will result in an impaired recruitment of sensor and repair proteins, while the accumulation of H4K16ac, as a result of using SIRT2 or VRK1 inhibitors, will prevent progression of the DNA repair pathway, because the dynamic regulation is blocked by maintaining H4K16 in an acetylated state. The involvement of three enzymes, VRK1, Tip60/KAT5 and SIRT2, in the regulation of the level of acetylation of H4K16 opens up the possibility of its pharmacological manipulation by their combination, to promote the elimination of tumor cells. The persistence of an open chromatin will facilitate the access to genotoxic agents such as oxidative stress of chemotherapeutic drugs, and these will promote the accumulation of DNA damage and compromise tumor cell viability. An alternative effect, as a consequence of increased genetic damage, is the stimulation of an immunogenic response against new tumor antigens that may contribute to the elimination of tumor cells [48,49]. AGK2, AK7, thiomyristoyl and selisistat were purchased from Selleckchem (Houston, TX, USA); MG149 from Axon MedChem (Groningen, The Netherlands); doxorubicin hydrochloride from Sigma-Aldrich (St. Louis, MO, USA); and VRK-IN1 from MedChemExpress (Monmouth Junction, NJ, USA). Cells were treated following the indicated schemes (Table 1). Plasmid pCEFL-HA-VRK1 was used to express human VRK1 [32,50] and pcDNA3.1-Flag-SIRT1 and pcDNA3.1-Flag-SIRT2 plasmids were used to express human SIRT1 and SIRT2 [13,51]. GeneJET Plasmid Maxiprep kit (Thermo Fisher Scientific, Waltham, MA, USA) was used for plasmid purifications. For in vitro kinase assays, PGEX-4T-VRK1-GST, pGEX-4T-VRK1[K179E]-GST, pGEX-2T-p53[1-84]-GST and pET30a-SIRT2-6xHis plasmids [13,46,50] were used for expression and purification of the fusion proteins expressed in Escherichia coli strain BL21. Protein expressions were induced with IPTG 0.2 M 37 °C for 2 h and bacteria were lysed with lysis buffer (20 mM Tris HCl pH 8.0, NaCl 500 mM, 1% Triton X-100, 0.025% NaN3, 0.2 μg/mL lysozyme and 5 mM DTT) or BC-500 buffer (20 mM Tris pH 8.0, 100 mM NaCl, 10 mM EDTA pH 8.0, 0.1% NP40 and 2% sarkosyl). The resulting GST or His fusion proteins were incubated with Glutathione Sepharose 4B beads (GE Healthcare Systems; Chicago, IL, USA) or NiNTA Agarose beads (Qiagen; Hilden, Germany), respectively. After several washes with the corresponding lysis buffer, the proteins were obtained by elution with glutathione 20 mM or imidazole 50 mM. Purified proteins were aliquoted and stored at −80 °C. The following validated cell lines HEK 293T (CRL-3216), A549 (CCL-185) and U2OS (HTB-96) were obtained from the American Type Culture Collection (ATCC), and were mycoplasma free. Cells were cultured in DMEM (Gibco-Life Technologies Invitrogen; Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS), 2 mM glutamine (L-glutamine) and 1% penicillin-streptomycin (Pen/Strep), all obtained from Gibco-Life Technologies (Waltham, MA, USA). For the purpose of experiments, cells were grown to 80% confluence. Cells were washed with PBS and detached using TrypLE-Express (Gibco-Life Technologies-Invitrogen; Waltham, MA, USA). Serum starvation (DMEM supplemented with 0.5% FBS, 2 mM L-glutamine, 1% Pen/Strep) was performed for 48 h when indicated. Plasmid transfections were performed as previously reported [26]. Briefly, 4–6 µg DNA was diluted in polyethylenimine (PEI; Polysciences; Warrington, PA, USA) reagent and incubated for 30 min. DNA-PEI mix was added by gently pipetting dropwise to the cells, which were assayed 48 h after transfection. Si-RNA was used for depletion of VRK1. The VRK1 sequences targeted by these siRNA from Dharmacon were 5′-CAAGGAACCTGGTGTTGAA-3′ (siVRK1-02), and 5′-GGAAUGGAAAGUAGGAUUA-3′ (siVRK1-03). ON-TARGET plus siControl non-targeting siRNA (siControl) was used as a negative control. Lipotransfectin (Solmeglas; Madrid, Spain) was diluted in Opti-MEM (GIBCO-Life Technologies) according to manufacturer guidelines. siRNA (200 nM) was diluted in Opti-MEM and added to the lipotransfectin-Opti-MEM mix. After 30 min of incubation, the lipotransfectin-Opti-MEM-RNA mix was added by gently pipetting dropwise to the cells. Cells were maintained with antibiotic-free media 72 h after siRNA transfection, as previously reported [52]. All steps used for protein extraction were performed in ice. Cell lysates were prepared by suspending cells in lysis buffer (50 mM Tris HCl pH 8.0, 150 mM NaCl, 1% triton X-100 and 1 mM EDTA) supplemented by phosphatases inhibitors (1 mM sodium fluoride and 1 mM sodium orthovanadate) and proteases inhibitors (1 mM PMSF, 10 mg/mL aprotinin, and 10 mg/mL leupeptin). The suspension was incubated at 4 °C for 15 min followed by centrifugation (16,000× g, 15 min, 4 °C). Histones were isolated by acidic extraction, as previously described [53]. Protein concentration was determined using the BCA protein assay kit (Thermo Fisher Scientific; Waltham, MA, USA). Forty micrograms of protein was used for immunoblots; 5–10 µg of acidic extracts of histones were used for immunoblots. Antibodies used in this study, applications and conditions are listed in Table 2. They were diluted in TBS-T buffer (25 mM Tris HCl pH 8.0, 50 mM NaCl and 2.5 mM KCl, 0.1% Tween-20) or PBS-1% BSA for immunoblots or immunofluorescence assays, respectively. Immunoprecipitations were performed using 0.5–1 mg of protein from cell lysates. Protein extracts were incubated with the corresponding antibody for each experiment for 6–8 h at 4 °C in rotation. Subsequently, 40 µL of Protein G–Agarose Resin 4 Rapid Run (4RRPG, Agarose Bead Technologies; Madrid, Spain) was added to the protein-antibody immune complexes overnight at 4 °C on a rotating wheel5. The immunoprecipitated was collected by centrifugation (500× g, 2 min, 4 °C) and washed three times with lysis buffer [52,55]. Lysates and immunoprecipitates were boiled at 95 °C for 5 min in sample loading buffer (62.5 mM Tris-HCl pH 6.8, 10% glycerol, 2.3% SDS, 0.1% bromophenol blue and 5% β-mercaptoethanol). After separation via SDS-PAGE, proteins were transferred to PVDF Immobilon-FL membranes (0.22 or 0.45 µm pore size; Millipore; Burlington, MA, USA) [26,55]. Membranes were blocked for 1 h at room temperature with 5% nonfat milk or 5% of BSA in TBS-T buffer. Next, membranes were washed 3 times for 10 min each time in TBS-T and incubated with the primary antibody overnight at 4 °C. Next day, after three washes of 10 min in TBS-T buffer, membranes were incubated in the darkness with their corresponding secondary antibodies (Table 3) diluted 1:10,000 in TBS-T for 1 h. Membranes were washed three more times in TBS-T for 10 min. Finally, fluorescence signals were detected using a LI-COR Odyssey Infrared Imaging System (LI-COR Biosciences; Lincoln, NE, USA). Densitometric analysis of Western blots were performed using ImageJ software (version 1.53e). All Western blots were performed in triplicate and correspond to the accompanying immunofluorescence image. Cells were cultured with glass coverslips (Thermo Fisher Scientific; Waltham, MA, USA) in the culture dishes as previously described. After the corresponding times and treatments, cells were fixed with 3% paraformaldehyde (PFA) in PBS for 15 min, and treated with 200 mM glycine solution to eliminate the PFA. Cells were permeabilized with 0.2% triton X-100 for 15 min and blocked with PBS-1% BSA with 0.1% sodium azide for 1 h at room temperature, or overnight at 4 °C [32,56]. Coverslips were consecutively incubated with two primary antibodies for concurrently protein detection. The primary antibodies were incubated between 56 h at room temperature or overnight at 4 °C. Afterwards, cells were washed with PBS 3 times and incubated with the secondary antibodies (Table 3) at 1:1000 dilution for 1 h at room temperature in the dark. All next steps were carried out in darkness. After 3 more washes with PBS, nuclei were stained with DAPI (4′, 6diamidino-2-phenylindole) at 1:1000 dilution for 5 min, followed by three washes with PBS. Coverslips were mounted with a drop of mounting medium (MOWIOL) in microscope slides. Cell Images were captured with a LEICA SP5 DMI-6000B confocal microscope (Leica; Wetzlar, Germany), with the following lasers: Argon (488 nm), DPSS (561 nm) and UV Diode (405 nm). These images were acquired with a 63.0× lens zoomed in 1.5× with a 1024 × 1024 frame and 600 Hz scanning speed. Images were analyzed with ImageJ (version 1.53e) software (https://imagej.nih.gov/ij). These imaging experiments were independently performed three times. Accessible 3′-OH free DNA ends caused by DNA damage were detected by labeling with fluorescein-dUTP by thymidine deoxynucleotidyl transferase (TdT) using the detection kit from Roche-Merck (Darmstadt, Germany) (ref. 11684795910) according to the manufacturer protocol. Cells were fixed, permeabilized and blocked according to the section on immunofluorescence. Pull-down assays were performed to study the interaction between VRK1 and SIRT2, in manner similar to previous studies [57]. For this purpose, purified GSTVRK1 and His-SIRT2 in the amounts indicated in the experiment were used. Proteins were incubated in a buffer containing 20 mM Tris-HCl pH 7.5, 5 mM MgCl2, 0.5 mM DTT and 150 mM KCl in a volume of 25 µL at 37 °C and gentle agitation for 45 min. After that, 40 µL of Glutathione Sepharose 4B beads (GE Healthcare; Chicago, IL, USA), previously equilibrated with the same buffer, were added. The mix was incubated overnight at 4 °C. The pull-down was performed by centrifugation (500× g, 2 min, 4 °C) and the resin was washed in the same pull-down buffer three times. Agarose-immune complexes were resuspended in sample loading buffer and detected by Coomassie Blue staining (3 g/L Coomassie Brilliant Blue R250, 45% methanol, and 10% glacial acetic acid) in the case of purified proteins. Reactions were performed in kinase assay buffer (20 mM Tris-HCl pH 7.5, 5 mM MgCl2, 0.5 mM DTT, and 150 mM KCl) containing 1 µg of GST-VRK1 wildtype or GST-VRK1-K179E (kinase-dead) and the varying amounts of His-SIRT2, GST-p53(1-84) and recombinant human histone H3 [58]. ATP (10 µM) was added to the mix, in the presence of 7.5 µCi of γ-32P when there was not an available commercial phospho-specific antibody. Reactions were performed at 37 °C for 45 min and stopped by the addition of sample loading buffer. Electrophoresis in acrylamide gel was performed following the aforementioned instructions. When a commercial phospho-specific antibody was available, the signal was detected following immunoblots description. In the case of radioactively labeled membranes, radioactive signal was detected using Fuji Medical X-ray films. Afterwards, membranes were blocked in milk for 1 h at room temperature and incubated with the corresponding primary antibody for 2–4 h. Subsequently, membranes were washed 3 times in TBS-T and incubated with secondary antibodies (ECL Anti-Mouse or Rabbit) for 1 h. Right after 3 more washes, blots were developed with the ECL detection system (Solution A: 0.1 M Tris HCl pH 8.5, 0.2 mM coumaric acid, and 1.25 mM Luminol; Solution B: 3% H2O2) after 5 min incubation, using Fuji Medical X-ray films. Graphs and statistical differences were computed using GraphPad Prism 8. Results are presented as dot plots with the median, first and third quartiles and whiskers. After confirming samples did not adjust to a normal distribution (nonparametric distributions) according to a two-tailed Kolmogorov test, a Kruskal–Wallis test was used for two-group comparisons in all experiments. Values of p < 0.05 were considered significant. Values of p < 0.05 were ranked as *: p < 0.05, **: p < 0.01 and ***: p < 0.001. n.s.: non-significant differences. In this work, we have studied the crosstalk between the VRK1 chromatin kinase and the SIRT2 histone deacetylase that regulate the level of H4K16ac, a key modification regulating the accessibility of chromatin. VRK1 promotes the acetylation of H4K16 by activating Tip60, and SIRT2 removes this modification. In order to carry out this role SIRT2 forms as complex with VRK1, inhibiting its activity on Tip60/KAT5, and thus facilitating H4K16 deacetylation. The novel VRK-IN-1 inhibitor facilitates H4 deacetylation and promotes the accumulation of DNA breaks, but prevents the progression of the DNA repair processes. This VRK1 inhibitor can be of use for designing novel synthetic lethality strategies to promote tumor cell death.

PMC10003088

Fulvia Ceccarelli,Francesco Natalucci,Licia Picciariello,Claudia Ciancarella,Giulio Dolcini,Angelica Gattamelata,Cristiano Alessandri,Fabrizio Conti

Application of Machine Learning Models in Systemic Lupus Erythematosus

24-02-2023

Systemic Lupus Erythematosus,artificial intelligence,machine learning models

Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario.

Application of Machine Learning Models in Systemic Lupus Erythematosus Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario. Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease, extremely heterogeneous in terms of immunological features and clinical manifestations (Figure 1A). Thus, this condition could potentially involve any organ and system, leading to different severity degrees and outcomes. Traditionally, it is possible to distinguish more severe disease, including renal and neurological manifestations, from mild/moderate disease, characterized by other manifestations such as skin and joint involvement [1]. This clinical complexity could result in a diagnostic delay, especially evident when the disease begins with rarer manifestations. Data from the literature reported an interval between the appearance of first symptom and diagnosis of about 70 months. Of note, it must be underlined that diagnostic delay, even when it amounts to only 6 months, could lead to severe organ involvement, high flare rates and chronic damage development. This derives certainly from the later introduction of appropriate treatment, together with prolonged treatment of glucocorticoids, widely recognized as the most relevant risk factors for chronic damage progression [2,3]. In this view, the purpose of the classification criteria is to facilitate and to anticipate SLE diagnosis and to allow the identification of homogeneous populations for clinical studies. The classification criteria proposed until now have been summarized in Figure 1B [4,5,6]. The latest EULAR/ACR criteria published in 2019 introduced important innovations. First of all, the presence of an entry criterion, represented by the ANA positivity, is necessary to apply these criteria, underlining the autoimmune pathogenesis of SLE. In addition, a weighted score system has been introduced, with different scores for different clinical and laboratory features. Accordingly, only patients reaching a score higher than 10 could be classified as affected by SLE. The application of these criteria leads to a sensitivity and specificity of 98.0% and 96.4%, respectively in the derivation cohort, and of 96.1% and 93.4%, respectively in the validation cohort [6]. From a pathogenic point of view, a multifactorial etiology has been widely demonstrated for SLE. More than one hundred genetic variants have been associated with disease susceptibility and phenotype. Then, the interplay between genetic background and different environmental factors leads to the activation of an aberrant autoimmune response with the production of several autoantibodies [1,7]. The production of autoantibodies has been described several years before the appearance of clinical manifestations, suggesting a stage of subclinical autoimmunity preceding the disease development [8,9]. SLE is traditionally characterized by a relapsing-remitting course, with the occurrence of disease flare. This evolution could result in the development of irreversible chronic damage, determined by disease activity itself and by the adverse events of treatment, in particular glucocorticoids [10,11]. The application of more appropriate therapeutic approaches, in particular the so-called treat-to-target, could significantly impact the course of the disease. In fact, a better control of disease activity, by reaching remission or a low disease activity state, could determine the reduction of chronic damage progression, with improvement in long-term outcome and survival [12]. In 2019, the latest recommendations have been published, based on a comprehensive management of SLE patients. In fact, it is not only the need to treat the disease itself that has been underlined, but also comorbidities, and the need to educate patients to an appropriate lifestyle, with emphasis on sun protection, vaccination, exercise, and smoking cessation [13]. Concerning the pharmacological approach, the recommendations distinguished mild, moderate and severe manifestations to prescribe more appropriate treatment. Of note, the possibility to use a biological treatment, in particular belimumab, was introduced for the first time in the routine care of SLE patients [13]. In the view of disease complexity, several unmet needs are still present for the diagnosis and the management of SLE patients, suggesting the application of innovative tools, such as machine learning models (MLMs). Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence (AI) in patients with SLE from a medical perspective. A literature search was done in PubMed, accessed via the National Library of Medicine PubMed interface (http://www.ncbi.nlm.nih.gov/pubmed, accessed on 1 December 2022). Firstly, PubMed was searched using the term “systemic lupus erythematosus” OR “lupus” in combination with (AND) “machine learning models”. Secondly, the same PubMed search was combined with other terms, such as “artificial intelligence” OR “classification” OR “clustering” OR “regression”. In the last years, AI has generated increasing interest in the field of medical conditions, including rheumatic diseases. In particular MLMs, a subcategory of AI, have been widely applied for different purposes, such as diagnosis, identification of disease phenotypes, prognosis and precision medicine [14]. Differently from the statistical method, MLMs extract knowledge from input data. Indeed, if the statistical models aim at explaining specified or hypothesis-driven relationships, MLMs work to search underlying data connections and make decisions according to the newly discovered associations. Thus, MLMs extrapolate relationships unidentifiable with other statistical techniques that are more suitable to generate new hypotheses [15]. The ideal application of MLMs involves the use of so-called big data, deriving from electronic health records, imaging tools, genetics, and transcriptomic procedures. This could be very interesting in the evaluation of complex chronic conditions, such as rheumatic diseases, characterized by great heterogeneity in clinical and laboratory features, by overtime evolution and by the contribution of multiple factors in disease susceptibility and course [15]. Thus, MLMs could help in predicting disease outcome e treatment response, a challenge in diseases such as SLE, characterized by alternating clinical course and various severity degrees requiring different treatments. The aim of MLMs is the generation of a predictive model, potentially relevant in routine care for the following outcomes: classification, regression or clustering [16,17]. As reported in Figure 2A, different types of data could be used as input to create the MLMs. In particular, it is possible to use clinical/demographic information, laboratory data, results from patient-reported outcomes, data from tissues analysis or imaging tools, response to different treatments, and information about disease activity course or chronic damage development [14,16,17]. The use of medical data in MLMs frequently requires a process of adaptation, in particular they should be translated into a numerical format that could be processed by the AI. Furthermore, it should also be considered the possibility of missing data. Sometimes, a scaling process should be applied to transform existing features into a smaller set of variables [15,18]. Moreover, MLMs perform better when the number of input variables is optimized. Indeed, features selection is a dimensionality technique of reduction that is applied to identify the most appropriate variables to use as input into MLMs algorithm, as all measured variables might not provide information that is necessary for outcome prediction. The features selection could be made by using different modalities, including filter, wrapper and embedded methods [19]. In detail, different types of MLMs are available: to summarize, supervised and unsupervised algorithms can be differentiated according to the labeling of used variables. Thus, a supervised model is constructed to predict known values, whereas an unsupervised model works to predict unknown variables [20,21]. Figure 2B summarizes the different MLMs that could be applied in the supervised and unsupervised modalities [15,20,21]. Of note, the performance of supervised models could be improved by using two independent datasets: the training and the validation dataset. Furthermore, the performance could be assessed by applying different metrics, such as accuracy (the ratio of correct predictions to total predictions), sensitivity (the true positive rate) and specificity (the true negative rate). If the classification problem is binary, these values are often represented by using receiver operating characteristic (ROC) curves. Thus, the area under the ROC curve (AUC) represents the probability that the model can distinguish correct and incorrect outcomes. An AUC value of 1.0 indicates a perfect model performance, whereas a score of 0.5 indicates that the model’s performance is comparable to random chance [22]. For regression analysis, other parameters could be used to assess the model performance: in particular, mean squared error, root mean squared error and the coefficient of determination [23]. Given the availability of different algorithms, it is essential to select the most appropriate MLMs according to the goal (classification, regression, clustering or reduction of dimensionality). Furthermore, the MLMs selection should be based on the available input data, and the comparison between multiple algorithms is recommended in order to identify the model with the greatest performance [24,25]. In the last years several studies have applied MLMs in SLE cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, outcomes and treatment. Table 1 summarizes data about the studies applying MLMs for diagnostic purposes [26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41]. Overall, it is possible to identify three fields of application according to the data input considered in the studies. First of all, moving from the role exerted by the genetic background in disease development, more recent studies applied MLMs in this context [27,28,29,30]. Therefore, MLMs could be applied to select candidate genes able to identify SLE patients, suggesting the possibility to use these inputs as diagnostic biomarkers. Furthermore, other laboratory features have been considered as input for AI models, such as proteomic data deriving from serum, plasma or peripheral blood mononuclear cells (PBMCs) of SLE patients [26,41]. Already in 2009 Huang and colleagues proposed a Decision Trees model, including a panel of four proteins that resulted able to recognize SLE patients [41]. More recently, Li and colleagues, by using Random Forest model, demonstrated a good performance for a six-protein combination model (SLE versus healthy controls, AUC = 0.7; SLE versus rheumatoid arthritis, AUC = 0.815). The AUC increased up to 0.990 when considering the ability of a nine-protein combination in discriminating SLE patients with disease flare from patients with stable disease [26]. In 2021, Matthiensen and colleagues for the first time applied MLMs to assess the diagnostic role of plasma lipidome, showing good sensitivity and specificity in distinguishing SLE from patients with cardiovascular disease and ischemic stroke [32]. In the remaining studies, the ability of MLMs for a diagnostic purpose has been tested by using electronic health data (EHD) or clinical/laboratory disease-related features, frequently as defined by the available classification criteria. Overall, the use of EHD as input demonstrated a good performance of MLMs in identifying SLE patients in terms of AUC values (up to 0.97) [38,39]. The study published by Adamichou and colleagues in 2020 aimed at assessing the accuracy of 2019 EULAR/ACR criteria in SLE diagnosis by using a LASSO-LR model (ref). The inclusion as input of all the features included in the three classification criteria sets (ACR 1997, SLICC 2012, ACR/EULAR 2019) allowed to observe an accuracy for the most recent criteria of 94.8% in identifying SLE patients. In detail, a higher sensitivity was demonstrated for subjects with an early disease, for patients with Lupus Nephritis (LN) and neuropsychiatric SLE (NPSLE), and for patients treated by immunosuppressant drugs or biological agents. Furthermore, the authors were able to develop a predictive score (the so-called SLERPI score): for a score higher than seven, an accuracy of 94.2% was observed [33]. Our group employed different MLMs—in particular the ReliefF algorithm, Logistic Regression, nonlinear Support Vector Machines, and Decision Trees models—to identify the stronger predictors for SLE diagnosis. By enrolling SLE patients and control subjects with miscellaneous rheumatic diseases, relevant to the differential diagnosis, we obtained a good model’s performance, already when only the three highest scoring features were considered (AUC = 0.94). Furthermore, anti-dsDNA positivity, low C3/C4 serum levels and malar/maculopapular rash resulted in the strongest predictor features for classifying a patient as having SLE [34]. Moreover, the application of cluster analysis could be used to identify subsets of patients by integrating clinical features, immunological profiles and molecular pathways. In this context, the study conducted by Guthridge and colleagues in 2020 used different parameters as input, by combining data from plasma, serum and RNA evaluation with clinical and immunological features. Indeed, the application of a cluster analysis allowed to identify different disease clusters in terms of molecular profile, such as expression of interferon, and disease activity, as assessed by SLEDAI-2k [36]. Similarly, Diaz-Gallo and colleagues in 2022 applied an unsupervised cluster analysis by identifying four SLE subgroups, different in terms of the autoantibody profile, HLA-DRB1 alleles, immunological and clinical features [42]. The same model allowed to differentiate SLE patients according to lymphocyte subsets. Indeed, the study conducted by Lu and colleagues identified four clusters (B high, CD4 high, CD8 high and NK high). These clusters differed in terms of clinical manifestations: in fact, the incidence of arthritis was significantly higher in B high cluster, while nephritis was more frequent in CD8 high and NK high clusters. Finally, CD4 high cluster showed SLEDAI-2k values significantly lower compared with the remaining three clusters [43]. In this view, cluster analysis could also differentiate SLE patients according to cytokine profile: as demonstrated by Reynold and colleagues, it is possible to identify three distinct groups of patients, characterized by higher levels of interferon-alpha and B lymphocyte stimulator (group 1), increased CXCL10 and CXCL13 (group 2) or low levels of cytokines (group 3). Furthermore, group 2 had significantly lower serum complement and higher anti-dsDNA antibodies with increased prevalence of arthritis [44]. The majority of the available studies focused on the application of MLMs on SLE cohorts with renal involvement, representing one of the most fearful disease-related manifestations, with possible progress into end-stage renal disease in 20% of patients and then requiring more aggressive treatment [45]. Table 2 summarizes data about these studies [46,47,48,49,50,51,52], the first of which was published in 2011 and focused on the probability of 3-year allograft survival after renal transplantation [46]. By considering different input data, such as previous and current treatments and data about transplantation and comorbidities, the authors applied different models, obtaining a good performance in terms of AUC (up to 0.74 when considering the logistic regression model) [46]. Only one recent study included, as input, gene expression datasets, downloaded from the GEO database. The application of LASSO and SVM-FRE models suggested the possible role as diagnostic biomarkers for the following genetic variants: C1QA (AUC = 0.741), C1QB (AUC = 0.758), MX1 (AUC = 0.865), RORC (AUC = 0.911), CD177 (AUC = 0.855), DEFA4 (AUC = 0.843), HERC5 (AUC = 0.880) [48]. In the remaining studies on LN, the models used simultaneously clinical and demographic data, serum and urinary biomarkers, and histological features for diagnostic and predictive purposes [47,49,50,51,52]. Two studies published in 2022 demonstrated a good performance of MLMs in discriminating different histological classes. Indeed, Wang and colleagues proposed a model able to distinguish between ISN/RPS pure class V and classes III ± V or IV ± V, while Yang and colleagues observed good accuracy for mask R-CNN and LSTM models on recognizing different glomerular diseases based on slide images (AUC = 0.947) [48,52]. Furthermore, MLMs resulted able to predict a one-year response to treatment, the complete remission, or the risk of flare at 5 years follow-up [47,49,51]. Neurological involvement represents another complex SLE manifestation, with heterogeneous phenotype and lack of specific biomarkers. Thus, the differential diagnosis between SLE-related neurological symptoms and other confounder disorders is not always easy [53]. In this view, MLMs could facilitate clinicians in discriminating the real NPSLE from other pathological conditions. The main aspects of the studies published so far were summarized in Table 2 [54,55,56,57]. In detail, two studies applied MLMs in the analysis of the role of imaging techniques for diagnostic purposes. Thus, cluster analysis resulted able to discriminate five subsets of magnetic resonance characterized by the predominant involvement of different cerebral areas in terms of white matter hyperintensities distribution [55]. Moreover, the application of proton magnetic resonance spectroscopy was evaluated by SVM with feature selection. The authors proposed a diagnostic model with 94.9% of accuracy, which was able to identify patients with early NPSLE [56]. The study conducted by Barraclough and colleagues in 2022 focused on patients with cognitive impairment: the application of the network fusion model is able to discriminate patients with different performances in cognitive functions [57]. Gu and colleagues proposed a model by integrating the presence of anxiety and T-cells subsets evaluated by flow cytometry: the XGBoost model allowed to identify a significant difference in terms of T-cell subsets in patients with or without anxiety (AUC= 0.922) [54]. Two studies conducted by our research group focused on the application of MLMs in SLE-related joint involvement, one of the most frequent manifestation, potentially involving up to 90% of patients [58]. The first study published in 2018 applied logistic regression with the Forward Wrapper method in a cohort of patients with joint involvement evaluated from a laboratory and ultrasonographic point of view. We obtained a model with a good performance in identifying SLE patients with erosive arthritis (AUC = 0.806). Furthermore, at the feature selection, anti-carbamylated proteins antibodies (anti-CarP) resulted the most relevant factors for the presence of erosive arthritis [59]. Thus, an unsupervised hierarchical cluster analysis was applied to identify the aggregation of patients with and without erosive arthritis into different subgroups sharing common characteristics in terms of clinical and laboratory phenotypes. Our results demonstrated the identification of four main clusters: in particular, erosive arthritis was located in a cluster including renal and neuropsychiatric involvement, serositis, positivity for anti-CarP, anti-citrullinated protein antibodies, anti-Sm, anti-RNP, detectable levels of Dkk1 [60]. This could suggest the presence of a more aggressive disease phenotype, sharing a common pathogenic background [61]. Furthermore, MLMs have been also applied in the field of SLE comorbidity. In detail, Liu and colleagues in 2022 used AI to identify potential biomarkers for SLE patients with atherosclerosis (AS). By applying LASSO, SVM-RFE, and RF models, the authors identified five hub genes (specifically, SPI1, MMP9, C1QA, CX3CR1, and MNDA) with a high predictive performance in distinguishing subjects with and without AS (AUC ranging from 0.900 to 0.981) [62]. Wang and colleagues aimed at identifying the shared genes between SLE and metabolic syndrome (MetS): RF and LASSO algorithms were used to screen shared hub genes, and a diagnostic model was created by applying XG-Boost. Finally, the authors identified shared hub genes and constructed an effective diagnostic model in SLE and MetS. In detail, TNFSF13B and OAS1 had a positive correlation with cholesterol and xenobiotic metabolism. Both biomarkers and metabolic pathways were potentially linked to monocytes, providing novel insights into the disease pathogenesis [63]. The main outcome in the management of SLE patients is certainly the control of disease activity in order to prevent chronic damage development. The longitudinal assessment of disease activity allowed to identify different patterns: the so-called relapsing-remitting pattern has been prevalently associated with damage progression, due to the need to use glucocorticoids to treat disease relapse [12]. Several efforts have been made to develop tools able to properly measure disease activity, but the failure of the majority of randomized controlled trials enrolling SLE patients suggests that this field represents still an unmet need [64]. In this view, MLMs could play a potential role. In 2018 the study published by Toro-Dominguez aimed at stratifying SLE patients in terms of disease activity according to gene expression. The application of cluster analysis allowed to identify three different clusters in pediatric and adult patients; furthermore, in one cluster the authors observed a significant correlation between neutrophils percentage and a lower disease activity, evaluated by SLEDAI [65]. Furthermore, by using a real-world dataset, MLMs resulted able to discriminate SLE patients with different SLEDAI values, when using a cut-off equal to five [66]. Other studies proposed the integration of clinical data with gene expression, also providing suggestions for pathogenic mechanisms implicated in determining disease activity. In this field, Kegerreis and colleagues proposed a Random Forest model with an accuracy equal to 83% in discriminating patients with active and inactive disease according to genetic profile [67]. More recently, rule-based machine learning models and rule networks were applied to develop gene networks to separate pediatric SLE patients according to a state of low and high disease activity. The authors proposed a model with a good performance (accuracy 81%) to distinguish different levels of disease activity. Furthermore, the application of unsupervised hierarchical clustering revealed additional subgroups characterized by the association between specific gene pathways and disease activity. In detail, the following genetic variants have been clustered: IFI35 and OTOF; KLRB1 encoding CD161; CKAP4 [68]. Interestingly, cluster analysis was applied to identify an association between risk flare and peripheral immunophenotypes, as assessed by flow cytometry. Thus, the so-called memory B-cells cluster showed a lower risk to develop disease flares compared with the non-memory B-cells group, including naïve B- and T-cells [69]. In 2017 our research group applied recurrent neural networks to predict chronic damage development, assessed by the SLICC Damage index (SDI) [70]. Thus, for the Recurrent Neural Network model we selected two groups of patients: patients with SDI = 0 at the baseline, developing damage during the follow-up, and those without damage during the whole follow-up. By using these data inputs, we could create a model with an AUC value equal to 0.77, able to predict damage development. A threshold value of 0.35 (sensitivity = 0.74, specificity = 0.76) seemed able to identify patients at risk to develop damage [71]. More recently, in the study conducted by Ahn and colleagues, cluster analysis allowed to identify three groups of patients according to the damage severity and mortality risk [72]. The relationship between damage clustering and mortality was previously evaluated by Pego-Regoisa et al. in a large Spanish SLE cohort. Overall, the authors identified three clusters according to the severity of damage, two of them showed a significantly higher mortality rate [73]. MLMs were recently used by our group to propose a new outcome in SLE field: the so-called Lupus comprehensive disease control (LupusCDC), including both the achievement of remission and the absence of damage progression [74]. The proposal of LupusCDC originates from the evidence that the control of disease activity is not always sufficient to stop the damage progression, due to the presence of other factors concurring with its development [11,75]. Thus, we applied SVM models and Decision Trees, followed by features ranking with the ReliefF algorithm. Our model, characterized by AUC value equal to 0.703, identified glucocorticoids, renal involvement and the use of immunosuppressant drugs as the most relevant factors concurring to the failure to achieve LupusCDC [74]. In the last years the concept of precision medicine has been widely spread in the context of rheumatic conditions, including SLE. The heterogeneity of this disease, possible expression of different underlying pathogenic mechanisms, suggests the need for personalized treatment according to the most relevant manifestation [76]. In this context, MLMs could help the clinician in the treatment choice, by predicting drug response. However, very few data are available on this specific topic. In 2016 Kan and colleagues evaluated a large newly diagnosed SLE cohort by using cluster analysis: 10 treatment clusters were identified and the most common consisted of minimally treated patients (42.8%). In this cluster, hydroxychloroquine monotherapy, glucocorticoid monotherapy, and corticosteroid/hydroxychloroquine combination therapy were received by 34.0%, 11.2%, and 7.8% of patients, respectively [77]. More recently, Carter and colleagues observed that response to RTX in non-European SLE patients was lowest in an interferon-low, neutrophil-high cluster and highest in a cluster with high expression across all signatures (p < 0.001) [78]. Wang et al. applied MLMs to predict the effect of sirolimus on disease activity in 103 SLE patients. The so-called Emax model was selected for MLMs, where the evaluation indicator was the change rate of SLEDAI from the baseline value. The authors concluded that in order to achieve a better therapeutic effect (80% Emax, plateau), maintaining a concentration of 8–10 ng/mL sirolimus for at least 6–12 months was necessary [79]. Finally, recently MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions has been proposed. This is a machine learning-based classification model aiming at assessing the association between dysregulation in immunological response, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. The model MyPROSLE allowed to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. Preliminary results suggest that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Thus, the authors suggest the possible use of this model to predict clinical outcomes, including treatment response [80]. SLE mostly affects women of childbearing age and as widely demonstrated, it could be associated with unfavorable pregnancy outcomes. Furthermore, fetal complications, in particular, fetal death and neonatal lupus syndrome could develop in SLE. Finally, disease flare during and after pregnancy is a common complication, with a prevalence ranging from 35% to 70% of patients [81]. In the last years, the pre-gestational counseling and the multidisciplinary approach adopted in the daily clinical practice allowed SLE patients to experience even more uncomplicated pregnancies [82]. Nonetheless, it is very important to select factors able to identify patients at risk of maternal–fetal complications. In this context, the possible role of MLMs have been evaluated by two recent studies. Thus, Deng and colleagues applied Random Forest, support vector machine-recursive feature elimination and least absolute shrinkage with selection operator to identify genetic biomarkers for adverse pregnancy outcomes. The model identified three feature genes, specifically SEZ6, NRAD1, and LPAR4. Among these, SEZ6 showed the highest in-sample predictive performance, with an AUC value equal to 0.753 [83]. Moreover, Fazzari and colleagues confirmed, by using MLMs, the role of antihypertensive medication use, low platelets, SLE disease activity and lupus anticoagulant positivity as risk factors for adverse events during pregnancy. In detail, the authors evaluated a large SLE cohort by applying different models, in particular Logistic regression with stepwise selection, LASSO, Random Forest, neural network, Support Vector Machines, gradient boosting and SuperLearner. The best performance in terms of AUC was observed for LASSO model (AUC = 0.78) [84]. The increasing interest in the possible role of MLMs in SLE cohorts was demonstrated by the application of these tools in other disease-related fields. Jorge and colleagues applied decision tree, Random Forest, naïve Bayes and logistic regression to predict hospitalization in SLE patients. By analyzing 1996 patients, 4.6% of them were hospitalized in the most recent year of follow-up, the authors demonstrated a good performance for Random Forest model (AUC = 0.751) in predicting hospitalization. Furthermore, anti-dsDNA positivity, low C3 levels, blood cell counts, and increased inflammatory biomarkers, as well as age and albumin, represented the most relevant risk factors for hospitalization [85]. Finally, Margiotta and colleagues used MLMs in the evaluation of quality of life in SLE patients by using cluster analysis. This approach allowed to distinguish different patterns of quality of life, characterized by the prominent involvement of mental or physical components, as assessed by Short-Form 36 (SF-36) [86]. Furthermore, the same MLM was able to identify different clusters related to sleep disorders in SLE subjects, by integrating data deriving from the Pittsburgh Sleep Quality Index and those from SF-36 and anxiety scores [87]. In conclusion, the present review focused on the possible application of MLMs in the SLE scenario. In particular, MLMs have been applied in the field of diagnosis, pathogenic mechanisms, definition of different disease features and courses, and finally treatment response. As demonstrated by our literature revision, several models have been proposed, revealing good performance in terms of accuracy and AUC. These results suggest several possible future applications for MLMs. Among these, the application of specific models could help the physicians to identify patients at risk to develop more aggressive disease phenotypes, and thus could guide in the choice of a more appropriate treatments. Nonetheless, MLMs could be used to predict different phenomena, including the response to treatment, thus finding a place in the so-called precision medicine. However, the application of MLMs in a real-life context finds some obstacles and may still be anticipatory. First of all, they require studies for internal and external validation, secondly it is mandatory to test the MLMs reliability and reproducibility. In the SLE scenario, the studies published so far are characterized by some limitations, such as the sample size of the analyzed cohorts and the lack of replication studies. These aspects certainly do not allow the use of these models in a real-life context.

PMC10003089

Ilias Kalafatakis,Fevronia Papagianni,Konstantinos Theodorakis,Domna Karagogeos

Nogo-A and LINGO-1: Two Important Targets for Remyelination and Regeneration

24-02-2023

multiple sclerosis,demyelination,regeneration,remyelination,Nogo-A,LINGO-1

Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) that causes progressive neurological disability in most patients due to neurodegeneration. Activated immune cells infiltrate the CNS, triggering an inflammatory cascade that leads to demyelination and axonal injury. Non-inflammatory mechanisms are also involved in axonal degeneration, although they are not fully elucidated yet. Current therapies focus on immunosuppression; however, no therapies to promote regeneration, myelin repair, or maintenance are currently available. Two different negative regulators of myelination have been proposed as promising targets to induce remyelination and regeneration, namely the Nogo-A and LINGO-1 proteins. Although Nogo-A was first discovered as a potent neurite outgrowth inhibitor in the CNS, it has emerged as a multifunctional protein. It is involved in numerous developmental processes and is necessary for shaping and later maintaining CNS structure and functionality. However, the growth-restricting properties of Nogo-A have negative effects on CNS injury or disease. LINGO-1 is also an inhibitor of neurite outgrowth, axonal regeneration, oligodendrocyte differentiation, and myelin production. Inhibiting the actions of Nogo-A or LINGO-1 promotes remyelination both in vitro and in vivo, while Nogo-A or LINGO-1 antagonists have been suggested as promising therapeutic approaches for demyelinating diseases. In this review, we focus on these two negative regulators of myelination while also providing an overview of the available data on the effects of Nogo-A and LINGO-1 inhibition on oligodendrocyte differentiation and remyelination.

Nogo-A and LINGO-1: Two Important Targets for Remyelination and Regeneration Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) that causes progressive neurological disability in most patients due to neurodegeneration. Activated immune cells infiltrate the CNS, triggering an inflammatory cascade that leads to demyelination and axonal injury. Non-inflammatory mechanisms are also involved in axonal degeneration, although they are not fully elucidated yet. Current therapies focus on immunosuppression; however, no therapies to promote regeneration, myelin repair, or maintenance are currently available. Two different negative regulators of myelination have been proposed as promising targets to induce remyelination and regeneration, namely the Nogo-A and LINGO-1 proteins. Although Nogo-A was first discovered as a potent neurite outgrowth inhibitor in the CNS, it has emerged as a multifunctional protein. It is involved in numerous developmental processes and is necessary for shaping and later maintaining CNS structure and functionality. However, the growth-restricting properties of Nogo-A have negative effects on CNS injury or disease. LINGO-1 is also an inhibitor of neurite outgrowth, axonal regeneration, oligodendrocyte differentiation, and myelin production. Inhibiting the actions of Nogo-A or LINGO-1 promotes remyelination both in vitro and in vivo, while Nogo-A or LINGO-1 antagonists have been suggested as promising therapeutic approaches for demyelinating diseases. In this review, we focus on these two negative regulators of myelination while also providing an overview of the available data on the effects of Nogo-A and LINGO-1 inhibition on oligodendrocyte differentiation and remyelination. Myelin, produced by specialized myelinating glial cells (oligodendrocytes (OLs) in the CNS and Schwann cells (SCs) in the PNS, provides mammals with an evolutionary advantage that insulates the axon, provides trophic support, and ensures the rapid and efficient propagation of action potentials along its length. Its disruption, termed demyelination, may occur as a consequence of aging, from genetic alterations in genes encoding myelin proteins (dysmyelination), or from an inflammatory response against myelin producing cells, as is the case in Multiple Sclerosis (MS). The extent of demyelination is consistent with the neurological decline in the previously mentioned conditions, including impairments in motor and cognitive functions [1,2]. One of the most common demyelinating diseases of the CNS is multiple sclerosis (MS), affecting 2.8 million people globally. Previous studies have shown that immunity-associated genes are able to increase the risk of MS, confirming a role of autoimmune mechanisms in the pathogenesis of the disease. In MS, there is infiltration of the activated mononuclear cells in the CNS and microglia activation in the lesion site, which trigger an inflammatory cascade, resulting in demyelination and axonal injury. Non-inflammatory mechanisms, such as the generation of oxygen and nitrogen reactive species, mitochondrial damage, and intra-axonal accumulation of calcium, also play an important role in axonal degeneration. These mechanisms lead to impaired energy production and progressive proteolytic degradation of cytoskeleton proteins resulting in further axonal degeneration and neuronal loss [1]. Remyelination is the generation of new myelin sheaths that acts as a homeostatic repair process and involves the recruitment of oligodendrocyte precursor cells (OPCs) at the lesion site. These OPCs will then differentiate to mature myelinating OLs. Nevertheless, in most cases, remyelination is insufficient as the damaged fibers are not able to function properly. The reason is that either few OPCs are recruited in the affected area due to decreased proliferation or migration, or alternatively, the recruited OPCs may not properly differentiate to fully myelinating OLs. Indeed, it has been shown that OPC maturation can stall after the premyelinating stage; therefore, these differentiating oligodendrocytes can contact or even enwrap axons but cannot produce compact myelin. As a result, axonal degeneration ensues, as observed in advanced stages of MS [2,3,4,5]. Current MS therapies include anti-inflammatory and immunomodulatory agents, drugs that inhibit inflammation, aiming to reduce the frequency of relapses and tissue injury associated with acute inflammation. Even though these drugs have the ability to slow the evolution of the disease [6,7,8,9,10], they do not appear to stop tissue loss or promote remyelination and axonal repair [11], while their effects on long-term disability progression are still controversial. Compounds that may promote OPC proliferation/migration or differentiation to fully myelinating OLs may provide the means of more efficient repair [5]. One of the main reasons for insufficient remyelination is the gradual disappearance of growth promoting factors and the enhanced appearance of growth inhibitors, such as Nogo-A and LINGO-1, which are our focus in this review [12]. Nogo protein is encoded by the RTN4 gene [13], which is part of the reticulons RTN4 ER family of genes [14] and has three isoforms [15]. Nogo-A (200 kDa) is expressed in the CNS. In adult mice, Nogo-A is mainly expressed in oligodendrocytes [16,17] but also in the neurons [18] and microglia [19] in brain areas such as the hippocampus, spinal cord, and cerebellum [18]. Nogo-B (55kDa) is expressed in cardiac myocytes [18], vascular and endothelial cells [20,21], and Nogo-C (25 kDa) is expressed in many cells such as neurons, liver cells, and muscle cells [22,23]. All three isoforms have the same conserved C-terminal (RHD) but different N-terminal domains [24]. In this review, we will focus on Nogo-A since it is one of the most important myelin-associated inhibitors of axonal regeneration [13,25,26,27,28] and neuronal plasticity in the CNS [16,17,18]. As mentioned above, during development, Nogo-A is expressed mainly by neurons, where it plays an important role in the migration of cells in neural tubes [29], the interaction between axons and oligodendrocytes [16], axon guidance by the repulsion of growing fibers [30], and angiogenesis [31]. Additionally, it is highly expressed in growing neurites [32], modulating their fasciculation and branching [33]. In the adult CNS, it is mainly expressed by oligodendrocytes [17] in the innermost and outer myelin membrane [18], and it is an inhibitor of axonal growth and plasticity [34], stabilizing the CNS wiring [26]. It is a long transmembrane protein consisting of 1192 amino acids localized in the plasma and the endoplasmic reticulum (ER) membrane [35,36]. There are two main functional domains of Nogo-A [37] that are important for neurite growth inhibition: Nogo-A-Δ20 (544–725 amino acid residues), which is included in the Nogo-A specific region/Exon 3 and is located near the N-terminal of the protein, and Nogo-66 (1055-1120 amino acid residues), which is located near the C-terminal between two hydrophobic domains (HP1, HP2) [13]. Nogo-A-Δ20 is important for the inhibition of axonal spreading and regrowth while modulating neuron migration in development. Nogo-66, which is anchored on the membrane surface of oligodendrocytes, is responsible for growth cone collapse (Figure 1) [38]. Recently, a new functional domain of Nogo-A was identified, Nogo-A aa (846–861 amino acids residues). This region is responsible for the inhibition of axonal growth and for the promotion of inflammatory pain [39]. The key to the inhibitory action of Nogo-A is the binding of Nogo-66 and Nogo-A-Δ20 domains with different receptors, such as the NgR1 (The Nogo Receptor) or the S1PR2 (sphingosine-1-phosphate receptor 2) [16,40], as depicted in Figure 2. NgR1 is the main receptor of Nogo-66, also encoded by the RTN4 gene, and is expressed in the neurons and axons of the CNS, microglia, and astrocytes [41]. NgR1 is a glycophosphatidylinositol-anchored protein (GPI), so it does not have an intracellular component [41], which is why it needs a transmembrane coreceptor like LINGO-1 to convert the signal from the extracellular to the cytosolic environment [42]. For the signaling of the receptor NgR1, its connection to p75, a neurotrophic receptor and/or its connection to TROY, a tumor necrosis factor [43,44], is important. Except for Nogo-A, MAG (myelin-associated glycoprotein) and OMgp (oligodendrocyte myelin glycoprotein) can also bind to NgR1, having similar effects regarding the inhibition of axonal regeneration and sprouting (Figure 2) [45,46,47]. Another receptor, which interacts with these three myelin-associated proteins, is the paired immunoglobulin-like receptor B (PirB, Figure 2) [48]. PirB plays an important role in plasticity in the visual cortex [49]. Recently, another receptor of Nogo-A has been found using CRISPR screening, the brain angiogenesis inhibitor 1, BAI1 (ADGRB1) [50]. Except for Nogo-66, there are interactions between the Nogo-A-Δ20 region and other receptors such as sphingosine-1-phosphate receptor 2 (S1PR2), heparan sulfate proteoglycans (HSPGs), and ephrin type-A receptor 4 (EphA4), which are important to NSC apoptosis via JNK MAPK pathway activation [51]. However, the main pathway, activated by the interactions of Nogo-66 with NgR1 and Nogo-A-Δ20 with S1PR2, HSPGs, and EphA4, is the Rho GTPase pathway [52] and, simultaneously, the downregulation of activated Rac1 [53]. The Ras homolog gene family member A, the RhoA gene, activates the Rho-associated protein kinase, ROCK, which promotes actomyosin contraction through the increase of myosin light chain (MLC) phosphorylation [54]. RhoA-ROCK signaling also promotes the stabilization of actin filaments through the induction of the LIM kinase-dependent phosphorylation (LIMK) and inactivation of cofilin [55,56]. ROCK also interacts with collapsin response mediator protein-2 (CRMP-2). CRMP-2 is a microtubule-binding protein that induces axon growth through the promotion of microtubule assembly. ROCK-mediated phosphorylation of CRMP-2 blocks its ability to bind to tubulin, thereby leading to the inhibition of microtubule assembly and growth cone collapse [57]. Last but not least, ROCK phosphorylates the dual protein/lipid phosphatase PTEN, which is a tumor suppressor able to inhibit cell growth and survival [58]. Thus, the signaling cascade includes reduced growth of actin filaments [59], the collapse of the growth cone [60], destabilization of microtubules, and downregulation of growth genes in the neuronal cell body, leading to axon growth inhibition and destabilization of synapses [41,61]. It is important to mention that CRMP-2 is inhibited during the progression of experimental autoimmune encephalomyelitis (EAE) in degenerating axons [62]. Moreover, expression of NgR1 is increased in astrocytes and microglia in actively demyelinating lesions of MS. Thus, this may indicate an alternative modulation of inflammation via the Nogo-A/NgR signaling pathway (Figure 2) [63]. Last but not least, as mentioned in the previous section, a new functional domain of Nogo-A was recently identified (Nogo-A aa). This domain was characterized as a novel extra ligand of NgR1 that is able to activate the downstream signaling pathways inhibiting axonal growth and promoting inflammatory pain [39]. Nogo-A plays a critical role in many neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS), temporal lobe epilepsy (TLE), and Alzheimer’s disease (AD). Previous studies have shown that Nogo-A expression is increased in both ALS and TLE patients [64,65]. Nogo-A also plays an important role in AD pathogenesis. Particularly, Nogo-A receptors modulate the generation of amyloid β-protein (Aβ), which is thought to be a major cause of AD [66]. Nogo-A is also crucial in other diseases like glioblastoma and schizophrenia. The Nogo-A/NgR pathway plays an important role in regulating cancer stem-like cells (CSCs) derived from glioblastoma affecting cell viability, cell cycle entry, invasion, and tumor formation [67]. Regarding the role of Nogo-A in schizophrenia, it is proposed that abnormal Nogo-A expression or NgR mutations may be characterized as genetic risks for neuropsychiatric disorders of presumed neurodevelopmental origin, such as in the case of schizophrenia. Previous studies in a mouse model of genetic Nogo-A deficiency have shown that Nogo-A deletion may lead to schizophrenia-like abnormalities [68]. Moreover, blocking Nogo-A leads to retinal and visual recovery [69]. For decades, studies have shown that blocking Nogo-A has a therapeutic role in MS [70,71], Parkinson’s disease (PD) [72], spinal cord injury (SCI) [73,74], and stroke [75]. Recently, it was demonstrated that deletion of the Nogo-A gene is able to modulate inflammatory diseases through the regulation of cytokines [76]. In this review, we will focus on the role of Nogo-A inhibition in demyelinating disorders such as MS. One promising approach for the promotion of remyelination is to design antibodies against the Nogo-A protein. Administration of anti-Nogo-A in vivo not only neutralizes the inhibitory role of Nogo-A but also enhances neurite outgrowth and neuronal survival. Additionally, no differences between the two genders and no side effects, in general, were observed [77,78]. Many studies in MS animal models support the idea that inhibition of Nogo-A, either by injections with specific antibodies or by depletion of the Nogo-A gene, could be a therapeutic approach for MS. To mimic demyelinating disorders like MS, there are three main animal models used: Cuprizone-induced, LPC (lysolecithin)-induced, and experimental autoimmune encephalomyelitis (EAE) [79], the last being the most widely used for this purpose [80]. In studies on the EAE model, the suppression of Nogo-A through injections with anti-Nogo-A antibodies showed promising results [71,81]. More specifically, they showed lower clinical scores of EAE, suggesting a decreased severity of the disease [81], while reduced levels of inflammation, demyelination, and axonal degeneration and a generally slower disease progression were also observed [71]. Additionally, in vivo and in vitro experiments in Nogo-A deficient mice through RNA silencing have shown enhanced axonal repair [81]. These results confirm the idea that axonal remyelination, as mentioned before, is the key to improving the clinical state of MS [70,82]. Moreover, depletion of the Nogo-A gene in LPC models of demyelination and stroke leads to enhanced axonal plasticity and fiber growth [83]. A study focusing on the expression pattern of Nogo-A during EAE progression showed a reduction of Nogo-A mRNA expression at preclinical and acute phases, followed by an increase during the chronic phase. The expression of Nogo-A protein was also found to increase in the chronic phase. This increase is correlated with an increase of cortical NgR protein and mRNA levels during the same time point, suggesting that there is active regulation of both Nogo-A and its receptor in EAE lesions [84]. Furthermore, the comparison of the expression of Nogo-A mRNA and, consequently, Nogo-A protein with the levels of growth-associated protein GAP43 (neuromodulin) in neurons has shown an interesting connection [85]. More specifically, in the primary phase of EAE, Nogo-A is downregulated while neuromodulin is upregulated. However, in the chronic demyelination stage, the opposite happens. Moreover, suppression of Nogo-A was associated with enhanced plasticity and the regrowth of fibers and improvement in locomotion via behavioral approaches in models of spinal cord or brain injury [26,27]. Finally, similar experiments on monkeys showed that neutralization of Nogo-A promotes axonal sprouting and functional recovery after spinal cord injury (Table 1) [77,78]. In addition to these preclinical studies, it is known that in MS patients with chronic demyelinated lesions, Nogo-A is upregulated. Some antibodies for Nogo-A were found in the blood serum of patients, just as they are found in healthy people [86]. The preclinical studies using different models of demyelinating diseases and data from MS patients suggest Nogo-A antibodies as a potential therapeutic approach for the treatment of relapsing-remitting MS (RRMS) and/or progressive forms of MS. Two Phase I studies for antibodies against Nogo-A were conducted in patients with RRMS (ClinicalTrials.gov, NCT01424423 and NCT01435993). Both studies, involving a limited number of patients, were terminated, and their results were not fully published [87]. Additionally, two other Phase I studies focusing on two other CNS diseases were successfully completed, testing the acute safety, tolerability, and pharmacokinetics of anti-Nogo-A antibodies. The first study focused on the intrathecal administration of anti-Nogo-A antibodies for 30 days in patients with SCI (NCT00406016). This study was the first one investigating anti-Nogo-A delivery for the treatment of acute SCI. It was shown that anti-Nogo-A (ATI335) was well-tolerated, and its delivery, particularly via bolus injection, is a viable method of drug administration in acute SCI. The small number of patients and the fact that this was an open-label study resulted in a limited ability to draw safe conclusions regarding drug efficacy in improving neurological recovery after SCI. The second study focused on the administration of doses of intravenously infused antibodies in patients with ALS(NCT00875446). In this study, it was shown that a humanized monoclonal antibody against Nogo-A (ozanezumab) was well tolerated. The differences observed regarding functional endpoints and the colocalization of ozanezumab in skeletal muscle were promising. These observations, together with the lack of emerging safety signals, support the planning of future clinical trials aiming to produce more successful outcomes in the treatment of neurodegenerative diseases like MS and ALS. Both clinical studies showed excellent safety and tolerability of the Nogo-A antibody treatment [88,89,90]. However, additional studies should be performed with a higher number of patients suffering from demyelinating diseases for more accurate and safe results regarding the role of Nogo-A antibodies as a promising therapeutic agent. Last but not least, it is worth mentioning that until today, one of the most important concerns regarding anti-Nogo-A administration is its potentially limited access to the CNS through the BBB [91]. Neurite outgrowth inhibitor receptor-interacting protein (LINGO-1), containing leucine-rich repeats and Ig domains, has served as a potent negative regulator of oligodendrocyte differentiation and myelination [92]. LINGO-1, which is encoded by the LRRN6A gene, is a type I transmembrane composed of 614 amino acids. LINGO-1 consists of an extracellular domain, which is heavily glycosylated with 12 leucine-rich repeat (LRR) motifs encompassing N- and C-terminal caps and an immunoglobulin (Igl1) domain [93,94]. The Ig domain of LINGO-1 is necessary and sufficient in mediating its biological function [95,96]. The protein forms a ring-shaped tetramer in which the Ig domain makes contact with the N-terminal LRR sequences from an adjacent LINGO-1 molecule (Figure 3) [97]. The LINGO-1 structure is highly conserved. A rostral to the caudal gradient of LINGO-1 expression in the adult CNS showed the highest levels in the cerebral cortex, the hippocampus, the amygdala, and the thalamus, with a more basal level of expression across the remainder of the brain, while the lowest levels of LINGO-1 expression are observed in the spinal cord [98]. Previous studies have shown that LINGO-1 mRNA is expressed in the CNS throughout embryonic and postnatal stages [42,43,92,93,99,100,101,102]. More specifically, LINGO-1 is expressed on oligodendrocytes and neurons [92,102], while it is associated with the Nogo-66 receptor (NgR1) complex [41,42,43,44,46,103,104]. As mentioned above, NgR1 binds to the following myelin-associated inhibitors: Nogo-A [13,37], MAG [45,105], and OMgp [46]. The binding of a myelin-associated inhibitor to the NgR1 complex induces an intracellular signaling cascade through LINGO-1 and p75NTR/TROY [106]. Protein kinase C and Ca2+-dependent or -independent activation of a small RhoA guanosine triphosphatase (RhoA GTPase) molecule is the key intracellular event leading to the inhibition of axonal regeneration, elongation, and oligodendrocyte differentiation [107,108] (Figure 4A) [109]. Other than its role as a negative regulator of myelination, LINGO-1 is also involved in the regulation of neural apoptosis by inhibiting WNK3 kinase activity. LINGO-1 is able to interact with different co-factors and coreceptors, leading to the activation of signaling pathways involved in the regulation of neuronal survival, axon regeneration, oligodendrocyte differentiation, and myelination processes in the brain. LINGO-1 binds to epidermal growth factor receptor 2 (ErbB2) and inhibits its translocation to the lipid rafts on oligodendroglial membranes. In the absence of LINGO-1, ErbB2 is modulated in lipid rafts by local kinases and phosphatases and, in this way, induces OPC differentiation (Figure 4B) [110,111,112]. Moreover, LINGO-1 is able to inhibit epidermal growth factor receptor (EGFR) signaling, preventing the activation of intracellular phosphoinositide 3-kinase (PI3K) [113]. Without PI3k activation, PIP2 cannot be further phosphorylated to its active form, and, as such, AKT and m-TOR remain inactive. Since both activated AKT and m-TOR have been shown to promote OPC survival and differentiation, LINGO-1 prevents OPC differentiation (Figure 4C) [114]. LINGO-1 also interacts with the nerve growth factor (NGF) and its receptor tropomyosin receptor kinase A (TrkA), brain-derived neurotrophic factor (BDNF) and its receptor tropomyosin receptor kinase B (TrkB), and amyloid precursor protein (APP). It also interacts with proteins that are implicated in neurological and psychiatric disorders, such as WNK lysine-deficient protein kinase 1 (WNK1), mitogen-activated protein kinase 2/3 (MEK 2/3), extracellular signal-reduced kinase 5 (ERK5), and others(Figure 4D) [98]. The expression of LINGO-1 is increased in many CNS diseases. This increase is associated with CNS injury and neuronal cell death, suggesting that LINGO-1 may play an important role during cell injury response. LINGO-1 is implicated in glaucoma, PD, SCI, traumatic brain injury, MS, essential tremor, as well as AD and epilepsy due to its role in the inhibition of axonal outgrowth, neuronal death, oligodendrocyte differentiation, and myelination [98]. More specifically, increased LINGO-1 expression is associated with glaucoma, which is characterized by the degeneration of retinal ganglion cells (RGCs) and their axons. LINGO-1 inhibition leads to the neuroprotection of damaged RGCs in well-established models of chronic glaucoma and acute optic nerve transection, possibly through inhibition of RhoA activation or activation of the Akt survival signaling pathway [115]. Increased LINGO-1 expression is also observed in the substantia nigra of PD patients and animal models of PD. LINGO-1 is expressed in midbrain dopaminergic (DA) neurons in both human and rodent brains. Depletion of LINGO-1 in mice is associated with increased survival of DA neurons and reduced behavioral abnormalities in PD models due to the activation of the EGFR/Akt signaling pathway [113]. LINGO-1 is also implicated in SCI since it is detected in the axonal tracts of rat spinal cords following injury, with an increase of LINGO-1 mRNA levels observed 14 days post-injury [42]. LINGO-1 expression is also associated with traumatic brain injury, which involves cell death in the cerebral cortex and hippocampus [116]. These areas highly express LINGO-1 during both development and adulthood [42,93], while RhoA pathway activation is responsible for the lack of regeneration of damaged axons [117]. Regarding the role of LINGO-1 in the pathophysiology of AD, LINGO-1 is able to bind to amyloid precursor protein and regulate its processing by increasing the production of amyloid-β peptide [100]. LINGO-1 is able to regulate the amount of amyloid precursor protein available for processing [118]. LINGO-1 also plays an important role in neurological disorders like tuberous sclerosis, focal cortical dysplasia, and TLE, which all include seizures as a common symptom. Previous studies showed that both protein and mRNA levels of Nogo-A, NgR, LINGO-1, TROY, and RhoA increased in the cortex of tuberous sclerosis and cortical dysplasia patients. LINGO-1 and TROY were also expressed in the reactive astrocytes of these patients, suggesting an important role of Nogo-A and its signaling complex LINGO-1/NgR/TROY in the development and progression of seizure activity [119]. Last but not least, LINGO-1 and its signaling partners are also implicated in the pathophysiology of schizophrenia and a number of other neuropsychiatric disorders like depression, attention-deficit hyperactivity disorder, autism spectrum disorder, anxiety, post-traumatic stress, and drug addiction mainly due to LINGO-1 activating or blocking pathways leading to negative regulation of myelination and neurite outgrowth [98]. Focusing on the role of LINGO-1 in myelination and demyelination, it is proposed that LINGO-1 has an important role in repressing oligodendrocytes differentiation, as mentioned above [92]. Additionally, extracellular blockage of LINGO-1 function overcomes the myelin inhibitory activity in the spinal cord that prevents axonal regeneration after lesions in rats [120]. Moreover, LINGO-1 inhibition improves dopaminergic neuron activity in a model of Parkinson’s disease and promotes spinal cord remyelination in an experimental model of autoimmune encephalomyelitis [113,121]. LINGO-1 function has also been investigated in animal models of demyelination. The measurement of transcranial magnetic motor-evoked potentials (tcMMEPs) provides an accurate readout of the electrophysiological function of descending tract demyelination/remyelination of the spinal [122]. In rats and mice, tcMMEPs are only transmitted through the ventrolateral funiculus (VLF) region [123,124]. Demyelination increases the latency while decreasing the amplitude of tcMMEPs. In LPC-induced demyelinating lesions of the rat VLF, inhibition of LINGO-1 improves the recovery of tcMMEP amplitude in parallel with increases in the thickness of myelin sheaths [125]. Inhibition of LINGO-1 by using specific antibodies improved remyelination and neurobehavioral deficits in cuprizone-induced demyelination. In this study, levels of MBP, BDNF, and NF200 were increased after the treatment of anti-LINGO-1 in this model, while behavioral studies showed an improvement regarding motor impairments after the same treatment [126]. Another study confirmed that LINGO-1 antagonism is able to promote repair in the EAE model of demyelination through the ability of LINGO-1 antagonists to promote the differentiation of OPCs. The EAE mouse model is characterized by learning and memory deficits occurring in late EAE and decreased expression of MBP in the parahippocampal cortex (PHC) and fimbria-fornix. Administration of the LINGO-1 antibody significantly improved learning and memory in EAE and partially restored MBP in PHC [127]. Anti–LINGO-1 antibody treatments significantly increased the in vivo rate of remyelination in two different models of demyelination (LPC and cuprizone) and enhanced axonal conduction in LPC lesions [125]. Additional studies confirmed the promising results above. More specifically, mice treated with LINGO-1-directed siRNA–chitosan nanoparticles performed better remyelination after ethidium bromide-induced demyelination. Mice treated with LINGO-1 siRNA nanoparticles exhibit enhanced motor performance compared to the non-treated group. LINGO-1 downregulation was associated with signs of repair in histopathological sections as indicated by increased expression of MBP mRNA and protein in the pons and lower levels of caspase-3 activity [128]. Last but not least, studies have shown that LINGO-1 inhibition via RNA interference led to the functional recovery of the EAE mouse model, suggesting higher levels of myelination through Luxol Fast Blue (LFB) staining and better locomotor activity through specific behavioral approaches (Table 2) [129]. All these data propose that a major function of LINGO-1 is to inhibit the differentiation of OPCs, thereby preventing remyelination and that antagonizing the LINGO-1 function represents potential therapeutics for repair in CNS demyelinating diseases. For this reason, there have been studies focusing on designing specific antibodies against LINGO-1 with a potential beneficial role in remyelination and neuroprotection. To induce remyelination, the human monoclonal IgG antibody, opicinumab (BIIB003), was designed in order to inhibit LINGO-1-mediated pathways [130]. Two Phase I clinical studies, including opicinumab administration in healthy volunteers and relapsing MS patients, indicated a tolerable safety profile [131]. A double-blind Phase II study (RENEW) was conducted in patients with acute optic neuritis (AON). After treatment with a standard high dose of methylprednisolone (IVMPS), participants received either 100 mg/kg opicinumab or a placebo within 28 days after symptom onset. Administration of the treatment took place every 4 weeks up to week 20. After week 20, there was a 12-week observation period. The visually evoked potentials (VEPs) assessed the recovery of the affected optic nerve conduction after 24 weeks. Although treatment with opicinumab resulted in amelioration of P100 latency (the time from the stimulus onset to the main positive peak), this difference was not statistically significant [132]. Furthermore, in a new substudy, multifocal VEP measurements were used to examine optic nerve repair. No statistically significant differences towards reduced latency prolongation and increased recovery of VEP amplitude were observed in the active treatment group [133]. Moreover, a two-year follow-up study of the RENEW trial was conducted (RENEWED). Participants of the RENEW clinical study, who received at least one dose of opicinumab or placebo, could join this follow-up trial. Investigation of VEP latency showed that the observed positive trend in the opicinumab group was maintained over two years. However, as mentioned above, this trend was not statistically significant [134,135,136]. Furthermore, a double-blind Phase II SYNERGY trial was conducted, including RRMS and secondary progressive MS (SPMS) patients with relapses who were randomly assigned to either 3, 10, 30 or 100 mg/kg of opicinumab or a placebo treatment. Patients received treatment or a placebo every 4 weeks for 72 weeks in addition to interferon-β1α. In this study, there was no statistically significant beneficial effect regarding treatment with 3, 10, and 100 mg/kg of opicinumab. The only statistically significant beneficial effect was observed in patients who received a dose of 30 mg/kg opicinumab. Although these patients showed an improvement regarding their disability, there was no significant dose linear improvement [137]. Last but not least, a placebo-controlled, randomised, double-blind Phase II trial (AFFINITY) was also conducted, including RRMS and SPMS patients. This study aimed to evaluate the administration of 750 mg of opicinumab, equivalent to a dose of 10 mg/kg. The primary study endpoints (pSE) included the integrated response score already used in the SYNERGY study. After some time, it was announced that the AFFINITY trial failed to meet the pSE [135]. Despite the less-than-promising results, SYNERGY has provided useful information regarding trial design in patients with established MS-related disabilities. This study confirmed a good tolerability and feasibility of treatment with monoclonal antibodies for CNS neurodegenerative diseases. Due to many contradictory results in the literature, future studies must aim to clarify some important aspects regarding LINGO-1. More specifically, it should be clarified whether LINGO-1 is localised to the extracellular cell surface and if it is present in human MS tissue. Additionally, new potential partners involved in downstream LINGO-1 signaling should be identified [135]. The clinical trials conducted so far did not yield promising results as expected based on the preclinical studies, but there are some concerns regarding these trials. They relate to trial design (numbers or characteristics of patients recruited and specific clinical outcomes or time frames), particularly poor penetration of antibodies across the blood–brain barrier due to physical size, and active efflux of antibodies from the CNS compartment. Moreover, additional studies will investigate whether some subpopulations identified might benefit from opicinumab treatment at an optimum dose. Current therapeutic approaches for the treatment of MS focus on drugs with anti-inflammatory or immunomodulatory properties. These drugs are useful since they slow disease progression by reducing brain inflammation. However, none of the available therapeutic approaches have been shown to promote tissue recovery. Once CNS damage has occurred, the progression of disability is typically continuous and irreversible. In this direction, new therapeutic approaches should emerge that will promote remyelination and regeneration leading to neurological recovery. As mentioned above, in most MS cases, remyelination is insufficient, failing to restore axonal function, while the presence of undifferentiated OPCs within lesions suggests that OPC differentiation is blocked. For this reason, antagonists of inhibitors of oligodendrocyte differentiation may promote remyelination. In that regard, Nogo-A and LINGO-1 are attractive therapeutic targets. Blocking of Nogo-A or LINGO-1 in different models of demyelination showed some promising results regarding remyelination and recovery. This raises the exciting prospect that antagonists of Nogo-A and LINGO-1 may promote neuronal remyelination, survival, and function, leading to the critical neurological recovery of MS patients in the future. The clinical studies performed regarding the impact of anti-Nogo-A and anti-LINGO-1 in MS-related patients did not yield the promise that was expected, but additional studies and information regarding Nogo-A and LINGO-1 will support the interpretation and planning of future clinical trials aiming for more successful outcomes in the treatment of neurodegenerative diseases like MS.

PMC10003090

Di Wang,Valeriia Kuzyk,Katarina Madunić,Tao Zhang,Oleg A. Mayboroda,Manfred Wuhrer,Guinevere S. M. Lageveen-Kammeijer

In-Depth Analysis of the N-Glycome of Colorectal Cancer Cell Lines

02-03-2023

N-glycosylation,colorectal cancer,cell line,glycosyltransferases,transcription factor,porous graphitized carbon liquid chromatography,mass spectrometry

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer deaths worldwide. A well-known hallmark of cancer is altered glycosylation. Analyzing the N-glycosylation of CRC cell lines may provide potential therapeutic or diagnostic targets. In this study, an in-depth N-glycomic analysis of 25 CRC cell lines was conducted using porous graphitized carbon nano-liquid chromatography coupled to electrospray ionization mass spectrometry. This method allows for the separation of isomers and performs structural characterization, revealing profound N-glycomic diversity among the studied CRC cell lines with the elucidation of a number of 139 N-glycans. A high degree of similarity between the two N-glycan datasets measured on the two different platforms (porous graphitized carbon nano-liquid chromatography electrospray ionization tandem mass spectrometry (PGC-nano-LC-ESI-MS) and matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF-MS)) was discovered. Furthermore, we studied the associations between glycosylation features, glycosyltransferases (GTs), and transcription factors (TFs). While no significant correlations between the glycosylation features and GTs were found, the association between TF CDX1 and (s)Le antigen expression and relevant GTs FUT3/6 suggests that CDX1 contributes to the expression of the (s)Le antigen through the regulation of FUT3/6. Our study provides a comprehensive characterization of the N-glycome of CRC cell lines, which may contribute to the future discovery of novel glyco-biomarkers of CRC.

In-Depth Analysis of the N-Glycome of Colorectal Cancer Cell Lines Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer deaths worldwide. A well-known hallmark of cancer is altered glycosylation. Analyzing the N-glycosylation of CRC cell lines may provide potential therapeutic or diagnostic targets. In this study, an in-depth N-glycomic analysis of 25 CRC cell lines was conducted using porous graphitized carbon nano-liquid chromatography coupled to electrospray ionization mass spectrometry. This method allows for the separation of isomers and performs structural characterization, revealing profound N-glycomic diversity among the studied CRC cell lines with the elucidation of a number of 139 N-glycans. A high degree of similarity between the two N-glycan datasets measured on the two different platforms (porous graphitized carbon nano-liquid chromatography electrospray ionization tandem mass spectrometry (PGC-nano-LC-ESI-MS) and matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF-MS)) was discovered. Furthermore, we studied the associations between glycosylation features, glycosyltransferases (GTs), and transcription factors (TFs). While no significant correlations between the glycosylation features and GTs were found, the association between TF CDX1 and (s)Le antigen expression and relevant GTs FUT3/6 suggests that CDX1 contributes to the expression of the (s)Le antigen through the regulation of FUT3/6. Our study provides a comprehensive characterization of the N-glycome of CRC cell lines, which may contribute to the future discovery of novel glyco-biomarkers of CRC. Colorectal cancer (CRC) is the third most commonly diagnosed cancer, accounting for 10.0% of all cancer cases, and is the second leading cause of cancer death, accounting for 9.4% of all cancer deaths worldwide [1]. Advances in diagnostics, particularly in population screening, and therapeutic treatments over the past 50 years, have led to significant reductions in incidence and mortality [2,3]. However, many tumors are still only detected at advanced stages which often results in treatment failure [4]. Glycosylation is a well-known hallmark of cancer [5] and, therefore, investigating the expression and regulation of glycosylation in relation to CRC is essential for the discovery of potential cancer-associated biomarkers. The complex, nontemplate-based biosynthetic pathways of glycosylation create an enormous structural diversity and a rich pool of putative biomarkers. Furthermore, the discovery of glycomic biomarkers can be derived from various data arrays. For example, one may investigate the entire glycomic pattern of a biofluid (e.g., salivary glycome for oral cancer) [6] or tissue sample (colonic tissues for CRC) [7], or focus on glycan signatures of a specific protein group (such as immunoglobulins in the serum of ovarian cancer patients) [8]. Alternatively, the search can be narrowed down to the glycosylation of one glycoprotein that is known to be cancer-associated, as it was probed for the glycosylation of haptoglobin in hepatocellular carcinoma and carcinoembryonic antigen in CRC [9,10,11]. To model the response to treatment and biomolecular signatures, cell lines are extensively used in cancer research thereby being capable of revealing potential biomarkers [12,13]. The established cell lines are well characterized at the gene and protein expression levels and retain tissue molecular features with regard to DNA, RNA, and proteins making them an essential tool in preclinical drug screening experiments [14]. An integrated data analysis approach, which combines DNA mutations, RNA, and protein expression levels, has been used to classify the CRC cell lines into two distinct groups: colon-like cell lines with a characteristic expression of gastrointestinal differentiation markers and undifferentiated cell lines that show overexpression of both epithelial-mesenchymal transition (EMT) pathway and transforming growth factor β (TGF-β) signaling [15]. However, the glycan signatures are often neglected in these studies, partly due to their high heterogeneity and complexity. Previous research found a high diversity in the N-glycomic fingerprints between different CRC cell lines analyzed with matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF-MS), which can be used as glycobiological tumor model systems [16]. It is important to note that seemingly small differences in glycan structures may result in significant physiological outcomes. For instance, a shift from dominating α2-3 sialylation in sialic acid linkage isomers towards α2-6 sialylated species has been reported to be indicative of early ovarian cancer [17] and was found to accompany drug resistance in metastatic CRC [18]. Our group has previously explored the glycosylation of glycosphingolipids (GSLs), N- and O-glycans of CRC cell lines [16,19,20], and CRC tissues [21]. Colon-like cell lines exhibited a high abundance of sialyl LewisA/X (sLeA/X) antigens on O-glycans and GSLs glycans, whereas undifferentiated cell lines presented an upregulation of blood group antigens on GSLs glycans and truncated α2-6 core sialylated glycans on O-glycans [19,20]. Yet, the previously performed N-glycomic analysis of CRC cell lines measured with MALDI-TOF-MS had limitations in resolving isomers, as no separation dimension was applied, and, from the glycan isomers perspective, only differences in sialic acid linkage could be resolved via linkage-specific sialic acid derivatization [16]. Certain glycan motifs that are defining pathological processes (such as sLeA/X glycan antigens) are difficult to identify reliably without an in-depth structural analysis. All these considerations prompt the need for a more detailed structural analysis of CRC cell lines’ glycosylation. Glycosylation is a dynamic process in response to microenvironment demands and is only partially dependent on glycosyltransferase expression. The localization of these enzymes, the enzymes synthesizing the monosaccharide precursors, the availability of nucleotide sugar donors and transporters, and alterations of the peptide backbone substrate all contribute to the final glycan signature [22,23,24,25]. In this study, to gain a better understanding of the underlying mechanisms related to newly found glycosylation alterations, we combined mRNA expression data of CRC cell lines with its N-glycomic profile. With these considerations, we have characterized and provided insights into the structural diversity of the N-glycome and investigated the regulation of the N-glycan expression in 25 CRC cell lines. In total, a number of 139 N-glycans were structurally identified with a porous graphitized carbon nano-liquid chromatography electrospray ionization tandem mass spectrometry (PGC-nano-LC-ESI-MS/MS). This method provides the in-depth structural characterization of isomeric species due to the separation of (isomeric) N-glycan species. Moreover, we investigated the association of glycomic features and relevant glycosyltransferases (GTs) in CRC cell lines. Overall, our findings enrich the current understanding of CRC cell lines as model objects and pave the way for discovering potential cancer-associated targets for the treatment of CRC. To characterize the N-glycan profiles of 25 CRC cell lines, released N-glycans were measured on a PGC-nano-LC-ESI-MS/MS system in negative mode, providing fragment-specific diagnostic ions derived from cross-ring and glycosidic-linkage fragmentation to characterize the glycans and differentiate isomers [26,27,28,29,30,31,32]. In total, 139 different N-glycans were structurally confirmed ranging in size from 4 up to 14 monosaccharides per structure (Supplementary Information, Table S1). Relative abundances of the N-glycans, based on the first three isotopic peaks of singly and doubly charged ions, were determined, which may somewhat deviate from the actual relative abundances due to possible biases in sample preparation and mass spectrometric detection. Our analysis revealed a high degree of diversity in N-glycomic profiles among the studied CRC cell lines (Figure 1 and Supplementary Information, Figure S1). The undifferentiated Caco2 cell line expressed high phosphorylated oligomannosidic type structures and complex N-glycans with Lewis antigens, while the colon-like SW1463 cell line showed a higher diversity of sialylated N-glycans (Figure 1). The undifferentiated cell line HCT116 expressed a higher diversity of N-glycans compared to the colon-like cell line HT29 and, apart from typically predominant (phosphorylated) oligomannosidic species (Supplementary Information, Figure S1A), was further characterized by the sialylated complex and hybrid N-glycans (Supplementary Information, Figure S1B). Notably, LacdiNAc (GalNAcβ1-4GlcNAc) motifs were observed for two isomers with composition H4N5S1 with a relative abundance of 0.7% and 0.4% (Supplementary Information, Table S1). While the colon-like cell line HT29 was characterized by a high abundance of oligomannosidic N-glycans, a high abundance of paucimannosidic types (3.5%), along with a sulfated N-glycan (H6N3Su1) with a relative abundance of 0.8% (Supplementary Information, Figure S1C, and Supplementary Information, Table S1), which is in contrast to HCT116. Structural information of the identified N-glycans can be found in Supplementary Information, Table S1. The N-glycomic phenotypes of CRC cell lines were relatively quantified and assigned into different glycosylation groups based on specific glycan types (paucimannosidic, oligomannosidic, complex, and hybrid), glycan epitopes (core/antennae fucosylation, sialylation, LacdiNAc motifs, Lewis type antigens, and H blood group antigen), as well as additional modifications (sulfation and phosphorylation) (Supplementary Information, Tables S1 and S2-1–S2-25). Principal component analysis (PCA) of the abundance of N-glycan derived traits did not reveal a clear grouping between the glycosylation features and the CRC cell line differentiation (Supplementary Information, Figure S2). For instance, colon-like cell lines LS174T and LS180, as well as the undifferentiated cell line SW48 and the unassigned cell line SW1398, clustered together at the top of the score plot due to the high abundance of paucimannosidic N-glycans, (core/antenna) fucosylation, and LeA/X as well as sLeA/X antigens (Supplementary Information, Figure S2A). At the right-bottom panel, most colon-like cell lines clustered together with a few undifferentiated cell lines, including SW620, Caco2, RKO, and HCT115, and the unassigned cell line HCT8, driven by the high expression of oligomannosidic N-glycans, phosphorylation, bisection, LeB/Y antigens, and H antigens (Supplementary Information, Figure S2). We further explored the distribution of N-glycosylation features in two different classifications of CRC cell lines (classification was based on gene expression) [15]. Briefly, colon-like cell lines (Colo205, HT29, SW1116, KM12, SW948, LS174T, SW1463, LS180, and WiDr) were characterized by the high expression of gastrointestinal differentiation markers, while the undifferentiated cell lines (Caco2, Co115, LOVO, DLD-1, HCT15, HCT116, RKO, SW48, SW480, and SW620) were marked by upregulation of the EMT and TGF-β signatures. Cell lines T84, Colo320, LS411N, SW1398, C10, and HCT8, which were not characterized for their differentiation status, were kept as unassigned. The profound diversity of N-glycomic profiles was revealed among CRC cell lines (Figure 2). Regarding Lewis antigens, LeB/Y were only detected in five specimens (colon-like cell lines HT29, SW948, and LS180, and the undifferentiated cell lines SW480 and HCT8) with the highest abundance in HCT8 (0.8%), (Figure 2 and Supplementary Information, Table S3). The LS180 cell line expressed the highest abundance of LeA/X antigens (5.5%), followed by 4.5% in the colon-like cell line LS174T. Only three lines were found to express sLeA/X antigens (LS174T, LS180, and SW1116), all of them being colon-like cell lines (Figure 2 and Supplementary Information, Table S3). H blood group antigen was most abundant in the unassigned cell line HCT8 (2.3%), followed by the two undifferentiated cell lines Caco2 (1.0%) and SW480 (0.7%). In regard to sialylation, α2-3 sialylation was found to be highest in the colon-like cell line SW1463 (19.8%), followed by the undifferentiated cell lines Co115 (17.0%) and DLD-1 (14.9%). To note, α2-6 sialylation was expressed in all CRC cell lines, with the highest expression in the undifferentiated cell line HCT116 (25.4%). Furthermore, paucimannosidic N-glycans were detected in all cell lines, with the highest expression in the undifferentiated cell line SW48 (15.1%). Meanwhile, SW48 expressed the second most abundance of triantennary N-glycans (1.1%). The highest abundance of this feature, of all cell lines, was found in the unassigned cell line C10 (1.7%). Tetraantennary N-glycans were only expressed in three cell lines, including the unassigned cell line SW1398 (0.9%) and the undifferentiated cell lines SW48 and LOVO (Figure 2 and Supplementary Information, Table S3). The distribution of glycosylation features based on cell line classifications is illustrated in Supplementary Information, Figure S3, and Table S3. The N-glycans carrying LacdiNAc with or without fucose linked to GlcNAc via α1-3 linkage (GalNAc(β1-4)[+/−Fuc(α1-3)]GlcNAc(β1-3)GalNAc(β1-4)[+/−Fuc(α1-3)]GlcNAc(β1-), phosphorylation, bisection, and α2-3 sialylation, as well as the paucimannosidic N-glycans, were highly expressed in undifferentiated cell lines with a low expression of antenna fucosylation, LeB/Y, LeA/X, and the hybrid N-glycans (Supplementary Information, Figure S3). In contrast, the colon-like cell lines demonstrated a high abundance of sulfation, LeA/X, sLeA/X, LeB/Y, antenna fucosylation, and high levels of oligomannosidic, as well as hybrid N-glycans. Notably, antenna fucosylation and LeA/X were found to be expressed significantly higher in colon-like cell lines in comparison with undifferentiated cell lines (Supplementary Information, Figure S3 and Table S3). Previously, we performed a total N-glycome characterization of the same CRC cell lines panel using MALDI-TOF-MS [16]. A Spearman correlation analysis was conducted to determine the similarity between the two N-glycan datasets measured on two different platforms (PGC-nano-LC-ESI-MS and MALDI-TOF-MS) (Figure 3, Supplementary Information, Table S4). Significant correlations were found for the relative abundance of paucimannosidic and hybrid N-glycans, however, no correlation between the datasets for oligomannosidic and complex N-glycans was observed. The HexNAc ≥ Hex glycosylation trait (MALDI-TOF-MS) correlated positively with the bisection trait (PGC-nano-LC-ESI-MS). The HexNAc ≥ Hex trait can be seen as an indicator of bisection in complex-type N-glycans, though other glycosylation features such as truncated antennae, LacdiNAc motifs, Sda antigens, and blood-type A motifs can also shift the composition towards more HexNAc units, making the assessment of bisection levels ambiguous. In the current study, the presence of bisection is confirmed by negative mode MS/MS fragmentation spectra as well as retention time on PGC, thereby attributing the bisection trait with high confidence. As for antennarity, the diantennary N-glycans correlated between the two datasets. Moreover, (core)fucosylation in the present study correlated significantly with (mono)fucosylation measured by MALDI-TOF-MS. Antennae fucosylation (PGC-nano-LC-ESI-MS) showed a significant and strong correlation with multifucosylation (MALDI-TOF-MS), which also correlated positively with LeA/X, sLeA/X, LeB/Y, and H antigens measured in the present study. With the current application, the location of fucose can be identified with more certainty through diagnostic MS/MS fragments and the absence of fucose migration [33]. To illustrate the presence of the Z ions, m/z 350 and 553, as well as the Y ions, m/z 368 and 571, which indicates the fucose being linked to the innermost GlcNAc of N-glycans, i.e., core fucosylation. The presence of terminal B ion cleavages, m/z 510, and C ion, m/z 528, indicates terminally linked fucose on the N-glycan antenna commonly associated with Lewis antigen structures [26]. A strong positive correlation was found for (α2-6) sialylation in both datasets. However, no significant correlation was observed for α2-3 sialylation. Next to features overlapping with the MALDI-TOF-MS results, the PGC method provided additional, unique insights into CRC cell line N-glycosylation. The additional separation of isomers using the PGC-nano-LC-ESI-MS platform alongside diagnostic ions produced in the MS/MS spectra provided an in-depth structural characterization of the N-glycans and allowed us to identify the sequence and location of monosaccharides such as core fucosylation, Lewis structures, and blood group motifs. The presence of the D-221 ion, which is formed from the additional loss of the β1-4 linked GlcNAc from the D ion of bisected N-glycans, indicated the presence of bisecting GlcNAc, 1,3A cleavage ions, indicating the composition of antennae [26]. MS/MS spectra of the selected N-glycans were presented in the Supplementary Information, Figure S4. On the other hand, while present in low abundance, the MALDI-TOF-MS dataset has revealed more high-branching complex and hybrid structures. To summarize, next to the already obtained MALDI-TOF-MS information, the usage of PGC-nano-LC-ESI-MS proved to be a comprehensive and complementary tool for the structural identification of N-glycans. Recently, we explored the N-glycome of various acute myeloid leukemia (AML) cell lines and revealed the diversity of their N-glycosylation [34]. In the current study, we investigated the correlation of N-glycosylation features and corresponding GTs for both the AML and CRC cell lines (Figure 4A, Supplementary Information, Figure S5 and Table S5). The transcriptomic of the GT’s expression in the AML cell lines was obtained from a publicly available dataset [35]. Overall, a significant association was found for (core)fucosylation with FUT8 for the CRC cell lines. However, no significant correlation was observed for the AML cell lines (Figure 4A). The expression of (core)fucosylation between the AML and CRC cell lines was further explored, and this revealed a higher expression of (core)fucosylation in the AML cell lines (Figure 4B), although no significant difference was found between the AML and CRC cell lines regarding the transcriptomic expression level of FUT8 (Supplementary Information, Figure S6). FUT4/7/9 are involved in the expression of sLeX [36,37]. Contrary to most CRC cell lines, significant correlations were observed between LeA/X, sLeA/X, and FUT4/7/9 for the AML cell lines (Figure 4A). An overall higher expression of LeA/X and sLeA/X was found for the AML cell lines in comparison to the CRC cell lines (Figure 4B), with accordingly higher expression of the FUT4/7 in the AML cell lines compared to the CRC cell lines (Supplementary Information, Figure S6). The AML cell lines exhibited a high degree of (α2-3/6) sialylation, relatively, compared to the CRC cell lines (Figure 4B), which might result from the increased transcriptomic expression of ST3GAL1/3/4/6 and ST6GAL1 in AML cell lines in comparison to the CRC cell lines (Supplementary Information, Figure S6). To gain insight into the regulation of N-glycosylation in the CRC cell lines, the transcriptomic expression of relevant genes (GTs and certain transcription factors (TFs)) was selected and obtained from the Cancer Cell Line Encyclopedia public dataset based on their involvement in the biosynthesis of N-glycans [15]. A previous study has shown that certain TFs, such as TFs CDX1, ETS2, HNF1A, HNF4A, MECOM, and MYB are notably expressed in colon-like cell lines. In contrast, undifferentiated cell lines showed a significantly higher expression of other TFs (e.g., MLLT10, MSX1, SIX4, ZNF286A, and ZNF286B) [19]. In this study we found the GANAB gene (encoding the GT responsible for removal of the two innermost α1-3 linked glucose residues from Glc(2)Man(9)GlcNAc(2) oligosaccharide precursor) [38] to correlate significantly with ETS2. This, in turn, was positively associated with the oligomannosidic trait, although the latter relationship was insignificant (Figure 5A; Supplementary Information, Table S6). A significant positive association was demonstrated between MGAT1 (encoding a GT essential for the conversion of oligomannosidic to hybrid type N-glycans) and HNF4A, which showed a positive trend towards the association with hybrid type N-glycans expression (not significant). Additionally, MGAT3 (GT catalyzing the addition of N-acetylglucosamine in β1-4 linkage to core mannose of N-glycan to form bisected N-glycans) was significantly associated with HNF1A and HNF4A which, subsequently, coincreased along with the N-glycans bisection (Figure 5A). The enzyme involved in the biosynthesis of tri- and tetraantennary N-glycans (MGAT4B) positively associated with the TFs ETS2, HNF1A, HNF4A, MECOM, and MYB which, however, exhibited negative correlations (not significant) with tri- and tetraantennary N-glycans. In our study, FUT3, involved in the biosynthesis of LeA/X/B/Y antigens [39,40,41], showed a positive association with ETS2 and MYB, which significantly correlated with the LeA/X antigens, as well as with CDX1, which was in positive correlation with sLeA/X glycosylation. A similar pattern was observed for FUT4, involved in the expression of (s)LeX [36,42,43]. Notably, FUT6, its corresponding GT involved in the biosynthesis of E-selectin ligand sLeX [44,45], positively correlated with CDX1 and also revealed a positive association with the sLeA/X glycosylation trait. FUT9, a GT catalyzing the biosynthesis of the LeX antigen, positively correlated with HNF4A and showed a trend toward positive correlation with LeA/X (Figure 5B). Moreover, FUT2, catalyzing the biosynthesis of terminal α1-2 fucose in the H blood group antigen, showed a positive correlation with ETS2. However, no correlation was found between this TF and the H blood group antigen glycosylation trait, however, a slight positive correlation was seen with LeB/Y (Figure 5B). In this study, an in-depth characterization of the N-glycome of 25 CRC cell lines was conducted using PGC-nano-LC-ESI-MS/MS and revealed the diversity of the N-glycomic signatures among the CRC cell lines. Our platform allowed the separation of isomeric N-glycan species with structural elucidation based on MS/MS fragmentation patterns in negative ion mode. Currently, carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)19-9 are used as tumor markers in clinical practice for the diagnosis, prognosis, and monitoring of CRC patients [46,47,48,49,50]. Nonetheless, as these markers exhibit low specificities and suboptimal sensitivities, especially in the early stages of the disease [51,52,53,54], there is an urgent need for novel biomarkers and therapeutic targets. Cancer progression frequently correlates with N-glycome alterations [55], making the discovery of tumor-associated carbohydrate antigens (TACAs) a promising area for identifying the new molecular signatures of tumors for improved diagnostics, stratification, and targeted treatment [21,56]. Recently, we have investigated the glycomic profiles of GSL glycans in relation to CRC and revealed that colon-like cells are dominated by a high expression of glycans carrying (s)Le antigens, while, undifferentiated cell lines showed an increased level of glycans with the terminal blood group antigens H, A, and B [20]. When it comes to O-glycans, colon-like cell lines presented an upregulation of (s)Le antigens, while undifferentiated cell lines were dominated with truncated α2-6 core sialylated O-glycans, with specific cell lines expressing high levels of H blood group antigen [19]. Consistent with these previous findings, the present study demonstrated a high expression of (s)Le antigens in CRC colon-like cell lines (Figure 2). However, H blood group antigens were only found in limited quantities in undifferentiated cell lines. In another study, focusing on the comprehensive TACAson O-glycans in CRC primary tissues, revealed that specific (s)Le core two were exclusively expressed in tumors and absent in the normal mucosa from the same patients [21]. Additionally, N-glycan expression analyzed in the same set of tumor samples, revealed several N-glycans carrying (s)Le antigens exclusively expressed in tumor samples [57]. In this study, we found that (s)Le antigens were highly expressed in the colon-like cell lines LS180 and LS174T (Supplementary Information Table S3). A decrease of core fucosylated diantennary N-glycans and an increase of highly galactosylated, highly sialylated, and tetraantennary N-glycans were found in the plasma of CRC patients, in comparison to healthy individuals [58]. That variety of glycosylation phenotypes originating from different studies only corroborates the complexity of the glycosylation machinery and its multilevel regulation. Therefore, an integration of the glycosylation features on the glycoprotein and glycolipid levels appears as the most fruitful biomarker discovery strategy for further studies. It is important to note that the employed method of analysis has a significant impact on the resulting data pool. Previously, we characterized the total cell N-glycome of these CRC cell lines by MALDI-TOF-MS and concluded that they have a high potential to be used as glycobiological tumor model systems [16]. However, while MALDI-TOF-MS is efficient for high-throughput glycan profiling, it lacks the ability to separate glycan isomers or provide structural information when no separation is applied prior to the measurement [26]. Moreover, a derivatization strategy needs to be performed to prevent the loss of sialic acids during laser-assisted ionization [59]. In this study, we took a deeper dive into the total N-glycome of the CRC cell line panel by structural analysis using PGC-nano-LC-ESI-MS/MS, which is capable of separating isomeric glycans [26]. A total of 139 N-glycans could be identified and structurally characterized (Supplementary Information, Table S1). Statistically significant correlations were observed between the glycosylation features of both datasets (MALDI-TOF-MS versus PGC-nano-LC-ESI-MS; Figure 3 and Supplementary Information, Table S4). However, some differences in the resulting data were also observed between the two methods. While PGC-nano-LC-ESI-MS provided a better insight into the midrange mass N-glycan diversity, the coverage of the high-mass N-glycans was rather limited compared to MALDI-TOF-MS. This could be explained by the dynamic range and/or the sensitivity of the two methods. The relative intensities of these structures in the MALDI-TOF-MS dataset are relatively low and, as no separation is occurring in this method, all the present structural isomers’ mass contributes to the total intensity. In the case of PGC, the isomers would be separated and the intensity per isomer would be inevitably lower. In order to further explore this relationship, we have performed a correlation analysis between N-glycomic profile traits and TFs and sought unique gene and N-glycan expression patterns in the CRC cell lines compared to their AML counterparts (Figure 4). These two datasets revealed a highly different expression of glycosylation features accompanied by an alternative activation of GTs and regulation systems. Increasing evidence demonstrates N-glycans influencing the processing and functioning of GTs, including their secretion, stability, and substrate–acceptor affinity [60,61]. Growing evidence suggests that N-glycans play a crucial role in regulating the processing and function of GTs through facilitating the folding of the polypeptide chain, ensuring the correct subcellular localization of the protein, and preventing protein aggregation [62]. Thus, the observation of higher expression of (core)fucosylation, (α2-3/6) sialylation, LeA/X, and sLeA/X in AML cell lines compared to the CRC cell lines may partially explain the differences in the GT expression observed between the two types of cancer (Figure 4B). Furthermore, it is possible that TFs also play a role in regulating GT expression. However, little is known about TFs that can directly participate in the regulation of the expression of GTs. Further research is needed to fully understand the mechanisms by which TFs regulate glycans in cancer and how this knowledge can inform targeted treatment strategies for CRC. The biosynthesis and expression of N-glycans are primarily attributed to the series of actions of GTs and glycosidases. Hitherto, little was explored for potential regulatory layers. A separate study demonstrated that several regulatory processes such as post-transcriptional, translational, and protein degradation regulation are also involved in controlling steady-state protein abundances after the production of mRNA [63]. This means that transcript levels may be insufficient to accurately predict protein expression levels [64]. With regard to the expression of GTs, a previous study reported that signal peptide peptidase-like 3 (SPPL3) alters cellular N-glycosylation by the proteolytic release of the ectodomain of various GTs and glycosidase such as N-acetylglucosaminyltransferase V, β1-3, N-acetylglucosaminyltransferase 1 and β1-4 galactosyltransferase 1 [65]. Subsequently, the higher expression of SPPL3 leads to hypoglycosylation, and decreased SPPL3 expression causes hyperglycosylation [65]. Meanwhile, the activity of B3GNT5, a key enzyme responsible for the synthesis of the neolacto-series of GSLs, was suppressed by SPPL3, which notably affects the expression of GSL glycans on the cell surface [66]. Another study demonstrated that protease β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) is responsible for the proteolytic cleavage of the beta-galactoside alpha-2,6-sialyltransferase 1 enzyme (encoded by ST6GAL1) [67]. These findings suggest that the protease-mediated degradation of GTs may result in a poor correlation between transcript level and protein level. That may partly explain the differences in correlations between mRNA expression of GTs with glycosylation features in CRC and AML found in the present study (Figure 4). In addition, N-glycan diversity may be influenced by several factors, such as substrate availability for GTs and glycosidases in Golgi, nucleotide sugar metabolism, transport rates of the glycoprotein through the lumen of the ER and Golgi, and the proximity of an N-glycan attachment sequon to a transmembrane domain [68], which may also contribute to the unexpected observations between GTs and the glycosylation features in CRC cell lines. Another relationship we have explored is an association between highly fucosylated N-glycans and the expression of CDX1—caudal-related homeobox protein 1 (CDX1)—that, as a TF, plays an essential part in the development, differentiation, and homeostasis of the gut [69,70], and this link was previously reported for CRC cell lines [16]. However, in the present study, no significant correlation was revealed, which may be attributed to the application of correlation analysis on all CRC cell lines instead of the CRC cell lines with a high expression of CDX1. However, (s)Le structures, which are promising targets for novel treatment strategies [21], had a strong correlation with CDX1, which, in turn, is positively associated with FUT3/6 (Figure 5). Corroborating our findings, a previous study showed that a high level of CDX1 expression and less invasive and aggressive phenotype was associated with a higher abundance of multifucosylation on N-glycans in the CRC cell lines and was supported by the upregulation of GTs involved in antenna fucosylation such as FUT3/5/6 (Figure 5) [16,71], Taking into account the previous and current findings, we hypothesize that CDX1 may play an essential role in the formation of (s)Le antigens on colon-like cell lines via the regulation of the corresponding GTs (mainly FUT3/6). However, further research is needed to validate if other TFs may conduct the fucosylation patterns in the undifferentiated cell lines (e.g., Caco2). In conclusion, our detailed analysis of 25 CRC cell lines revealed a distinct diversity of N-glycomic profiles and showed a strong relationship with previous findings for the same set of cell lines measured by MALDI-TOF-MS. Our results suggest that, from the glycosylation features’ point of view, using different platforms for similar samples does not yield conflicting results and demonstrates a high degree of similarity. Instead, the observed differences are complimentary in nature. Our data also indicate that certain glycosylation features have a cell type-specific distribution among different CRC cell line classifications. Namely, colon-like cell lines exhibit a relatively high expression of (s)Le antigens, while undifferentiated cell lines are characterized by an upregulation of paucimannosidic, bisected N-glycans, α2-3 sialylation, and N-glycans carrying with (fucosylated) LacdiNAc. Associations were observed between TF CDX1 and (s)Le antigen, and corresponding GTs indicated that the potential mechanism of expression and regulation of glycosylation features, especially, (s)Le antigen, which might be under the control of the corresponding GTs FUT3/6 regulated by CDX1. Trifluoroacetic acid (TFA), guanidine hydrochloride (GuHCl), sodium borohydride, sodium chloride, DL-dithiothreitol (DTT), ammonium bicarbonate (ABC), fetuin from fetal bovine serum, cation exchange resin Dowex 50W X8 and ammonium acetate were obtained from Sigma Aldrich (St. Louis, MO, USA). Ethanol, NaCl, and methanol (MeOH) were purchased from Merck (Darmstadt, Germany). Acetonitrile LC-MS grade (MeCN) was acquired from Biosolve (Valkenswaard, The Netherlands), KOH and glacial acetic acid were obtained from Honeywell Fluka (Charlotte, NC, USA), and PNGase F (Flavobacterium meningosepticum recombinant in E. coli) from Roche (Mannheim, Germany). SPE bulk sorbent Carbograph was from BGB Analytik USA LLC (Alexandria, VA, USA), MultiScreen® HTS 96-multiwell plates (pore size 0.45 m) with a high protein-binding membrane (hydrophobic Immobilon-P PVDF membrane) and 96-well PP Microplate were obtained from Millipore (Amsterdam, The Netherlands). The 96-well PP filter plate from Orochem technologies (Naperville, IL, USA) and isopropanol were purchased from Biosolve Chimie (Dieuze, France). T75 cell culture flasks were obtained from Greiner-Bio One B.V. (Alphen aan de Rijn, The Netherlands) and Hepes-buffered RPMI 1640 and Dulbecco’s Modified Eagle (DMEM) culture media were obtained from Gibco (Paisley, UK). Fetal bovine serum (FBS) and penicillin/streptomycin were bought from Invitrogen (Carlsbad, CA, USA) and 0.5% trypsin-EDTA solution 10× was from Santa Cruz Biotechnology (Dallas, TX, USA). Ultrapure water (mQ) generated by the ELGA system (ELGA, High Wycombe, UK) maintained at ≥18 MΩ was used for all solvent preparations and washing steps. Human CRC cell lines were provided by the Department of Surgery of the Leiden University Medical Center (LUMC, Leiden, the Netherlands) and the Department of Pathology of the VU University Medical Center (VUmc, Amsterdam, The Netherlands). The LUMC cell lines were cultured with Hepes-buffered RPMI 1640 medium with 2 mM L-glutamine with the supplement of penicillin (5000 IU/mL), streptomycin (5 mg/mL), and 10% (v/v) FBS. The VUmc cell lines were cultured with Dulbecco’s Modified Eagle (DMEM) medium and were supplemented with 10% (v/v) FBS and antibiotics, with the exception of cell line KM12 which was cultured with RPMI 1640 medium with L-glutamine, 10% FCS, and antibiotics. The cells were kept in a cell incubator with 5% CO2 at 37 °C in humidified air. The cells were harvested when 80% confluence was reached and a trypsin/EDTA solution in 1× PBS was added to detach cells, followed by termination of the enzyme activity by a mixture of trypsin and a medium in a ratio of 2:5 (v/v). Cell counting was performed with a TC20 automated cell counter based on trypan blue staining. After washing the cells twice with 5 mL of 1× PBS, the cells were aliquoted to 2 × 106 cells/mL of 1× PBS and centrifuged at 1500× g for 3 min. The cell pellets were stored at −20 °C. N-glycans were released from the cells as previously described with some slight modifications [72]. In brief, 96-well plates with hydrophobic Immobilon-P PVDF membrane were preconditioned with 200 µL 70% ethanol, and 3 × 200 µL mQ water. Simultaneously, to resuspend the cell pellets containing 2 × 106 cells, 100 μL of lysis buffer were added, followed by 60 min sonication at 60 °C. In total, 25 µL of the cell lysate (containing 5 × 105 cells) was applied to the preconditioned PVDF membrane wells. Protein denaturation was performed by adding 75 mL of a denaturation mixture, consisting of 72.5 µL 8 M GuHCl and 2.5 µL 200 mM DTT, to each well. Subsequently, the sample mixture was incubated in a humidified plastic box at 60 °C for 60 min. The plate was washed 3 times with mQ to remove the remaining denaturation agents via centrifugation at 500× g for approximately 2 min. The N-glycans were released from the denatured proteins by adding, subsequently, 2 µL of PNGase F (20 units) and 13 µL of mQ to each well followed by incubation at 37 °C for 15 min. Additionally, 15 µL of mQ water was added to each well and an overnight incubation was started in a humidified plastic box at 37 °C. Released N-glycans were collected by centrifugation at 500× g for 1 min and by washing the wells 3 times with mQ. The collected flow-through and washes were pooled for further processing. To hydrolyze the glycosylamine forms of the released N-glycans, 20 µL of 100 mM ammonium acetate (pH 5) was added to the collected N-glycans, followed by horizontal shaking for 10 min. Finally, the samples were dried in a SpeedVac concentrator. To reconstitute and reduce the released N-glycans [72], 40 µL of freshly prepared 1M NaBH4 in 50 mM KOH were added to each well. The samples were incubated in a humidified plastic box for 3 h at 50 °C. Afterward, the reaction was quenched by adding 4 µL of glacial acetic acid to each well, which also neutralized the sample. Samples were desalted in 96-well filter plates self-packed with cation exchange resin Dowex 50W X8. The packed plate was preconditioned by washing 3 times with 100 µL of 1 M HCl, followed by applying 3 times 100 µL of MeOH and 3 times 100 µL of mQ with centrifugation of 500 rpm for 1 min in between. The samples were applied onto the preconditioned plate and centrifuged at 500 rpm for 1 min followed by washing with two times 40 µL of mQ using centrifugation (2000 rpm for 3 min). The collected flow through and wash were combined and dried using a SpeedVac concentrator. To remove the remaining borate, 150 µL of MeOH were added 3 times to each well during the drying procedure. The cleanup of the samples was carried out on a 96-well filter plate packed with 60 µL (approximately 6 mg) of bulk sorbent carbograph slurry in MeOH which was preconditioned by applying 3 times 100 µL of 80% MeCN in mQ containing 0.1% TFA, subsequently followed by adding 3 times 100 µL mQ with 0.1% TFA. After sample loading (in 0.1% TFA), the columns were washed by applying 3 times 100 µL mQ with 0.1% TFA followed by elution adding 3 times 40 µL of 60% MeCN in mQ containing 0.1% TFA. The eluate was dried in a SpeedVac concentrator. The purified N-glycan alditols were resuspended in 15 µL of mQ. A total of 5 µL of the sample was loaded onto a Hypercarb PGC trap column (5 µm Hypercarb Kappa, 320 µm × 30 mm, packed in the house) with 98% buffer A (10 mM ammonium bicarbonate) at 6 μL/min of loading flow. The N-glycans were separated on a Hypercarb PGC nanocolumn (3 µm Hypercarb Kappa, 100 µm × 100 mm, in house packed) with a multistep gradient of buffer B (60% MeCN in 10 mM ABC) of 2–9% in 1 min, followed by 9–49% in 80 min at a flow rate of 0.6 µL/min using the Dionex Ultimate 3000 nanoLC system. The column was washed with a 95% buffer B for 10 min. The column was held at a constant temperature of 35 °C. The separated N-glycans were detected by an amaZon speed ion trap MS with a capillary voltage set at 1000 V in negative mode, the dry gas temperature at 280 °C at a flow of 3 L/min and the nebulizer at 3 pounds per square inch (psi). The target mass was set at m/z 1200. MS spectra were acquired within a range of m/z 500-1850. MS and MS spectra were generated by collision-induced dissociation (CID) on the top 3 precursors with an isolation width of 3 Th. To enhance sensitivity, isopropanol was used as a dopant for the dopant-enriched nitrogen gas [73]. The N-glycan analysis workflow for the cells, prepared in a 96-well plate, is described in Supplementary Information, Figure S7. Identification of N-glycan structures was performed on the basis of accurate mass, retention time on the PGC column previously described diagnostic fragment ions (e.g., cross-ring fragments), and known biosynthetic pathways of N-glycans [26,68]. A single-letter code was used to refer to the monosaccharides: H for hexose, N for N-acetylhexosamine, F for fucose, and S for N-acetylneuraminic acid. Data analysis was conducted with Bruker Compass DataAnalysis software (version 5.0). Briefly, extracted ion chromatograms were produced by extracting the theoretical mass of the first three isotopes of all observed (singly and doubly charged) species. The peak area under the curve was produced by integrating each peak with a signal to noise ratio ≥ 6 for all the technical and biological replicates. Relative quantification was calculated on the total area of all N-glycans detected in one sample normalized to 100%. “R” software (version 4.2.1) was used for further data analysis and visualization with packages “tidyverse”, “readxl”, “corrplot”, “Rcpm”, “pcaMethods”, “stringi”, “ggplot2”, “ggrepel”, “reshape2”, “ggpubr” and “tidyHeatmap”.

PMC10003091

Mingyan Xu,Junling Zhang,Xuemei Lu,Fan Liu,Songlin Shi,Xiaoling Deng

MiR-199a-5p-Regulated SMARCA4 Promotes Oral Squamous Cell Carcinoma Tumorigenesis

01-03-2023

SMARCA4,miR-199a-5p,oral squamous cell carcinoma,EMT

SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4, also known as BRG1), an ATPase subunit of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex, plays an important regulatory role in many cytogenetic and cytological processes during cancer development. However, the biological function and mechanism of SMARCA4 in oral squamous cell carcinoma (OSCC) remain unclear. The present study aimed to investigate the role of SMARCA4 in OSCC and its potential mechanism. Using a tissue microarray, SMARCA4 expression was found to be highly upregulated in OSCC tissues. In addition, SMARCA4 upregulate expression led to increased migration and invasion of OSCC cells in vitro, as well as tumor growth and invasion in vivo. These events were associated with the promotion of epithelial–mesenchymal transition (EMT). Bioinformatic analysis and luciferase reporter assay confirmed that SMARCA4 is a target gene of microRNA miR-199a-5p. Further mechanistic studies showed that the miR-199a-5p regulated SMARCA4 can promote the invasion and metastasis of tumor cells through EMT. These findings indicate that the miR-199a-5p- SMARCA4 axis plays a role in tumorigenesis by promoting OSCC cell invasion and metastasis through EMT regulation. Our findings provide insights into the role of SMARCA4 in OSCC and the mechanism involved, which may have important implications for therapeutic purposes.

MiR-199a-5p-Regulated SMARCA4 Promotes Oral Squamous Cell Carcinoma Tumorigenesis SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4, also known as BRG1), an ATPase subunit of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex, plays an important regulatory role in many cytogenetic and cytological processes during cancer development. However, the biological function and mechanism of SMARCA4 in oral squamous cell carcinoma (OSCC) remain unclear. The present study aimed to investigate the role of SMARCA4 in OSCC and its potential mechanism. Using a tissue microarray, SMARCA4 expression was found to be highly upregulated in OSCC tissues. In addition, SMARCA4 upregulate expression led to increased migration and invasion of OSCC cells in vitro, as well as tumor growth and invasion in vivo. These events were associated with the promotion of epithelial–mesenchymal transition (EMT). Bioinformatic analysis and luciferase reporter assay confirmed that SMARCA4 is a target gene of microRNA miR-199a-5p. Further mechanistic studies showed that the miR-199a-5p regulated SMARCA4 can promote the invasion and metastasis of tumor cells through EMT. These findings indicate that the miR-199a-5p- SMARCA4 axis plays a role in tumorigenesis by promoting OSCC cell invasion and metastasis through EMT regulation. Our findings provide insights into the role of SMARCA4 in OSCC and the mechanism involved, which may have important implications for therapeutic purposes. Oral squamous cell carcinoma (OSCC) is the most common malignancy in the head and neck region, accounting for approximately 2% of new cancer cases and 1.8% of mortality worldwide in 2021 [1,2,3]. In the past two decades, numerous studies have shown that tumor metastasis is one of the main reasons the 5-year survival rate of OSCC is lower than 50% [4]. Therefore, understanding the molecular mechanism of metastasis of OSCC is of great significance to identifying new therapeutic intervention targets, developing new anticancer drugs, and improving the survival rate. Epithelial–mesenchymal transition (EMT) is a major driving mechanism of the invasion and metastasis of tumor cells [5]. The hallmark of EMT is E-cadherin downregulation [6] and vimentin upregulation [7], resulting in loss of intercellular adhesion and increased cell motility [8]. SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4), the core ATPase subunit of the human SWI/SNF chromatin remodeling complex, regulates gene transcription through the regulation of chromatin structure [9]. It plays an essential role in a variety of cellular processes including differentiation, proliferation, and DNA repair [10,11,12]. Increasing evidence suggests that SMARCA4 plays an important role in tumorigenesis [13,14,15,16]. However, whether SMARCA4 acts as a tumor suppressor gene or oncogene remains controversial [17,18]. SMARCA4 was originally reported as a tumor suppressor gene due to its inactivating mutations or downregulation of its expression in several cancers and cancer cell lines [19,20,21,22,23]. However, SMARCA4 is also known to act as oncogene to promote tumorigenesis due to its high expression level found in certain cancers, including prostate cancer [24], breast cancer [25], liver cancer [26], and gastric cancer [27]. As an oncogene, several studies have shown that SMARCA4 promotes the occurrence and development of tumors by promoting the invasion and metastasis of tumor cells through the process of EMT [12,25,28,29]. In OSCC, no gene mutation but increased mRNA expression of SMARCA4 was detected in 62% of OSCC samples compared with normal controls [30]. However, the mechanism of SMARCA4 in promoting OSCC remains largely unknown. MicroRNAs (miRNAs) are endogenous non-coding RNAs that modulate gene expression at the post-transcriptional level [31]. Alterations in miRNA expression have been implicated in many cancers, including OSCC [32,33,34]. Low expression of several miRNAs has been found in OSCC [35,36], among which downregulation of miR-199a-5p is thought to be closely related to the recurrence and progression of OSCC [35,36,37,38]. However, whether the upregulation of SMARCA4 in OSCC is due to reduced expression of miR-199a-5p in OSCC needs to be investigated. The aim of the current study was to investigate the functional significance of SMARCA4 in promoting OSCC tumorigenesis both in vitro and in vivo, and the mechanisms involved. To examine the role of SMARCA4 in the progression of OSCC we performed tissue microarray analysis by IHC staining to assess the SMARCA4 expression levels in normal epithelial tissues and OSCC tissues. SMARCA4 was detected mainly in the nucleus of squamous carcinoma cells (weak staining in the region of squamous pearl formation) in about 75% of OSCC tissue samples, and normal oral mucosa specimens showed positivity mainly in sporadic cells of basal layers (Figure 1A). The proportion of SMARCA4-positive cells and the intensity of SMARCA4 protein immunostaining further confirmed that the SMARCA4 expression level in OSCC was significantly higher than that in normal tissues (Figure 1B). We also analyzed the SMARCA4 mRNA and protein expression levels in different OSCC cell lines, including SAS and CAL-27, in comparison to normal human epithelial cells HaCaT. The qRT-PCR and western blot analysis revealed increased expression levels of SMARCA4 mRNA and protein in both OSCC cell lines compared to that in HaCaT cells (Figure 1C,D). Therefore, the upregulation of SMARCA4 in the OSCC tissues is positively correlated with tumor progression, suggesting that SMARCA4 may play an oncogenic role in OSCC. Since tumor invasion and metastasis are closely related to OSCC progression, we examined whether SMARCA4 is involved in OSCC cell migration and invasion. We first examined the effect of SMARCA4 overexpression on the invasion and metastasis of OSCC cells through a series of in vitro functional assays in OSCC cells (SAS and CAL-27) transiently transfected with a plasmid expressing SMARCA4 (pCMV5- SMARCA4). The expression of SMARCA4 increased five times for SAS cells and three times for CAL-27 cells after transfection with a pCMV5- SMARCA4 construct. The wound healing assay (Figure 2A,B) showed that overexpression of SMARCA4 markedly enhanced the mobility of SAS and CAL-27 cells. The Transwell migration assay showed that overexpression of SMARCA4 significantly promoted SAS and CAL-27 cell migration and invasion compared with their corresponding NC groups (Figure 2C,D). The invasion and eventual metastasis of cancer cells require epithelial cells to undergo a process of de-differentiation known as EMT [39]. Loss of E-cadherin and upregulation of mesenchymal markers, such as vimentin, are thought to be key events in EMT. The immunofluorescence experiment showed that overexpression of SMARCA4 markedly attenuated E-cadherin expression in OSCC cells, whereas vimentin expression was upregulated (Figure 2E,F). The western blot analysis further confirmed these results (Figure 2G,H). To further elucidate the effect of SMARCA4 expression on OSCC cell migration and invasion, we examined the effect of SMARCA4 knockdown on the invasion and metastasis of OSCC cells. The expression of SMARCA4 was knocked down about 70%–80% in both SAS and CAL-27 cells after transfection with the shRNA target SMARCA4 constructs. Wound healing assay of OSCC cells (SAS and CAL-27) transiently transfected with sh-NC, or sh-SMARCA4 (Figure 3A,B,C,D) showed that SMARCA4 knockdown markedly reduced the mobility of SAS and HSC3 cells. The Transwell migration assay (Figure 3E,F) additionally revealed that suppression of SMARCA4 expression markedly reduced OSCC cell migration and invasion, and these findings were confirmed by quantitative analysis (Figure 3G,H). Overall, these results showed that overexpression of SMARCA4 significantly promoted OSCC cell migration and invasion, whereas inhibition of SMARCA4 reduced OSCC cell migration and invasion. We investigated the underlying mechanism involved in SMARCA4 upregulation in OSCC. We used bioinformatic analysis tools and database, including ENCORI and MiRDB to predict a potential microRNA that may directly target SMARCA4. The results showed that SMARCA4 3′UTR has a conserved seed region for miR-199a-5p (Figure 4A). Therefore, we constructed plasmids containing the partial WT or MUT sequences of the 3′-UTR of SMARCA4 with miR-199a-5p target sites. The dual-luciferase assay results with these constructs showed that co-transfection of the WT plasmid with miR-199a-5p mimics significantly inhibited the relative luciferase activity compared with the co-transfection the WT plasmid with mimics NC, while co-transfection of the MUT plasmid with miR-199a-5p mimics blocked the inhibition of the luciferase activity by the WT plasmid, thus preventing the reduction of luminescence intensity (Figure 4B). In addition, significantly increased luciferase activity was observed in the group co-transfected with the WT plasmid and miR-199a-5p inhibitor, compared to the group co-transfected with the WT plasmid and inhibitor NC. In contrast, co-transfection of the MUT plasmid and miR-199a-5p inhibitor has no effect on luminescence intensity compared to co-transfection of the MUT plasmid with inhibitor NC (Figure 4C). These findings indicated that miR-199a-5p directly binds to specific sites in the 3′-UTR of SMARCA4. Thus, we examined the regulatory effect of miR-199a-5p on SMARCA4 expression in OSCC cells. SAS and CAL-27 cells were transfected with miR-199a-5p mimics or miR-199a-5p inhibitors, along with their corresponding NCs, and the transfection efficiency was assessed by qRT-PCR (Figure 4D,E). The results (Figure 4F–I) revealed that miR-199a-5p mimics markedly reduced SMARCA4 mRNA and protein expression, whereas inhibition of miR-199a-5p with its inhibitor significantly increased SMARCA4 mRNA and protein expression. Together, these results indicate that miR-199a-5p regulates the expression of SMARCA4 and SMARCA4 is a target gene of miR-199a-5p in OSCC cells. We firstly compared the expression levels of miR-199a-5p in normal epithelial cell line HaCaT and OSCC cells to examine the effect of miR-199a-5p on OSCC cell migration and invasion. The results showed that the miR-199a-5p expression level was significantly downregulated in OSCC cells, compared with HaCaT cells (Figure 5A). Next, the results of the wound healing assay showed that transfection with miR-199a-5p mimics dramatically reduced the migration capacity of SAS and CAL-27 cells within 6 h (Figure 5D,E), while miR-199a-5p inhibition restored the migration ability of SAS and CAL-27 cells within 6 h (Figure 5F,G). Additionally, the Transwell migration assay also revealed that SAS and CAL-27 cells transfected with miR-199a-5p mimics had less migratory and invasive ability than their corresponding mimics NC groups (Figure 6A,B). In contrast, miR-199a-5p inhibition increased the migration and invasion ability of SAS and CAL-27 cells compared with the corresponding inhibitor NC groups (Figure 6D,E). In addition, transfection with miR-199a-5p mimics significantly increased the E-cadherin protein expression level, whereas the vimentin protein level was decreased in OSCC cells (Figure 5B). Having demonstrated that SMARCA4 is a direct target gene of miR-199a-5p in OSCC cells, we hypothesized that the role of SMARCA4 in OSCC cell migration and invasion is regulated by miR-199a-5p. To verify this hypothesis, we first investigated whether SMARCA4 overexpression can rescue the miR-199a-5p mimics-mediated inhibition of OSCC cell migration and invasion. To this end, we conducted various assays on SAS cells transfected with miR-199a-5p mimics alone, or co-transfected with miR-199a-5p mimics and SMARCA4. The results of the wound healing assays and Transwell assays demonstrated that the migration and invasion ability of SAS cells was restored by co-transfection of SMARCA4 with miR-199a-5p compared to cells transfected with miR-199a-5p only (Figure 7A,C), and these results were confirmed by quantitative analysis (Figure 7B,D). We also examined the effect of silencing SMARCA4 on the OSCC cell migration and invasion promoted by the inhibition of miR-199a-5p -. As expected, SMARCA4 inhibition successfully attenuated OSCC cell migration and invasion mediated by inhibition of miR-199a-5p (Figure 7E,G), and the results were also verified by quantitative analysis (Figure 7F,H). In summary, the above results suggest that the role of SMARCA4 in OSCC cell migration and invasion is regulated by miR-199a-5p. To further elucidate the tumorigenesis effect of SMARCA4 on OSCC in vivo, we examined the effect of SMARCA4 inhibition on tumor growth using a xenografts model in nude mice. As shown in Figure 8A, the xenograft tumors formed in mice of the sh-SMARCA4 group (with an average size of tumors about 100.84 ) were significantly smaller than those in the sh-NC group (with an average size of tumors about 374.6 ). In addition, the tumor growth rate (Figure 8B) and the tumor weight (Figure 8C) with SMARCA4 knocked down were significantly lower than those of the control group. The qRT-PCR analysis (Figure 8E) and immunohistochemistry staining analysis (Figure 8D) showed that the SMARCA4 level was significantly lower in the SMARCA4 knockdown group than that in the control group. The measurement of the changes in E-cadherin and vimentin levels in vivo revealed, as shown in Figure 8D, that E-cadherin was significantly upregulated, whereas vimentin was downregulated in the sh-SMARCA4 group compared with the sh-NC group (Figure 8D). These results further confirmed that SMARCA4 promotes the growth and metastasis of OSCC in vivo. Surprisingly, the measurement of the mRNA expression level of miR-199a-5p (Figure 8E) showed that the miR-199a-5p expression level was highly upregulated in the sh-SMARCA4 group. Previous studies have revealed that SMARCA4 plays a tumor-suppressive or oncogenic role in a context-dependent manner in various cancers. However, the function of SMARCA4 in OSCC remains unclear. This study investigated the potential role of SMARCA4 in OSCC tumorigenesis and its underlying regulatory mechanisms. Our results revealed that SMARCA4 is highly expressed in OSCC. Furthermore, SMARCA4 was found to be involved in the tumorigenesis of OSCC in vivo. We further found that miRNA 199a-5p directly targets SMARCA4 to modulate the EMT process, which may be an important link between SMARCA4 and OSCC cell migration and invasion. This study, for the first time, provides in vivo and in vitro evidence supporting the oncogenic role of SMARCA4 in OSCC tumorigenesis. SMARCA4 is one of the most frequently mutated chromatin remodeling ATPases in cancer, and it manifests itself in a highly tumor-specific and tissue-specific manner [16,40]. Numerous studies have suggested that SMARCA4 is involved in tumorigenesis as a tumor suppressor, mainly through its loss-of-function mutations. However, mutation of the SMARCA4 gene was not detected in OSCC [30]. In fact, SMARCA4 mRNA level was found to be significantly upregulated in OSCC patients compared with that in matched normal controls [30]. Our results also showed that SMARCA4 is upregulated in both OSCC tissues and cell lines, which is consistent with a previous study [30]. Moreover, injection with SMARCA4-knockout SAS cells into nude mice significantly reduced tumor development. These findings strongly support the notion that SMARCA4 functions as an oncogene rather than a tumor suppressor gene in OSCC. In line with our finding, SMARCA4 has also been found to be highly upregulated and promote cancer development in other organ systems, such as prostate cancer [24], breast cancer [25], liver cancer [12], gastric cancer [41] and melanoma [29]. However, SMARCA4 has also been shown to be a tumor suppressor in various cancers, including lung cancer, colorectal cancer, and pancreatic cancer. Interestingly, SMARCA4 played both tumor-suppressive and oncogenic roles at distinct stages of pancreatic cancer formation [42]. Although its role in carcinogenesis remains controversial, it is generally recognized that SMARCA4 plays a dual role depending on the tissue type and cellular context. SMARCA4 is involved in many cellular processes, some of which are associated with cancer development, such as differentiation, development, cell adhesion, growth control, metabolism, and DNA repair. Previous studies have shown that overexpression of SMARCA4 is involved in the development of various tumors by promoting tumor cell invasion and motility [12,25,28,29]. However, the specific function of SMARCA4 in OSCC remains unclear. In this study, although the efficiency of individual oral squamous cell carcinomas cells was different after transfection target SMARCA4 construct (overexpression or knockdown of SMARCA4), the transfection efficiency had no effect on OSCC cell migration and invasion ability. The different transfection efficiency might be due to experimental OSCC cells obtained from different OSCC individuals with their own genetic backgrounds. Therefore, the results of this study strongly support the notion that SMARCA4 is involved in the tumorigenesis of OSCC by promoting OSCC invasion and metastasis. EMT is an essential process in cancer progression and metastasis [43,44,45]. During EMT, cells lose their plasticity, which facilitates cell migration and invasion. The typical biological changes in EMT are the decreased expression of the epithelial marker E-cadherin and the increased expression of mesenchymal markers, such as vimentin [46]. It has been reported that SMARCA4 synergizes with RUNX2 to promote EMT in colorectal cancer cells [47]. SMARCA4 promotes gastric cancer metastasis by suppressing E-cadherin expression and increasing vimentin expression [48]. Indeed, our study also showed that SMARCA4 regulates EMT-driven gene transcription to induce metastasis. Our results also showed that overexpression of SMARCA4 significantly decreased E-cadherin expression, but upregulated vimentin levels in OSCC cancer cell lines. These results were also confirmed in an in vivo nude mouse model. SMARCA4 depletion led to a marked decrease in the endogenous levels of E-cadherin that was coupled with an elevation of vimentin expression in the nude mouse model. It is therefore plausible that SMARCA4 promotes OSCC metastasis through EMT. As a key component of the SWI/SNF chromatin remodeling complex, SMARCA4 plays a key role in regulating chromatin structure and gene transcription. However, the upstream regulation of the SMARCA4 gene expression remains largely elusive. The miRNAs represent a class of endogenous small non-coding RNAs that regulate gene expression at the posttranslational level and are important regulators of oncogenes and tumor suppressor genes in various tumors, including OSCC [33,49,50]. Several miRNAs have been reported to regulate SMARCA4 gene expression, including miR-199a-5p [51,52,53,54]. According to the previous study, miR-199a-5p is one of the most downregulated miRNAs in OSCC [35]. We, therefore, hypothesized that SMARCA4 upregulation may be partially due to the low expression of miR-199a-5p in OSCC. Through bioinformatic analysis and luciferase reporter assay, we confirmed that miR-199a-5p directly targets SMARCA4 in OSCC cell lines. Moreover, miR-199a-5p mimics significantly decreased SMARCA4expression levels, whereas miR-199a-5p inhibitor restored the SMARCA4 expression levels. These results indicate that SMARCA4 is a direct target gene of miR-199a-5p. Importantly, in this study, the expression of miR-199a-5p was low in OSCC cell lines with a high expression of SMARCA4. In addition, the miR-199a-5p expression level was significantly upregulated in the nude mouse model with SMARCA4 knockdown. These results suggested that there may be a negative regulatory relationship between SMARCA4 and miR-199a-5p, which may partially explain why SMARCA4 has been shown to be either overexpressed or downregulated in a variety of tumors. In these regards, SMARCA2 (also known as BRM), another catalytic subunit of the SWI/SNF complex, has been reported to form a double-negative feedback loop with miR-199a-5p in cancers [55]. Further research is warranted to corroborate the findings of the current study. Previous studies have shown that miR-199a-5p plays a suppressive role in OSCC [35,37,38]. Accordingly, several mechanisms appear to be involved, including the inhibition of cancer cell migration and invasion by inhibiting EMT. Our study also showed that miR-199a-5p inhibited OSCC migration and invasion through inhibition of the EMT. These miR-199a-5p effects were in contrast to those of SMARCA4, further indicating the negative relationship between SMARCA4 and miR-199a-5p. In conclusion, our study showed for the first time that SMARCA4 plays an oncogenic role in OSCC tumorigenesis. SMARCA4 was highly expressed in OSCC due in part to the low expression of miR-199a-5p. As a result, the high expression of SMARCA4 promoted OSCC cell migration and invasion through EMT, and the knockdown of SMARCA4 in vivo significantly suppressed OSCC metastasis (Figure 9). Therefore, the novel miR-199a-5p-regulated-SMARCA4 axis may serve as a novel potential diagnostic and anticancer therapeutic target in OSCC. The human keratinocyte cell line HaCaT was purchased from the Kunming Cell Bank of the Chinese Academy of Sciences (Kunming, China). The human OSCC cell line SAS was purchased from Japanese Collection of Research Bioresources (JCRB) cell bank (Tokyo, Japan). The CAL-27 cell line was obtained from the National Infrastructure of Cell Line Resources (NICR, Wuhan, China), All cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM), and supplemented with penicillin (100 U/mL), glutamine (100 U/mL), streptomycin (100 U/mL), and 10% fetal bovine serum (FBS), in a humidified atmosphere containing 5% CO2. A human oral squamous cell carcinoma tissue microarray, containing 40 OSCC tissues and 8 normal oral mucosa tissues, was obtained from Alina Biological Technology Company (Xi’An, China). Immunohistochemistry (IHC) staining was conducted as previously described [56] using anti-SMARCA4 antibody (1:200, #49360S, Cell Signaling Technology, Danvers, MA, USA). The images were obtained by M8 Digital Scanning Microscope System (Precipoint, Freising, Germany). The images were examined independently by a pathologist. Optical density analysis of SMARCA4 expression in every piece of tissue (including 8 normal tissues and 40 OSCC tissues) was quantified by using Image Pro Plus version1 1.48 software. The SMARCA4 expressions were statistically analyzed using unpaired t-test. Mimics and inhibitors of miR-199a-5p and corresponding negative control (NC) were synthesized by GenePharma Co., Ltd. (Shanghai, China). The oligonucleotide sequences are listed in Table 1. Transfections were performed using siRNA-mate (GenePharma Co, Ltd., Shanghai, China), according to the manufacturer’s instructions. The human SMARCA4 expression construct was cloned into vector pCMV5-Flag (Addgene, Watertown, MA, USA), and an empty pCMV5-Flag vector was used as a negative control. Transfections were performed using Metafectene K4 (Biontex Laboratories GmbH, Munich, Germany) according to the manufacturer’s instructions. In order to construct a stable low-expression SMARCA4 lentivirus system, the SMARCA4-targeted short hairpin RNA (shRNA) sequences were synthesized and cloned into the lentiviral vector pLKO.1 (TRC Human SMARCA4 shRNA; Open Biosystems Inc., Huntsville, AL, USA). The recombinant plasmid pLKO.1-sh-SMARCA4 was verified by DNA sequencing. The pLKO.1-sh-SMARCA4, and packaging plasmids pVSV-G, and pHR (HanBio Therapeutics, Shanghai, China) were co-transfected into 293T cells using the TurboFect Transfection Reagent (Thermo Fisher Scientific Inc., Waltham, MA, USA) to produce pLKO.1-sh-SMARCA4 lentivirus. After transfection for 24 h, viral supernatants were collected to infect SAS or CAL-27 cells for 72 h. In all, 2 mg/mL puromycin (MedChemExpress, Monmouth Junction, NJ, USA) was used to select stable cells. Cells were collected and lysed in radioimmunoprecipitation assay (RIPA) buffer containing a cocktail of protease inhibitors (MilliporeSigma, Burlington, MA, USA), and protein quantification was performed using the bicinchoninic acid (BCA) assay. Equal amounts of protein were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred to a polyvinylidene difluoride (PVDF) membrane (BioTraceTM NT; Pall Corporation, Ann Arbor, MI, USA). The membrane was blocked with non-fat milk for 1 h at room temperature followed by overnight incubation at 4 °C with anti-SMARCA4 antibody (1:1000, #49360S; Cell Signaling Technology Inc., Danvers, MA, USA), anti-E-Cadherin antibody (1:1000, #sc-8426; Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA), anti-vimentin antibody (1:1000, #sc-373717; Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA) and anti-GAPDH antibody (1:2000, #5174, Cell Signaling Technology Inc., Danvers, MA, USA). Membranes were then incubated with Anti-rabbit IgG antibody (1:2000, #7074; Cell Signaling Technology Inc., Danvers, MA, USA) or anti-mouse IgG antibody (1:2000, #7076, Cell Signaling Technology Inc., Danvers, MA, USA) at room temperature for 2 h. Membranes were eventually visualized with the ChemiDoc Touch Imaging System (Bio-Rad Laboratories, Hercules, CA, USA). Quantification of the resulting bands is achieved using densitometry software ImageJ. Results are normalized against reference protein GAPDH. Total RNA was extracted from cells or xenograft tumor tissue by using Trizol (Takara Bio, Shiga, Japan), and used to synthesize cDNA with the PrimeScript RT reagent Kit (Takara Bio, Shiga, Japan). Quantitative Real-Time polymerase chain reaction (qPCR) was performed using SuperReal PreMix Plus (SYBR Green, Tiangen Biotech Co., Ltd., Beijing, China) on an ABI 7500 Fast Real-Time PCR Detection system (Applied Biosystems, Foster City, CA, USA). Relative quantitation was performed using the 2−ΔΔCt method [57], with GAPDH or U6 as the reference gene. Primer sequences were listed in Table 2. SAS cells transfected with the SMARCA4 overexpression plasmid were plated on glass slides for 24 h. Afterwards, the cell slides were rinsed with phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde for 30 min, followed by permeabilization with 0.2% Triton X-100 at room temperature. To avoid non-specific binding, the slides were then incubated with 5% goat serum for 1 h. Primary anti-E-cadherin antibody (1:300, #sc-8426; Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA) and anti-vimentin antibody (1:300, #sc-373717, Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA) were incubated at 4 °C overnight. The cell slides were next incubated with the corresponding secondary antibody (fluorescein isothiocyanate (FITC)-conjugated goat-anti-rabbit for E-cadherin, or DyLight-594-conjugated rabbit-anti-mouse for vimentin) in the dark for 1 h at room temperature. Immunofluorescence images were eventually acquired by confocal laser scanning microscopy using an Olympus Multi-Photon Laser Scanning Microscope (Olympus Corporation, Tokyo, Japan). Various miRNA target prediction tools, including the Biosynthetic websites TargetScan (Accessed on 11 January 2021. Available online: https://www.targetscan.org/vert_80/), Starbase (Accessed on 11 January 2021. Available online: https://starbase.sysu.edu.cn/), and MiRDB (Accessed on 8 February 2021. Available online: http://mirdb.org/), were used to predict the binding sites between SMARCA4 and miR-199a-5p. The 3′UTR fragment of SMARCA4 targeted by miR-199a-5p and the mutated sequence were inserted into the reporter vector pmirGLO (Public Protein/Plasmid Library, PPL, NanJing, China) to construct the wild-type (WT) SMARCA4-3′UTR vector and mutated-type (MUT) SMARCA4-3′UTR vector, respectively. For the luciferase reporter assay, 293T cells were transfected with WT-SMARCA4-3′-UTR and miR-199a-5p mimics, MUT-SMARCA4- 3′-UTR and miR-199a-5p mimics, WT-SMARCA4-3′-UTR and miR-199a-5p inhibitor, or MUT-SMARCA4-3′-UTR and miR-199a-5p using METAFECTENE K4 (Biontex Laboratories GmbH, Munich, Germany). Dual-luciferase activity was detected 24 h later using the GloMax®-Multi+ Detection System (Promega, Madison, WI, USA), normalizing the reference of firefly luciferase to Renilla luciferase. Cells (5 105) were plated in 12-well plates. After 24 h when the cells were confluent, a micropipette tip was used to create a scratch wound in the cell monolayer in the center of each well. At the indicated time points (6 h for SAS cells, and 30 h for CAL-27 cells), the migration status was assessed by measuring the movement of cells into the scratched wound. Migration and invasion assays were performed using a 24-well plate Transwell assay system (Corning Inc. Cat#3422, Corning, NY, USA). Cells (1 105 for SAS cells or 2 105 for Cal-27 cells) in 200 µL of serum-free medium were resuspended and placed into the upper chamber for migration or 150mg Matrigel-coated chamber (BD Biosciences, San Jose, CA, USA) for invasion, and 600 µL of complete medium was added in the lower chamber as chemoattractant. After incubation for the indicated times (24 h for SAS cells, 48 h for CAL-27 cells), cells adhering to the surface of the membrane in lower chambers were fixed in 4% paraformaldehyde and stained with 0.1% crystal violet. Images of SAS and CAL-27 cells in migration and invasion Transwell assays were taken from six randomly selected fields under an IX51 Olympus microscope (Olympus Corporation, Tokyo, Japan). Quantification of the migrated cell number is achieved using densitometry software ImageJ. All experiments were repeated at least three times. The results were representative of at least three independent experiments. Ten 4–5 week-old (18–20 g) male nude mice were purchased from Vital River Laboratory Animal Technology (Beijing, China). The mice were randomly divided into two groups (5 mice/group). To establish a xenograft model, SAS cells (3 106, 100 µL) stably transfected with sh-SMARCA4 lentivirus or sh-NC were resuspended in PBS and injected into the right upper limb of each nude mouse. Tumor volumes and mouse weight were recorded every 4 days using scale. Two weeks later, nude mice were sacrificed using high concentrations of carbon dioxide, and tumor tissues were collected for subsequent analysis. Tumor tissues of nude mice embedded in paraffin were dewaxed in xylene and rehydrated in a graded alcohol series. The tissue morphology was observed by using HE staining. Immunohistochemistry (IHC) was performed as previously described [56] by using antibodies of anti-SMARCA4(1:200, #49360S, Cell Signaling Technology, Danvers, MA, USA), anti-E-cadherin (1:200, #sc-8426, Santa Cruz Biotechnology, Santa Cruz, CA, USA) and anti-Vimentin (1:200, #sc-373717, Santa Cruz Biotechnology, Santa Cruz, CA, USA). The images were obtained by microscope (IX51, Olympus America, Redmond, WA, USA). Optical density analysis of protein expression was conducted with Image Pro Plus. The images were also examined and scored independently by a pathologist. The animal experiments were approved by the Institutional Animal Experiment Committee of Xiamen University (XMULAC20200160). All experiments were independently repeated three times for error analysis. Statistical results are presented as the mean and standard deviation (mean ± SD) or p-value. The difference between the two sets of data was analyzed using a t-test for paired data, while one-way analysis of variance (ANOVA) was used for more than two sets of data. A p-value < 0.05 was considered to be statistically significant, and the results were statistically analyzed and plotted using the Graph Pad Prism 7.0 software (GraphPad Software Inc., San Diego, CA, USA).

PMC10003093

Marta Correia de Sousa,Etienne Delangre,Miranda Türkal,Michelangelo Foti,Monika Gjorgjieva

Endoplasmic Reticulum Stress in Renal Cell Carcinoma

03-03-2023

renal cell carcinoma (RCC),chronic kidney disease (CKD),endoplasmic reticulum (ER) stress

The endoplasmic reticulum is an organelle exerting crucial functions in protein production, metabolism homeostasis and cell signaling. Endoplasmic reticulum stress occurs when cells are damaged and the capacity of this organelle to perform its normal functions is reduced. Subsequently, specific signaling cascades, together forming the so-called unfolded protein response, are activated and deeply impact cell fate. In normal renal cells, these molecular pathways strive to either resolve cell injury or activate cell death, depending on the extent of cell damage. Therefore, the activation of the endoplasmic reticulum stress pathway was suggested as an interesting therapeutic strategy for pathologies such as cancer. However, renal cancer cells are known to hijack these stress mechanisms and exploit them to their advantage in order to promote their survival through rewiring of their metabolism, activation of oxidative stress responses, autophagy, inhibition of apoptosis and senescence. Recent data strongly suggest that a certain threshold of endoplasmic reticulum stress activation needs to be attained in cancer cells in order to shift endoplasmic reticulum stress responses from a pro-survival to a pro-apoptotic outcome. Several endoplasmic reticulum stress pharmacological modulators of interest for therapeutic purposes are already available, but only a handful were tested in the case of renal carcinoma, and their effects in an in vivo setting remain poorly known. This review discusses the relevance of endoplasmic reticulum stress activation or suppression in renal cancer cell progression and the therapeutic potential of targeting this cellular process for this cancer.

Endoplasmic Reticulum Stress in Renal Cell Carcinoma The endoplasmic reticulum is an organelle exerting crucial functions in protein production, metabolism homeostasis and cell signaling. Endoplasmic reticulum stress occurs when cells are damaged and the capacity of this organelle to perform its normal functions is reduced. Subsequently, specific signaling cascades, together forming the so-called unfolded protein response, are activated and deeply impact cell fate. In normal renal cells, these molecular pathways strive to either resolve cell injury or activate cell death, depending on the extent of cell damage. Therefore, the activation of the endoplasmic reticulum stress pathway was suggested as an interesting therapeutic strategy for pathologies such as cancer. However, renal cancer cells are known to hijack these stress mechanisms and exploit them to their advantage in order to promote their survival through rewiring of their metabolism, activation of oxidative stress responses, autophagy, inhibition of apoptosis and senescence. Recent data strongly suggest that a certain threshold of endoplasmic reticulum stress activation needs to be attained in cancer cells in order to shift endoplasmic reticulum stress responses from a pro-survival to a pro-apoptotic outcome. Several endoplasmic reticulum stress pharmacological modulators of interest for therapeutic purposes are already available, but only a handful were tested in the case of renal carcinoma, and their effects in an in vivo setting remain poorly known. This review discusses the relevance of endoplasmic reticulum stress activation or suppression in renal cancer cell progression and the therapeutic potential of targeting this cellular process for this cancer. The kidney carries out key physiological functions in the organism including blood filtration and pressure regulation, drug metabolism and glycemia control, as well as excretion of toxic metabolites. Tubular cells are the most abundant cell type of the kidney, and are major actors in the filtration/reabsorption processes and glycaemia control exerted by the kidney [1,2,3]. These cells are thus highly metabolically active and have high energetic requirements, usually satisfied by lipid β-oxidation but also through glycolysis in pathological conditions [3,4]. This variety of functions renders tubular cells particularly susceptible to stress-induced cell injury associated with drugs/metabolites toxicity and ischemic episodes, which with chronicity can lead to the development of renal cancer. Renal cell carcinoma (RCC) mostly arises from tubular cells, although other kidney cell types were also suggested be at the origin of this cancer [5]. GLOBOCAN data reported over 400,000 new cases in 2020, accounting for 2% of all cancer diagnoses, with a higher prevalence in male patients [6]. Risk factors include smoking, obesity, diabetes, hypertension, chronic kidney disease and exposure to radiation and toxins such as trichloroethylene [6]. Other rare hereditary conditions, such as von Hippel-Lindau syndrome, Birt-Hogg-Dubé syndrome and Tuberous Sclerosis syndrome, can also contribute to the incidence of RCC [7]. The survival of the patients is strongly dependent on the stage of the disease at the time of diagnosis. The staging of the tumors (I–IV) is based on their size and invasiveness, with only 12% survival rate in the 5 years following diagnosis for patients with stage IV tumors [5,6]. RCC englobes a very heterogenous group of cancers in the kidney. The three major groups of RCC are clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC), with ccRCC being the most frequent type (around 80% of all RCC) [8]. Histologically, ccRCC cells are characterized by a cytoplasm rich in lipids and glycogen, giving a clear cell aspect to this tumoral subtype [9]. These lipid and glycogen accumulations result from striking alterations of the cellular metabolism, as discussed below [8]. This cancer type originates from proximal tubular cells in the kidney. On the contrary, pRCC are tumors with smaller cells organized in a papillary architecture, with either basophilic (type I) or eosinophilic (type II) cytoplasm [9]. pRCC can also originate from proximal tubular cells, yet single-cell analysis suggested that this subgroup could arise from kidney collecting duct principal cells as well [10]. Finally, chRCC are characterized by large, pale cells with peri-nuclear halos and reticular cytoplasm, and they originate from distal convoluted tubules [9,11]. The mutation profile in RCC varies depending on the different types of tumors. Indeed, the most commonly mutated gene in ccRCC is, by far, the von Hippel-Lindau tumor suppressor gene (VHL) [12], found to be genetically altered in up to 60% of all ccRCC [13]. Other frequently mutated genes include Polybromo 1 (PBRM1), BRCA-associated protein 1 (BAP1) and SET Domain Containing 2 (SETD2) [14]. pRCC, on the other hand, frequently bears mutations in the hepatocyte growth factor receptor (MET proto-oncogene), SETD2 and Moesin-Ezrin-Radixin Like Tumor Suppressor (NF2), while chRCC tumors are characterized by TP53 and Phosphatase and tensin homolog (PTEN) mutations [14]. While metabolic alterations in pRCC and chRCC are still poorly characterized, a deep reprogramming of the energetic metabolism was highlighted in ccRCC by several studies [8,15]. Consistent with the high levels of lactate found in the urine of patients [16], ccRCC undergo metabolic switches that increase glycolysis and lactate fermentation to fuel cell proliferation [15,17]. Glucose uptake through the GLUT1 glucose transporter and glycogen accumulation are increased in ccRCC [15,17,18,19,20], and glycolytic intermediates partition to feed both the pentose phosphate pathway (PPP) and the TCA cycle and one carbon metabolism [15,17]. The increased stimulation of the PPP allows the nucleotide synthesis required for cell proliferation, but this metabolic rewiring also attenuates mitochondrial activity and respiration, thus preserving lipids and cholesterol for membrane production and signalization while protecting the cells from oxidative stress by decreasing mitochondrial reactive oxygen species (ROS) production [15,17,21]. This classical Warburg effect further increases with the severe clinical stage of ccRCC [22,23]. The expression of glycolytic enzymes, e.g., glucose-6-phosphate isomerase (GPI), GLUT1 and MCT1, also increases with the different ccRCC stages and represents the independent prognostics marker for this cancer type [19,24]. Accordingly, glycolytic gene-related signatures in RCC patient cohorts correlate with the prognosis and therapeutic responses of the patients [25,26]. As described later on in detail, loss of the tumor suppressor VHL in ccRCC triggers the expression of hypoxia-induced factor 1 (HIF1), a glycolytic transcription factor [27]. However, HIF1 activity is not restricted to glycolysis promotion; other metabolic pathways are also under the HIF1 control. Integrated multi-omics analysis of human ccRCC samples revealed that (i) NDUFA4L2 targeted by HIF1 triggers mitochondrial dysfunction and blockage of mitochondrial respiration through inhibition of the Complex I of the respiration chain [28]; (ii) HIF1 interactor MUC1 regulates glycogen degradation, glycolysis, PPP, TCA cycle in RCC [29]; and (iii) HIF1-mediated transcription of PFKFB4 promotes PPP activation in RCC [30,31]. Further supporting the importance of the PPP for carcinogenesis, overexpression of glucose-6-phosphate dehydrogenase (G6PDH), a rate-limiting enzyme in the PPP, was shown to favor cell survival and to protect RCC cells from oxidative stress, while its inhibition by 6-aminonicotinamide resulted in decreased NADPH levels and increased ROS concentration in primary renal tumor cells [31]. Consistent with the impairment of mitochondrial respiration and increased PPP in ccRCC, the lipid metabolism is also strongly deregulated in this cancer type. Aberrant accumulation of lipids occurs in ccRCC cells, thus contributing to the clear aspect of these cancer cells in histology. Lipidomic analysis of human ccRCC confirmed an extensive accumulation of lipids in these cancer cells, in particular ether phospholipids, cholesterol esters, and triacylglycerols [32]. Supporting an aberrant accumulation of lipids in ccRCC cells, analysis of early stage human ccRCC revealed an increased expression of the lipid transporter CD36, the lipid synthesis enzymes SCD1 and ELOVL2, and the structural component of lipid droplets PLIN2, as well as downregulation of ANXA3, a negative regulator of lipid accumulation [21,33]. Treatment options for RCC have varied greatly over the years. Almost two decades ago, the most exploited options were IL-2- and IFNα-based therapies, despite the underlying toxicity of these treatments [34]. Advancements in drug development then led to the extensive usage of tyrosine kinase inhibitors (TKI), such as Sunitinib, Sorafenib, Axitinib and Cabozantinib [35]. Inhibitors of the mTOR pathway, such as Everolimus and Temsirolimus, were also considered, as this pathway is frequently upregulated in RCC [4]. Moreover, targeting of the VEGF angiogenic pathway was also exploited using Sunitinib or Bevacizumab and in further combination with PD-1 inhibitors such as Pembrolizumab [36]. Indeed, immune checkpoint inhibitors (ICI) are increasingly considered as treatment for RCC, as well as the combination of ICI with TKI. Therapeutic approaches based on ICI are highly relevant, since RCC are among the most immune-infiltrated tumors [37,38]. Interestingly, evidence is emerging suggesting that the activation of specific metabolic pathways is tightly associated with inflammatory signatures and angiogenesis [39,40]. In this regard, in silico analyses suggested that high metabolic activity in ccRCC tumors can suppress immune infiltration and that both metabolic and immune status of the tumors could be used for prognosis [41]. In agreement with this concept and the fact that the tumor microenvironment heavily affect responses to systemic therapy [42], patients with RCC characterized by high inflammation and low metabolic activity are the ones that benefit mostly from immunotherapy [41]. The most commonly used TKI show conflicting results regarding the beneficial effect on patients, as demonstrated in different RCC patient cohort studies (e.g., study ASSURE vs. S-TRAC for Sunitinib and Sorafenib [43]), indicating that the underlying molecular mechanisms involved in RCC are more complex and likely need combined therapies. Nephrectomy can also be envisaged as an option, particularly in advanced cases of RCC. However, very few patients are eligible for these procedures, which are limited by the location and accessibility of the tumor, the associated comorbidities and the extent of the symptoms [44]. Finally, in patients with metastatic RCC, radiotherapy can also be employed, but the survival of the patients is poorly improved [45]. Therefore, novel therapeutic options are needed to optimize the treatment for RCC. As mentioned, current therapies in RCC, in particular TKI, exhibit poor efficiency and lack in durable results. For example, more than one quarter of RCC patients undergoing Sunitinib or Sorafenib treatment were reported to be primary refractory to this therapeutic approach [46]. This resistance to the treatment can be due to the specific mutational profile of the tumor and the genetic background of the patient, as well as different redundant pro-angiogenic mechanisms that allow cancer cells to bypass the pathways targeted by the TKI and insure their survival [46]. One other major factor that can facilitate renal cancer cell survival with TKI-based therapies is the induction of endoplasmic reticulum (ER) stress, which in turn activates pro-inflammatory/pro-survival molecular mechanisms that foster RCC progression. Indeed, both Sunitinib and Sorafenib have been demonstrated to induce ER stress responses in RCC cells [47,48]. In the following sections, we discuss how ER stress signaling promotes renal cancer cells survival, and how these molecular pathways could be either hyperactivated or suppressed as two different therapeutic strategies against RCC. The ER is an organelle that exerts various vital functions in the cell, such as protein folding, lipid synthesis, regulation of carbohydrate metabolism and Ca2+ homeostasis [49]. The ER compartment thus represents an important cellular site at the crossroad of a plethora of cellular processes regulating cell homeostasis. Alterations of ER functions drive cellular stresses that affect the structural and functional integrity of the ER and trigger signaling responses from this organelle known as the unfolded protein response (UPR). While UPR activation is a molecular process aiming at restoring homeostasis in the cell following an insult, its prolonged activation can lead to programmed cell death. A multitude of different stress factors can affect ER functions and lead to the activation of the UPR. These include, in particular, (i) metabolic alterations such as hyperglycemia, hyperlipidemia and nutrient availability, (ii) abnormalities in the Ca2+-dependent signaling, (iii) mutational changes that favor a constitutive activation of the UPR (frequently observed in cancer), (iv) damage induced by reactive oxygen species (ROS), (v) heat shock, and (vi) toxin/drug exposure [50]. ER stress activates three main UPR signaling axes, which are under the control of the inositol requiring enzyme 1 (IRE1α), the PKR-like ER kinase (PERK) and activating transcription factor 6 (ATF6), respectively (Figure 1) [51]. Each of these signaling axes exerts a particular role in re-establishing normal homeostasis following cell injuries. IRE1α, PERK and ATF6 are ER-transmembrane proteins, and their activation is dependent on sensory proteins, among which the best-characterized is glucose-related protein 78 (GRP78, also called BiP) [52]. GRP78 is a resident protein in the ER lumen that binds to IRE1α, PERK and ATF6 in the absence of ER stress to prevent the UPR. Upon ER stress, GRP78 dissociates from the ER-lumen domains of IRE1α, PERK and ATF6, thus allowing their activation. GRP78 dissociation from the UPR drivers is triggered by the higher affinity of GRP78 for misfolded proteins, which accumulate in the ER in stress conditions. Other ER stress sensors, e.g., sarco-ER calcium-ATPase (SERCA) and ER-associated calcium sensors stromal interacting molecule (STIM), can also drive UPR activation, but through indirect mechanisms modulating Ca2+ levels in the ER [52]. Dissociation of GRP78 from IRE1α allows autophosphorylation and conformational changes of IRE1α, conferring to it cytoplasmic nuclease activity towards the mRNA of the XBP1 transcription factor, which is spliced into the XBP1S active mRNA variant. The XBP1S protein then migrates to the nucleus, where it activates the transcription of chaperone proteins, as well as other factors in the ER-associated protein degradation (ERAD) pathway, to restore proteostasis (Figure 1) [53]. Increased expression of chaperone proteins alleviates ER stress by preventing further accumulation of misfolded proteins and/or inducing their degradation. The XBP1S transcription factor was also shown to regulate metabolism, in particular through the activation of lipogenesis by stimulating the transcription of acetyl-CoA carboxylase 2 (ACC2), stearoyl-CoA desaturase 1 (SCD1) and diacylglycerol acyltransferase 2 (DGAT2) [53]. Therefore, while metabolic alterations themselves induce ER stress, this mechanism can further contribute to these abnormalities by stimulating lipid synthesis in a vicious cycle. The second axis of the UPR mediated through PERK is responsible for the decrease in protein synthesis under ER stress. PERK is activated upon GRP78 dissociation and phosphorylates the eukaryotic translation initiation factor 2α (eIF2α), halting global protein translation, yet the production of specific proteins, such as activating transcription factor 4 (ATF4), is induced. ATF4 in turn triggers the transcription of oxidative stress response proteins and autophagy-related proteins (Figure 1). Finally, the mediator of the third axis, the ATF6 transcription factor, is activated by cleavage upon GRP78 dissociation. Active ATF6 then translocates into the nucleus and promotes the transcription of genes encoding chaperone proteins and enzymes of the lipid metabolism, as well as proteins involved in UPR mediation, such as XBP1S and GRP78 (Figure 1) [54]. In this way, ATF6 tends to alleviate protein burden in the ER, but is also responsible for metabolic changes in the cell, reducing cell stress. As mentioned, the UPR initially aims to restore the normal functioning of the ER through the activation of chaperone proteins by decreasing protein synthesis, regulating the lipid metabolism and activating other stress responses, such as autophagy and antioxidant activity [55]. Together these responses mediate the pro-survival phase of the UPR (also called adaptive phase of the UPR). Nevertheless, if the initial cause triggering the ER stress is not resolved and the stress stimuli persist, the continuous activation of the UPR leads to cell death (pro-apoptotic response of the UPR). UPR-dependent apoptosis can be conveyed via different pathways, including: (i) ATF4- and ATF6-mediated activation of CCAAT/enhancer binding protein homologous protein (CHOP) transcription, which is the main pro-apoptotic actor of ER stress; (ii) IRE1α-induced activation of tumor necrosis factor α (TNFα) receptor-associated factor 2 (TRAF2), which leads to JNK activation and apoptosis; or (iii) IRE1α-induced activation of Caspases [56,57]. The ability of the UPR to trigger either pro-survival or pro-apoptotic mechanisms, when the cellular damage is deemed irreversible, is very attractive for therapeutic purposes in diseases such as cancer and needs attention when considering personalized medicine approaches. To exploit these molecular pathways as therapeutic targets, several critical factors in ER stress signaling need to be better understood. First, it is important to precisely define the threshold of cell damages above which ER stress becomes irreversible and triggers the activation of the pro-apoptotic machinery. This limit, from which the UPR induces a switch from a pro-survival to a pro-apoptotic response, still remains obscure and is thought to be highly variable between different cell types, tissues and/or organs. Furthermore, the main cellular actors governing this switch need to be identified and characterized, as well as whether the three signaling axes of the UPR are equally important in the switch from anti- to pro-apoptotic mechanisms induction. In this regard, the E2F1 transcription factor was suggested to act as a molecular switch indispensable for ER stress-mediated activation of apoptosis [58]. Indeed, the downregulation of E2F1 in vitro under ER stress conditions leads to the upregulation of the pro-apoptotic factors Noxa and Puma, which are required for ER stress-induced apoptosis [58]. Nevertheless, such mechanism still needs to be experimentally confirmed in animal models and in humans. Chronic kidney diseases (CKD) are a favorable ground for RCC development, and patients suffering from these diseases are at higher risk of developing renal cancer, in comparison to the general population [59,60]. Metabolic abnormalities, ischemia, abnormal redox homeostasis, inflammation and fibrosis are all drivers of carcinogenesis, as well as major hallmarks of CKD [61,62,63]. As illustrated in Figure 2, in the case of diabetic nephropathy (DN) [64,65,66] and renal fibrosis [67], which occurs in almost all CKD [68], ER stress and activation of the UPR develop in both acute and chronic injuries in the kidney [69], including ischemic and nephrotoxic acute kidney injury [70], alcoholic nephropathy [71], autosomal dominant tubulointerstitial kidney disease [72], autosomal dominant polycystic kidney disease [73], membranous nephropathy [74,75], Fabry disease [76] and lupus nephritis [77]. As further described in this section, ER stress often occurs in tubular cells from which most RCC originate, e.g., in DN [78], thus not only contributing to aggravating CKDs, but also providing a further priming for RCC development. The underlying pathology driving CKD determines the type of RCC that the patient is most likely to develop [60]. For example, in a CKD such as DN, metabolic alterations induce oxidative stress, renin-angiotensin-aldosterone system (RAAS) activation and immunological changes in the kidney that promote cancer induction and progression [87]. Oxidative stress can induce DNA damage in the cell, facilitating tumoral transformation. Moreover, chronic exposure of proximal tubular cells to oxidative stress leads to the acquisition of stem cell-like features/markers facilitating tumoral transformation, as observed in HK-2 normal kidney tubular cells [88]. The RAAS is known to induce renal fibrosis and thus create a deleterious microenvironment (e.g., hypoxia, hyper-proliferative state), priming the kidney for renal carcinogenesis. High circulating glucose and lipids also promote cell proliferation. Hyperglycemia was suggested to foster DN-associated RCC development [89] by (i) hyperactivating glycolysis (reported in transcriptomic/metabolomics analysis of diabetic mouse kidneys [90]) and (ii) activating the AKT/mTOR and the insulin growth factor (IGF) proliferative signaling pathways, both shown to be activated in DN in mouse models of diabetes [91,92]. Hyperlipidemia promotes lipid uptake in renal cells via the CD36 transporter, resulting in ectopic accumulation of lipids in cytoplasmic droplets of kidney cells, as observed in immortalized mouse kidney cells stimulated with lipids in vitro, as well as in human diabetic kidney biopsies [93,94]. While lipid droplet accumulation per se seems to not be deleterious for tubular cells, overcoming the lipid storage capacities of these cells becomes toxic (lipotoxicity) and was suggested to stimulate cancer initiation; nevertheless, concrete experimental data are still missing [94]. Intracellular free fatty acids and their metabolites in renal cells can indeed interact with DNA, RNA, proteins and organelles and thereby affect their normal functioning, entailing genetic instability that fosters cancer development, as previously suggested in vivo in mouse models with renal metabolic alterations similar to DN (K.G6pc-/-mouse model) in which renal neoplasia development was noted [95,96,97]. Finally, inflammation associated with DN might also contribute to renal carcinogenesis, as is the case for many other cancers, but this remains to be clearly demonstrated [62,98,99]. Inflammatory mediators mainly produced by immune cells that infiltrate the kidney, but also renal cells in the kidney cortex, e.g., IL-6, TNF-α, IL-1β, and related signaling pathways such as JNK and NF-kB, were reported to significantly contribute to the development and progression of DN in mouse or rat streptozotocin-induced diabetic models of nephropathy [100,101,102], as well as major cancer hallmarks such as sustained proliferation, angiogenesis, immune escape and metastasis, which could facilitate renal cancer development with CKD [103,104]. All these metabolic alterations and inflammatory processes occurring in CKD and priming cells for carcinogenesis are tightly linked to ER stress, but whether ER stress is a cause or an effect of these alterations remains unclear. For example, tunicamycin-induced ER stress in non-cancerous renal epithelial HEK-293 cells induces lipotoxicity by increasing the intracellular content of long-chain ceramides and polyunsaturated fatty acids, which damage cells and trigger apoptosis [105]. On the other hand, in non-cancerous kidney tubular HK-2 cells, the decreased expression of VHL, a major tumor suppressor lost in kidney cancer, induces ER stress, as supported by GRP78, IRE1α/XBP1, eIF2α, JNK and NF-kB activation, as well as upregulation of NF-kB target genes (TNFα and Il-1β) [106]. VHL loss also resulted in an increased recruitment of macrophages and inflammation in a IRE1α-dependent manner in the same study [106]. This observation was reported in an in vitro setting in which the HK-2 cells with or without VHL expression were seeded in a Boyden chamber, allowing them to recruit or not recruit RAW264.7 macrophages through a porous membrane, respectively [106]. These findings suggest that the ER stress and UPR responses induced by the loss of VHL in pre-cancerous stages of kidney cells could represent an early event driving cell transformation and induction of RCC. The UPR, through activation of IRE1α, PERK and ATF6, could also contribute to maintaining an inflammatory environment, promoting carcinogenesis by stimulating the production and secretion of inflammatory mediators or modulating immune cell infiltration [107,108]. For example, the IRE1α axis of the UPR was shown to drive acute-to-chronic kidney disease transition in tubular cells by activating JNK signaling and by increasing IL-6 and MCP1 production and secretion in an in vivo model of renal ischemia/reperfusion [109]. PERK was further reported to upregulate the JAK2/STAT3 inflammation pathway in normal rat kidney NRK-52E cells [110]. Although the molecular mechanisms linking ER stress and inflammation remain to be deeply investigated, it is clear that a sustained inflammatory environment in the kidney evoked by ER stress signaling is likely an important factor priming the kidney for RCC development. ER stress can modulate the autophagic capacity of renal cells [111]. Tunicamycin injection in mice to induce ER stress resulted in increased autophagy and apoptosis in the tubular cells of the kidneys through activation of PERK/eIF2α-dependent UPR, thus promoting chronic kidney injury [112]. Autophagy suppression in proximal tubular HK-2 cells in vitro, in turn, potentiated the activation of ER stress (as observed through an increase in GRP78 and eIF2α phosphorylation), thus suggesting an intricate relationship between these two cellular processes in kidney diseases. The authors suggest that autophagy activated in these conditions possibly provides a negative feedback regulation aiming to resolve the ER stress. Importantly, autophagy represents an important mechanism involved in the initiation and progression of RCC by allowing cells to recycle their intracellular materials/organelles to promote proliferation (as observed, for example, in vitro in Caki RCC cells, in which p53 is degraded in autophagic vesicles, favoring rapid proliferation of renal cancer cells [113,114]). Finally, ER stress leads to structural alterations of the ER cisternae, which may in turn affect the functions of other organelles in the cell [115]. For example, ER interactions with mitochondria and/or the plasma membrane through specific contact sites (mitochondria-associated endoplasmic reticulum membranes or MAMs) can be severely impaired upon ER stress [116,117]. The functional integrity of MAMs are indeed required for a normal ER or mitochondrial Ca2+ homeostasis, mitochondrial ROS production, fusion and lipid transfer, as well as for the cell metabolic homeostasis and processes such as apoptosis [118]. However, how the UPR and/or associated ultrastructural changes in the ER affect MAMs’ integrity, ER interactions with other organelles and their functions is still unclear in the context of RCC or kidney disease in general [119]. Only a few studies indicated that in an in vivo model of streptozotocin-induced DN, tubular cells and podocytes undergo a loss of MAMs integrity associated with an induction of apoptosis and renal injury [120,121]. Of note, studies with primary human ccRCC samples and retrospective analyses of ccRCC patients’ cohorts uncover significant mitochondrial dysfunctions and a decreased capacity for mitochondrial oxidation in this cancer subtype [122,123]. Further studies are now required to explore in more detail the pathological relevance of UPR-independent ER stress-associated cellular defects in the different subtypes of RCC. As previously mentioned, metabolic reprogramming of renal cancer cells [124] is in part dependent on the type of mutations driving carcinogenesis [125]. For example, ccRCC in humans are characterized by aerobic glycolysis and pseudohypoxia, along with activation of the pentose phosphate pathway and a decreased oxidative phosphorylation, typical of a Warburg-like reprogramming [126]. These metabolic features are consistent with the recurrent loss of the tumor suppressor VHL in this cancer type. Indeed, VHL ubiquitinates and targets HIF1 for degradation, and loss of this tumor suppressor leads to HIF1 accumulation and activation of hypoxia responsive factors, glycolysis and glucose uptake in renal tubular cells [127]. VHL mutations are further associated with an upregulation of the pro-angiogenic vascular endothelial growth factor (VEGF) and mammalian target of rapamycin (mTOR) pathway, a major regulator of cell proliferation, energy metabolism and autophagy [127]. pRCC, like ccRCC, is also characterized by mTOR overactivation and loss of oxidative phosphorylation capacities; however, this cancer subtype is more dependent on glutamine consumption than glucose consumption in humans [128,129]. One of the most frequently mutated proto-oncogenes in pRCC, MET, can activate the PI3K-AKT-mTOR and LKB1-AMPK-mTOR nutrient-sensing pathway, which facilitates growth of the tumor [125]. Finally, loss of the tumor suppressor PTEN, often reported in human chRCC, can also re-wire the metabolism of RCC through activation of the PI3K/AKT pathway, thus fostering growth and progression of tumors [130,131]. However, sequencing of the mitochondrial DNA in this cancer subtype indicated that the mitochondrial oxidative phosphorylation pathway is not attenuated, in contrast to ccRCC [132]. Finally, the tumor suppressor TP53 can be mutated in human chRCC, pRCC and ccRCC, thereby affecting not only the cell cycle and DNA repair but also the glucose metabolism by promoting a Warburg effect [133]. All the mutation-dependent metabolic alterations described for ccRCC, pRCC and chRCC are beneficial for the growth and progression of these cancers but also trigger severe stress responses, in particular from the ER. Ectopic accumulation of fat-containing droplets in ccRCC can indeed induce lipotoxicity and damage intracellular organelles, DNA, RNA and proteins, thereby activating the ER stress pathways in an attempt to restore homeostasis [134]. In addition, increased intracellular glucose levels exacerbate lipid-induced ER stress through the activation of lipogenesis and glucotoxicity [92]. Accordingly, lessons from diabetic nephropathy models have highlighted the importance of hyperglycemia and dyslipidemia in the activation of ER stress and the pathological outcome of the UPR on kidney disease [65]. Finally, abnormal activation of the mTOR pathway, which frequently occurs in ccRCC and pRCC, was also shown to activate ER stress responses in the kidney, as seen in podocytes in vitro [91]. The impact of the most frequent RCC mutations on metabolism and metabolism-mediated ER stress activation is summarized in Figure 3. It is crucial to stress that while ER stress responses are mostly induced by drastic metabolic alterations, other factors, such as exposure to drugs and toxins can also activate UPR in kidney cells. Importantly, the activation of the UPR pathway can, in turn, regulate distinct metabolic activities, including lipid [135] and glucose metabolism [136]. This is exemplified by the overexpression of ATF6 in human tubular HK2 cells, which leads to a decrease in fatty acid oxidation, as well as the accumulation of lipids in these cells, causing mitochondrial dysfunction and apoptosis [137]. Therefore, while mutation-driven metabolic reprogramming can lead to ER stress activation, the latter can also modulate the metabolic activity of the tumor. Finally, expression of the three most frequently lost tumor suppressors (VHL, PBRM1 and BAP1) in ccRCC do not correlate in the same manner with the expression of the different UPR mediators. Indeed, analyses of the TCGA-KIRC cohort of ccRCC patients via the Gepia2 cancer database (RCC biopsies of the patients) showed that VHL and PBRM1 expressions correlate with ERN1, EIF2AK3 and ATF6, whereas BAP1 does not correlate with any of the ER stress mediators (Figure 4). These correlative data suggest that some of the most frequently mutated genes in RCC (VHL and PBRM1) might be able to regulate the activation status of the UPR, however, this activation does not apply to the three branches but rather a branch-specific mediation of the UPR. This would imply that the outcome of the UPR activation might be different depending on the mutation that is present in the RCC, thus modulating the type of ER stress signaling. Further studies are now required to evaluate in depth this hypothesis for its relevance to therapeutic strategies based on targeting of ER stress signaling, as discussed later in this review. As described in the previous section, metabolic alterations driven by specific mutations can activate ER stress in RCC. Nevertheless, the genes coding for the different proteins involved in ER stress signaling can also be mutated and lead to constitutive activation of the UPR, promoting cancer development. For example, the gene coding for IRE1α (ERN1) was shown to be frequently mutated (increased copy number) and to contribute to breast cancer malignancy, with a specific subtype of breast cancer (luminal B breast cancer) showing the strongest ERN1 gene gain/amplification frequency, over 68%, as observed through in silico assessment of the Pan-Cancer Atlas of The Cancer Genome Atlas (TCGA) [138]. However, in RCC, activating mutations of UPR mediators are uncommon. Indeed, analyses of five different cohorts of ccRCC (Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas), Clear Cell Renal Cell Carcinoma (DFCI, Science 2019), Kidney Renal Clear Cell Carcinoma (BGI, Nat Genet 2012), Kidney Renal Clear Cell Carcinoma (IRC, Nat Genet 2014), Renal Clear Cell Carcinoma (UTokyo, Nat Genet 2013), combining together 761 patients and using the cBioportal (www.cbioportal.org, accessed 24 October 2022) database, indicated that the frequency of mutations in ER stress mediators is extremely low in RCC. Indeed, HSPA5 (GRP78) was mutated in 2/761 patients (missense mutations), ERN1 (IRE1α) in 2/761 patients (missense mutation and frame shift deletion), ATF4 in 3/761 patients (2 missense and 1 in frame deletion), ATF6 in 2/761 patient (in frame deletion) and XBP1, EIF2AK3 (PERK) and DDIT3 (CHOP) were not mutated in any of the patients. It is therefore clear that the frequent activation of ER stress responses in RCC cannot be attributed to mutational changes in genes encoding the UPR mediators. Based on normal cell physiology, induction of ER stress should be beneficial against pathologies such as cancer, since it should induce the death of transformed cells. However, while a normal cell would either resolve ER stress or undergo apoptosis, the profound changes characterizing transformed cells can lead to different outcomes of ER stress. Indeed, prolonged activation of the UPR does not always induce apoptosis in cancer cells, one of the main characteristics of which is precisely resistance to cell death. Instead, mild and prolonged UPR activation leads to mutational and metabolic adaptations of the transformed cell, which in turn favor its growth, metabolic status and proliferation/migration capacities [139]. In this regard, several UPR mediators were reported to favor cancer cell survival and proliferation. For example, ATF4 was shown to be critical for the survival of fibrosarcoma and colorectal adenocarcinoma cells under nutrient deprivation in vitro [140] and could also promote neoplastic transformation of mouse primary embryo fibroblasts by inhibiting senescence factors [141]. Overexpression of GRP78 was found to exert an anti-apoptotic role through the blockage of apoptotic mediators such as caspase-7 or BIK in breast cancer in vitro [142,143]. PERK was reported to induce resistance to cell death and chemotherapy and to confer NRF2-dependent protection to colon cancer HT29 cells against oxidative stress [144]. ATF6 was shown to sustain the expression of oncogenes such as BRCA1 or CIP2A (in vitro data in human colon cancer cell lines CaCO2, and SW480), as well as prevent DNA damage and to improve cancer cell viability, as observed in RKO and HCT116 colon cancer cell lines [145,146]. These observations suggest that the induction of ER stress can lead to cancer cell death only in certain conditions allowing it to surpass the resistance threshold of the tumoral cells, also called ER stress tolerance or ERST. ERST can be highly dependent on the mutations, tumor microenvironment and the progression stage. (Figure 5). Therefore, two therapeutic strategies targeting ER stress to eliminate cancer cells in RCC can be considered. On one hand, hyperactivation of ER stress to tip over the ERST and induce cell death appears as an interesting approach [139]; the second option that could be envisaged is to inhibit ER stress in RCC cells in order to facilitate cell death mediated by other therapeutics, such as TKI. Both approaches are discussed in the following sections. Various studies analyzed combinatory treatments in pre-clinical settings, aiming to increase ER stress in order to induce cell death as a therapeutic option in RCC. The combined usage of GZ17-6.02 (curcumin, harmine and isovanillin) with axitinib, a tyrosine kinases inhibitor (TKI), was shown to induce apoptosis in RCC A498 and UOK121LN cell lines in a ER stress-, autophagy- and death receptor signaling-dependent manner [147]. More precisely, the combination of these two treatments led to the activation of the PERK branch and the subsequent inhibition of eIF2α, along with strong activation of the autophagic flux, eventually resulting in both apoptotic and non-apoptotic cell death events. The microtubule stabilizer Ixabepilone and the mTOR inhibitor Temsirolimus also led to significant induction of ER stress (GRP78 and CHOP increase) in renal cancer cell lines Caki-1 and Caki-2, triggering their growth arrest in vitro [148]. The combined effect of the histone deacetylase inhibitor Panobinostat and the human immunodeficiency virus protease inhibitor Nelfinavir were further tested in RCC [149]. This combination effectively induced ER stress (observed through GRP78 upregulation), histone acetylation and, to a great extent, cell death of RCC, both in vitro in 769-P, 786-O, Caki-2 RCC cells and in vivo in a xenograft mouse model of subcutaneous grafting of Caki-2 cells. Simultaneous treatments of Fluvastatin (statin-inhibiting cholesterol synthesis) and Vorinostat (histone deacetylase inhibitor) further resulted in decreased renal cancer growth in vitro in ACHN, A498 and Renca cells and in vivo in an allograft model of Renca subcutaneous injection in nude mice, through cooperative induction of histone acetylation and ER stress induction (detected as GRP78 upregulation) [150]. Finally, the HIV protease inhibitor Ritonavir, along with the proteasome inhibitor Delanzomib induced ER stress and inhibited the mTOR pathway, resulting in tumor growth arrest and suppressed colony formation in vitro in 769-P, 786-O, Caki-2 and Renca RCC cell lines and in in vivo mouse models of subcutaneous grafting of Renca cells [151]. A second study using Ritonavir—combined, this time, with Belinostat, a histone deacetylase inhibitor—led to a decrease in RCC growth and an induction of apoptosis, again, through ER stress activation [152]. It thus appears that combining different drugs that induce ER stress, such as histone deacetylases or microtubule destabilization agents, along with other drugs providing a second hit in cancer cells—such as proteasome inhibitors, which exacerbate the accumulation of misfolded proteins thus reinforcing ER stress—are promising therapeutic strategies for RCC. Many different pharmacological ER stress modulators, e.g., synthetic or natural compounds, exist and usually target a specific branch of the UPR, as previously extensively reviewed [153]. Among those, only a handful were tested in the context of RCC and shown to trigger cell death. It remains, however, very difficult to quantify the relative extent of ER stress induced by these various compounds, since most of them were tested in different conditions and settings. For example, the plant extract englerin A was reported to induce a strong alteration of ceramide metabolism in RCC A498 cells in vitro, which, in turn, activated ER stress and acute inflammatory responses [154]. As RCC is a cancer type that is characterized by a strongly altered lipid metabolism, the authors suggest targeting this pathway in order to induce ER stress-mediated cell death. Another plant extract, withaferin A, was shown to induce ER stress in Caki RCC cells through the generation of ROS, thus triggering apoptosis of these cells [155]. Similar results were obtained in vitro in (i) RCC Caki cells treated with carnosic acid (rosemary extract); (ii) KCC853 cells treated with chitosan oligosaccharide (from the shells of shrimp and crab); (iii) Caki and 786-O cells treated with Chelerythrine (a protein kinase C inhibitor extracted from plants such as Chelidonium majus); (iv) 786-O, CaKi-1, ACHN and A-498 cells treated with norcantharidin (an anti-cancer drug inducing cell cycle arrest, isolated from natural blister beetles); and (v) A-498, 786-0 and ACHN cells treated with Bicyclol (a synthetic anti-hepatitis drug) [156,157,158,159,160]. The effect of RU486, a known progesterone and glucocorticoid receptor inhibitor, was also tested in RCC Caki cells, but in contrast to the previously mentioned compounds, which trigger ROS-dependent ER stress, this inhibitor induced CHOP and apoptosis through C/EBPδ-dependent mechanisms [161]. Finally, inflammatory cytokines such as Il-1β were reported to induce a strong ER stress sufficient to kill RCC cells. In the case of Il-1β, both in vitro and in vivo data using 786-O renal cancer cells xenografts in mice indicated that this cytokine induces dysregulation in protein folding accompanied by activation of monocyte chemoattractant protein 1 (MCP-1)/ MCPIP-1 signaling in RCC, which in turn activates ER stress (GRP78 and PERK increase) and ER stress-induced apoptosis (CHOP increase) [162]. Altogether, these studies demonstrated that ERST can be overcome by specific or combined stimuli in RCC cells, therefore supporting ER stress-mediated apoptosis in RCC as a relevant therapeutic approach. However, additional in vivo pre-clinical studies are required before envisaging such clinical applications, in order to better delineate the cellular and systemic effects of these ER stress inducers and to evaluate their potential relevance in clinics. Nanoparticles made of silver, gold, copper, graphene and iron have recently been suggested as a strategy for cancer therapies, as these compounds have the ability to induce important cytotoxicity and to promote ER stress-mediated cell death [163]. Nanocatalyst-induced ER stress has also been tested for renal cancer therapy in an in vitro and in vivo setting (cultured RCC 786-O cells and a xenograft mouse model injected with 786-O cells) [164]. In this study, the administration of iron oxide nanoparticles (Fe3O4 NPs) leading to exacerbated ROS production, in particular through generation of ·OH by Fe3O4, damaged the ER in cancer cells and induced stress in this organelle [164]. Nevertheless, to avoid adaptive UPR responses in the RCC cell that would favor its survival, this strategy was coupled with the administration of a deubiquitinase inhibitor PR-619 treatment. PR-619 blocks the ERAD-dependent protein degradation axis, which is activated by UPR, and therefore contributes to a further exacerbation of abnormal protein accumulation and ER stress in RCC cells. This prolonged activation of ER stress led to apoptosis in cultured renal cancer 786-O cells and in the 786-O-derived tumors in a xenograft mouse model [164]. Another study reported the usage of cuprous oxide nanoparticles in order to disrupt normal copper transportation by altering the copper chaperone proteins ATOX1 and CCS in RCC cells [165]. A498 and SR786O RCC cell exposure to these nanoparticles triggered the accumulation of intracellular Ca2+ and ROS and subsequent ER stress, leading to the inhibition of migration and invasion, cell cycle arrest and apoptosis. In the same study, in vivo cuprous oxide nanoparticles administration led to the inhibition of tumor development in a RCC xenograft model of athymic BALB/c nude mice injected subcutaneously with 786-O or SR786O cells. Interestingly, these nanoparticles were also suggested to re-sensitize RCC cells to the TKI Sunitinib by reducing the expression of cellular factors promoting resistance to this TKI, such as AXL, MET, AKT, and ERK signaling effectors [165]. As previously mentioned, the TKI Sunitinib displays therapeutic effects only in a subset of RCC patients [43]. The inefficacy of currently used pharmacological therapies, in particular Sunitinib, was attributed to some extent to their ability to induce ER stress in a mild range and therefore to foster tumor survival instead of inducing apoptosis. It was indeed well demonstrated that Sunitinib activates ER stress in RCC (summarized in Figure 6) through different mechanisms. First, Sunitinib triggers the activity of pro-tumorigenic NF-kB, through the IRE1α/TRAF2/IKKβ signaling axis, therefore promoting cell survival, as reported in vitro in 786-O RCC cells [47]. In the same study, Sunitinib was shown to activate the PERK signaling branch of ER stress, leading to the production of inflammatory mediators such as Il-6, Il-8 and TNFα [47]. Similarly, treatment of the RCC Caki-1 cell line with Sunitinib in vitro increased the expression of GRP78, which can in turn lead to increased proliferation of the renal cancer cells in hypoxic/hypoglycemic stress situations and confer resistance to apoptosis by stimulating the PERK/eIF2α signaling axis [166]. The importance of GRP78 in Sunitinib resistance was also demonstrated in vivo in the same study, where xenografting of Caki-1 cells lacking the expression of GRP78 in nude mice resulted in significantly lower tumor growth, compared to Caki-1 cells expressing GRP78, when the mice were treated with Sunitinib [166]. Sunitinib was also shown to induce GRP78 indirectly in RCC by increasing the expression of the oncogene EIF3D, thus resulting in GRP78 stabilization and Sunitinib resistance, as observed in 786-O and ACHN cells [167]. Finally, ATF6, the third axis of ER stress, can also be stimulated by Sunitinib in 786-O and ACHN RCC cells with functional Death-Associated Protein Kinase 1 (DAPK1) expression [168]. As this mild, chronic activation of ER stress in RCC under TKI treatment confers resistance of RCC cells to death, targeting the UPR along with TKI treatment was considered in order to decrease their pro-survival and to restore their pro-apoptotic effects. This concept was particularly investigated for Sunitinib-based therapies. For example, downregulation of GRP78 expression by specific GRP78 siRNAs sensitized renal cancer Caki-1 cells to Sunitinib-induced apoptosis [169]. Similar results were described in RENCA renal carcinoma cells, where in vitro incubation with GRP78 siRNA lipoplex prior to exposure to Sunitinib triggered growth arrest [170]. As mentioned, Sunitinib was also described to activate the IRE1α and the PERK branches of the UPR in vitro in 786-O RCC cells, therefore increasing the expression of NF-kB, as well as those of the pro-inflammatory cytokines Il-6, Il-8 and TNFα [47]. The same study reported that inhibitors of PERK (GSK2656157) or IRE1α (4μ8C), or, alternatively, genetic deletion of PERK or IRE1α, significantly prevented overexpression of these inflammatory cytokines in 786-O RCC cells [47]. This study further allowed the conclusion that the different branches of the UPR signaling are not redundant, and, therefore, Sunitinib-mediated overexpression of NF-kB and RCC survival were mediated by IRE1α signaling, while the Sunitinib-mediated pro-tumorigenic cytokine increase was dependent of the PERK signaling [47]. A current clinical challenge consists now in understanding which branch of the UPR must be targeted along with Sunitinib treatment to minimize systemic toxicity while maximizing cell death of renal cancer cells. Investigating the potential of targeting ER stress to treat RCC is challenging and hampered by the lack of highly relevant in vivo experimental models. The in vivo models most often used to study RCC include (i) xenograft models, which do not recapitulate cell transformation and tumor initiation in normal kidney tissues); (ii) genetic models of cancer induction in the kidney (e.g., knockouts of renal tumor suppressors in mice), which create a very specific setting of carcinogenesis poorly representative of the majority of RCC patients; and (iii) chemical induction of RCC, where the carcinogenic agents also affect other organs in the animal model, besides the kidney [171]. These important differences and drawbacks characterizing each type of RCC model challenge the establishment of relevant data on ER stress, which would reflect the pathophysiology in the vast majority of human RCC patients. Because no currently available animal models faithfully recapitulate the human RCC pathologies and associated ER stress process, alternative experimental models need to be implemented to improve our understanding of the pathophysiological role of ER stress in RCC and the molecular mechanisms governing these processes. In this regard, studies with tumoral organoid cultures of RCC are encouraging. These tumoral organoids do indeed (i) retain more RCC characteristics than 2D cultures of cancer cells; (ii) have a human genome; (iii) can originate from different parts of the tumoral kidney; (iv) can contain different cell types; and (v) can be used to study ccRCC, pRCC or chRCC [172,173,174]. While the heterogeneity of tumoral organoids might appear to be a disadvantage in experimental settings, this variability illustrates the reality in patients and investigating a sufficient number of these tumoral organoids would likely bring relevant information about ER stress signaling in different types of RCC, on ERST in patients and on other relevant data about the impact of ER stress pharmacological modulators in tumoral progression. Similar studies performed recently to investigate dose responses of different TKI (Sunitinib, Sorafenib Axitinib, Pazopanib and Cabozantinib) on organoid viability further support the experimental use of such organoids to increase the relevance of these type of studies for human pathologies [175]. A recent study highlighted GRP78 as a single prognostic marker in RCC involved in UPR signaling. GRP78 mRNA and protein levels were indeed increased in RCC, as well as serum levels, which correlated with the stage of the tumors [176]. GRP78 may thus represent an important potential non-invasive biomarker for RCC staging, but its relevance needs further confirmation in larger human patient cohorts. Since RCC is frequently associated with ER stress, an increase in cellular and serum levels of GRP78 may seem counterintuitive in RCC, since GRP78 is a gatekeeper of UPR activation that binds and restrains the activity of IRE1α, PERK and ATF6. Actually, the function of GRP78 is more complex than just inhibiting the UPR in the ER. Alternative splicing of GRP78 was shown to target the protein to different cellular compartments, such as the cytoplasm, the mitochondria, the nucleus and the cell surface [177]. For example, the cytosolic isoform of GRP78 results from an alternative splicing event involving retention of the first intron and subsequent internal translation initiation, finally leading to the loss of the ER-targeting signal [178]. Non-canonical functions of GRP78 were further reported to associate with its localization outside of the ER, such as (i) inhibition of DNA damage-induced apoptosis in the nucleus or (ii) regulation of cell survival signaling pathways such as the PI3K/AKT signaling at the cell surface [177]. So far, these non-canonical functions of GRP78 outside of the ER have not been investigated specifically in RCC but could potentially promote RCC survival. Finally, it is also possible that increased levels of the canonical ER-lumen form of GRP78 in RCC cells prevent ER stress hyperactivation and maintain UPR activation under the ERST. This would allow RCC cells to avoid pro-apoptotic signaling under mild ER stress while still maintaining the benefits of weak UPR activation. Future studies should shed light on the potential role of GRP78 in determining the ERST in RCC. Retrospective in silico analyses of RCC patient datasets have allowed for the identification of ER stress signatures tightly correlated with the outcome of the patient. Indeed, consensus-clustering of the ccRCC patients from the TCGA cohort depending on their ER stress-related gene expression led to the formation of two different clusters (C1 and C2). This segregation of the patients in two clusters highlighted that the ER stress signature can vary greatly between patients. Strikingly, the clinical features of the tumors in each ER stress cluster were different, with RCC samples belonging to the C2 being more advanced/aggressive (more advanced tumor T stage, TNM stage and grade level) in comparison to C1 RCC [179]. Interestingly, the C2 cluster displayed a significant increase in PERK and ATF6 expression in contrast to C1, whereas IRE1α expression remained unchanged. Coincidentally, patients clustered in the C2 were better responders to Sunitinib compared to patients in C1, potentially because of their higher basal activation of the UPR. The extent of ER stress signaling based on this gene signature was further correlated with the type of immune responses in the patients’ tumors [179]. Indeed, the infiltration ratios of regulatory T (T regs) and CD8 T cells were higher in the C2, compared to the C1 cluster, whereas infiltration levels of monocytes, neutrophils, M1 macrophages, dendritic cells and mast cells were higher in C1 cluster. These correlative observations need to be further confirmed by more extensive clinical data, however. Based on these in silico analyses, an ER stress-related prognostic risk model has been established for RCC, suggesting ER stress signatures be considered not only for patient prognosis but also for the design of appropriated therapeutic strategies [179]. A similar in silico study of the TCGA cohort confirmed these findings by identifying an 8 ER stress-related gene prognostics signature that could be used to determine whether the outcome of the patient is high- or low-risk (in terms of prognosis), with high-risk patients presenting more important immune infiltration and higher immune scoring [180]. Our own analyses of the publicly available GEO dataset GSE150404 allowed us to also observe that more advanced stages of human ccRCC (stage III and IV) are associated with higher expression of UPR mediators, compared to early ccRCC stages (Figure 7). RCC is a global health issue, due to poor patient survival for this cancer and the low efficiency of treatments currently available [181]. Indeed, while nephrectomy and radio-ablation, as well as first line treatments such as TKI, immunotherapies and combinatory strategies remain valid therapeutic options, the criteria of eligibility for these treatments are restrictive and the efficiency of these therapeutic approaches is patient-specific. When considering the therapeutic targeting of ER stress, two different approaches can be envisaged based on currently available data. First, ER stress can be pharmacologically hyperactivated to a point overpassing the ERST, where damage caused by the ER stress induction is deemed irreversible in RCC cells and therefore leads to cell death. Second, pharmacological inhibition of a specific branch of the UPR, or global suppression of UPR signaling, could be performed to prevent mild ER stress induction of pro-survival mechanisms in RCC cells, along with another drug, such as TKI, to induce death of cancer cells. Chronic ER stress activation is a key hallmark of RCC that helps cancer cells cope with hypoxia, lack of vascularization in early-stage tumors and scarce nutritional conditions, e.g., by activating autophagy in order to efficiently grow and proliferate. The exact mechanism by which cancer cells manage to survive and not undergo apoptosis during chronic UPR activation remains poorly understood but could result from selective attenuation of specific UPR signaling, as well as epigenetic or post-translational negative regulation of ER stress mediators, as has been suggested for CHOP [182]. The threshold of ER stress tolerance shifting this process from an anti-apoptotic to a pro-apoptotic event and whether this threshold is dependent of a specific branch of the UPR, such as the PERK or ATF6 induction of CHOP, also currently remain poorly understood. Moreover, how patient genetic specificities, lifestyle and the type or mutations in RCC determine ERST is also unknown but deserves in depth investigation prior to clinical application of ER stress-targeting therapies for RCC treatment. Finally, key master regulators, e.g., E2F1 [58], that potentially switch the UPR from an adaptive mechanism to s pro-apoptotic process when ERST is attained need to be further identified and characterized. As well, the weight of indirect mechanisms that can also impact ERST with chronic ER stress, e.g., the PERK-mediated inhibition of protein translation [183] or prolonged IRE1α endonuclease activity [183], are important questions that need extensive clarification before considering targeting of the UPR for therapeutic purposes. Finally, the decision to effectively hyperactivate ER stress in RCC or to sensitize RCC to specific treatment by suppressing ER stress signaling needs to include the determination and standardization of basal UPR activation levels in patients’ tumors in order to proceed with such personalized medicine approaches. New standardized procedures and quantitative measures of ER stress in patients’ tumors needs to be developed in addition to the classical analyses of ATF4/GRP78 mRNA expression, XBP1 splicing or protein analyses of total of phosphorylated UPR effectors (IRE1α, eIF2α, cleaved and total ATF6, total PERK, CHOP and GRP78) [184]. This requires establishing a standardized multi-parametric activation/inhibition range for the UPR that would clearly indicate the strategy of ER stress modulation that would be best for a given patient.

PMC10003095

Shuqi Wang,Huanxiang Li,Zhengxing Lian,Shoulong Deng

The Role of m6A Modifications in B-Cell Development and B-Cell-Related Diseases

01-03-2023

B cell,immunodeficiency,m6A,B-cell-related diseases

B cells are a class of professional antigen-presenting cells that produce antibodies to mediate humoral immune response and participate in immune regulation. m6A modification is the most common RNA modification in mRNA; it involves almost all aspects of RNA metabolism and can affect RNA splicing, translation, stability, etc. This review focuses on the B-cell maturation process as well as the role of three m6A modification-related regulators—writer, eraser, and reader—in B-cell development and B-cell-related diseases. The identification of genes and modifiers that contribute to immune deficiency may shed light on regulatory requirements for normal B-cell development and the underlying mechanism of some common diseases.

The Role of m6A Modifications in B-Cell Development and B-Cell-Related Diseases B cells are a class of professional antigen-presenting cells that produce antibodies to mediate humoral immune response and participate in immune regulation. m6A modification is the most common RNA modification in mRNA; it involves almost all aspects of RNA metabolism and can affect RNA splicing, translation, stability, etc. This review focuses on the B-cell maturation process as well as the role of three m6A modification-related regulators—writer, eraser, and reader—in B-cell development and B-cell-related diseases. The identification of genes and modifiers that contribute to immune deficiency may shed light on regulatory requirements for normal B-cell development and the underlying mechanism of some common diseases. B lymphocytes develop from hematopoietic progenitor cells in bone marrow (BM) [1,2]. Hematopoietic stem cells (HSC) differentiate into B cells via downstream pluripotent progenitors, lymphoid-induced pluripotent progenitors, common lymphoprogenitors, and B-cell precursors, thus differentiating into naive B cells expressing surface immunoglobulin [3,4]. Under the effect of the internal environment of the bone marrow, the bone marrow stem cells differentiate into pre-B cells, immature B cells, and finally mature B cells, according to the established genetic sequence. The process of immunoglobulin gene rearrangement, gene activation, transcriptional expression, and so on, finally results in the unique surface marker, the B-cell antigen receptor (BCR) [5]. Naive cells receive antigen stimulation in peripheral lymphoid organs or blood and differentiate into memory B cells and plasma cells for humoral immunity(Figure 1) [6,7]. N6-methyladenosine (m6A) is the most common, abundant, and conserved internal co-transcription modification in eukaryotic cells, especially higher eukaryotic cells. m6A modification helps to achieve different basic biological functions at the molecular, cellular, and physiological levels. Recent studies have shown that m6A RNA modification plays a crucial role in both physiological and pathological conditions, and m6A plays an important role in regulating immune cell function and immune response. The modification of m6A adds another layer of regulation to an already complex pathway of gene expression regulation in mammals. m6A methylation is integral to the function of innate immune responses. m6A modification controls a variety of innate immune responses, such as interferon expression, inflammatory responses, and homeostasis of macrophages and dendritic cells. However, little is known about the role of m6A in B-cell development and B-cell-related diseases. In this review, we summarize recent findings regarding the influence of m6A on B-cell development and its role in B-cell-related diseases. The development of hematopoietic stem cell B lymphocytes can be divided into different stages according to the sequential expression of proteins on the cell surface or within the cell, and the rearrangement of immunoglobulin (Ig) genes. Hematopoietic stem cells produce pluripotent progenitors (MPPs) and lymphoid-induced pluripotent progenitors (LMPPs) that lack the ability to self-renew. LMPPs have the ability to differentiate into common lymphoid progenitor cells (CLPs), granulocyte/macrophage progenitor cells (GMPs), or early T-cell progenitor cells (ETPs) [8]. The CLP compartment consists of all lymphoid progenitors (ALPs) and B-cell-biased lymphoid progenitors (BLPs). BLPs mainly differentiate into B-line cells [9]. The progression of HSCs in successive developmental stages requires changes in their cellular gene expression and chromatin status, reflecting genetic and epigenetic regulation [4]. In the context of sequential development, the core bypass network that orchestrates the fate specification of B cells is established. Transcription factors Ikaros, PU.1, and E2A regulate lymphocyte and myeloid fate selection, and EBF and Pax5 control B-cell specification and commitment. Ikaros transcription factor is a major regulator of the progression of HSC into the lymphatic system. Ikaros regulates cytokine receptor flt3, λ5 precursor B-cell receptor chain, and Rag1/2 gene expression, and its activity is required in LMPPs and early B-cell precursors. The expression of PU.1 in MPPs limits the fate of MEPs, and then the synergistic action of PU.1 and Ikaros-induced Gfi-1 (growth factory-independent-1) transcription factors establish selection of B-cell and myeloid fate by stabilizing PU.1 levels [10,11]. E2A promotes the production and/or maintenance of MPPs and LMPPs and is required for bone marrow restriction of LMPPs. In addition, E2A is required to promote progression of the B-cell lineage through a cascade of the regulatory factors EBF, Pax5, and Foxo1 [12,13]. Forced expression of EBF in MPPs activates the pedigree-related genes Pax5, λ5, VpreB, and Cd79b, and inhibits other fate-related genes, including c/EBPα [14]. Binding of the interferon regulatory factor IRF8 to the EBF promoter leads to transcriptional activation of EBF, while binding to the Sfp1 promoter inhibits PU.1 [15]. EBF in turn enhances E2A activity by inhibiting ID inhibitors of E2A [16]. The progression of BLPs to mature B cells involves multiple stages, with pro-B cells undergoing Rag-mediated assembly of the immunoglobulin heavy-chain (IgH) gene and successfully pairing IgH chain with alternative light-chain VpreB and λ5 to produce pre-B cells expressing pre-B cell receptors (pre-BCRs). This process allows the rearrangement of light-chain genes of immunoglobulin and successful pairing of IgH with IgK or IgX chains to produce immature B cells expressing BCRs that monitor the reactivity of B cells, which eventually differentiate into mature B cells from bone marrow [17]. B-cell deficiency (antibody deficiency disorder) is the most common type of immunodeficiency. It is caused by abnormal development and/or function of B cells and is the major primary immunodeficiency, accounting for approximately 50% of all PID diagnoses [18,19]. B cells develop in bone marrow and are the main cells of humoral immunity. The main functions of B cells are to produce antibodies, act as antigen-presenting cells, and secrete cytokines. Stimulated by antigens, B cells can differentiate into antibody-producing plasma cells and memory B cells to perform specific humoral immunity. A common feature of B-cell immunodeficiency disorders is a significant reduction in or absence of serum immunoglobulin. Antibody deficiency increases susceptibility to infection by bacterial pathogens, particularly Streptococcus pneumoniae and Hemophilus influenzae [20,21]. The manifestations and complications of B-cell developmental defects vary depending on the location or degree of functional impairment. There are three main types of primary B-cell defects: X-linked agammaglobulinemia [22,23,24,25,26,27,28,29], common variable immune deficiency [20,30,31,32,33,34,35,36,37,38,39,40], and high immunoglobulin syndrome [41,42,43,44]. X-linked agammaglobulinemia (XLA) was the first innate immune error found in humans and is the most common primary B-cell defect disease. It is characterized by B-cell and plasma cell defects and severe hypogammaglobulinemia; increased susceptibility to enveloped bacteria; and recurrent bacterial infections in infected men early in life [22]. The first case, an eight-year-old male child, was reported on by Ogden Bruton in 1952. The child experienced multiple bacterial pathogens: his serum sample was evaluated by protein electrophoresis and showed no globulin portion [23]. The affected gene, located on the long arm of the X chromosome, encodes a cytoplasmic tyrosine kinase named Bruton’s tyrosine kinase (BTK) [24,25]. Signals transduced with the help of BTK play a key role in the production of naive, mature B cells from the bone marrow into the circulation. When the expression level of BTK is low or gene mutation occurs, the developing B cells in bone marrow show maturation stagnation and cannot differentiate, and the level of mature B lymphocytes in the peripheral blood of patients is significantly reduced [26]. The clinical manifestations of XLA are repeated and severe bacterial infections can occur, such as upper respiratory tract infection, lower respiratory tract infection, nasal and pulmonary infection, otitis media, meningitis, osteomyelitis, sepsis, bronchitis, rheumatoid arthritis, etc. [27,28,29]. Common variable immune deficiency (CVID) is a major antibody deficiency and one of the most common primary immune deficiencies. In 1954, Sanford et al. reported the first clinical case of CVID in a 39-year-old woman with low serum levels of gamma globulin and recurrent infection [30]. In 1971, a committee of the World Health Organization coined the term “common variable immune deficiency” (CVID) to distinguish the less well-defined antibody deficiency syndrome from other conditions with more consistent clinical descriptions and Mendelian inheritance [31]. Patients with CVID, most of whom are diagnosed between the ages of 20 and 45 years, are characterized by significantly reduced serum immunoglobulin IgG and IgA, normal or low serum IgM, and defects in specific antibody production [20,32]. Different barriers to B-cell development occur in CVID, such as the failure of B cells to fully activate, proliferate normally, and eventually differentiate into plasma and/or memory B cells [33]. Patients with CVID often also have numerous T-cell abnormalities, such as defective T-cell activation [34], enhanced cell apoptosis [35], cytokine defects [36], lymphocytopenia [37], defects in mitogen and antigen proliferation [38], abnormal cell response to chemokines [39], etc. Clinical symptoms of CVID include severe lung disease, recurrent gastrointestinal infections, autoimmune, and inflammatory diseases [40]. High immunoglobulin M syndrome (HIGM), also known as immunoglobulin class switch recombination (Ig-CSR) deficiencies, is a rare primary immunodeficiency characterized by severely reduced serum levels of immunoglobulin A, G, and E; serum immunoglobulin M levels are normal or elevated [43]. The HIGM was first described by Rosen et al. in 1961. The HIGM was molecularly defined in a 1992 Notarangelo report on the CD40 ligand (CD40L) gene [41,42]. The HIGM phenotype has been observed in different single-gene immunodeficiency diseases, such as CD40L and CD40 defects, AICDA-encoded activation-induced cytidine deaminase (AID), and uracil-DNA glycosylase (UNG) deficiency disorders [43]. The CD40 molecule on B cells and its activated T cell ligand, CD40L, play a role in B-cell immunoglobulin isogenic signaling, and patients with CD40L mutations account for 65% of HIGM patients [44]. The main clinical symptoms of HIGM patients are upper and lower respiratory tract infections, otitis media, gastrointestinal infections, oral ulcers, autoimmune, lymphoid hyperplasia, and malignant tumors [42]. More than 170 chemical modifications of RNA have been found in living organisms [45]. RNA modification has been found in all types of RNA molecules, including transfer RNA (tRNA), ribosomal RNA (rRNA), and messenger RNA (mRNA), as well as microRNA (miRNA), long non-coding RNA (lncRNA), and circRNA [45,46,47,48,49,50]. RNA modification plays an important role in RNA metabolism, including RNA structure formation; stability and dynamics [51]; RNA splicing; polyadenosine decomposition; transport; localization; and translatability. Currently, the most studied RNA modifications include N1-methyladenosine (m1A), 5-methylcytosine (m5C), N6-methyladenosine (m6A), N7-methylguanosine (m7G), N6,2′-O-dimethyladenosine (m6Am), 8-oxo-7,8-dihydroguanosine (8-oxoG), etc. [52,53,54,55]. Methylation of the N6 position of RNA (N6-methyladenosine [m6A]) is one of the most common post-transcriptional modifications of RNA and the most abundant internal mRNA modification. m6A plays an important role in almost every aspect of the mRNA life cycle, as well as in various cellular, developmental, and disease processes [56]. In mammalian cells, there are an average of 1–2 m6A sites per 1000 nucleotides [57,58]. m6A was first discovered in 1974 [59,60] and is mainly enriched in the 3′ untranslated region (3′ utrs), near the stop codon, inside and outside the long exon, intergenic region, intron, and 5′ untranslated region (5′ utrs) [61,62,63,64]. Similar to epigenetics, the deposition of RNA modification is dynamic and it has been identified that specific proteomes influence the fate of RNA, such as “writers” for catalytic modification deposition, “erasers” for catalytic modification removal, and “readers” for recognizing and binding modified nucleotides (Figure 2) [65]. The physiological roles of m6A and its reader in various biochemical processes have been studied and identified, such as embryonic stem cell differentiation [66], hematopoietic stem cell development [67,68,69], and immune response [70,71]. The characterization of these effector proteins in various biological systems underscores the multifaceted and adjustable nature of their function. Once the protein involved in m6A modification is abnormal, a series of diseases will be caused, including tumors, neurological diseases, embryonic development delay, etc. m6A writers are methyl transferases that catalyze the formation of m6A modification [72]. The multicomponent methyltransferase complex consists of S-adenosine methionine (SAM)-binding protein methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14) heterodimer catalytic cores, and various other methyltransferases [73,74]. The METTL3-METTL14 heterodimer is essential for the methylation process. METTL3 catalyzes the conversion of adenosine to m6A through its methyltransferase active domain, and METLL14 plays a key role in the substrate recognition process, providing structural support for METTL3 close to its active site, thus achieving catalysis [75,76]. The heterodimerization complex of the methyltransferase domain binds to the CCCH motif to form the minimum region required for the formation of m6A modification in vitro [75]. Wilms’ tumor 1-associated protein (WTAP) interacts with METTL3 and METTL14 to catalyze m6A methyltransferase activity in vivo. WTAP may also play a role in regulating the recruitment of m6A methyltransferase complex to mRNA targets [74,77]. Recent studies have shown that zinc finger protein Zc3h13 (Flacc) is required for the nuclear localization of the ZC3H13-WTAP-Virilizer-Hakai complex and promotes m6A methylation [78]. Through proteomic methods, KIAA1429 (also known as vir-like m6A methyltransferase associated (VIRMA)) is identified as another component of the m6A methyltransferase complex; KIAA1429 is one of the main interaction factors of WTAP [79,80,81]. In addition, RBM15 and its analog RBM15B are functional components of the methyltransferase complex and interact with METTL3 in a WTAP-dependent manner [82]. RBM15 and RBM15B bind to the uridine-rich region and then recruit the WTAP/METTL3 complex to methylate the nearby DRACH motif [82]. METTL16 has recently been identified as an m6A “writer” that plays a methyltransferase activity-dependent and independent role in gene regulation, promoting translation in an m6A independent manner [83]. METTL16-mediated methylation is mainly caused by small nuclear RNAs, some intron sites in pre-mRNA, and other ncRNAs [84,85,86]. m6A-modified deposition is reversible and dependent on demethylase. A-ketoglutarate-dependent dioxygenase alkB homology 5 (ALKBH5) and Fat Mass and Obesity Associated Protein (FTO) are “erasers” to reverse m6A methylation [87]. FTO is the first demethylated enzyme identified to catalyze the reversal of m6A methylation in mRNA, both in vitro and intracellularly [88,89]. In most cell lines, FTO is localized primarily in the nucleus and mediates 5–10% of total mRNA m6A demethylation. In leukemia cells, FTO is highly abundant in the cytoplasm, mediating up to about 40% of m6A demethylation [65]. In addition, AlkB homolog 3 (ALKBH3) was found to preferentially act on m6A modifications in tRNAs [90]. Because m6A demethylase is distributed differently in tissues and plays an important role in regulating m6A methylation, additional cell or tissue-specific demethylases may exist to act on different RNA substrates [91]. m6A modification sites can be recognized by “reader” proteins to regulate RNA metabolism, splicing, translocation, degradation, and processing [91]. Some m6A binding proteins with YTH domains, including YTHDF1, YTHDF2, YTHDF3, YTHDC1, and YTHDC2, act as “readers” of m6A to regulate the translation and mediated degradation of m6A-modified RNA [56,92]. YTHDF1 can enhance mRNA translation, YTHDF2 can promote mRNA degradation, and YTHDF3 can enhance both translation and degradation. The main function of YTHDFs is to inhibit gene expression by enhancing the degradation of methylated mRNA in cytoplasm [76,93,94,95]. YTHDC1 binds to certain m6A sites in both mRNA and non-coding RNA, while YTHDC2 mainly binds to non-coding RNA [96,97]. YTHDC1 of Drosophila melanogaster participates in sex determination and dose compensation by regulating selective splicing of Sxl. In humans, YTHDC1 also plays a role in dose compensation. YTHDC1 interacts with splicing factors to regulate alternative splicing and nuclear output. YTHDC2 is a nucleoplasmic protein that only exists in mammals. It is characterized by a gyrase domain, anchor repeat sequence, YTH domain, and DUF1065 domain [98]. Later, other readers were discovered: Eukaryotic translation initiation factor 3 (EIF3), heterogeneous nuclear ribonucleoprotein (hnRNPC and hnRNPA2/B1), insulin-like growth factors (IGF2BP1, IGF2BP2, and IGF2BP3), proline-rich and curled protein 2A (PRRC2A), and fragile X mental retardation protein (FMRP), etc. YTHDF1 binds to the m6A site around the stop codon of mRNA and can recruit the 40S ribosomal complex, including eIF3, eukaryotic translation initiation factor 4E (eIF4E), eukaryotic translation initiation factor 4G (eIF4G), poly (A)-binding protein (PABP), and 40S ribosome subunits to promote the translation of target RNA [95]. The eIF3 can be recruited directly by m6A in the 5′ UTR region of the transcript and then recruited into the 43S ribosomal pre-initiation complex, promoting cap-independent translation [64]. hnRNPA2/B1 can recognize m6A on the transcriptional subset of primary microRNA (pri-miRNA) and interact with the microRNA microprocessor complex protein DGCR8 to promote the processing of pri-miRNA [46]. IGF2BPs can recognize m6A, promote mRNA stability and translation, and depend on m6A [99]. Deficiency of PRRC2A, a novel m6A-specific binding protein found in nerve cells, leads to hypomyelination by affecting oligodendrocyte regulation in the brain [100]. By studying the regulatory mechanism of RNA-binding protein FMR1, we found that FMR1 is a novel m6A reader, which affects the translation of target mRNA and the transport of mRNA particles [101]. m6A modification and its regulatory factors regulate the expression of genes, which are associated with many B-cell diseases (Table 1). m6A modification can regulate the development of early B cells. Deletion of METTL14 significantly reduced m6A methylation in developing B cells and severely hindered the development of mouse B cells. The large-pre-B-to-small-pre-B transition process in METTL14 knockout mice was impaired. Loss of METTL14 in developing B cells reduces YTHDF2 binding to its target and specifically leads to up-regulation of a set of YTHDF2-bound transcripts. YTHDF2-mediated degradation of mRNA is key to the transition from pro-B stage to large pre-B stage, and both METTL14 deletion and YTHDF2 deletion significantly block IL-7-induced pro-B-cell proliferation [105]. Grenov et al. have shown in their studies that Mettl3 regulates the response of GC B cells through YthDF2-mediated degradation of genes associated with oxidative phosphorylation and IGF2BP3, enhancing the stability of m6A-modified Myc transcripts. METTL3 deletion in GC B cells slowed down the cell cycle process and reduced the expression of genes related to proliferation and oxidative phosphorylation. m6A interaction factor IGF2BP3 is required for GC persistence to support Myc transcriptional stabilization and downstream pathways. YTHDF2 as a reader of m6A can regulate appropriate gene expression and function of mitochondrial respiration [102]. In Huang et al.’s study, it was found that METTL14-mediated RNA modification of m6A is essential for germinal center (GC) B-cell response in mice. When METTL14 was specifically deleted from B cells, the response of GC B cells was impaired, and BCR and CD40 signals in GC B cells were attenuated. METTL14-mediated m6A indirectly up-regulates the expression of genes critical for positive selection and proliferation of GC B cells by promoting mRNA decay of genes encoding a set of negative immunomodulators, including Lax1 and Tipe2 [106]. The deletion of METTL3 affected the stability of Myc mRNA, while the deletion of METTL14 did not reduce the level of Myc mRNA in GC B cells. This difference may be due to incomplete functional overlap between METTL3 and METTL14, with METTL3 having methyltransferase activity instead of METTL14 [119,120]. In Jiang et al.’s study, genetic analysis of the B-cell CRISPR/Cas9 system was used to identify positive and negative regulators of CD40 response. In the study, WTAP components VIRMA/KIAA1429 had a strong negative regulatory effect on CD40, and WTAP regulated CD40 response by negatively regulating CD40 mRNA levels [107]. GC is a secondary lymphoid organ structure essential for key aspects of B-cell development, differentiation, somatic super-mutation, and class transformation recombination. Interference with CD40/CD40L signaling collapses GC, which is the basis of adaptive humoral immune response [121,122]. In the study of Xu et al., it was found that the expression levels of ZC3H13, RBM15, RBM15B and VIRMA were positively correlated with the expression of RAB39B through comprehensive biological information analysis. RAB39B is associated with proliferation, apoptosis and drug sensitivity of diffuse large B-cell lymphoma (DLBCL), the most common aggressive lymphoma. RAB39B can be used as an effective biomarker for the diagnosis and treatment of DLBCL [108]. In a study by Raffel et al., loss of RBM15 resulted in the obstruction of pro/pre-B-cell differentiation and the loss of peripheral B cells in adult mice. It has also been shown that RBM15 is essential for B lymphocyte generation and has inhibitory effects on myeloid, megakaryocytes, and the progenitor cell compartment [109]. Niu et al. found that RBM15 may function in part by regulating the expression of the proto-oncogene c-Myc, which is necessary for normal hematopoietic stem cell-niche interaction and normal promotion of adult hematopoietic cells and normal megakaryocyte development [110]. m6A methylation can significantly improve the expression of innate immune cells associated with inflammatory processes [123]. FTO is a potential anti-inflammatory target [111]. The expression of RAB39B, an effective biomarker of DLBCL, was significantly positively correlated with FTO and ALKBH5 [108]. Translation-regulated lncRNA1 (TRERNA1) was first reported as an enhancer-like RNA, which can mediate the expression of its neighboring genes [124]. TRERNA1 was positively correlated with lymph node metastasis, and its expression stimulated the invasion and metastasis of breast cancer and gastric cancer [125,126]. TRERNA1 modifies its promoter region by H3K27me3 and recruits EZH2 to silence the expression of cyclin-dependent kinase inhibitor p21 in an epigenetic manner. TRERNA1 can be modified by ALKBH5, the up-regulation of ALKBH5 promotes the expression of TRERNA1, and the N6-methyladenosine-modified TRERNA1 mediated by ALKBH5 promotes the occurrence of DLBCL [112]. In addition, ALKBH5 is related to the growth of Myc-dysregulated B-cell lymphoma, and inhibition of ALKBH5 can effectively inhibit the growth of MYC-dysregulated B-cell lymphoma, both in vitro and in vivo. Myc activated the expression of ALKBH5 and decreased the level of m6A in mRNA [113]. Jiang et al. showed that m6A reader YTHDF2 was a negative regulator of CD40, and the knocking out of YTHDF2 could increase the abundance of CD40 [107]. The expression levels of YTHDC1, YTHDC2, YTHDF1, YTHDF2, and YTHDF3 in RAB39B high-expression cells were significantly up-regulated [108]. Grenov et al. reported a post-transcriptional mechanism that inhibits plasmoblastic genetic programming and promotes GC B cells. In their study, using single-cell RNA sequencing (RNA-seq) techniques and transgenic mice, they found that antigen-specific B-cell precursors up-regulate YTHDF2 in the pre-GC phase, thereby enhancing the decay of methylated transcribed proteins during the early stage of B-cell immune response [114]. Recent studies have shown that hnRNPC is closely associated with alternative splicing associated with overall survival in DLBCL [127]. Yin et al. found that hnRNPA2/B1 was associated with the proliferation of human glioma cells. The down-regulation of hnRNPA2/B1 led to the inactivation of AKT and STAT3 signaling pathways, and ultimately decreased the expression of B-cell lymphoma-2 (Bcl-2), cyclin D1 and proliferating cell nuclear antigen (PCNA) [117]. In addition, IGF2BP1-3 has been shown to play a role in B-lymphoid precursor tumors [118]. In B-cell acute lymphoblastic leukemia (B-ALL), the high mRNA expression of IGF2BP3 is associated with the high expression of proliferative “metagene” markers and CDK6 [128]. IGF2BP3 is also used as a diagnostic and prognostic marker for several malignant tumors. Mutations in the RRRC2A gene affect the risk of non-Hodgkin lymphoma (NHL) [115]. The formation and function of B lymphocytes largely depends on the precise regulation of multilayer gene expression. More and more evidence is showing that post-transcriptional modification of RNA is another important regulatory link of gene expression, which can regulate mRNA degradation, splicing or translation during B-lymphocyte generation. This review briefly introduces the development and maturation of B cells. Many studies have shown that B-cell-related diseases are related to m6A modifier regulators. The identification of disease-causing genes and modification factors may help clarify the regulatory requirements for normal B-cell development as well as the potential basis for some common diseases and the search for new drug targets. In short, this topic has high research value and needs further study.

PMC10003096

Alessandro Zucchi,Francesco Claps,Antonio Luigi Pastore,Alessandro Perotti,Andrea Biagini,Luana Sallicandro,Rosaria Gentile,Concetta Caglioti,Federico Palazzetti,Bernard Fioretti

Focus on the Use of Resveratrol in Bladder Cancer

26-02-2023

apoptosis,bladder cancer,angiogenesis,proliferation,resveratrol

Bladder cancer is the most common tumor of the urinary system, with a high incidence in the male population. Surgery and intravesical instillations can eradicate it, although recurrences are very common, with possible progression. For this reason, adjuvant therapy should be considered in all patients. Resveratrol displays a biphasic dose response both in vitro and in vivo (intravesical application) with an antiproliferative effect at high concentrations and antiangiogenic action in vivo (intraperitoneal application) at a low concentration, suggesting a potential role for it in clinical management as an adjuvant to conventional therapy. In this review, we examine the standard therapeutical approach to bladder cancer and the preclinical studies that have investigated resveratrol in xenotransplantation models of bladder cancer. Molecular signals are also discussed, with a particular focus on the STAT3 pathway and angiogenic growth factor modulation.

Focus on the Use of Resveratrol in Bladder Cancer Bladder cancer is the most common tumor of the urinary system, with a high incidence in the male population. Surgery and intravesical instillations can eradicate it, although recurrences are very common, with possible progression. For this reason, adjuvant therapy should be considered in all patients. Resveratrol displays a biphasic dose response both in vitro and in vivo (intravesical application) with an antiproliferative effect at high concentrations and antiangiogenic action in vivo (intraperitoneal application) at a low concentration, suggesting a potential role for it in clinical management as an adjuvant to conventional therapy. In this review, we examine the standard therapeutical approach to bladder cancer and the preclinical studies that have investigated resveratrol in xenotransplantation models of bladder cancer. Molecular signals are also discussed, with a particular focus on the STAT3 pathway and angiogenic growth factor modulation. Resveratrol (trans-3,4′,5′-trihydroxystilbene) is a stilbene that consists of two aromatic rings joined together by an ethylene bridge. It is found in several plants and fruits, such as grapes (Vitis vinifera), mulberries (Morus spp.), and peanuts (Arachis hypogaea) [1]. Resveratrol is also a phytoalexin, a compound with an antibiotic function that is produced by higher plants in response to infections or other stressors [2]. Therefore, the concentration of resveratrol in plants increases in response to environmental stress, heavy metals, and UV light [3]. Resveratrol was isolated for the first time from the roots of Veratrum grandiflorum in 1940 and, subsequently, in 1963 from the roots of Polygonum cuspidatum, a plant used in traditional Chinese and Japanese medicine [2], rich in resveratrol 3-O-β-d-glucoside (piceid) [4]. Resveratrol has shown several beneficial properties for human health, such as anti-aging [5], anti-inflammatory [6], neuroprotective [7], hepatoprotective [8], cardioprotective [9], antidiabetic [10], and antioxidant activity [8]. Resveratrol displays chemopreventive action and anticancer action in several types of neoplasia [11]. Recently, resveratrol has attracted great interest for application in bladder cancer therapy [12]. The main obstacle in understanding the health potential of resveratrol is the difficulty of comparing the effects observed in vitro with those observed in vivo as the concentrations reached in the latter are lower than those that can be studied in vitro. With these limitations and the pharmacokinetics of resveratrol in mind, we critically reviewed in vivo studies (animal models) that have sought to evaluate the uses of resveratrol in the treatment of bladder cancer. Bladder cancer is the seventh most frequent cancer in the male population worldwide, with 9.5 cases per 100.000 people/year in men and 2.4 cases per 100.000 people/year in women. The incidence of bladder cancer in Europe is significantly higher than in the rest of the world, with 20 cases in men and 4.6 cases in women per 100.000 people/year [13]. The incidence in the world changes significantly in relation to the various risk factors to which the population is exposed, as well as due to the different diagnostic techniques and the availability of treatments [14]. At least 75% of the patients present, at the first diagnosis, non-muscle-invasive bladder cancer (NMBC) at different stages (Ta, carcinoma in situ, or T1), with a higher percentage in younger patients [15]. Smoking is the major risk factor in the pathogenesis of urothelial bladder cancer and the main causative agent in at least 50% of cases of bladder cancer. The risk increases progressively with the intensity and duration of smoke exposure. Bladder cancer is classified using the TNM Classification of Malignant Tumours (TNM), approved by the Union for International Cancer Control (UICC). This classification is essential to define the appropriate treatment for each individual case of bladder cancer [16]. When the bladder tumor is removed endoscopically, it is possible to establish the “T” of the TNM, i.e., to define whether the tumor is non-muscle invasive (Ta and T1, which indicate whether it invades the lamina propria or not, respectively) or T2 (which indicates that it is muscle-invasive). The so-called “CIS” (carcinoma in situ), a flat, non-invasive, high-grade cancer, deserves special mention. It can be invisible to cystoscopy and, therefore, may not be diagnosed or may be interpreted as a simple inflammatory area due to its usually reddish appearance [17]. Therefore, the “T” of the TNM, together with the histology of the bladder tumor, is essential to define the therapeutic or follow-up procedure to adopt. Regarding histology, over 90% of bladder tumors are urothelial, and they are classified on the basis of the risk of progression (but not of recurrence) with a double classification: WHO 1973, which divides bladder tumors into G1, G2, or G3; WHO 2004/2016, which divides them into papillary urothelial neoplasm of low malignant potential (PUNLMP), low-grade, and high-grade [18,19]. Cancer is mostly non-muscle-invasive in the early stages, and up to 15% will eventually progress to muscle-invasive bladder urothelial carcinoma [20]. Superficial bladder cancers, such as stages Ta (superficial), Tis (in situ), and T1 (tumor invades subepithelial connective tissue) account for 75–85% of neoplasms at clinical presentation, while the remaining 15–25% are invasive (T2, T3, and T4) or have metastasized at the time of diagnosis [21]. As already mentioned above, the management of bladder cancer requires correct staging using the TNM system. The “T” of TNM is obtained by transurethral resection surgery. Transurethral resection of bladder tumor (TURBT) can stage up to T2, and it alone is capable of eradicating completely a Ta or T1 tumor. However, recurrences in bladder cancer are very common, with a possible progression. More than 70% of all patients treated for superficial bladder cancer will subsequently develop one or more recurrent tumors, and about one-third of these patients will progress to cancer that invades the surrounding muscle [22,23]. Adjuvant therapy should be considered in all patients (Figure 1): in low-grade bladder tumors, a single dose of intravesical chemotherapy (mitomycin C, epirubicin, or pyrarubicin) is suggested within 24 h of resection to prevent recurrence [24,25,26,27,28]. More intravesical instillations of chemotherapy may be necessary and suggested depending on the risk of progression and recurrence: for those patients with low-grade, low-risk tumors, only a single instillation post-surgical resection may be advised. Conversely, high-risk patients benefit from repeated treatment over time [29]. Patients with histological evidence of high-grade bladder cancer should undergo bladder instillations with bacillus Calmette–Guérin (BCG), which has a higher efficacy than chemotherapy in preventing the recurrence of non-muscle-invasive high-grade urothelial cancer [30,31,32,33,34]. CIS deserves a separate mention also regarding the treatment: in fact, it cannot be treated only with an endoscopic resection procedure. When a histological diagnosis of CIS is present, it is mandatory to perform intravesical instillations of BCG or, in certain cases, even to propose a radical cystectomy. There are some cases where the bladder tumor does not respond to BCG instillations and “relapsed tumors” or “recurrent tumors” are reported. In these cases, radical cystectomy must be proposed due to the high risk of progression and metastasis that BCG-unresponsive cancer has [35]. The in vitro and in vivo effects of resveratrol as an antineoplastic agent in bladder cancer have recently been reviewed [11,12]. While several researchers have studied the in vitro effects of resveratrol in bladder cancer biology, only two studies have considered its potential use in in vivo models. Notably, clinical studies on the use of resveratrol in bladder cancer therapy protocols are completely missing (evaluated in https://clinicaltrials.gov/ website by using keywords such as “cancer bladder” and “resveratrol”, accessed on 4 January 2023). In this review, we focus on the possible applications of resveratrol in bladder cancer treatment by considering the evidence derived mainly from in vivo models. A resveratrol dose of 20 mg/kg body weight, with daily intraperitoneal (i.p.) administration, inhibited the growth of subcutaneous (s.c.) xenografted bladder cancer [36]. Other investigators used resveratrol i.p. administration to evaluate the efficacy of resveratrol to inhibit tumor cell growth different from bladder cancer. In s.c. xenografted ovarian cancer using Balb/c nu/nu mice, i.p. injection at concentrations of 50 and 100 mg/kg body weight for 4 weeks reduced tumor growth [37]. Similarly, concentrations of 20 and 40 mg/kg body weight reduced the s.c. growth of tumors from Erlich’s ascites [38]. In addition, in an s.c. neuroblastoma tumor model, 5 mg of resveratrol decreased cancer growth [39]. Surprisingly, 10 mg/kg body weight of i.p. resveratrol was not able to reduce cancer growth and survival in NOD.CB17-Prkdcscid/J mice engrafted with the human t(4;11) acute lymphoblastic leukemia (ALL) cell line [40]. The lack of anticancer effects of 10 mg/kg daily of i.p. resveratrol can be associated with the low dose used since, in other studies, the relationship between anticancer effects and dose has been observed. For example, in glioblastoma s.c. syngeneic rat xenotransplants models, the i.p. injection of resveratrol (10 or 40 mg/kg daily for 4 weeks) reduced tumor mass only at the highest concentration through an antiangiogenic action [41]. Interestingly, an antiangiogenic action of resveratrol (reduction of VEGF and FGF-2) was suggested to be involved in the tumor reduction of the s.c. xenotransplated human T24 bladder cancer model [36]. Overall, i.p. resveratrol displays anticancer effects in bladder tumor xenotransplantation similar to other neoplasia at an i.p. dose higher than 10 mg/kg. A pharmacokinetic study of i.p. administration of 10 mg/kg of resveratrol in a single dose in mice displayed a sub-micromolar plasma concentration after 1 h from the administration (the serum concentrations of the total resveratrol were ~4 ± 2 μM, roughly distributed at a 1:3:1 ratio of resveratrol/resveratrol glucuronide/resveratrol sulfate [40]), indicating that this value represents the threshold to observe the cancer growth reduction in vivo [41]. Unfortunately, scant information was reported in in vitro studies of the effects of a low micromolar concentration of resveratrol on bladder cancer biology. This last consideration made it difficult to compare and use the data obtained from the in vitro experiment where resveratrol was tested in bladder cancer cell lines at concentrations higher than 10 μM and up to 200 μM [12]. Resveratrol showed a biphasic effect on proliferation, which was related to the concentration when it was applied to a bladder cancer cell line. Specifically, at low concentrations (lower or equal to 20 μM), it had no antiproliferative effects, while at high concentrations (greater or equal to 20 μM), it exhibited an antiproliferative effect by inducing apoptosis [42]. This outcome was confirmed in several studies, as in the bladder cancer cell line T24, BTT739, Pumc-91/ADM, where an antiproliferative effect (i.e., cell cycle blockade or apoptosis) was observed at concentrations higher than 20 μM [36,43,44,45,46,47,48]. In a few studies, the antiproliferative action was observed to be time-dependent [49], whereas, in others, it depended on the status of the tumor protein p53 (TP53) [47]. At low concentrations (2.5 μM), resveratrol did not show any antiproliferative activity but retained the ability to induce the mitochondrial BCL2 apoptosis regulator (BCL2) protein and BCL2-associated agonist of cell death (BAD) after 48 h of treatment, without a significant change in the BAD/BCL2 ratio [42]. Although the mechanism is still unclear, resveratrol reduced the growth of the tumor mass in vivo when treated via i.p. (low systemic concentration), by modulating processes such as angiogenesis [36], with a reduction of the vascular endothelial growth factor (VEGF) and fibroblast growth factor 2 (FGF-2). Therefore, we can hypothesize (Figure 2) that at low concentrations (obtained through a systemic administration, for example, i.p.) resveratrol has an antiangiogenic effect, reducing FGF-2 and VEGF, while at high concentrations (obtained through a local intravesical administration [44]) it has an antiproliferative effect as a consequence either of the reduction of miRNA21 [49], the signal transducer and activator of transcription 3 (STAT3), or its downstream genes, such as c-Myc, cyclinD1, survivin, and VEGF [44]. The beneficial effects of resveratrol were associated with antioxidant properties and the ability to activate the sirtuins and protein kinase AMP-activated (AMPK) pathway. Because of the presence of more than one phenolic group, resveratrol belongs to the category of polyphenols and shows strong antioxidant properties, since it reacts with free radicals, resulting in more stable adducts, which are therefore less reactive and less toxic than the radicals themself [1], enhancing the cellular antioxidant activity. For example, resveratrol upregulates the tumor suppressor phosphatase and tensin homolog (PTEN), the major antagonist of phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K), by blocking AKT serine/threonine kinase 1 (Akt) activation, which leads to an upregulation of the mRNA levels of antioxidant enzymes such as catalase (CAT) and superoxide dismutase (SOD) [50]. Resveratrol stimulates the nuclear factor erythroid 2-related factor 2 (Nrf2), which initiates the transcription of many antioxidant genes such as SOD and CAT to reduce oxidative stress. Resveratrol could also improve the antioxidant defense system by modulating the action of antioxidant enzymes through the downregulation of the extracellular signal-regulated kinase (ERK) kinases that are activated by the reactive oxygen species (ROS). Neoplastic progression is associated with the alteration or mutation of genes that can occur spontaneously or following exposure to carcinogens. Oxidative stress plays a crucial role in the carcinogenesis process; ROS can react with DNA, causing serious damage, such as mutations [51]. Resveratrol, as a radical scavenger, appears as an anticancer agent by limiting the genotoxic impact of ROS and attenuating the processes of transformation into neoplastic cells [52]. In general, the anticancer effects have been correlated with other mechanisms of action independent from its radical scavenger properties [53]. In bladder cancer cell lines, resveratrol exerts its anticancer activity by inducing cell cycle arrest, apoptosis, differentiation, and inhibition of the proliferation of tumor cells. It was demonstrated that resveratrol can activate the silent mating type information regulation 2 homolog 1 (SIRT1) and mimic the same beneficial effects induced by caloric restriction [54]. SIRT1 is a nicotinamide adenine dinucleotide (NAD)-dependent protein, one of the seven members of sirtuins, and belongs to the large family of the mammalian class III histone deacetylases [55]. It is mainly localized in the nucleus [56], and it is encoded by Sir2 (silent information regulator 2) [57], a highly preserved gene; homologs of Sir2 have also been found in lower organisms, such as the yeast Saccharomyces cerevisiae, the nematode Caenorhabditis elegans, and the dipterous Drosophila melanogaster [58,59]. The stimulation of SIRT1 leads to the deacetylation of lysine, coupled with the breakdown of NAD+ into nicotinamide adenine mononucleotide (NAM) and 1′-O-acetyl-ADP-ribose [59] or 1′- and 2′-O-acetyl-ADP-ribose [60], resulting in the modulation of the activity of the peroxisome proliferator-activated receptor gamma coactivator 1 alpha, (PPARGC1A, or PGC-1α) and other transcriptional factors related to aging and life span [47,61], including mitochondrial biogenesis [62]. However, even if the effects of resveratrol on SIRT1 and PGC-1α are well-known, the mechanism behind the regulation is still controversial [63]. Some studies have reported an indirect activation of SIRT1 by resveratrol, which firstly acts on AMPK, leading to an increase in NAD+ levels and, as a consequence, increases in SIRT1 and PGC-1α [64]. On the other hand, other studies have found a direct stimulation of SIRT1 by resveratrol, followed by the activation of AMPK through the deacetylation and activation of serine/threonine kinase 11 (LKB1) [65]. Data from in vitro and in vivo studies indicate a dose-dependent mechanism of resveratrol: when the dose of resveratrol was moderate (25 μM), the activation of AMPK was SIRT1-dependent, similar to that which occurs during caloric restriction, whereas a 2-fold concentration (50 μM) of resveratrol resulted in a SIRT1-independent activation of AMPK activation [63]. Furthermore, murine models lacking SIRT1 showed no differences in mitochondrial activity following treatment with both doses. In osteoporosis rats, treatment with a high dose of resveratrol revealed a downregulation of Akt phosphorylation and a mechanistic target of rapamycin kinase (mTOR) phosphorylation, suggesting an involvement of the Akt/mTOR pathway in the bone cell autophagy activation induced by resveratrol [66] and the upregulation of the insulin signaling pathway through the phosphorylation of insulin receptor substrate 1 (IRS-1), PI3K, pyruvate dehydrogenase kinase 1 (PDK-1), Akt, and glycogen synthase kinase 3 (GSK-3) [67]. A double-blind randomized trial showed an improvement in the insulin sensitivity in T2D patients after 3 g/die of resveratrol per 12 weeks, with a significant increase in the SIRT1 and AMPK expressions in the skeletal muscle, which also determined an upregulation of the solute carrier family 2 member 4 (GLUT4) [68]. Because of its low solubility in water, resveratrol shows a limited bioavailability which complicates the possibility of replicating in vivo what has been demonstrated by in vitro studies [47,69]. Once ingested through food or as a food supplement, resveratrol is rapidly assimilated in the small intestine [70,71] by passive diffusion [72] or by carrier [73]. In the enterocyte, it undergoes conjugation with uridine diphosphoglucuronic acid (UDP-GA) or 3′-phosphoadenosine-5′-phosphosulphate (PAPS), in reactions respectively mediated by different enzymatic isoforms of UDP-glucuronyltransferase (UGT) and cytosolic sulphotransferase (SULT) [74,75,76]. The conjugated resveratrol moves from the enterocyte through the transporters breast cancer resistance protein (BCRP) and multidrug resistance-associated protein 2 (MRP2) located on the apical membrane or through MRP3 on the basolateral side, entering the portal vein system until it reaches the liver. After that, the conjugation can further be catalyzed by UGT1A1, UGT9A, and SULT1A1—the same isoforms mainly expressed in the intestine [77,78]. From the hepatocyte, free resveratrol or its metabolites, including resveratrol-3-O-sulphate, resveratrol-3-O-4’-O-disulphate, and resveratrol-3-O-glucuronide, undergo enterohepatic recirculation and are re-absorbed in the small intestine before entering the portal system and reaching the liver. Here, they can go through new reactions or head into the systemic circulation to be distributed to the whole body and definitively eliminated through the urine (Figure 3). Alternatively, resveratrol can be absorbed in the large intestine, specifically in the colon, where it is metabolized by the intestinal microbiota with the formation of dehydro-resveratrol, lunularin, or 3,4’-dihydroxy-trans-stilbene [77], or eliminated through the feces [70]. Otherwise, similarly to what is described above, free resveratrol or its metabolites can reach the liver and undergo enterohepatic recirculation or enter the systemic circulation and reach the kidneys, to be excreted [77,78]. The pharmacokinetics of trans-resveratrol can change according to the type of administration, dosages, and protocol treatment [79], while its plasma concentration depends on the ingested dose [77]. Despite this, a study revealed a low plasma level concentration of trans-resveratrol following a high dose intake and a short dosing interval, with a circadian variation that was correlated with higher bioavailability after morning administration [80]. Resveratrol was well-absorbed when administered orally in 500 mg tablets, and its plasma concentrations or metabolites corresponded to the concentrations of its in vitro efficacy [81]. In addition, another study reported a plasma concentration of 1 μM of resveratrol and much higher concentrations of its glucuronide and sulfate conjugates [82]. Several approaches to improve resveratrol’s bioavailability and pharmacokinetics profile have provided promising results, such as nanocrystals [83], casein nanoparticles [84], liquid micellar formulations [85], self-emulsifying drug delivery systems [86], oat protein–shellac nanoparticles [87], and layer-by-layer nano-formulations [88]. Selective organ targeting is also possible with trans-resveratrol-loaded mixed micelles, which target the brain [89], and resveratrol-loaded glycyrrhizic acid-conjugated human serum albumin nanoparticles, which target the liver [90]. Recently, we developed a solid dispersion of resveratrol supported on magnesium dihydroxide (Resv@MDH) with better water solubility in simulated gastric fluids and an improved pharmacokinetic profile and bioavailability. Our investigation demonstrated that Resv@MDH increased resveratrol bioavailability by three times after oral administration in rabbit compared to pure resveratrol [91]. A clinical study also demonstrated that Resv@MDH improved the pharmacokinetic profile in humans [92], with a peak of plasma concentration in the micromolar range. The use of resveratrol in combination with chemotherapeutic agents could allow for avoiding the development of drug resistance, which is a potential risk to not underestimate. Resveratrol can modulate and re-sensitize cancer cells to chemotherapeutic agents [37,93] when applied in combination with drugs in clinical therapy (Table 1). The combination of resveratrol (75 and 150 μM) with gemcitabine (10 μM) in the T24-GCB cell line revealed an additive effect by reducing the cytoplasmic levels of deoxycytidine kinase (DCK), thymidine kinase 1 (TK1), and thymidine kinase 2 (TK2), while ATP binding cassette subfamily C member 2 (ABCC2) was increased [93,94]. Poly (ADP-ribose) polymerase (PARP) cleavage and apoptosis were also increased by the combined therapy. In addition, relatively low doses of resveratrol (10 μM) reduced the migratory ability of T24-GCB cells [94]. All these findings confirm the ability of resveratrol to reverse the drug resistance of T24-GCB cells to gemcitabine. On the other hand, in vitro treatment with rapamycin (20 nM) and resveratrol (100 μM) in different cell lines (TSC1-null MEFS, WTMEFs, 639V, HCV29, and MGH-U1 cells) unveiled the efficacy of the combination in maintaining rapamycin-induced inhibition of mTOR and resveratrol-induced inhibition of Akt activation. In addition, the combined therapy of resveratrol and rapamycin upregulated PARP and caspase 3, inducing apoptosis and preventing cell migration and colony formation in TSC1-null MEFs but not in WTMEFs, suggesting a TSC1-dependent mechanism of action [95]. These data confirm the potential of combined therapy with resveratrol and rapamycin to inhibit bladder cancer cell growth and induce cancer cell death, which could be specifically fitted for bladder cancer patients with tumors characterized by TSC1 mutations or activating PI3K/mTORC1 pathway mutations. Another study investigated the role of resveratrol (0, 10, 50, and 100 µM) on pumc-91/ADM cells, showing a decrease in the resistance to adriamycin but an increase in the cytotoxicity of the drug by upregulating the expression levels of DNA topoisomerase II (TOP2) and downregulating the expression levels of glutathione S-transferase (GST), LDL receptor-related protein (LRP), BCL2, and MRP1 [45]. Combined therapy with doxorubicin at a low dose (2 µM) and resveratrol at high doses (150, 200, and 250 µM) in the 5637 and T24 bladder cancer cell lines showed an additive effect between the molecules, which caused enhanced cytotoxicity in both cell lines. Moreover, the combination of doxorubicin and resveratrol was more effective on the oxidative stress, cell colony formation, cell morphology, cell migration, and nuclear division index (NDI) assay [96] compared to the treatment with doxorubicin and resveratrol alone. Resveratrol displays potential anticancer activity in vivo, but data for synergetic effects with anticancer agents are missing. In glioblastoma, the combined action of resveratrol with anticancer agents needs pre-incubation [97]. In bladder cancer, this has not yet been studied, but it should be considered in order to be able to schedule the administration times in association with other chemo and radio-therapeutic agents. Another aspect of the future of the use of resveratrol for bladder cancer is the development of new formulations with better bioavailability and plasma concentrations. In fact, resveratrol has a plasma peak and low bioavailability that limit its efficacy as an anticancer agent since the plasma levels necessary for therapeutical effects are difficult to reach with common formulations [98,99]. Thus, research on a better resveratrol formulation with an increased pharmacokinetic profile represents a challenge for its potential use as adjuvant therapy in bladder cancer. The outcomes from the combination therapy of resveratrol and drugs such as gemcitabine and rapamycin suggest a key role of resveratrol as an adjuvant in clinical therapy. The high concentrations (from 75 μM to 250 μM) indicated in the studies may be obtained using intravesical administration. However, the potential cytotoxic effect should be considered not only on the cancer cells but for the whole surrounding environment too. Therefore, we propose the instillation of resveratrol through intravesical injection after or before treatment, especially with gemcitabine, adriamycin, and doxorubicin, as rapamycin is cytostatic and not cytotoxic, in order to reduce the cytotoxicity of the combination. Another crucial aspect regarding resveratrol is its action on miRNA21. As already highlighted, resveratrol can downregulate miRNA21 expression, especially when high doses are injected through intravesical administration. The expression of miRNA21 is high in bladder cancer and stromal cells and strictly related to cancer development [100], as it increases cancer progression by polarizing tumor-associated macrophages (TAMs) [101]. These macrophages are similar to M2 macrophage phenotypes and inhibit the function of cytotoxic T-lymphocytes (CTL). Moreover, the inhibition of miRNA21 was also correlated with the suppression of the Warburg effect in the osteosarcoma MG-63 cell line, through the reduction of the levels of lactic acid, adenosine triphosphate (ATP), and glucose uptake, and the downregulation of those proteins involved in the Warburg effect, such as GLUT1, lactate dehydrogenase A (LDHA), hexokinase 2 (HK2), and pyruvate kinase M1/2 (PKM) [102]. A similar effect is also plausible in bladder cancer, as indicated by the literature available so far. Further studies should be carried out to better understand how these molecules work together and enhance the effectiveness of the standard clinical approach. These results could pave the way for new opportunities, such as the use of this novel resveratrol formulation in clinical applications as an adjuvant therapy for bladder cancer.

PMC10003097

36847161

Chris Richardson,Robert N. Kelsh,Rebecca J. Richardson

New advances in CRISPR/Cas-mediated precise gene-editing techniques

27-02-2023

CRISPR/Cas,HDR,Precise genome editing,Base/prime editing,Human disease modelling

ABSTRACT Over the past decade, CRISPR/Cas-based gene editing has become a powerful tool for generating mutations in a variety of model organisms, from Escherichia coli to zebrafish, rodents and large mammals. CRISPR/Cas-based gene editing effectively generates insertions or deletions (indels), which allow for rapid gene disruption. However, a large proportion of human genetic diseases are caused by single-base-pair substitutions, which result in more subtle alterations to protein function, and which require more complex and precise editing to recreate in model systems. Precise genome editing (PGE) methods, however, typically have efficiencies of less than a tenth of those that generate less-specific indels, and so there has been a great deal of effort to improve PGE efficiency. Such optimisations include optimal guide RNA and mutation-bearing donor DNA template design, modulation of DNA repair pathways that underpin how edits result from Cas-induced cuts, and the development of Cas9 fusion proteins that introduce edits via alternative mechanisms. In this Review, we provide an overview of the recent progress in optimising PGE methods and their potential for generating models of human genetic disease.

New advances in CRISPR/Cas-mediated precise gene-editing techniques Over the past decade, CRISPR/Cas-based gene editing has become a powerful tool for generating mutations in a variety of model organisms, from Escherichia coli to zebrafish, rodents and large mammals. CRISPR/Cas-based gene editing effectively generates insertions or deletions (indels), which allow for rapid gene disruption. However, a large proportion of human genetic diseases are caused by single-base-pair substitutions, which result in more subtle alterations to protein function, and which require more complex and precise editing to recreate in model systems. Precise genome editing (PGE) methods, however, typically have efficiencies of less than a tenth of those that generate less-specific indels, and so there has been a great deal of effort to improve PGE efficiency. Such optimisations include optimal guide RNA and mutation-bearing donor DNA template design, modulation of DNA repair pathways that underpin how edits result from Cas-induced cuts, and the development of Cas9 fusion proteins that introduce edits via alternative mechanisms. In this Review, we provide an overview of the recent progress in optimising PGE methods and their potential for generating models of human genetic disease. Gene editing via CRISPR/Cas technology has become a key tool for researchers in many areas, including plant and agricultural biology, human disease and synthetic biology. The relative ease of its implementation in many systems, availability of bioinformatic tools (Heigwer et al., 2014; Labun et al., 2019; Liu et al., 2015), commercially available reagents, flexibility and effectiveness all combine to make CRISPR/Cas an invaluable tool for modifying gene and protein function in vitro and in vivo. The Streptococcus pyogenes Cas9 (SpCas9) endonuclease has become a workhorse for generating genetic knockouts, as well as facilitating more precise edits (Anders et al., 2014; Jinek et al., 2012). Cas9-based gene-editing approaches exploit two key features of this endonuclease: its ability to recognise and bind to specific DNA sequences based on the complementarity of a guide RNA (gRNA) (Anders et al., 2014), and its ability to introduce double-stranded breaks (DSBs) in the target DNA strand (Jinek et al., 2012) (Fig. 1). Cas9 gRNAs are composed of two small non-coding RNAs: a uniform trans-activating CRISPR RNA (tracrRNA) that is recognised by the Cas9 and a CRISPR RNA (crRNA) that contains the locus-specific sequence. Together, these form a duplex called a single-guide RNA (sgRNA), which then forms a ribonucleoprotein (RNP) complex with Cas9 (Karvelis et al., 2013). Other Cas endonucleases, such as Cas12a, only require crRNAs (Zetsche et al., 2015; Zetsche et al., 2017). To cover all types of Cas endonucleases, we use the collective term ‘gRNA’ in this Review. gRNAs require the presence of a protospacer adjacent motif (PAM) (Anders et al., 2014), a specific sequence of nucleotides without which Cas will not cut. PAM site specificity, such as NGG for SpCas9, however, limits the loci that Cas can be targeted to. The ability of Cas endonucleases to generate DSBs triggers the recruitment of the endogenous DNA repair machinery to the break, and a specific genetic locus can be targeted via a gRNA. The most common DNA repair pathway, non-homologous end joining (NHEJ), results in the introduction of insertions or deletions (indels) due to the error-prone nature of this repair mechanism (Fig. 1). However, the initiation of DSBs also allows for the possibility of faithful homologous recombination (HR)-driven repair mechanisms, such as homology-directed repair (HDR) or single-stranded template repair (SSTR), which utilise a donor sequence to repair the DSB, allowing the engineered incorporation of specific edits into the target strand (Fig. 1). Although NHEJ is active throughout the cell cycle, HDR and SSTR are limited to the S and G2 phases, when sister chromatids would naturally be located close together to act as a repair template (Heyer et al., 2010). Gene knockout or mutant disease models have been generated using numerous techniques, including chemical mutagenesis, such as with N-ethyl-N-nitrosourea (ENU) (de Angelis et al., 2000; Fossett et al., 1990; Hitotsumachi et al., 1985; Solnica-Krezel et al., 1994), engineered endonucleases such as transcription activator-like effector nucleases (TALENs) (Ke et al., 2016; Li et al., 2011), targeted genetic modification of mammalian embryonic stem cells to generate chimeric modified mice (Mak, 2007) or rescue of knockout models with humanised sequences containing disease-associated mutations (Switonski et al., 2015). However, these techniques can be laborious, chemical mutagenesis cannot be targeted to a specific region of the genome, and rescue with humanised mutation-bearing constructs is not always faithful to the expression level of the endogenous gene. More recently, the use of Cas endonucleases to generate indels has been optimised in many systems: efficiencies can exceed 90% in vivo in zebrafish (Kroll et al., 2021; Burger et al., 2016), with recent adaptions for high-throughput screening (Parvez et al., 2021), 85% in mammalian cell culture (Seki and Rutz, 2018), 66% in Arabidopsis thaliana (Tsutsui and Higashiyama, 2016) and 85.7% in rats (Bae et al., 2020). Indel formation, arising as a result of DSB repair via NHEJ and leading to loss-of-function gene disruption, can be used to study gene and protein function and can model many diseases (Hai et al., 2014; Kang et al., 2015; Yuan et al., 2016; Wang et al., 2019; Stenson et al., 2003). However, in many cases, diseases are caused by single-nucleotide substitutions rather than full gene disruption (Stenson et al., 2003), and the resulting subtle changes in function cannot always be fully replicated with knockout models (Hancox et al., 2019; De Gobbi et al., 2006; Ingram, 1957). Therefore, generation of targeted, specific mutations in endogenous genes is desirable. Modelling such genetic alterations requires precise genome editing (PGE) methods. However, PGE methods that rely on HDR/SSTR to resolve Cas-induced DSBs are significantly less efficient than NHEJ-driven indel formation. PGE methods often achieve <4% efficiency (Cui et al., 2018; Prykhozhij et al., 2017 preprint; Wu et al., 2013) (Table 1), making the generation of precise human disease models, particularly in vivo (Box 1), laborious and expensive. Therefore, optimisations to PGE methods and efficiencies are urgently required. Increasing PGE efficiency is a multifaceted challenge that will likely require a combination of approaches to solve. These include efficient DNA cleavage, efficient delivery of PGE components into the target cell, the timing of editing, careful design and choice of donor DNA, the ability to effectively pass on mutations to the next generation in model organisms and the capability to subsequently screen for desired mutations. Importantly, these also require optimisation of strategies to manipulate the competitive DSB repair pathways that can either give rise to indels or PGE. Although robustly and reproducibly increasing PGE efficiency remains a challenge, there have been considerable recent advances, which we summarise in this Review. We discuss recent progress in multiple model systems and provide an overview of methods that can be employed to increase PGE efficiency. Box 1. Use of precise genome editing (PGE) in vivo for the generation of disease modelsMany developments in CRISPR technology are first investigated and proven in vitro (Table 1) as these platforms allow researchers to elucidate how the genome-editing process and the resulting mutations affect protein and cell function. Translation of these methods to generate in vivo human disease models is a powerful use of this technology. However, adapting methods developed in vitro for use in vivo is challenging. In cell culture, thousands of cells can be transfected with PGE components simultaneously, whereas germ-line mutations in whole animals typically require skilled and time-consuming manual microinjection of PGE components into fertilised embryos (the F0 generation) (Cui et al., 2018; Lamas-Toranzo et al., 2020; Park et al., 2017; Zhang et al., 2018; Song et al., 2018; Tessadori et al., 2018; Aksoy et al., 2019). Furthermore, the end goal of in vivo modelling is typically a stable precisely edited strain, which also requires efficient transmission of the edits to offspring (the F1 generation).Despite these challenges, PGE has been achieved in several model organisms, including mice (Miura et al., 2018; Wu et al., 2013), zebrafish (Hoshijima et al., 2016; Irion et al., 2014; Wierson et al., 2020; Zhang et al., 2018) rabbits (Song et al., 2016; Song et al., 2018), pigs (Song et al., 2016; Song et al., 2018) and non-human primates (Lamas-Toranzo et al., 2020; Wang et al., 2016; Yan et al., 2018). The efficiency of in vivo PGE methods, however, varies considerably between experiment, model organism and targeted loci (Table 1). For example, in vitro use of the DNA-PKcs inhibitor NU7441, which blocks non-homologous end joining and thus promotes PGE repair pathways, increased PGE efficiency to between 6.2% and 15% in HEK293 cells and induced pluripotent stem cells (Cui et al., 2018; Kang et al., 2019). When used in vivo, in zebrafish, NU7441 addition resulted in 50% somatic PGE and three of six fish produced chimeric-edited F1 progeny (Aksoy et al., 2019). Conversely, using single-stranded oligodeoxynucleotides (ssODNs) and foregoing chemical modulation for PGE in pigs resulted in between 0% and 60% of viable F0 piglets being mosaic for the desired edits and this varied between litters/experiments (Park et al., 2017). These differences in PGE efficiencies make it difficult to compare methods between studies and underscore the broad variability between organisms and protocols.Although efficient in vivo gene editing remains challenging, human diseases caused by single-nucleotide substitutions have been successfully modelled in vivo using PGE methods. Base editing has been employed in zebrafish to generate cancer models by precise mutation of tp53 and nras (Rosello et al., 2021). ssODN donor templates have been used to generate gene-edited mice that carry single-nucleotide polymorphisms implicated in human thrombosis and platelet function, which were identified from genome-wide association studies (Zhu et al., 2017). A linearised plasmid has also been used to generate knock-in pig models of Huntington's disease that exhibited germ-line transmission of the edited alleles to F1 and F2 generations (Yan et al., 2018). Such examples show the potential of Cas-based PGE for producing animal models for human genetic diseases, which can be used to better understand the function of disease-associated mutations and develop more personalised treatments. The induction of DNA repair mechanisms upon Cas-induced breaks creates the opportunity to supply exogenous donor DNA (dDNA) that contains the required change of sequence. dDNA templates for HDR or SSTR are composed of homology arms flanking the desired edits. These edits can be single-base-pair changes, specific deletions or insertions ranging from a few base pairs to complete loxP sites (Yang et al., 2013), or molecular tags or fluorescent reporters (Wierson et al., 2020; Aksoy et al., 2019; Kurihara et al., 2020). When generating such precise edits, scarless integration is desired at a specific locus, driven by the specificity of the gRNA, with the flanking recipient genomic DNA sequence remaining unaltered. Such an event, regardless of method, is encapsulated by the term PGE. Different methods exist within this umbrella term, separated by their mode of action: HDR and SSTR are separate DNA repair mechanisms that can be harnessed using dDNA (Fig. 1), whereas the more recently described base editing (BE) and prime editing (PE) employ different mechanisms to alter the target DNA sequence, which we discuss in more detail below. Researchers have used various strategies to tackle PGE optimisation and each will be discussed in this Review. Some studies have focused on altering which DSB repair pathway is favoured, either through chemical modulation (Aksoy et al., 2019; Bischoff et al., 2020; Zhang et al., 2018) or through overexpression or silencing of key genes in the HDR/SSTR or NHEJ pathways (Kurihara et al., 2020; Li et al., 2018). The search for alternative Cas endonucleases (Makarova et al., 2011) has expanded the genome-editing toolbox to include Cas12a (Cpf1) and variants of Cas9, such as Staphylococcus aureus Cas9 (SaCas9) (Kleinstiver et al., 2015a; Ran et al., 2015) and Neisseria meningitidis Cas9 (NmCas9) (Hou et al., 2013), which have differing target preferences (Chen et al., 2018; Swarts and Jinek, 2018; Zetsche et al., 2015; Nakade et al., 2017) and thus allow the targeting of new loci. Alteration (Walton et al., 2020) of the Cas9 PAM preference (Doudna and Charpentier, 2014; Mojica et al., 2009) has likewise increased the spectrum of potential genetic targets, while identification of high-fidelity Cas9 variants has increased specificity (Walton et al., 2020; Kleinstiver et al., 2016, 2015b). The ability of Cas to act as a genetic homing mechanism has also been exploited independently of its endonuclease activity. Cas9 variants that lack the ability to introduce DSBs are termed dead Cas9 (dCas9) if they lack any endonuclease activity or Cas9 nickase (nCas9) if they only cut one DNA strand (Cong et al., 2013). dCas9 and nCas9 have been used to reduce observed off-target effects (Ran et al., 2013; Mali et al., 2013) and as a chassis onto which to fuse other enzymes, such as deaminases (Gaudelli et al., 2017; Kim et al., 2017b; Komor et al., 2016, 2017) and reverse transcriptases (Anzalone et al., 2019; Liang et al., 2022; Lin et al., 2020; Petri et al., 2021), which can induce PGE via non-HR methods, such as BE and PE. Cas9 fusions have also been used to increase PGE efficiency by assisting with the colocalisation of the dDNA or of key PGE effector proteins to the DSB site (Charpentier et al., 2018; Savic et al., 2018) (Table 1). Different dDNA conformations have also been investigated. Researchers have compared PGE efficiencies of circular plasmid DNA, double-stranded DNA (dsDNA), single-stranded oligodeoxynucleotides (ssODNs) and long single-stranded oligodeoxynucleotides (lssODNs) (Bai et al., 2020; Miura et al., 2018; Ranawakage et al., 2021; Song and Stieger, 2017), dDNA length, strand complementarity and symmetry. These parameters have all been reported to affect HR efficiency (Okamoto et al., 2019; Richardson et al., 2016) (Table 1). In addition, researchers have developed a number of bioinformatics tools to assist with the design of dDNA and gRNAs for optimal HDR efficiencies (O'Brien et al., 2019; Prykhozhij et al., 2021). Processes involved in DNA repair are a necessary bedrock on which to build an understanding of PGE optimisation. In-depth descriptions of DSB repair pathways have been provided elsewhere (Shrivastav et al., 2008; Ceccaldi et al., 2016; Hustedt and Durocher, 2017) and will not be covered in detail here. Briefly, numerous proteins are involved in the repair of DSBs (outlined in Fig. 1). Six core components of NHEJ have been identified: Ku70/80, DNA-PKcs (also known as PRKDC), Artemis, LIGIV and XRCC4. Ku70 and Ku80 form a heterodimer that binds to DNA ends and recruits DNA-PKcs. DNA-PKcs is a kinase that phosphorylates Artemis, an endonuclease that trims the DSB ends and prepares them for ligation by LIGIV. Finally, XRCC4 acts as a scaffolding protein (Andres et al., 2012) and forms a complex with LIGIV (Drouet et al., 2005) to assist with its nuclear import (Berg et al., 2011). The suppression of LIGIV activity in zebrafish (Zhang et al., 2018) and silencing of Ku70/80 in pig foetal fibroblasts (Li et al., 2018) or XRCC4 in plants (Populus trichocarpa) (Movahedi et al., 2022) all increase PGE events, indicating that downregulation of NHEJ components is a promising avenue for increasing CRISPR-mediated PGE efficiency (Fig. 2). An alternative approach to increasing PGE is to upregulate components of faithful repair mechanisms. As described in Fig. 1, DNA end resection is the first step towards HDR or SSTR. As such, the end resection-initiating MRN complex, formed of MRE11, Rad50 and NSB1 and activated by CtIP (also known as RBBP8), is a potential target for upregulation (Figs 1 and 2). Indeed, overexpression of CtIP and MRE11 (Movahedi et al., 2022) and fusion of a CtIP domain to Cas9 (Charpentier et al., 2018) increase PGE events. Additionally, the nucleases EXO1 and DNA2 catalyse the more extensive DNA end resection that faithful repair mechanisms require, and overexpression of an EXO1 mimic increases SSTR in mammalian cell culture (Seigel, 2018) (Fig. 2). Once extensive DNA end resection has occurred, the resulting exposed single-stranded DNA (ssDNA) is bound by RPA (Wobbe et al., 1987; Wold, 1997), and the repair pathways available to the cell then include HDR, SSTR and single-strand annealing (SSA) (Fig. 1). The recombinases Rad51 and Rad52 appear to be key mediators of DSB resolution at this stage, but the type of template available for repair is also critical. Rad51 facilitates HDR using a dsDNA template, whereas overexpression of Rad52 has been shown to increase PGE via SSTR with ssODN templates (Gallagher and Haber, 2021; Gallagher et al., 2020). Overexpression of Rad51 increases PGE events with double-stranded plasmid dDNA in utero in mice (Kurihara et al., 2020), in rabbit embryos (Song et al., 2016) and in human embryonic and induced pluripotent stem cells (Takayama et al., 2017) (Fig. 2). In addition, small molecules selected for their ability to stimulate Rad51 drive similar increases in PGE in rabbit (Song et al., 2016) and zebrafish (Zhang et al., 2018) embryos. However, when using ssODN donors, which require SSTR, overexpression of Rad51 appears to be detrimental to the rate of PGE (Paulsen et al., 2017). Instead, overexpression of Rad52 increases PGE events when using single-stranded dDNA (Paulsen et al., 2017) (Fig. 2). BRCA1 and BRCA2 also play key roles in facilitating DSB repair via HDR and SSTR (Roy et al., 2012). BRCA1 likely facilitates DNA end resection by recruiting CtIP to the DSB (Yun and Hiom, 2009; Chen et al., 2008). In a separate function, BRCA1 promotes BRCA2 localisation to resected ssDNA via the intermediary protein PALB2 (Xia et al., 2006; Zhang et al., 2009). Subsequently, BRCA2 loads Rad51 onto the RPA-coated ssDNA, enabling nucleofilament formation (Thorslund et al., 2010; Liu et al., 2010). Overexpression of BRCA1 variants that display a hyper-recombination phenotype increases PGE when using plasmid donors in vitro compared to wild-type BRCA1 overexpression (Pinder et al., 2015). The examples above demonstrate a clear potential to increase the efficiency of PGE events via the manipulation of individual components of the DNA repair pathways. This approach presents a promising avenue of inquiry towards the ultimate development of super-high-efficiency Cas-mediated PGE in both in vitro and in vivo systems (Table 1). The rational step of combining simultaneous downregulation of proteins that promote error-prone repair with upregulation of proteins that mediate faithful repair has also been explored. For example, combining overexpression of Rad52 and a dominant-negative form of 53BP1 (also known as TP53BP1), a protein that supresses DNA end resection to favour NHEJ (Chapman et al., 2013), significantly increases ssODN donor-mediated PGE events in induced pluripotent stem cells (Paulsen et al., 2017). In a similar approach, the small molecules RS-1 and SCR7, which are proposed to upregulate Rad51 and downregulate LIGIV activity, respectively, significantly increase the frequency of PGE events in zebrafish embryos (Zhang et al., 2018). As exemplified in the study summarised above (Zhang et al., 2018), small molecules are an attractive option for the modulation of DNA repair pathways and optimisation of PGE. One benefit is that they can interact directly with proteins that already exist within the target cell, unlike small interfering RNAs (siRNAs) or morpholinos that target mRNA transcripts. This direct function facilitates more rapid effects. From a practical standpoint, it may also be easier to dissolve pre-synthesised chemicals in cell culture or embryo medium for delivery into the cells or tissue, rather than producing and delivering RNA for overexpression or knockdown of endogenous transcripts. For these reasons, researchers have investigated a range of chemicals that affect DNA repair proteins. Although promising, chemical interventions using small molecules to alter the activity of DSB repair proteins have had somewhat variable success (Table 1). For example, RS-1 and SCR7 were effective in some cases yet had small or negative effects on PGE efficiency in others (Zhang et al., 2018; Riesenberg and Maricic, 2018). The specific interplays between chemicals and the dDNA type are a potential explanation for this variability, especially when considering the Rad51-dependent nature of HDR compared to Rad52-mediated SSTR. The proposed effect of RS-1 is to stabilise the binding of Rad51 to the resected target strand (Jayathilaka et al., 2008). Studies manipulating key proteins in combination with different dDNA types can go some way to explaining the variable effects of small molecules on PGE rates. However, a more complete understanding of the precise roles of these proteins in faithful repair mechanisms is still required. For example, Lamas-Toranzo and colleagues suggested that RS-1 can stimulate other Rad51-like proteins, and this could explain how combining HDR/Rad51-promoting RS-1 with an SSTR-related ssODN donor can still increase the rate of PGE (Lamas-Toranzo et al., 2020). Outcomes of small-molecule treatments could potentially also be affected by the chosen model system or Cas variant. For example, Cas12 produces staggered DNA ends, whereas Cas9 can generate blunt and staggered ends (Riesenberg and Maricic, 2018; Shou et al., 2018). This may alter how DSB repair proteins and the chemicals that modulate them take effect. However, the reasons why small molecules may not reproduce the same results in all model organisms, cell types or with different dDNA remain unclear. Typically, studies in which panels of compounds have been assessed for their effects on PGE identified at least one chemical that increased PGE efficiency, but different studies often identified different beneficial chemicals (Aksoy et al., 2019; Zhang et al., 2018; Riesenberg and Maricic, 2018). These discrepancies could be caused by the aforementioned differences in dDNA and cell type or by other minor protocol differences, which add additional variables and make direct comparisons difficult. Despite the lack of consensus, these studies do suggest that small molecules can effectively increase PGE, even if the optimal choice must be carefully selected based on the model system and dDNA. The range of chemicals, and their effects on PGE, are broad. We have summarised these in Table 1 and they have been covered in other recent reviews (Bischoff et al., 2020; Yeh et al., 2019). One of the reasons why PGE may be less efficient than NHEJ-mediated indels is the limited cell cycle window in which faithful DNA repair can occur. Therefore, researchers have sought to synchronise the cell cycle phase for timed delivery of Cas proteins and donors to increase PGE rates (Fig. 2B). The microtubule polymerisation inhibitors nocodazole and ABT-751 have been used to arrest human embryonic cell lines, induced pluripotent stem cells, neural progenitor cells and HEK293T cells in the S/G2 phases of the cell cycle, resulting in a significant increase in both HDR and NHEJ events (Yang et al., 2016; Lin et al., 2014). As an alternative approach, researchers have generated a Cas9-Geminin fusion. The presence of Geminin targets this fusion for ubiquitin-mediated degradation in the M and G1 phases of the cell cycle. Expressing this fusion in HEK293T cells limits Cas9, and therefore DSB formation, to the HDR/SSTR-active cell cycle stages, leading to increases in PGE rates (Gutschner et al., 2016). These techniques, however, may be difficult to translate into in vivo model generation, where fertilised embryos may be harvested at different time points. In practice, many embryos need to be microinjected in sequence. Holding embryo development at the one-cell stage or in the cell cycle phases that permit HDR/SSTR, therefore, is desirable. This is especially important in organisms with rapid post-fertilisation cell cycles, such as zebrafish (Kimmel et al., 1995). A simple protocol modification to incubate zebrafish embryos on ice before microinjection of the gene-editing components showed a non-significant increase in PGE in ice-cooled compared to room temperature embryos. However, when the addition of the small molecules NU7441 and RS-1 was combined with ice incubation, this resulted in a significant 1.5- to 2-fold increase in PGE over the use of the small molecules alone (Aksoy et al., 2019). This suggests that, in zebrafish embryos at least, a straightforward protocol adaptation to slow the cell cycle, when combined with alteration of DNA repair mechanisms via small molecules, can produce significant improvements to PGE efficiency. gRNAs enable the ‘homing mechanism’ of Cas endonucleases and are thus a core part of the CRISPR system that have also been targeted for optimisation. However, some gRNAs direct Cas to the target site more efficiently than others, inducing DSBs more frequently. The reasons for this variable efficiency are incompletely understood, but sequence preferences that allow the complex to locate the target loci are thought to be crucial (Moreb and Lynch, 2021). In addition, poor gRNA specificity can lead to off-target effects (Wong et al., 2015; Manghwar et al., 2020; Schaefer et al., 2017; Varshney et al., 2015; Akcakaya et al., 2018). Furthermore, the requirement of a precise PAM site means that the positioning options of a gRNA and therefore the Cas-induced break are finite (Sternberg et al., 2014). To assist optimal gRNA design, researchers have designed a multitude of computational tools based on large datasets of on-target and off-target efficiencies (Heigwer et al., 2014; Montague et al., 2014; Moreno-Mateos et al., 2015) that provide metrics by which users can judge candidate gRNA sequences. The on-target score predicts the rate at which a given gRNA should induce cutting at the target locus, and the off-target score provides the predicted Cas endonuclease activity at unintended loci. These design tools have been comprehensively described and compared elsewhere (Chuai et al., 2017). It is clear, however, that the in silico-designed gRNAs still require in vivo and in vitro validation, and the efficacy of design tools across different cell types has been questioned (Chuai et al., 2017). In zebrafish, it has been found that two gRNA design tools underestimated the indel generation rate of gRNAs by ∼20% (Uribe-Salazar et al., 2022). In our own experience in zebrafish using Cas9 RNPs, even gRNAs with predicted low on-target scores (<40) can achieve cutting of >80% (as judged by indel rates in the absence of dDNA). Many tools, however, are based on algorithms trained on gRNA screens in mouse and human cells (Doench et al., 2014), and so may be more accurate in mammalian systems. The development of species-specific gRNA design tools, especially with in-built functionality for PGE, could be a valuable contribution to the field. Although off-target edits do not directly affect PGE efficiency, they have the potential to reduce the validity of the modified cell or organism through unwanted indels in other genes (Schaefer et al., 2017). When attempting to achieve PGE, the distance from the DSB to the intended mutation site is also important. Cas9 induces a cut 3 bp upstream of the PAM recognition site (Chen et al., 2014), and mutation site distances of >15 bp from this cut result in suboptimal PGE efficiency, with an increase in distance having a more pronounced negative impact (O'Brien et al., 2019; Schubert et al., 2021; Wang et al., 2016). However, these studies also showed that the cutting efficiency of the gRNA still has a greater magnitude of effect on PGE efficiency than distance between cut and mutation site. Experimentally, gRNAs with higher cutting efficiencies can outperform gRNAs with lesser cutting efficiencies that cut closer to the edit site (Schubert et al., 2021). When choosing gRNAs, it is advisable to aim for those with a PAM site as close as possible to the site of the desired edit, with a high on-target score and low off-target score to avoid unwanted mutations. As PGE mediated by HDR and SSTR requires a donor template, several studies have compared different dDNA designs and their effects on PGE efficiency, again often reaching different conclusions (Zhang et al., 2018; Bai et al., 2020). One group investigated whether ssODNs with either symmetrical or asymmetrical arms of homology (with relation to the length of the sequence either side of the cut site) could improve PGE efficiency. Indeed, they achieved HDR rates of up to 60% in HEK293 cells by using asymmetric ssODNs with complementarity to the non-target DNA strand (which is not bound by the gRNA) (Richardson et al., 2016). The use of ssODNs with non-target DNA strand specificity has also been validated by other researchers (Janssen et al., 2019). Multiple groups have investigated the length of dDNA homology arms, often reaching different conclusions (Table 1). According to these studies, the optimal length of ssODN homology arms varies between 30 bp and 60 bp (Okamoto et al., 2019; Wang et al., 2016; Schubert et al., 2021). However, the inability to generate ssODNs longer than 200 bp has previously been a limiting factor, both to the length of homology arms and for the length of the exogenous insert, e.g. limiting the ability to insert fluorophore tags at a specific site. Subsequent research has allowed the development of lssODNs that are up to ∼2.0 kb in length (Miura et al., 2018), enabling the design of 300 bp homology arms and the insertion of up to 200 bp of exogenous sequence (Bai et al., 2020; Ranawakage et al., 2021). An alternative approach to lssODNs is to deliver donor templates as plasmids, which are linearised in the cell by Cas9 to produce dsDNA donors in situ (Wierson et al., 2020; Zhang et al., 2017a). This approach has achieved high PGE efficiencies in Drosophila melanogaster (Kanca et al., 2019) and up to 77% PGE in zebrafish (Hisano et al., 2015). However, there is disagreement over the optimal length of homology arms in the linearised dDNA, with one study suggesting very short, 24-48 bp homology arms for PGE in zebrafish and in porcine and human cell lines (Wierson et al., 2020), and other studies suggesting relatively long homology arms of 600 bp as being the most efficient (Zhang et al., 2017a). The introduction of silent mutations within dDNA sequences should also be considered. Several studies have identified that a silent ‘blocking’ mutation within the PAM site of the linearised dDNA, which should prevent re-cutting of the edited locus by residual Cas, increases PGE rates (Okamoto et al., 2019; Paquet et al., 2016; Schubert et al., 2021). To aid subsequent screening, silent mutations that add or remove restriction enzyme sites (Paulsen et al., 2017; Schubert et al., 2021) can identify edited loci without the need to resort to sequencing. Aside from specific dDNA design, dDNA availability is also a key aspect of optimising PGE. Because dDNA is physically required at the site of the DSB to act as an HDR template, increasing dDNA concentration is a logical approach to maximise its availability. However, high concentrations of ssODNs (Kagita et al., 2021; Nakanishi et al., 2015) and dsDNA can be cytotoxic (Luecke et al., 2017; Nguyen et al., 2020). An alternative approach is to fuse dDNA directly to the Cas endonuclease (Savic et al., 2018) or the gRNA (Lee et al., 2017), thereby optimising the spatial and temporal colocalisation of the template to the DSB site and increasing PGE rates, which has been effective in cell culture. As we discussed above, manipulation of key proteins within the DSB repair pathways, either via chemical modulation, overexpression or knockdown, can have robust and reproducible success in increasing PGE rates. In theory, there is no limit to the number of DNA repair proteins that could be simultaneously targeted for upregulation or downregulation. Indeed, combinations of up to seven chemicals to alter DSB repair protein function in cell culture have been investigated (Riesenberg and Maricic, 2018). The resulting degree of change in PGE rates depended on cell type, and whether Cas9, nCas9 or Cas12a was used, with the DNA-PKcs inhibitor NU7026 providing the bulk of PGE improvement when using standard Cas9. However, in other cases, the use of only two agents, one downregulating NHEJ and one upregulating HDR/SSTR, have successfully increased PGE rates in cell culture (Paulsen et al., 2017) and in zebrafish (Zhang et al., 2018). It remains to be seen whether the increases in PGE rates that can be achieved by directly altering DSB repair protein function have an upper limit. Overexpression of key faithful repair components or knockdown of NHEJ proteins aim to increase the abundance of proteins interacting with a DSB leading to PGE. It is also important to consider the rates of NHEJ alongside those of PGE. In vivo, where genome editing affects a whole organism, the resulting animals often carry both NHEJ and PGE events (Zhang et al., 2018; Cui et al., 2018). As such, it can be useful to compare rates of PGE relative to indel formation as each animal will likely carry both types of genetic edit. The absolute degree of somatic PGE is also relevant for its germline transmission (Aksoy et al., 2019), which is important when the goal is to generate a stable line (see Box 1). The use of nCas9 variants and other methods that avoid DSBs (Anzalone et al., 2019; Gaudelli et al., 2017) sidestep the possibility of indel formation via NHEJ, thereby effectively increasing PGE rates. The physical properties of the genomic landscape targeted for PGE are also worth considering. In HEK293 cells, targeting physically restrained heterochromatin rather than open euchromatin improved the PGE-to-NHEJ ratio (Janssen et al., 2019). In this study, HDR rates using dsDNA donors varied little between heterochromatin and euchromatin, whereas using ssODNs increased absolute PGE rates at euchromatin over heterochromatin. However, in both experiments, the authors observed higher rates of NHEJ when euchromatin was targeted, offsetting any gains in PGE. The use of multiple histone deacetylase inhibitors, which promote an open chromatin state, has also resulted in PGE and NHEJ increases in induced pluripotent stem cells (Zhang et al., 2021). The researchers noted, however, that some of this improvement was due to increased Cas9 and gRNA expression from their plasmid. However, at least in zebrafish, Cas9 reportedly lacks a preference for binding to heterochromatin or euchromatin (Moreno-Mateos et al., 2015). Gene locus- and cell-type-dependent variation in PGE efficiency has been noted in many studies (Bosch et al., 2020; Miyaoka et al., 2016; Remy et al., 2017; Petri et al., 2021), which may be due to chromatin structure or gRNA design limitations for a specific locus, although the factors controlling this variation are incompletely understood and warrant further investigation. The best approach for optimising CRISPR-based PGE varies by model system and by the kind of edits that are desired. A consensus on optimal approaches has yet to be reached in the field, but the recent advancements described here provide some general advice. For small insertions and substitutions, the use of ssODNs complementary to the non-target strand, with chemical or protein modulation, may yield good PGE rates, whereas PGE of larger inserts may require the use of plasmid or lssODN donors, each with their own complement of chemical or protein modulation. When choosing targets for PGE, it may also be worth considering targeting multiple genes of interest, as some may be more amenable to editing. Employing Cas nucleases to form DSBs followed by endogenous DNA repair is only one approach to achieve PGE. Newer techniques that rely on fusing Cas to effector enzymes, chiefly reverse transcriptase and cytidine deaminase (Fig. 3), effectively achieve PGE in cell culture and in vivo in zebrafish and mice (Anzalone et al., 2019; Böck et al., 2022; Gaudelli et al., 2017; Kim et al., 2017a; Koblan et al., 2018; Komor et al., 2016; Liu et al., 2020; Petri et al., 2021; Rosello et al., 2022; Sasaguri et al., 2018; Walton et al., 2020; Xu et al., 2020; Zhang et al., 2017b) (summarised in Table 2). Typically, these approaches utilise nCas9 variants that cause single-stranded DNA nicks, avoiding the bulk of deleterious NHEJ events that can result from DSB repair (Fig. 3). BE was the first to step away from manipulating endogenous DSB repair pathways. The original iteration of this system used dCas9 fused to the deaminase APOBEC1 (Harris et al., 2002; Petersen-Mahrt et al., 2002), which can ultimately convert any cytidine residues within a five-nucleotide PAM-upstream activity window to thymine (Komor et al., 2016). The more recently developed adenosine base editors are constructed with nCas9 fused to an evolved transfer RNA adenosine deaminase, which expands the BE toolbox for A>G conversion (Gaudelli et al., 2017). Researchers have continued to improve this system, increasing the base conversion edit efficiency, narrowing the deaminase activity window to increase targeting specificity, and adding PAM-less Cas9 nucleases to increase the targeting scope of the system (Gaudelli et al., 2017; Koblan et al., 2018; Komor et al., 2016; Walton et al., 2020) (Table 2). These improvements, culminating in the development of BE4, achieve a maximum editing rate of almost 70% base conversion in human cell culture (Komor et al., 2017), but these rates vary depending on the application and organism (Table 2). They range from low efficiencies of 1.3% in wheat (Zong et al., 2017) and 9-28% in zebrafish (Zhang et al., 2017b) to high efficiencies of 96% in yeast (Nishida et al., 2016), with varied levels of efficiency reported for mammalian in vitro (∼30-70%) and in vivo (44-57%) systems (Komor et al., 2017; Kim et al., 2017a). Recent attempts to apply BE to zebrafish have yielded better results, with some experiments generating up to 50% of larvae showing high rates of BE homozygosity, and up to 100% bearing some degree of BE (Rosello et al., 2022; Liang et al., 2022). Importantly, concurrent indel formation, which can be an issue in DSB pathway-based PGE methods (Zhang et al., 2018; Cui et al., 2018), is typically very low in most applications of BE and ranges between 2% and 10% (Anzalone et al., 2019; Zhang et al., 2017b), giving the technique an advantage. The purpose of using BE is often to replicate diseases caused by single-base changes in model organisms, as has been done so successfully in zebrafish (Rosello et al., 2021), mice (Sasaguri et al., 2018) and Drosophila (Marr and Potter, 2021). However, the somewhat indiscriminate activity window of the deaminase is a key drawback, as it introduces a downstream screening issue, which reduces the potentially higher efficiency of the technology due to fewer indels. If a desired edit is a single-base conversion within an area that contains multiple target residues, then it is likely that BE will generate unwanted mutations. Another limitation of BE is its inability to introduce larger targeted insertions or multiple different base pair changes simultaneously. BE does have advantages over methods that rely on DSBs, but it is not yet a silver bullet for the targeted generation of single-base changes, although continued improvements may ameliorate these issues. PE (Anzalone et al., 2019) is a still more recent advancement and again uses a nCas9 protein as a targeting chassis for an enzyme. However, in place of a deaminase, nCas9 is fused with a reverse transcriptase, such as the Moloney murine leukaemia virus (M-MLV) reverse transcriptase and bound to an extended gRNA that acts as a reverse transcription template, referred to as prime editing gRNA (pegRNA). PE has wider applicability than BE, as it can insert up to 44 bp of exogenous sequence and delete up to 80 bp (Lin et al., 2020; Anzalone et al., 2019), and it can generate any combination of base substitutions within those boundaries (Liu et al., 2020; Xu et al., 2020). Initial efforts to construct, optimise and apply PE in HEK293T cells resulted in the generation of three prime editor versions, PE1-3 (Table 2). PE3 achieved an average point mutation efficiency of 36±8.7%, with an average concurrent indel formation of 8.6±2.0% (Anzalone et al., 2019), and is more efficient than previous PE versions at generating larger precise deletions of varied sizes, from 5 bp to 80 bp, displaying editing efficiencies of 52-78% with average indel formation rates of 11±4.8% (Anzalone et al., 2019). PE has been successfully applied to in vivo models, although, as is often the case with PGE, in vivo efficiency is generally much lower than that in cell culture. In zebrafish, PE3 did not always generate more efficient PGE than its predecessor PE2, although altering microinjection and embryo incubation temperature improved overall PE efficiency (Petri et al., 2021). The authors achieved average somatic PGE rates of up to 3.33% and 6.53% for two separate loci. From 14 edited F0 fish, only one passed PGEs onto the F1 generation at a rate of 8.3% (Petri et al., 2021). A separate study of PE in mice also identified discrepancies between the in vivo efficiencies of PE2 and PE3 compared to their efficiencies in mammalian cell culture (Aida et al., 2020 preprint). Here, PGE occurred in 44-75% of blastocysts, but the frequency of those PGEs accounted for only 1.1-18.5% of total embryo genomic DNA. The degree of editing within an embryo is an important factor, and one which complicates the process of generating PGEs in vivo. Higher rates of mosaicism (differences in the genetic sequence harboured by different cells within an organism) cause complications when trying to establish future generations that are genetically homogenous carriers of the desired edit. In addition, low rates of PGE within a single organism mean that few of the organism's offspring will likely contain the desired edit. Both outcomes cause more downstream work for researchers. An ideal technique will achieve a high number of individual embryos that bear any degree of editing, and each of those embryos should have a high percentage of their cells that bear the PGE. In another study, adeno-associated virus-mediated PE of newborn mice achieved G>C conversion with an efficiency of 14.4±6.6% in primary hepatocytes isolated at 4 weeks post injection, and the authors did not detect any indels (Böck et al., 2022). A preprint by Aida et al. indicates that PE in mouse embryos resulted in 10.5-13% PGE compared to a rate of 24-36.95% PGE when using Cas9 with ssODN donors. However, they also observed a much higher rate of PE-mediated indel formation than initially reported for mammalian cell culture (Aida et al., 2020 preprint). In Drosophila, PE2 has also been successfully implemented to generate efficient germline transmission of specific edits, with 36% transmission of PGEs to progeny (Bosch et al., 2021). PE is clearly a promising step forward in PGE; but, as is often the case with new technologies, there are hurdles that need to be overcome before it can become a routine and robust tool for use in varied model organisms. The generally low indel formation and versatility of precise deletion, insertion and substitution in one platform are advantages that certainly make the continued development of PE worthwhile. In summary, BE is effective, especially when off-target mutations in the activity window are acceptable or if the targeted base is the only C or A residue in the activity window. PE can also be used to target larger indels. It is currently unclear whether previously tested chemical or protein modulation can further increase BE or PE efficiencies. Using CRISPR systems to generate gene knockouts via NHEJ remains easier than PGE. However, the refinement and improvement of methods to leverage endogenous HDR and SSTR, and the development of new techniques such as BE and PE, are paving the way for routine PGE. These advances can be effectively applied to disease modelling but still require careful selection and design of the PGE components, optimisation for a specific locus or model system, and the screening of large numbers of animals or cells to isolate those that carry the desired edits. Comprehensive comparisons of technical modifications and their effect on PGE efficiency across loci and model systems would aid a methodological consensus benefitting multiple fields of research. With continued improvement of PGE methods, however, the future of engineering precise human disease models looks bright. Increased reliability and reduction of labour time facilitates the high-throughput or more specialised use of PGE. For example, the introduction of patient-specific mutations into animal models to generate patient ‘avatars’ would allow for pre-testing of drugs and treatments. This strategy is already being used in zebrafish and Drosophila for cancer patients (Bangi et al., 2021; Fazio et al., 2020). Additionally, genome-wide association studies are identifying thousands of disease-related single-nucleotide polymorphisms (Visscher et al., 2012; Yengo et al., 2022) and novel genetic pathways from gene networks (Mäkinen et al., 2014), which ultimately require validation in vivo. Large-scale PGE screens could be carried out to investigate these, potentially in combination, to model complex traits and assess the phenotypic impact of multiple genetic variants. Precise mutations and tagging of endogenous genes also allow for the study of how misfunctioning proteins interact. Generating disease models to study the subtle effects of genes bearing deleterious mutations is only one application of Cas-based PGE, however. There is also huge potential for PGE to treat human disease. Recently, the CRISPR system has been used to knock out genes repressing foetal haemoglobin production to treat sickle cell anaemia in somatic cells, and additional clinical trials are underway (Kan and Doudna, 2022). Additionally, multiple clinical trials of CRISPR-edited T cells for cancer immunotherapy are underway (Lu et al., 2020; Stadtmauer et al., 2020; Kan and Doudna, 2022). Although the transition from disease modelling to treatment raises further efficacy and ethical implications, with efficient delivery, off-target screening and safety protocols all requiring careful implementation, this future application of PGE represents an exciting new use for this technology.

PMC10003101

Ana Belén Azuaga,Julio Ramírez,Juan D. Cañete

Psoriatic Arthritis: Pathogenesis and Targeted Therapies

03-03-2023

psoriatic arthritis,pathogenesis,tissue heterogeneity,immune cells,synovial fibroblasts,cytokines,multiomics,single-cell RNA sequencing,biological therapy,JAK inhibitors

Psoriatic arthritis (PsA), a heterogeneous chronic inflammatory immune-mediated disease characterized by musculoskeletal inflammation (arthritis, enthesitis, spondylitis, and dactylitis), generally occurs in patients with psoriasis. PsA is also associated with uveitis and inflammatory bowel disease (Crohn’s disease and ulcerative colitis). To capture these manifestations as well as the associated comorbidities, and to recognize their underlining common pathogenesis, the name of psoriatic disease was coined. The pathogenesis of PsA is complex and multifaceted, with an interplay of genetic predisposition, triggering environmental factors, and activation of the innate and adaptive immune system, although autoinflammation has also been implicated. Research has identified several immune-inflammatory pathways defined by cytokines (IL-23/IL-17, TNF), leading to the development of efficacious therapeutic targets. However, heterogeneous responses to these drugs occur in different patients and in the different tissues involved, resulting in a challenge to the global management of the disease. Therefore, more translational research is necessary in order to identify new targets and improve current disease outcomes. Hopefully, this may become a reality through the integration of different omics technologies that allow better understanding of the relevant cellular and molecular players of the different tissues and manifestations of the disease. In this narrative review, we aim to provide an updated overview of the pathophysiology, including the latest findings from multiomics studies, and to describe current targeted therapies.

Psoriatic Arthritis: Pathogenesis and Targeted Therapies Psoriatic arthritis (PsA), a heterogeneous chronic inflammatory immune-mediated disease characterized by musculoskeletal inflammation (arthritis, enthesitis, spondylitis, and dactylitis), generally occurs in patients with psoriasis. PsA is also associated with uveitis and inflammatory bowel disease (Crohn’s disease and ulcerative colitis). To capture these manifestations as well as the associated comorbidities, and to recognize their underlining common pathogenesis, the name of psoriatic disease was coined. The pathogenesis of PsA is complex and multifaceted, with an interplay of genetic predisposition, triggering environmental factors, and activation of the innate and adaptive immune system, although autoinflammation has also been implicated. Research has identified several immune-inflammatory pathways defined by cytokines (IL-23/IL-17, TNF), leading to the development of efficacious therapeutic targets. However, heterogeneous responses to these drugs occur in different patients and in the different tissues involved, resulting in a challenge to the global management of the disease. Therefore, more translational research is necessary in order to identify new targets and improve current disease outcomes. Hopefully, this may become a reality through the integration of different omics technologies that allow better understanding of the relevant cellular and molecular players of the different tissues and manifestations of the disease. In this narrative review, we aim to provide an updated overview of the pathophysiology, including the latest findings from multiomics studies, and to describe current targeted therapies. Psoriasis (PsO) is a chronic inflammatory immune-mediated skin disease characterized by erythematous and scaly plaque, but which also frequently affects the scalp and nails [1]. Roughly up to 30% of patients with PsO may develop psoriatic arthritis (PsA), especially those with severe psoriasis or nail or scalp involvement [2,3]. PsA is a chronic inflammatory disease with a heterogeneous presentation involving multiple tissues and clinical domains (arthritis, spondylitis, enthesitis, and dactylitis) [4]. Persistent inflammation may lead to joint destruction and disability that might be prevented with early diagnosis and treatment [5]. Patients with PsO or PsA have more risk of develop extra-musculoskeletal inflammation and comorbidities, such as inflammatory bowel disease, uveitis and depression, cardiovascular disease, and metabolic syndrome [6,7]. Genetic studies have found risk factors associated with the transition to PsA in patients with PsO [8]. PsO and PsA share multiple genetic risk variants related to innate, adaptive immune, and autoinflammatory pathways [9]. PsA-specific genetic variants have been reported [10] and a different pattern of cytokine gene expression has been identified between skin and synovial tissue, explaining differences in the response to biologic therapies between those clinical domains [11]. The multiomics strategy is a clear step forward to precision medicine [12]. These techniques could help to increase understanding of cellular and molecular pathways to identify biomarkers for early diagnosis, prognosis, and response to treatment, as well as to discover new therapeutic targets in patients with PsA. Through the stratification of patients according to their different molecular taxonomy in the tissues involved, these technologies could help to understand the heterogeneity of the disease and lead to personalized medicine by giving the appropriate treatment to the appropriate patient. Globally, this would culminate in improving the management of the disease by reducing or preventing its disability burden and adverse effects and diminishing the economic burden [13]. The prevalence in the general population of PsA ranges from 0.1% to 1% [14,15]. It may vary between continents, being higher in Europe than in Asia [16,17,18]. The incidence of PsA has been estimated in a meta-analysis of 83 for every 100,000 PY (95% CI, 41–167 every 100,000 person-years) [19]. Among patients with PsO, the prevalence of PsA varies according to the series. A meta-analysis estimated a prevalence of PsA in patients with PsO around 20% [3]. There are also discrepancies regarding the prevalence between men and women [20,21]. However, there are differences in the clinical manifestations depending on the sex. Studies have shown that peripheral PsA is more common in female patients, whereas axial disease is more common in male patients [22,23]. Females have less radiographic progression than male patients, but worse outcomes in pain, function, and fatigue [22,24], which contributes to poor response to treatment compared to male patients [25,26,27,28]. There is a hormonal influence in the development of the disease. Estrogens have a proinflammatory effect as they increase cytokines such as TNF, IL-6, and IL-1. In contrast, testosterone and progesterone have an anti-inflammatory effect by increasing IL-4, IL-5, and IL-10 [29]. Furthermore, the effect of testosterone levels did correlate inversely with PsA disease activity in males, but estradiol did not correlate with disease activity [30]. The presentation of PsA is usually in middle-aged people. However, up to 25% of patients may have a late onset [31]. Patients with late presentation tend to be male with a longer duration of PsO, obesity, and the presence of HLA-C*06 [32]. In addition, different studies have agreed that the appearance above 60–65 years is associated with more aggressive disease, a higher swollen joints count, higher acute phase reactants, and fatigue [33,34]. As expected, late onset is also associated with more comorbidity [34]. In addition, there are differences in terms of sex and age of presentation, male patients with early onset of PsA have greater axial involvement compared to women, while women have more family history of PsA [35]. The pathogenesis of PsA is still far from clear, due to the heterogeneity of the tissues and pathogenic pathways involved, the disparate clinical manifestations, variable progression, and different responses to treatment. A predisposing genetic background in the presence of environmental factors, such as infections, microbiota (dysbiosis), obesity, biomechanical stress on the entheses (“deep” Koebner phenomenon) or smoking could activate the innate immune system and precipitate the onset of the disease [36]. The integration of genetic predisposition, environmental triggers, and proinflammatory cytokines is represented in Figure 1. Psoriatic arthritis and PsO have a strong hereditary component. The prevalence of first-degree relatives (FDR) is around 7.7% in PsA and 17.7% in PsO [37,38]. A study using a mixed model method to assess the contribution of single nucleotide polymorphisms (SNP) from genomic wide association studies (GWAS) concluded that both PsO and PsA have a significant hereditary burden, although this is higher in PsO than in PsA [39]. The genetic region of the major histocompatibility complex (MHC) in the short arm of chromosome 6 contains several alleles or haplotypes of human leukocyte antigen (HLA) class I that are associated with an increased risk for PsO and PsA and are also associated with several clinical phenotypes of the disease. The HLA-C*06:02 association with PsO is stronger than with PsA and this allele is also associated with an early onset of PsO and a longer time between the onset of skin and joint involvement [8]. HLA-B*27, HLA-B*39, HLA-B*38, and HLA-B*08 are associated with the risk of PsA, but HLA-B*27 and HLA-B*39 are also associated with a shorter time between PsO and PsA onset. Other genotype-phenotype associations are: HLA B*08.01 with asymmetric sacroiliitis, peripheral arthritis, ankylosis and increased joint damage, whereas HLAB*27 is associated with symmetric sacroiliitis, dactylitis, and enthesitis [40]. Fine mapping of the MHC region showed that the risk heterogeneity between PsA and PsO might be driven by HLA-B amino acid at position 45, specifically glutamic acid (Glu), which is present in classical HL-B alleles associated with PsA [41]. In addition to the MHC complex, several SNPs in the il23r (IL-23 receptor), TNFAIP3 (TNF-regulated protein A20), and PTPN22 (tyrosine-protein phosphatase non-receptor type 22) genes, as well as an SNP within the 5q31 susceptibility locus, have a stronger association with PsA than with PsO [42]. TNFAIP3 and TNIP1 (TNFAIP3-interacting protein 1) encode proteins that interfere in the NF-κB pathway, resulting in negative regulation of inflammatory signaling. Therefore, variants associated with PsA could have loss of function leading to increased response to inflammatory stimulus. Variants in IL-12B (IL-23/IL-17 pathway), RUNX1 (CD8-lymphocyte activation and differentiation), and IL-13 genes have been also associated with PsA [42,43]. Deletions, insertions, and duplication events that cause copy number variants (CNVs) have been found in GWAS. A deletion in the ADAMTS9 and MAGI1 genes was associated with PsA, but not with PsO. ADAMTS9 gene belongs to the family of aggrecanases, enzymes related to the cartilage extracellular matrix. The MAGI1 gene is implicated in stabilizing adhesions and cell-to-cell contacts and probably also interferes with Tregs [10]. Epigenetic modifications have a potential role in the disease onset, activity, response to treatment and progression in immune-mediated inflammatory diseases, as has been shown in peripheral blood monocytes in rheumatoid arthritis (RA) [44,45] and in early chronic arthritis [46]. In fact, DNA methylation may be more stable than gene expression, which is sensitive to the immediate inflammatory milieu [47]. One study showed that the differentially methylated sites in peripheral blood can distinguish PsA from PsO, suggesting that DNA methylation is a potential predictive biomarker for PsA [48]. In another study, peripheral blood CD8+ T cells from 10 PsO and 7 PsA patients concluded that patients with skin psoriasis exhibit DNA methylation patterns in CD8+ T cells that allow differentiation from PsA patients, and reflect the clinical activity of skin disease [49]. There are relatively few studies on epigenetics in PsA, generally with small size samples and it is difficult to achieve relevant clinical results. Further prospective studies are needed in order to provide insights on the role of epigenetics in search of biomarkers of the transition from PsO to PsA, the prognosis and response to therapy. Dysbiosis is the imbalance in the composition, distribution, or metabolic activities of the commensal species composing the normal microflora of the human body barriers [50]. The interaction between the microbiome and the immune system is responsible for many immunoregulatory mechanisms, and dysbiosis leads to alterations in barrier permeability and the consequent activation of the immune system and secretion of pro-inflammatory cytokines destabilize the junctions between epithelial cells and increase gut or skin permeability, enabling the penetration of microbes [51,52]. In healthy conditions, type 3 innate lymphocytes (ILC3) are implicated in gut homeostasis, as IL-23-independent IL-17A is protective in the gut by promoting epithelial cell junctions, whereas IL-23-dependent IL-17 is pathogenic [53]. In patients with spondyloarthritis (SpA), including PsA, it is suggested that ILC3 elevates the levels of IL-17A and IL-22, perpetuating inflammation, and disrupting the intestinal barrier [54]. Additionally, dysbiosis in patients with SpA can increase zonulin, increasing the permeability of the intestinal epithelium and imprinting Th9 cells to migrate to the joint [55]. Recently, a study demonstrated microbiome alterations in the skin of predominantly systemic drug-naïve PsO and PsA patients, who exhibit lower diversity compared with healthy controls, even in the absence of clinical lesions. The bacterial association network in psoriatic non-lesional (NL) skin are more similar to psoriatic lesions (L) than to healthy skin, suggesting an underlying dysbiotic process in the cutaneous surface of patients with psoriatic disease, even in the absence of clinically evident lesions. Notably, the common cutaneous commensal Corynebacterium was enriched in NL PsA compared with NL PsO, which might serve as a biomarker of disease progression [56]. These findings show that although the PsO and PsA skin microbiomes share common traits, they also exhibit differences in key taxa that might potentially be used as diagnostic biomarkers, particularly in patients with PsO at risk for disease progression to PsA [56]. Mechanical loading is an important factor in musculoskeletal health and disease. Tendons and ligaments require physiological levels of mechanical loading to develop and maintain the tissue architecture. Pathological levels of force represent a biological (mechanical) stress that elicits an immune system-mediated tissue repair pathway in tendons and ligaments. The role of mechanical stress in ‘overuse’ injuries, such as tendinopathy, has long been known, but mechanical stress is now also emerging as a possible trigger for some forms of chronic inflammatory arthritis, including psoriatic arthritis [57]. The same authors showed that mechano-stimulation of mesenchymal cells induces CXCL1 and CCL2 for the recruitment of classical monocytes, which can differentiate into bone-resorbing osteoclasts. Therefore, biomechanical loading acts as a decisive factor in the transition from systemic autoimmunity to joint inflammation. Genetic ablation of CCL2 or pharmacologic targeting of its receptor, CCR2, abates the mechanically induced exacerbation of arthritis [58]. Thus, mechanical strain controls the site-specific localization of inflammation and tissue damage in arthritis [58]. The enthesis is the anatomical site where the tendons, ligaments, and joint capsule attach to the bone and it is subjected to biomechanical overload, being susceptible to mechanical stress (microtrauma) that induces the release of cytokines and growth factors, leading to secondary synovitis. Enthesitis characterizes the spondyloarthritis group, including PsA, compared with RA [59]. Interestingly, myeloid cells have been identified as the main source of local IL-23 at the enthesis [60]. Supporting the clinical relevance of these findings, PsO patients with previous bone trauma had an increased risk of PsA compared with PsO patients without trauma [61]. In PsA patients, a study found that the odds of obesity were higher than for patients with RA, PsO, and general population [62]. Furthermore, a higher body mass index (BMI) has been associated with an increased risk of PsO and PsA [62,63]. Adipose tissue is an extremely active endocrine organ that secretes proinflammatory cytokines and cytokine-like hormones called adipokines, with either pro- or anti-inflammatory effects. Leptin is an adipokine that Is considered a link between the neuroendocrine and immune systems, with multiple effects relevant to the pathogenesis of PsA [64]. PsA and obesity share certain pathogenic mechanisms, including angiogenesis and the role of proinflammatory macrophages. On the other hand, biomechanical stress due to obesity overload could induce an aberrant response to tissue microdamage in entheseal sites, predisposing to local inflammation [64]. Taken together, these data suggest that obesity has the potential to activate many of the known immune-inflammatory pathways underlying the pathogenesis of PsA. Therefore, the link between obesity and PsA provides a potential opportunity to reduce the occurrence of PsA and improve its management by encouraging a reduction in weight, a modifiable risk factor [65]. Smoking has been positively associated with the risk of PsA in the general population [66], although some studies have highlighted a possible paradoxical effect of smoking in patients with psoriasis [67]. In fact, a study based on a large multinational registry of patients with a diagnosis of SpA, concluded that smoking was associated with a lower prevalence of peripheral arthritis in PsA patients [68]. Infections function as a trigger for the immune system to develop an immune-mediated disease. Infection by Streptococcus has been closely linked to the development of guttate PsO [69]. Even in patients with PsA, Streptococcus has been found both in synovial fluid and in peripheral blood [70]. In addition, a pharyngeal infection can increase the risk of developing PsA, as strong specific association was recently found between positive pharyngeal culture, regardless the pathogen, with an increased risk of PsA [71]. The immune-inflammatory response is triggered in patients with a genetic predisposition after interacting with certain environmental factors (dysbiosis, biomechanical stress, obesity). Locally, these factors activate the Toll-like receptors (TLRs) type 2 present in the antigen-presenting cells (APC), particularly monocytes, dendritic cells (DC), and macrophages, stimulating the release of IL-1, IL-6, TNFα, IL-17, and IL-23 through exogenous pathogen-associated molecular patterns (PAMPs) and/or endogenous damage-associated molecular patterns (DAMPs) [72,73]. Furthermore, other cells locally found in tissues may contribute to the pathophysiology, such as innate lymphoid cells (ILC), natural killer (NK) cells and mucosal associated invariant T cells. Circulating ILC type 3 (ILC3), which exhibits a Th17 profile of cytokines, are significantly increased, while ILC type 2 (ILC2) are decreased in active PsA. The ILC2/ILC3 ratio correlated negatively with disease activity in PsA (DAPSA). In addition, the presence of enthesitis, synovitis, erosions, and bone proliferation assessed by MRI and high-resolution peripheral CT (HR-pQCT) correlated with ILC3 counts in patients with PsA, suggesting the clinically relevant local effects produced by these cells [74]. In lymph nodes and local tissues, APC activates T lymphocytes (mainly CD8 via MHC HLA-class I), leading to the release of cytokines perpetuating the innate and adaptive type effector responses [75,76]. Naïve T lymphocytes differentiate into Th17 cells in the presence of TGFß and IL-6, inducing the expression of RORγt and leading to the production of IL-17, IL-22, IL-21, and CCL20, which favor the proliferation of Th17 [73]. Likewise, TGFß and IL-6 induce the expression of IL-23R, promoting the response to IL-23 [77], which is pathogenic [78]. IL-17, particularly IL-17A, promotes the activation of synovial fibroblasts, chondrocytes, and osteoclasts, inducing an increase in the proliferation of synovial tissue, and bone reabsorption. The thickening of the synovial tissue (ST) plus the presence of active growth factors promotes hypoxia, which induces angiogenesis (neovascularization) [78,79,80]. Even though IL-17 is key to the pathophysiology of PsA, other cytokines are needed to orchestrate the signaling pathways. IL-23 is key to the differentiation of Th17 and Th22 cells [81]. Moreover, IL-23 stimulates αβ T cells, γδ T cells, and ILC3 to produce IL-17, IL-22, TNFα, and IFN-γ, promoting typical cytokine inflammatory loops leading to persistent inflammation. On the other hand, IL-23-dependent IL-22 can induce phosphorylation of STAT3 in osteoblasts at enthesis sites, leading to bone formation [82]. In addition, IL-22 downregulates keratinocyte differentiation, inducing hyperkeratosis [83]. Finally, TNFα, IL-17, and IL-23 induce the activation of the NF-κB pathway, promoting the synthesis of more pro-inflammatory cytokines [81]. The presence of IL-12 and IFNα stimulate the Th1 response, which releases TNFα and IFN-γ and IL-2. Regulation of the inflammatory cascade requires the response mediated by Treg cells through IL-2 and TGF-ß [84]. Finally, the activation of the inflammatory cascade is reflected pathologically as dermal hyperplasia, synovitis, enthesitis, erosions, and cartilage degradation (Figure 1). Understanding the differences between RA and PsA synovitis is a long-sought goal, as it may be crucial in explaining the different clinical phenotypes of the two diseases and their differential response to targeted therapies. Single-cell RNA sequencing (scRNA-seq) and other omics technologies are being used to reach a deeper understanding of the cellular and molecular pathways driving the disease. We comment on classic studies in synovitis and devote a space to summarize studies using omics methodologies. As analyzed by immunohistochemistry, synovial inflammation in PsA is characterized by synovial membrane hypertrophy containing synovial fibroblasts (SFs) and CD68+ macrophage infiltration. Increased synovial lining hyperplasia in RA, compared with PsA, has not been definitively confirmed [85,86]. By using the Hsp47 antibody, a marker of lining and sublining SFs, we found a significant increase in sublining SFs in RA compared with PsA [87,88]. A study on the effects of the Janus kinase inhibitor (JAKi) tofacitinib (TOF) on SF function suggested that PsA SFs are activated similarly to RA SFs [89]. The sublining in PsA is similar to RA, but with a greater relative abundance of neutrophils and mast cells [90,91]. Synovial tissue macrophages are key producers of cytokines relevant to the physiopathology of chronic arthritis and their changes correlate with disease activity, radiographic progression, and response to therapy. However, a study confirmed differential p53 expression in the ST of patients with RA and PsA, as well as an association of p53 expression and CD68+ macrophages with joint damage in RA, but not in PsA [92]. Despite the pathogenic differences between RA and PsA, we found similar patterns of expression of proteins induced by GM-CSF and M-CSF in CD163+ macrophages from both diseases. Although PsA ST had significantly more CD163+ macrophages expressing the anti-inflammatory CD209 marker, the subtype predominant in ST from healthy controls, which could suggest that CD163+ CD209+ are anti-inflammatory tissue-resident macrophages, no differences were found in the expression of proinflammatory markers (activin A, TNF, MMP-12) between CD163+ macrophages CD209+ and CD209low/− [93]. Dendritic cells have a key role in the initiation and progression of chronic arthritis. Recently it was identified a new DC population that derive from monocytes, characterized as CD209/CD14+ DC, which is enriched in the inflamed joint of RA and PsA, where they are further activated and exhibit a migratory phenotype, with expression of costimulatory molecules and chemokine receptors. The authors reported in this new DC subset differences in genes involved in endocytosis/antigen presentation with RA and PsA patients, which could contribute to joint inflammation. TOF specifically targets the development and functional capacity of these DCs [94]. The role of B cell in PsA synovitis remains unclear despite of the abundance of B cells and the presence of ST lymphoid neogenesis, similar to germinal center structures, has a similar frequency to RA [95]. Interestedly, serum levels of IgG autoantibodies against LL-37 and ADAMTS-L5 were correlated with the Psoriasis Area and Severity Index (PASI), and reflected disease progression in longitudinally collected serum samples from patients with psoriasis. Importantly, both anti-ADAMTS-L5 and anti-LL-37 autoantibody levels were also significantly elevated in PsO patients with PsA compared to those without PsA [96,97]. The identification of autoantibodies in PsA patients points to an autoimmune component in psoriatic disease; however, additional evidence is needed to determine the clinical utility of these autoantibodies and their contribution to disease pathogenesis [98]. B cells express surface type II MHC and co-stimulatory molecules that provide them antigen-presenting-cell features, and these phenotypic changes, although also demonstrated in psoriatic synovium, involve a larger molecule repertoire in rheumatoid synovium. This support a differential antigen-presenting B-cell phenotypes in ST of RA and PsA patients [99]. Moreover, B cells can produce multiple proinflammatory cytokines and chemokines, and regulatory B cells producing IL-10 (B10 cells) are a critical anti-inflammatory B-cell subset, which are decreased in PsA [100]. Undifferentiated arthritis (UA) patients who evolved to PsA had significantly more mast cells and lining fibroblasts compared with UA patients who evolved to RA [88]. In addition, studies have shown that PsA synovitis is characterized by macroscopic hypervascularization, resulting in higher vessel density compared with RA, showing the two diseases have different expressions of pro-angiogenic factors, with PsA exhibiting elevated levels of Ang-2 and RA having increased levels of Ang-1 [101,102]. Treatment with TNF inhibitors (TNFi) therapy in PsA synovitis reduces the expression of VEGF and its receptors VGFR1 and VGFR2, but not Ang-2 expression, leading to regression of neovessels, probably by inducing endothelial cell apoptosis [80]. One study reported functional and transcriptional differences between subsets of fibroblasts from RA synovial tissues using subpopulation-specific mass transcriptomics and single-cell transcriptomics. A subset of fibroblasts, characterized by the expression of podoplanin, THY1 membrane glycoprotein, and cadherin-11 proteins, but lacking CD34, located in the perivascular zone of the sublining, was tripled in RA patients compared with OA patients. These fibroblasts are proliferative, secrete proinflammatory cytokines, and exhibit an in vitro phenotype characteristic of invasive cells [103]. Another study used scRNA-seq to profile ST cells from the inflamed joints of five patients with PsA and four patients with RA. Synovial fibroblast subpopulations differed between the PsA and RA samples, with an abundance of fibroblast activating protein (FAP)+THY1+ fibroblast clusters in RA tissue and THY1-fibroblast clusters in PsA. By studying cell–cell interactions, the authors found that the synergy between T-cell-derived TGFβ and macrophage-derived IL-1b drives the metabolic dysregulation of invasive pro-inflammatory synovial fibroblasts, which are expanded in RA compared with PsA. These changes show that, although there are similarities between RA and PsA, they are different diseases with different cell subtypes and functions at the local level [104]. Besides inflammation, SFs also play an important role in the transition from joint inflammation to irreversible joint damage. A recent pre-print study shows that, after treatment with IL-17A/TNF-blocking antibodies, SFs change their phenotype from a destructive IL-6+/MMP3+THY1+ to a CD200+DKK3+ subtype, actively inducing the resolution of inflammation in PsA. This phenotypic switch can be visualized due to hitherto unexplored capacities of fibroblast subtypes with regard to receptor internalization of small molecular tracers with a high affinity to FAP. Although FAP expression levels are comparable between fibroblast subtypes in the joint, the FAP internalization rate correlates with the destructive potential of fibroblasts, and resolving fibroblasts have a lower FAP internalization rate, providing a valuable imaging tool to visualize the transition from joint damage to resolution of inflammation [105]. CD8+ T cells play a key role in the pathogenesis of PsA, as expected from the association of PsA with HLA-I alleles. However, the clonality of CD8+ T cells in PsA has been confirmed only recently. Using mass cytometry, a study detected a three-fold expansion of memory CD8+ T cells in the synovial fluid (SF) compared with the peripheral blood of patients with PsA. These cells exhibited clonal expansion when evaluated by scRNA-seq. Furthermore, it was shown that these cells are active and pro-inflammatory CD8+ T cells expressing the CXCR3 receptor with its ligands (CXCL9 and CXCL10) are elevated in the SF [106]. In addition, in support of the role of adaptive immunity in the pathogenesis of PsA, another study found higher levels of IL-17+CD4- (mainly CD8+) T cells as well as of IL-17+ CD4+ T cells in SF compared with peripheral blood. However, only IL-17+CD8+ T cells correlated with disease activity and joint damage progression in patients with PsA [76]. A study in PsA ST reported that infiltrating CD4+ T cells expressed higher levels of IL-17A, IFN-γ, GM-CSF, and CD161, with parallel enrichment of Th1, Th17, and exTh17 T-helper subsets. These polyfunctional T cells, but not the single cytokine-producing T cell subsets, correlated with disease activity (DAPSA), suggesting that polyfunctional T cells are significantly contributing to disease. The findings of this study could inform treatment decisions and the prognosis of PsA patients [107]. Advances in the pathogenesis of PsA have identified several inflammatory pathways driven by cytokines that have been successfully targeted with specific inhibitors. Treatment of PsA is based on non-pharmacological and pharmacological measures. Both European League Against Rheumatism (EULAR) and Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendation guidelines recommend the use of conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) as first-line treatment, followed by apremilast, biological therapy, or the use of targeted synthetic DMARDs (tsDMARDs) such as Janus kinase inhibitors (JAKi) [5,108]. First, TNF inhibitors were borrowed from RA but, most recently, the discovery of the key role that the IL-23/IL-17 axis plays in PsA resulted in the development of new targeted therapies for psoriatic disease. Finally, the inhibition of JAK can inhibit/reduce the signaling effects of multiple cytokines and growth factor on targeted cells. Figure 2 describes the main immune-inflammatory pathways and their targeted therapies, which we review below. Apremilast is an oral small molecule that inhibits phosphodiesterase 4 (PDE4). PD4 inhibition promotes an increase in intracellular cyclic AMP [109], which prevents the synthesis of proinflammatory cytokines, such as TNF [110], and elevates anti-inflammatory cytokines (IL-10) [111]. Apremilast has been shown to be effective in resolving plaque psoriasis as well as other endpoints, such as nail involvement in the ESTEEM trials [112,113]. The PALACE trials have demonstrated efficacy in PsA. Randomized controlled trials (RTC) have been developed in both naive patients and with prior exposure to both biologic therapy and csDMARDs [114,115,116,117]. All RTCs had ACR20 response at week 16 as their primary endpoint. Patients treated with both doses of apremilast (20 mg or 30 mg twice daily) achieved primary and other secondary endpoints significantly more than PBO. The most common adverse effects (AE) were diarrhea, nausea, headache, and upper respiratory tract infection. Recommendation guides suggest its use for patients with skin involvement, nail involvement, peripheral PsA, enthesitis, and dactylitis. TNFα is a master proinflammatory cytokine produced by T1 cells which promotes the activation of myeloid cells (macrophages and DC) and their production of other proinflammatory cytokines, including TNF, thus inducing systemic and local (skin and joint) inflammation. The efficacy of 5 TNFi with indications in PsA (certolizumab pegol [CZP], infliximab [IFX], adalimumab [ADA], etanercept [ETN] and golimumab [GOL]), has been shown compared with PBO [118,119]. TNFi is the first line biological therapy recommended by the most treatment guidelines for patients with PsA, proving to be effective in all PsA domains and to inhibit or decrease radiographic progression [5,120]. A meta-analysis showed no differences in the ACR20 response between ADA, ETN, and IFX [121]. ETN consists of a human recombinant protein (TNFR2) linked to a Fc region of IgG, whereas IFX, ADA, and GOL are monoclonal antibodies, and CZP is the only TNFα antagonist utilizing the Fab’ fragment of a humanized TNFα antibody which lacks the Fc region attached to two molecules of polyethylene glycol. ETN is less immunogenic than the other TNFi and does not require concomitant administration with methotrexate to maintain its long-term effectiveness [122,123]. However, ETN is less effective compared to monoclonal antibody TNFi (IFX, ADA, GOL, CZP) in the treatment of extra-musculoskeletal inflammatory manifestations associated with PsA, such as uveitis or IBD [124,125]. These differences may be related to the different mechanisms of action between only blocking soluble TNF (ETN) or, in addition, binding to transmembrane TNFα antagonist (ADA, IFX, GOL, CZP) [126]. Due to the safety protocols and guidelines implemented after the introduction of TNFi in the clinic, the current management of these drugs is safe in the short and long term [127,128]. Nevertheless, like other targeted therapies, TNFi may increase the risk of infections, reactivation of latent tuberculosis (TB), and increased incidence of neoplasms. For this reason, latent TB screening is recommended, as well as discouraged its used in patients with a recent history of cancer and maintaining an up-to-date vaccination schedule. On the other hand, as a rare AE, cases of the demyelinating disease have been described [129], therefore is not recommended in people with a personal or family history of this neurological disease [130]. The IL-17/IL-23 axis is key in the development and perpetuation of PsA. The use of molecules that block these cytokines shows benefits in controlling disease activity and preventing its progression. Ustekinumab is a monoclonal antibody that blocks the shared p40 subunit of IL-12 and IL-23, inhibiting differentiation of Th1 and Th17 cells. Its efficacy was demonstrated for skin, peripheral arthritis, enthesitis, and dactylitis, both in RTC and in real-world data [131,132,133]. More recently, guselkumab (GSK), a monoclonal antibody that binds to the p19 subunit and specifically neutralizes IL-23, was approved after two phase 3 RCT (DISCOVER trials). In naïve patients as well as those with previous exposure to TNFi [134,135,136], the ACR 20 response at week 24 was significantly higher for patients treated with both doses of GSK than placebo. However, although each 4 week dose demonstrated significant reduction of radiographic progression compared with PBO, there were no significant differences between GSK every 8 weeks and PBO [135]. Risankizumab (RZK), a monoclonal IL-23 antibody, has been approved for the treatment of PsA. The KEEPsAKE trials in patients naïve to and with previous biological therapy showed that significantly more patients treated with RZK achieved an ACR 20 response at week 24 than PBO [137,138]. No significant differences were found in radiographic progression. Tildrakizumab (TLK) is another monoclonal IL-23 antibody. Phase 3 RCTs (INSPIRE-1 and INSPIRE-2) are currently in development [139,140], but positive results are already available from the phase 2 trial in PsA [141]. All the specific anti-IL-23 drugs have demonstrated a good safety profile, similar to previous data with ustekinumab [136], although a longer follow-up is necessary to confirm it. All drugs neutralizing IL-23 (GSK, RZK, and UST) have failed to show effectiveness in axial spondyloarthritis (axSpA) in RCTs [142,143]. This lack of response was unexpected, since RCTs of IL-17i have positive outcomes in the same disease [144,145]. Data from animal models of axSpA suggest that IL-23 could be required for the initiation but not the maintenance of axSpA, whereas IL-17 has a role throughout and in an IL-23-independent manner in established disease. On the other hand, a variety of innate cells, including MAIT, ILC3, iNKT, and γδ T cells, can produce IL-17 in an IL-23-independent manner [146,147], implicating them in disease pathogenesis. These observations could explain the differential response seen with IL-23 and IL-17A inhibitors (IL-23i, IL-17i) in clinical trials in axSpA [142,143,144]. The effectiveness of IL-23i in axial PsA (axPsA) has been explored in a post-hoc analysis of the DISCOVER trials, where patients with axial involvement assessed by the clinician and the presence of sacroiliitis on magnetic resonance imaging (MRI) were evaluated, suggesting that this target might be effective in axPsA [148]. Currently, an RCT with GSK in PsA patients with axial activity as its primary outcome is being developed [149] to test the hypothesis that inflammatory mechanisms are more IL-23-driven in axial PsA than in axSpA, potentially because of different proportions of IL-23R-expressing cells in the tissues. Secukinumab (SEC), a fully human monoclonal antibody that selectively targets IL-17A, was approved in patients with PsA. SEC has shown superior efficacy to PBO in multiple disease domains including peripheral arthritis, spondylitis, dactylitis, enthesitis, and skin and nail disease [150,151,152,153,154]. In addition, SEC showed less radiographic progression compared to PBO. However, in ahead-to-head clinical trial, SEC was not superior to TNFi (ADA) in the musculoskeletal domain outcomes of patients with PsA (ACR 50 as primary endpoint), but was superior in the skin outcome [155]. The incidence of Candida infections in PsA is estimated to be 1.5 per 100 patient-years (PY), while the incidence of inflammatory bowel disease is 0.03–0.1 per 100 PY in PsA [156]. Ixekizumab (IXE) is also a monoclonal antibody that selectively targets IL-17A. Like SEC, IXE has been shown to be superior to PBO in ACR responses, inhibition of radiographic progression, and other clinical domains, in both TNFi refractory populations and naïve patients [157,158]. In the head-to-head clinical trial, IXE was superior to ADA in achieving the compose primary endpoint of ACR50 and a 100% improvement in the PASI 100 response at week 24, but without significant differences in the clinical musculoskeletal domains at the end of the study [159]. Bimekizumab (BMK) is a monoclonal antibody that inhibits region of IL-17 A and IL-17 F, resulting in a blockade of both homodimer and heterodimer combinations: IL-17AA, IL-17FF, and IL-17AF. Evidence from experimental and preclinical studies show that the production of IL-17A and IL-17F may be through the IL-23 classical pathway or in an IL-23-independent manner by innate and innate-like lymphocytes [79]. Furthermore, differences at the sources and signaling pathways of IL-17A and IL-17F in different stages of inflammation and through different tissues indicate that IL-17A and IL-17F contribute independently to chronic tissue inflammation, having non-redundant roles in axPsA or axSpA [160]. Therefore, dual inhibition of IL-17A and IL-17F might provide better outcomes than IL-17A blockade alone. BMK phase 3 RCT in PsA (BE COMPLETE) included patients previously exposed to TNFi, who were randomized to receive BMK 160 mg or PBO. The primary objective was the ACR 50 response at week 16, which was achieved by 43% of patients treated with BMK compared with 7% with PBO. The PASI 90 was reached at week 16 in more patients treated with BMK vs. PBO (69% vs. 7%; p < 0.0001) [161]. The BE OPTIMAL RCT included a third arm with an active comparator (ADA). At week 16, BMK and ADA-treated patients had a higher ACR50 response and there was evidence of less radiographic progression at week 16 in patients treated with BMK vs. PBO [162]. Pooled data from both trials showed significantly greater resolution of enthesitis and dactylitis in patients treated with BMK vs. PBO. The AEs were similar to those presented by other IL-17i, with Candida infection in 4% and serious AEs occurred in 4% of patients treated with BMK at week 24. Brodalumab (BRD) is a human anti-interleukin-17 receptor A (IL-17RA) monoclonal antibody which blocks its binding to IL-17 (A, F, and E). It is currently approved only for PsO [163]. Interleukin-17 inhibitors are indicated for all domains of PsA involvement, except when there is associated IBD. Despite their good safety profile, IL-17i is not recommended in patients with IBD since they do not demonstrate efficacy in RCT [164,165] and the possible worsening of the disease [166]. The janus family of intracellular kinases consists of four members: tyrosine-protein kinase 2 (TYK2), JAK1, JAK2, and JAK3. These molecules interact with various members of the signal transducers and activators of transcription (STAT) family to modulate gene transcription downstream of a variety of cell surface cytokine and growth factor receptors [167]. Tofacitinib (TOF) is a small molecule that specifically inhibits JAK1 and JAK3. Phase 3 RTC demonstrated the efficacy of TOF in relation to PBO in PsA patients naïve and also in patients who had failed with TNFi [168,169]. Regarding safety, the ORAL Surveillance study found that patients with RA treated with TOF had an increased risk of cardiovascular events compared with those treated with TNFi [170]. As a result, both the European Medicines Agency (EMA) and the U.S Food and Drug Administration (FDA) have issued a statement cautioning against the use of all JAKi as the first option in patients over 65 years of age, smokers, and those with cardiovascular risk factors, a history of thromboembolic events, or a history of malignancy. Upadacitinib (UPA) is a small molecule that inhibits JAK1. In 2021 the dose of 15 mg/day was approved for PsA. The Phase 3 trial, SELECT-PsA 1 demonstrated efficacy in the ACR20 response and safety compared with placebo. In addition, UPA 15 mg was not inferior to ADA while UPA 30 mg showed superiority over ADA, but also more severe adverse events [171]. Other secondary endpoints such as less radiographic progression, MDA, dactylitis resolution, and enthesitis were significantly higher in both UPA arms compared with PBO. Similarly, patients that were refractory or intolerant to TNFi (SELECT-PsA 2) achieved a significantly higher ACR20 response and MDA (36% and 45.44% with 15 and 30 mg/day, respectively) [172]. The most frequent AE was respiratory tract infection. The incidence of herpes zoster (HZ) was higher in both RCT compared with PBO. Filgotinib (FIL) is another selective JAK1 inhibitor under development for the treatment of PsA. In the EQUATOR study, a phase 2 RCT, the ACR20 response at week 16 was achieved by 80% of patients treated with FIL and 33% of those treated with PBO. Only one patient treated with FIL had a herpes zoster infection [173]. Phase 3 RTC are currently under development in naïve patients and those previously exposed to biological therapy (PENGUIN 1 and 2) [174,175]. Deucravacitinib (DEU) is a small molecule that is a non-competitive, allosteric inhibitor of tyrosine kinase 2 (TYK2). The phase 2 trial included patients with prior exposure to TNFi and showed the efficacy of both doses (6 mg and 12 mg/day) of DEU compared with placebo in arthritis, resolution of enthesitis, and dactylitis. Most AEs were mild. No thromboembolic events or HZ were found [176]. Currently, a phase 3 RCT is ongoing to assess the efficacy and safety of DEU in patients who have not previously received treatment with biological DMARDs and those who have previously received TNFi treatment [177,178]. Brepocitinib (BRE) is an oral molecule with dual, TYK2 and JAK1, inhibitor action under investigation for the treatment of PsA. Results from a phase 2 RCT were presented at the ACR convergence 2021. Patients with previous use of DMARDs and those with prior use of one TNFi were included in the trial. A significantly higher proportion of patients treated with BRE 30 mg (66.7%) and 60 mg (74.6%) achieved the primary endpoint (ACR20) vs. PBO (43.4%, p < 0.05) at week 16. At week 16, dactylitis and enthesitis resolution were superior to placebo. HZ was found in 1.7% and no thromboembolic event was reported [179]. As mentioned above, a higher incidence of HZ has been found in patients treated with JAKi. In addition, despite being specific, when increasing the dose they can inhibit other JAK, thus increasing the possible AEs [171]. The pathophysiology of PsA is characterized by the complexity of an activated immune system with multiple cellular pathways involved, which are dynamic in the different stages or presentations of the disease and, importantly, in the distinct tissues involved. The application of single-cell techniques is making it possible to identify different cell subtypes, mainly synovial fibroblasts and T cells, with either potential pathogenic or protective roles in PsA. Hopefully, this may help to improve the development of prognostic biomarkers and future targeted therapies with new mechanisms of action. However, the clinical application of multiomics data poses major challenges, including the joint requirement for expertise and advanced facilities in statistics, biology, and computer sciences, as well as the interpretation and therapeutic actionability of molecular findings [12]. Furthermore, the heterogenous clinical features and tissues pathogenesis of PsA could pose a major challenge to disentangle the molecular taxonomy of the disease. Although there is still much to learn about the local changes in RA and PsA synovial tissue, the progress achieved in RA by the new designs of clinical trials driven by molecular pathology in RA is impressive [180,181], and could be a model for PsA, taking into account the heterogeneity of tissues and clinical domains involved in PsA. Although the identification of biomarkers using different omics technologies (Figure 3) is still in the discovery phase, with much work to do to turn the anticipated results of these analyses into assays which are applicable in routine clinical settings [182], the EU IMI2 project HIPPOCRATES represents an exciting opportunity to address key research questions at scale and validate biomarkers for clinical implementation in PsA [183]. This will ultimately improve the quality of life for those living with PsA or at risk of developing it [131]. Because PsA is a complex, systemic, and heterogeneous disease in which multiple tissues and clinical domains are involved, there is a need to base disease diagnosis, classification, and management on the immunophenotypic basis of clinical domains at the tissue level, rather than clinical manifestations alone [184]. Interestingly, the experts revising unmet needs in PsA agree that “investigation of domains where tissue biopsy is not straightforward to obtain (e.g., entheses or spine), then ‘molecular imaging’ (e.g., advanced PET) with granular probes for specific cell types could help contextualize disease endotypes” [185]. In fact, we already have a successful example of the application of FAPI-PET imaging in the cellular and molecular understanding of bone damage in PsA [68]. Another area identified for improvement is the diagnosis and definition of “early PsA” or “pre-PsA” to facilitate treatment trials designed with the goal of preventing or early eradication of disease, which is ongoing with the PAMPA trial [186]. In addition, following the example of RA, new designs of molecular pathology-driven clinical trials in PsA could improve the outcome of current targeted therapies and bring us closer to the objective of personalized medicine [24].

PMC10003104

Yasir Sharif,Gandeka Mamadou,Qiang Yang,Tiecheng Cai,Yuhui Zhuang,Kun Chen,Ye Deng,Shahid Ali Khan,Niaz Ali,Chong Zhang,Ali Raza,Hua Chen,Rajeev K. Varshney,Weijian Zhuang

Genome-Wide Investigation of Apyrase (APY) Genes in Peanut (Arachis hypogaea L.) and Functional Characterization of a Pod-Abundant Expression Promoter AhAPY2-1p

27-02-2023

cis-elements,environmental stress,functional annotation,GUS activity,miRNAs,pericarp specific,phylogenetic analysis

Peanut (Arachis hypogaea L.) is an important food and feed crop worldwide and is affected by various biotic and abiotic stresses. The cellular ATP levels decrease significantly during stress as ATP molecules move to extracellular spaces, resulting in increased ROS production and cell apoptosis. Apyrases (APYs) are the nucleoside phosphatase (NPTs) superfamily members and play an important role in regulating cellular ATP levels under stress. We identified 17 APY homologs in A. hypogaea (AhAPYs), and their phylogenetic relationships, conserved motifs, putative miRNAs targeting different AhAPYs, cis-regulatory elements, etc., were studied in detail. The transcriptome expression data were used to observe the expression patterns in different tissues and under stress conditions. We found that the AhAPY2-1 gene showed abundant expression in the pericarp. As the pericarp is a key defense organ against environmental stress and promoters are the key elements regulating gene expression, we functionally characterized the AhAPY2-1 promoter for its possible use in future breeding programs. The functional characterization of AhAPY2-1P in transgenic Arabidopsis plants showed that it effectively regulated GUS gene expression in the pericarp. GUS expression was also detected in flowers of transgenic Arabidopsis plants. Overall, these results strongly suggest that APYs are an important future research subject for peanut and other crops, and AhPAY2-1P can be used to drive the resistance-related genes in a pericarp-specific manner to enhance the defensive abilities of the pericarp.

Genome-Wide Investigation of Apyrase (APY) Genes in Peanut (Arachis hypogaea L.) and Functional Characterization of a Pod-Abundant Expression Promoter AhAPY2-1p Peanut (Arachis hypogaea L.) is an important food and feed crop worldwide and is affected by various biotic and abiotic stresses. The cellular ATP levels decrease significantly during stress as ATP molecules move to extracellular spaces, resulting in increased ROS production and cell apoptosis. Apyrases (APYs) are the nucleoside phosphatase (NPTs) superfamily members and play an important role in regulating cellular ATP levels under stress. We identified 17 APY homologs in A. hypogaea (AhAPYs), and their phylogenetic relationships, conserved motifs, putative miRNAs targeting different AhAPYs, cis-regulatory elements, etc., were studied in detail. The transcriptome expression data were used to observe the expression patterns in different tissues and under stress conditions. We found that the AhAPY2-1 gene showed abundant expression in the pericarp. As the pericarp is a key defense organ against environmental stress and promoters are the key elements regulating gene expression, we functionally characterized the AhAPY2-1 promoter for its possible use in future breeding programs. The functional characterization of AhAPY2-1P in transgenic Arabidopsis plants showed that it effectively regulated GUS gene expression in the pericarp. GUS expression was also detected in flowers of transgenic Arabidopsis plants. Overall, these results strongly suggest that APYs are an important future research subject for peanut and other crops, and AhPAY2-1P can be used to drive the resistance-related genes in a pericarp-specific manner to enhance the defensive abilities of the pericarp. Peanut, or groundnut (Arachis hypogaea L.), is an important food legume of tropical and subtropical countries. It is the primary source of edible oil and proteins and the staple food of many African and Asian countries [1]. Peanut is cultivated in more than 100 countries across the world, while China, India, Nigeria, the United States, and Sudan are leading peanut-producing countries [2]. Botanically, peanut is a unique plant among legumes due to the pegging phenomenon [3]. It produces flowers above ground, and after pollination, the gynophore enters the soil and produce seeds underground [3,4]. As it bore seeds beneath the soil, seeds are always prone to attack by soil-borne fungal and bacterial pathogens. These pathogens mainly deteriorate peanut yield and quality [5]. The introduction of stress-resistant peanut cultivars could potentially solve the issue [6]. Investigating the stress-resistant mechanism and characterizing stress-responsive genes is key for any successful transgenic breeding program. In recent years, the genomes of many crop species have been worked out [7,8,9], and with the help of bioinformatics tools, genome-wide systematic studies of stress-related gene families are available. Similarly, the genome information of cultivated peanut [10,11] and its diploid progenitors [12] is available now. In peanut, the genome-wide studies for some gene/transcription factor families, including WRKY [13], bHLH [14], bZIP [15], GRF [16], ARF [17], APX [18], AP2/ERF [19], etc., have been performed, and their stress-responsive roles have been elucidated. Identifying more stress-responsive gene/protein families and incorporating them into resistance mechanisms could improve stress resistance in peanut. Extracellular ATP levels significantly increase in response to environmental stress, which initiates cell death and apoptosis [20]. The GDA1-CD39 nucleoside phosphatase/Apyrases family is ubiquitously found in animals, plants, bacteria, and fungi, and regulates cellular ATP levels [21,22,23,24]. APYRASEs (APYs) are a class of nucleoside triphosphate (NTP) diphosphohydolases (NTPDases) that maintain cellular NTP homeostasis by removing terminal phosphatases from NTPs and DTPs [21,25]. Based on subcellular localization, Apyrases are divided into two categories ecto- and endo-apyrases [26]. Endo-apyrases are usually localized in intracellular vesicles, endoplasmic reticulum (ER), and Golgi apparatus, while ecto-apyrases are present on the cell surface [27]. APYs, in contrast to ATPases, can use a variety of cofactors, including calcium Ca2+, magnesium Mg2+, manganese Mn2+, and zinc Zn2+, while ATPases use only Mg2+ as a cofactor [28]. The cellular ATP is not only the source of energy, but it also mediates different cellular mechanisms during stress, including potassium K+ homeostasis, vacuole Na+ distribution, Na+/H+ exchange, K+/Na+ exchange under salt stress [29], regulation of reactive oxygen species (ROS), and plasma membrane repairs [30]. Thus APYs/NTPs are essential in maintaining cellular ATP homeostasis for a plant’s normal functioning under stressed conditions. Human APYs are well-characterized, while among plants, APYs are well-described in Arabidopsis. Seven APYs have been identified in Arabidopsis, which are further divided into three classes based on their functions [25]. Arabidopsis APY1 and APY2 are located within the Golgi apparatus and play roles in root development, stomata opening/closure, and pollen development [31,32]. AtAPY1 and AtAPY2 are endo-APYs, but their mutations can increase extracellular ATP levels [33]. The biochemical and physiological functions of AtAPY3-AtAPY5 have not been worked out. Some initial studies for AtAPY6 and AtAPY7 are available; AtAPY6 and AtAPY7 are also involved in pollen development [34]. It is evident from recent studies that the APYs play a role in plant defense mechanisms. APYs are involved in plant defense against different pathogenic organisms, including fungal pathogens resistance [35], drought stress tolerance [36], salt stress tolerance [37], and waterlogging tolerance [38]. However, the molecular mechanisms responsible for the defense responses are still unclear. The advancements in modern biotechnological techniques have made bioinformatics work easy. Modern genotyping methods have revealed the genetic atlas of many important crop/plant species. A piece of comprehensive information on many quality traits, population structure, genetic diversity, etc., is available for peanut [39,40,41]. It is evident from previous studies that APYs play key roles against biotic and abiotic stress factors in plants. Functional studies of APYs in crop plants could provide new insights for stress breeding. Based on the studies mentioned above, we hypothesized that APYs in the peanut genome could be investigated for their potential involvement in stress-related or quality traits. So, we performed a comprehensive analysis to identify the APYs in the peanut genome. Fast and accurate sequencing methods have resulted in the availability of many transcriptome datasets for yield and stress-responsive traits [42]. Similarly, the QTL and fine-mapping techniques have generated a handsome amount of data for various quality- and stress-related traits [43,44,45]. The transcriptome profiles of cultivated peanut suggested that the AhAPY2-1 gene could be a potential candidate for pericarp-specific expression. The pericarp is the first organ that protects edible seeds from biotic and abiotic stresses. Several studies are available for pod/pericarp development, but there is a lack of work on the resistance-related behavior of the pericarp. We selected the pericarp-specific promoter for further study. Promoters are key regions to guide and regulate a gene’s expression. We cloned the promoter region of the AhAPY2-1 gene and functionally characterized it in transgenic Arabidopsis plants. This study first reported the Apyrases/Nucleotide phosphatases proteins in the genome of cultivated peanut and characterized a pericarp abundant expression promoter in peanut. We are convinced that this study will enhance the understanding of peanut apyrases and provide a base for further research. The APYs/NTPs genes in the genome of cultivated peanut were identified stepwise. Protein sequences of seven Arabidopsis apyrases were used as queries to search the apyrases in diploid peanut species. The BLAST results revealed the presence of eight APYs homologs in the genomes of A. duranensis and A. ipaensis each (Table S2), and 17 genes were found in the cultivated peanut genome (Table 1). The apyrases of A. duranensis, A. ipaensis, and A. hypogaea were named based on the phylogenetic relationships with Arabidopsis apyrases. The chromosomal distribution analysis of AhAPYs showed their uneven distribution in the genome. Chromosomes 2, 4, 7–9, 12, 14, 17–19 did not possess any apyrases. Chromosome 6 possessed four APYs, and chromosome 16 possessed three APYS. Chromosomes 1 and 5 possessed two APYs each, while all remaining chromosomes (3, 10, 11, 13, 15, and 20) possessed one APYs each (Figure 1). The chromosomal distribution of A. duranensis and A. ipaensis are presented in Figure S1. All AhAPYs possessed varying physicochemical properties. The subcellular localization prediction showed that most proteins are located in the plasma membrane, with few in the cytoplasm, chloroplast, mitochondria, extracellular spaces, nucleus, and vacuole. The theoretical isoelectric points of AhAPYs varied from 4.69 (AhAPY2-4) to 9.94 (AhAPY7-4), and molecular weight ranged from 14.96 KDa (AhAPY2-4) to 82.39 KDa (AhAPY7-1) (Table 1). The physicochemical properties, protein, CDS lengths, and the number of exons in AdAPYs and AiAPYs are given in Table S2. Structurally, all AhAPYs were diverse, and they possessed a different number of exons. Exon numbers varied from 2 to 12 exons, while 9 exons were common among AhAPYs (Figure 2). AhAPYs possessed varying genomic, CDS, and protein lengths, as AhAPY2-2 is the largest gene, comprising 11,962 bp long genomic sequence, 1395 bp long CDS, and 464 aa protein length, while the AhAPY2-4 is the smallest gene with genomic sequence of 2387 bp. Interestingly, AhAPY7-1 possessed the longest CDS and protein length of 2253 bp and 750 aa, respectively (Table 1). Conserved motif analysis revealed the presence of common and unique motifs in AhAPY genes. Proteins sharing common motifs tend to crowd in the same group, indicating their similar functions. The 1st, 3rd, 4th, and 10th motifs were found in most AhAPYs. AhAPY1-5 and AhAPY7-4 possessed only one motif each (Figure 2). Gene structures and conserved motif patterns of A. duranensis APYs are given in Figure S2, and of A. ipaensis are shown in Figure S3. Simulations of 3D modules of tertiary protein structures of 17 AhAPYs showed that an extended strand linked the similar subunits that are further surrounded by an alpha helix. Overall, this arrangement represents a characteristic feature of the GDA1-CD39 NPT superfamily (Figure S4). Previous studies on Arabidopsis APYs showed that AtAPY1 and AtAPY2 perform similar functions, and AtAPY6 and AtAPY7 perform similar functions; the 3D structures of AhAPYs represent the structural similarity of the first group with the second, and the sixth group with the seventh. This fact is also evident from the conserved motif analysis, which divides the peanut APYs into three groups. To study the evolutionary relationships of cultivated peanut APYs with their wild relatives and model legume crops, a phylogenetic tree was constructed among the protein sequences of A. hypogaea and their homologs in A. duranensis, A. ipaensis, A. thaliana, and G. max. The phylogenetic tree divided all the APYs into three main groups. APY1 and APY2 of all species tended to cluster in the same group. APY6 of all species clustered in a separate group, and members of APY7 from all species clustered in a separate group (Figure 3). Phylogenetic grouping provided evidence of solid evolutionary relationships among these species. Gene duplication is a major force behind genome evolution. Duplicated gene pairs among AhAPYs were identified by their phylogenetic relationships. Among 17 AhAPYs, seven duplicated gene pairs were found (Figure 4). The Ks and Ka values for each duplicated pair were calculated by a simple Ka/Ks calculator available at TBtools. Evolutionary rates (Ka/Ks ratio) for each duplicated gene pair were calculated. The Ka/Ks = 1 was considered neutral selection pressure, Ka/Ks > 1 was regarded as positive selection pressure, and Ka/Ks < 1 was considered purifying selection pressure [46]. Ka/Ks values of all gene pairs showed that purifying selection pressure was mainly involved in the duplication process (Table 2). The expected divergence time for duplicated pairs varied from 1.26 Mya (million years ago) for the gene pair AhAPY7-2:AhAPY7-3 to 127.405 Mya for AhAPY1-5:AhAPY1-4 (Table 2). Non-coding miRNAs, as the key regulators of post-transcriptional gene regulation, have attracted the attention of many researchers. Some studies have reported their role in biotic and abiotic stress responses [47,48]. To illustrate the possible miRNAs involved in regulating the peanut APYs, we predicted the miRNAs targeting the AhAPYs through the online miRNAs database, the PsRNATarget database. We found four different miRNAs targeting seven peanut APYs (Table S3). The ahy-miR3508 targeted AhAPY7-2 and AhAPY7-3; ahy-miR3513-5p targeted AhAPY2-2; ahy-miR3516 targeted AhAPY7-1 and AhAPY7-4; ahy-miR3520-5p targeted two genes, AhAPY6-1 and AhAPY6-2. These predicted miRNAs and their target sites in the CDS region are shown in Figure 5. These miRNAs provide future research dimensions for functional validation of their expression levels and role in gene regulation. To understand the putative functions of AhAPYs, the protein interaction network analysis was performed based on APYs orthologs in Arabidopsis using the STRING database. The top 10 interactions were considered with a high threshold level (0.7). The interaction network prediction showed that AhAPY1-5 has functions related to Arabidopsis ZEU1 protein, Arabidopsis ADSS (Adenylosuccinate synthetase, chloroplastic), Fac1 (AMP deaminase), and some other proteins (Figure S5). Protein AhAPY6-2 showed strong interactions with Arabidopsis ADSS, ZEU1, FAC1, THY1 (Bifunctional dihydrofolate reductase-thymidylate synthase 1), THY2 (Bifunctional dihydrofolate reductase-thymidylate synthase 2), and with other Arabidopsis proteins. AhAPY7-6 showed interaction with PUM10 (Putative pumilio homolog 10). Multiple sequence search methods showed that other AhAPYs did not interact with Arabidopsis proteins. Their interactions need more work, or there is a possibility that these proteins have some special functions that are not exploited well. Analyzing transcription factor binding sites or cis-regulatory elements is key for functional genomic studies. We searched the 2 kb upstream regions of promoters to find out the cis-regulatory elements to predict the possible functions of AhAPYs. Aside from the core promoter elements (TATA box, CAAT box), other important regulatory elements were also found in the promoter regions. Other important cis-elements mainly included light-responsive elements (G-box, Box 4, GATA-motif), hormone-responsive elements (abscisic acid, ABRE; salicylic acid, SARE; methyl jasmonate, MeJA; gibberellin, GBRE), growth- and development-related (anaerobic induction, ARE; zein metabolism, O2-site; meristem expression; CAT-box), and stress-responsive elements (wound responsive elements, WUN motif; low temperature responsive, LTR; defense responsive; TC-rich repeats). The detail of cis-regulatory elements and their positions in the promoter regions are shown in Figure 6. The collinearity analysis was performed among A. hypogaea, A. duranensis, A. ipaensis, and A. thaliana to assess their syntenic relationships. Collinearity analysis showed strong evolutionary relationships of APYs among these species. A. hypogaea showed strong syntenic relationships with its wild parents compared to Arabidopsis (Figure 7). The functional annotation analysis was performed to prophesize the potential functions of AhAPYs. Gene ontology (GO) enrichment analysis revealed that AhAPYs are involved in important GO categories, including molecular functions (MF), cellular components (CC), and biological processes (BP). For the MF category, AhAPYs were involved in hydrolase catalytic activity; for the CC category, the AhGLPs were mainly found as a component of the nucleus; and for the BP category, AhAPYs were involved in a large number of subcategories, including reproduction, catabolic processes, stress responses, and many developmental processes (Figure 8a). These results depict the importance of AhAPYs in different metabolic, cellular, and biological processes. The KEGG pathway is a computerized representation of a biological system through which we can infer the role of a protein/gene [49]. We also performed the KEGG enrichment analysis of AhAPYs to infer their metabolic roles. AhAPYs were involved in key metabolic pathways, including 00230 purine metabolism, B09104 Nucleotide metabolism, 00240 Pyrimidine metabolism, and A09100 metabolism pathways. AhAPYs were also enriched in signaling and cellular processes and as 04090 CD molecules (Figure 8b). The transcriptome expression pattern of AhAPYs in various tissues and under different hormones/stress treatments was assessed from the peanut genome resource database. All AhAPYs showed expression in studied tissues, including leaf, stem, root, flower, peg, pericarp, testa, cotyledons, and embryo. AhAPY7-1 to AhAPY7-6 did not show any remarkable expression in the studied tissue. AhAPY6-1 and AhAPY6-2 showed uniform expression in all tissues, but expression level was low, and AhAPY1-1 and AhAPY1-2 showed relatively higher expression levels in all tissues. AhAPY2-1 and AhAPY2-3 showed abundant expression in the pericarp compared to other tissues, and AhAPY2-2 showed abundant expression in the stem, root, and cotyledons. AhAPY2-4 showed decreased expression in the stem tip Figure 9a. AhAPYs showed varying expression levels under different hormones and stress treatments. AhAPY2-1 and AhAPY2-2 showed decreased expression under ABA treatment. In contrast, AhAPY1-1 and AhAPY1-2 showed higher expression under all stress conditions, including ABA, SA, Brassinolide, paclobutrazol, ethephon treatments, drought, normal irrigation, ddH2O spray, low temperature, and room temperature. AhAPY1-5 and AhAPY2-4 did not respond to the hormones, water, and temperature treatments. The expression matrix of AhAPYs in response to different hormones and stress agents is shown in Figure 9b. The FPKM values for transcriptome expression in different tissues and under different hormones are publicly available at (http://peanutgr.fafu.edu.cn/Transcriptome.php; accessed on 10 August 2022). Further, the expression of all AhAPYs genes was assessed under abscisic acid treatment to check whether their expression corresponds to the transcriptome expression. Peanut plants were treated with ABA (10 μg/mL), and quantitative expression was assessed at different time points. The qRT-PCR results validated the transcriptome expression data under ABA treatment. The qRT-PCR-based expression of 17 AhAPYs genes is shown in Figure 10. Genes of group 1 (AhAPY1-1 to AhAPY1-4), group 6 (AhAPY6-), and group 7 (AhAPY7-) showed upregulated transcriptome expression, and the qRT-PCR results also found similar expression pattern. AhAPY1-5, and all genes of group 2 (AhAPY2-), did not show any change in transcriptome expression, and real-time expression results found a similar expression pattern. In the previous section, the expression profiles showed that the AhAPY2-1 gene was more highly expressed in the pod or pericarp than in any other tissue; we considered it a pericarp-abundant gene. Based on this consideration, it can be assumed that the promoter of the pericarp-abundant gene can be used to drive a foreign gene in a pod-specific manner. The RNA seq- and gene-chip expression data of AhAPY2-1 is given in File S1. qPCR was performed to verify the expression of the AhAPY2-1 gene in different tissues. Results of the qRT-PCR analysis showed a high number of transcripts of AhAPY2-1 in pod/pericarp tissues compared to all other tissues, indicating its pod-abundant expression pattern Figure 11a. Based on these results, we hypothesized that the promoter of the AhAPY2-1 gene could be used to drive a foreign gene in a pod-abundant manner. For cloning of the AhAPY2-1 promoter, the 2044 bp upstream region was selected and scanned through online promoter analysis databases, the PlantCARE database. It was found that the promoter region contained core promoter elements, including the TATA Box and CAAT box, both of which are required for precise initiation of transcription and tissue-specific activity [50,51]. Aside from these core promoter elements, several other important cis-elements were also present in the AhAPY2-1 promoter. These elements include the hormone-responsive elements auxin (TGA-elements), gibberellin (TATC-box), salicylic acid (TCA-element), abscisic acid (ABRE), methyl jasmonate (TGACG-motif, CGTCA-motif), ethylene responsiveness (ERE), and light-responsive elements (GT1-motif, G-Box, GATA-motif, Box 4, AT-1 motif). Moreover, wound-responsive elements (WUN-motif), defense-related elements (MYB sites), anaerobic induction (ARE), and zein metabolism regulatory element O2-site were also present. Additionally, some elements with unknown functions were also present. Detailed information on the AhAPY2-1 promoter is provided in Figure S6. The new PLACE database also predicted several key elements in the promoter region, such as seed-specific elements (RY-element) and binding sites for WRKY and MYB transcription factors. Table S4 contains information on cis-elements, their position, sequence, and functions predicted by the PLACE database. These elements suggest that the AhAPY2-1 promoter could be used to replace the native promoter of a gene. The CDS, protein, and promoter sequences of the AhAPY2-1 gene are given in File S2. The promoter region of the AhAPY2-1 gene was amplified from the DNA template of the Xinhuixiaoli (XHXL) cultivar with the specific primers (Table S1). Clones having >99% sequence similarity with the original sequence were used to construct the vector. Two-step Gateway cloning was used in which the promoter was first ligated into entry vector pDONR207 by BP reaction. The promoter fragment was ligated into the expression vector pMDC164 by LR reaction in the second step. The complete procedure of amplifying the AhAPY2-1 promoter and vector construction is shown in Figure 11b–d. Vector pMDC164 contains the Hygromycin resistance gene and the GUS reporter gene for the identification of positively transformed plants and functional studies. The expression vector was named AhAPY2-1P-GUS. The expression vector was transformed into A. tumefaciens, and (GV3101) cells were used for the genetic transformation of Arabidopsis plants by the floral dip method. Positively transformed T0 seeds were screened on Hygromycin (50 mg mL−1) selection medium, and eight HygR resistant plants were verified by PCR amplification, Figure 11e. Hygromycin and PCR screening were performed in each generation, and homozygous T3 generation was obtained. Samples from different tissues of transgenic plants were used to check the activity of the AhAPY2-1-controlled GUS gene. Leaf, roots, stem, seedlings, flowers, siliques, and seeds were incubated in the GUS solution. The GUS staining showed that the siliques outer covering/pod has a dense blue color. Flowers of transgenic Arabidopsis plants also showed some blue color after GUS staining, while in all other tissues the GUS staining was very low or absent, Figure 12a. Arabidopsis wild plants (Col-0) were also used for GUS staining to compare the results. To assure the proper staining of cotyledons and embryos, seeds were ruptured and incubated in the staining solution. Cryostat sectioning of those seeds was performed to check whether staining was present in cotyledons and embryos. Staining was not detected in any seed tissues, including seed coat/testa, cotyledons, or embryos, Figure 12a. Arabidopsis wild type (Col-0) did not show any blue color. The staining results indicated that the AhAPY2-1 promoter has successfully regulated the GUS gene in a pod/pericarp-abundant manner in transgenic Arabidopsis plants. The qRT-PCR analysis was performed to check the quantitative expression of the GUS gene in different tissues of transgenic Arabidopsis plants. The qRT-PCR analysis showed that the GUS gene was highly expressed in silique outer coverings (pod/pericarp) of transgenic seedlings compared to other tissues, Figure 12b. In contrast, the expression level in all other tissues was very low. Collectively, these results showed that the AhAPY2-1 promoter effectively drove the expression of the GUS gene in the pericarp-abundant manner; hence, this promoter could be a suitable candidate for pod/pericarp-abundant expression of a transgene. Expression responses of AhAPY2-1 promoter under different phytohormones treatment were studied by exposing the transgenic Arabidopsis plants to different hormones stress. The expression of the GUS gene controlled by the AhAPY2-1 promoter was studied to check the activity of the promoter in response to these hormones. The GUS gene showed no remarkable expression under all hormonal/ddH2O treatments at all time points. The expression of the GUS gene was decreased as compared to the control. Under ABA treatment, expression level decreased at 3 h post-treatment and showed a decreasing trend until 24 h of ABA treatment. Under BR and SA treatment, a similar expression pattern was observed. In response to ethephon and paclobutrazol treatment, the expression level was decreased compared to the control. Still, there was a gradual increase in expression at different time points, but the expression was less than the controlled one. Overall, the expression of the GUS gene was decreased under all treatments than in control plants (Figure 13). These results indicated that the AhAPY2-1 promoter did not induce GUS gene expression under hormone treatments. In other words, we can say that AhAPY2-1 is a pericarp-specific gene that is not influenced by other stress conditions. Extracellular ATPs, the energy currency of all organisms, play key regulatory roles in plants and animals. The signaling roles of extracellular ATPs in mammals have been under investigation for the last 40 years [52], but these investigations are at an early stage in plants. Recent studies have demonstrated that extracellular ATP levels play critical roles in regulating various cellular and stress responses [53,54]. Apyrases (APYS)/Nucleoside phosphatases (NTPs) are key regulators of cell growth and stress responses by maintaining extracellular ATP levels [55]. Several studies have shown that cellular ATP levels decrease under stressed conditions, which ultimately results in increased cellular ROS levels causing cell apoptosis [56,57]. Thus, APYs are critical in cleaving the extracellular ATP in the stressed environment to maintain cellular ATP levels and avoid the adverse effects of ROS accumulation. Overexpression of APYs has been reported to inhibit ROS accumulation and increase stress tolerance [36]. During the past decade, some studies have shown that APYs play fundamental roles against cold stress [36], salt stress [58], and drought stress [21]. Their roles in biotic stress tolerance have recently been reported, including powdery mildew response in wheat [59]. These findings provide the future scope of APYs in managing the stress induced by external agents in plants. In Arabidopsis, seven apyrases have been reported, and some of them have been functionally characterized [55]. In 2019, Liu and his team investigated apyrases in wheat at a genome-wide scale and reported the defense roles of APYs against powdery mildew [59]. Peanut is an important legume crop worldwide and a livelihood source for many people. At present, peanut is a resource-rich legume with a large amount of data available on yield quality traits [60,61,62,63], diseases/pathogens resistance [5,6,64], seed dormancy [61,65], etc. With the availability of the genome sequence of tetraploid peanut (Arachis hypogaea) [10,11], it becomes easy to investigate the apyrases in peanut and study their function. In this study, we used seven Arabidopsis APYs and identified 17 APY homologs in the cultivated peanut genome (Table 1). These 17 peanut APYs were divided into three phylogenetic groups based on their evolutionary relationships with Arabidopsis and soybean. We also identified eight APYs in each A. duranensis and A. ipaensis (Table S2). The larger numbers of APYs in the genome of cultivated peanut than its diploid parents are due to its tetraploid nature and larger genome size. The evolutionary process has resulted in the structural diversity of genes/gene families in crops; similarly, the APYS of wild and cultivated peanuts possessed large structural diversity. As the number of exons is important in determining gene expression patterns and levels [66], the cultivated peanut also possessed varying exons ranging from 2 to 12 (Figure 2). The phylogenetic analysis divided the AhAPYs into three groups; mainly, these groups correlated to their functions. As previous studies have reported the similar functions of AtAPY1 and AtAPY2, their homologs in peanut tend to cluster in one group. AtAPY7 homologs in peanuts clustered into a separate group. Although AtAPY6 and AtAPY7 possessed almost the same functions, the AtAPY6 homologs clustered into separate groups (Figure 3). A similar phylogenetic grouping has been reported for wheat apyrases [59]. Gene duplication and variations in genome size are key features of genetic diversity. Gene duplication events are important for gene expression diversification and neofunctionalization. We performed the gene duplication analysis for AhAPYs. Gene duplication analysis revealed eight duplicated gene pairs (Table 2). Mainly purifying selection pressure was involved in the duplication process, and all of the genes were segmentally duplicated (Figure 4). Non-coding micro-RNAs are key regulatory elements that play multiple roles in growth, regulation, and defense responses [67]. miRNAs have been a research hotspot for the last few years, and more studies are becoming available on their regulatory roles [47,68,69]. miRNAs are important in managing stress responses. We predicted the putative miRNAs targeting the AhAPYs through the published miRNAs data [70]. We found four miRNAs targeting seven AhAPYs (Table S3, Figure 5). Cis-regulatory elements are of key importance as they determine a gene’s expression pattern, regulatory roles, and stress responses [71,72]. Cis-regulatory elements analysis showed important elements involved in light, hormones, growth and development, stress, and defense responses (Figure 6). Genome collinearity and syntenic relations are important evolutionary events that lead to understanding genome duplication and neofunctionalization [73]. The collinearity analysis revealed key syntenic relations of AhAPYs with their diploid parents and Arabidopsis (Figure 7). Similarly, functional annotation is an important tool to emphasize the functions of a gene/gene family. The gene ontology (GO) analysis showed that AhAPYs are part of molecular functions (MF), Biological processes (BP), and cellular components (CC), and (Figure 8a). The KEGG pathway enrichment analysis showed that AhAPYs were also involved in key metabolic pathways (Figure 8b). Owing to their geocarpic nature, peanut seeds are constantly attacked by soil- and seed-borne diseases. Different fungal, bacterial, and viral pathogens attack peanut plants at different growth stages and deteriorate yield and quality [45,74]. The pod/pericarp is an inedible part of peanut seed and a vital defense organ against various biotic and abiotic stress agents. The promoter is a part of a non-coding DNA sequence present upstream of a gene and regulates the expression of the downstream gene. Previous transgenic projects mainly use constitutive promoters to drive the desired gene(s). The constitutive expression of a foreign gene can have adverse effects on plant growth and development, as the constitutive expression imposes an extra metabolic burden by expressing the gene in tissues/organs where it is not required. Tissue-specific/abundant promoters are suitable alternatives to constitutive promoters as they express the desired gene in a tissue-specific manner. If a tissue-specific promoter with a resistant gene can successfully be transformed into peanut, it can improve the defense capabilities of the plant. We hypothesized that a pericarp-specific promoter would be a good choice to express resistant genes in a pericarp-specific manner to improve the defensive abilities of the pericarp. From the transcriptome expression data (Figure 9), we found that AhAPY2-1 is abundantly expressed in the pericarp without showing any remarkable expression in other tissues. We selected AhAPY2-1 for promoter cloning and functional characterization. Genetic transformation in peanut is a challenging task. There are some reports on successful genetic transformation in peanut [75,76], but not a single well-established protocol exists for transformation. Due to these bottlenecks, Arabidopsis becomes a better alternative for the functional characterization of genes and promoters. So, we selected Arabidopsis for the functional characterization of the AhAPY2-1 promoter. We cloned a 2044 bp upstream region of the AhAPY2-1 gene and analyzed the key cis-regulatory elements (Figure S6). Cis-regulatory elements clearly showed that AhAPY2-1P could be a suitable promoter. The qRT-PCR results validated the transcriptome expression data and clearly showed that this gene expresses in the pericarp-abundant manner (Figure 11a). The promoter was cloned from peanut variety XHXL, and the plant expression vector was constructed using the backbone of the pMDC164 vector following the gateway cloning system. The floral-dip method was used for the genetic transformation of Arabidopsis plants, and positively transformed plants were grown to T3 homozygous generation. GUS staining assay showed strong blue color in the silique’s outer coverings/pericarp; some staining was also present in the flowers. These minute changes in AhAPY2-1 expression in peanut and Arabidopsis are possibly due to the species change. Staining was absent in all other tissues. The cryostat sectioning of dissected seeds showed that the GUS gene was not expressed in seed coat/testa, cotyledons, and embryo. Expression of the GUS gene determined by qRT-PCR analysis also revealed significantly high expression of the GUS gene in the pericarp compared to other tissues. The literature shows that a set of phytohormones plays a key role in regulating several physiological, biochemical, and molecular processes under normal and stressed conditions [77]. Therefore, to check whether the expression of the GUS gene under the control of the AhAPY2-1 promoter in transgenic Arabidopsis corresponds to the transcriptome expression of the AhAPY2-1 gene in response to different hormones or not, transgenic plants were treated with phytohormones, and qPCR was performed. Although there were some deviations in the expression patterns, overall, we can conclude that it followed a similar expression pattern. These findings strongly suggest that AhAPY2-1P can regulate a foreign gene’s expression in a pericarp-abundant manner. The APYs from the peanut genome were identified in a systematic way. First, the protein sequences of seven apyrases from Arabidopsis AtAPY1-AtAPY7 [25] were obtained from the Arabidopsis genome database TAIR [78]. The AtAPYs protein sequences were used for BLAST search in the PeanutBase database (https://peanutbase.org/pb_sequenceserver; accessed on 2 August 2022) to find the APYs in diploid progenitors of cultivated peanut (A. duranensis and A. ipaensis) [12]. The protein sequences of AtAPYs, AdAPYs, and AiAPYs were used to search the APYs in the cultivated peanut genome through BLAST search in Peanut Genome Recourse (PGR) database (http://peanutgr.fafu.edu.cn/; accessed on 2 August 2022) [10]. The presence of the GDA1-CD39 domain (PF01150) in identified AhAPYs was confirmed through the NCBI (https://www.ncbi.nlm.nih.gov/; accessed on 2 August 2022) and Pfam databases (http://pfam.xfam.org/; accessed on 2 August 2022). The genomic positions of AhAPYs were determined from the PGR database [10]. Genes were mapped out using the TBtools software [79]. The information regarding the gene structure was also retrieved from the PGR database. The conserved motifs in the protein sequences were elucidated by the MEME suite while setting the maximum number of motifs as ten with other default parameters [80]. Protein tertiary structures were predicted by the ExPASy server, while 3D models were drawn by Swiss-Model (https://www.swissmodel.expasy.org/; accessed on 4 August 2022) following the default parameters. The physicochemical properties, such as theoretical molecular weight (MW) and isoelectric points (pI), were determined by the ProtParam tool (https://web.expasy.org/protparam/; accessed on 3 August 2022) [81], and subcellular localizations were predicted by CELLO v2.5 tool (http://cello.life.nctu.edu.tw/; accessed on 4 August 2022) [82]. The phylogenetic tree was constructed among the APYs of A. hypogaea, G. max, A. thaliana, A. duranensis, and A. ipaensis to study their evolutionary relationships. MUSCLE program was used to align the protein sequences, and an ML tree with 1000 bootstrap repeats was constructed by MEGA-X. The genome and GFF3 files were run through MCScanX to identify the duplicated gene pairs. A simple Ka/Ks calculator was used to calculate the expected synonymous (Ks) and non-synonymous (Ka) substitution rates. Divergence time (million years ago, MYA) for duplicated gene pairs was calculated as ‘t = Ks/2r’ while using the neutral substitution rate for peanut r = 8.12 × 10−9 [12]. Possible interactions of AhAPYs with other proteins were elucidated by constructing their protein–protein interaction network based on their homologs in Arabidopsis using the STRING 11.5 tool (https://www.string-db.org/cgi/; accessed on 5 August 2022). Interacting proteins with 100% similarity and <10−5 were considered. The top 10 interactions with a high threshold (0.7) were considered. MCL clustering with inflation parameter 3 was used, and dotted lines were used between cluster edges. The putative miRNAs targeting the peanut APYs were predicted through the psRNATarget database (https://www.zhaolab.org/psRNATarget/analysis?function=2; accessed on 7 August 2022) [70]. The CDS sequences of peanut apyrases were scanned through the psRNATarget database for the prediction of putative miRNAs with default settings. Online database available for the promoter elements prediction, viz., PlantCARE database (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/; accessed on 7 August 2022) [83] was used to identify the cis-elements in APY promoters. The promoter sequences of AhAPYs were obtained from the PGR database. For the identification of cis-elements, 2 kb upstream sequences were used. The syntenic relationships of three peanut species and Arabidopsis were developed to view the comparative genomic conservations. For this purpose, the genome and GFF3 files of all these species were scanned against each other through One Step MCScanX. The resulting Collinearity, GFF3, and CTL files were merged and used for multiple synteny plots with the help of TBtools [79]. We performed the functional annotation analysis to understand the possible functions/regulatory roles of AhAPYs. Whole-genome protein sequences were scanned for functional annotation analysis at the EggNOG server (http://eggnog-mapper.embl.de/; accessed on 8 August 2022). The resulting annotation files were used to perform the GO and KEGG enrichment analysis. To understand the expression matrices of AhAPYs in different tissues and under different hormones/stress agents, the transcriptome expression data were accessed from the peanut genome resource database [10]. The log10 normalized FPKM (fragments per kilobase million) values were used to construct the expression heatmaps for different tissues and under different stress conditions. Further, the transcriptome expression was verified by treating the peanut plants with abscisic acid (ABA) and performing the qRT-PCR analysis. The peanut seeds were grown in small plastic pots, and plants were grown in the greenhouse at 26 °C and 16 h/86 day/night photoperiod. Four-leaf-old plants were treated with ABA (10 μg/mL), and samples were taken at different time points. Total RNA was extracted by the CTAB method with some modification, and the first strand cDNA was synthesized by the PrimeScript 1st strand cDNA Synthesis Kit (Takara, Dalian, China). qRT-PCR analysis was performed to compare the transcriptome and real-time expression of all APY genes. The qRT-PCR reaction was performed by the Applied Biosystems 7500 real-time PCR system (Thermofisher Scientific, Waltham, MA, USA) with the cycling program: 94 °C (1 min), 60 °C (1 min), and 72 °C (1 min) for 40 cycles. Peanut Actin gene was used as an internal control. Primers used for qRT-PCR are given in Table S1. The seeds of peanut cultivar Xinhuixiaoli (XHXL) and Arabidopsis thaliana Col-0, used in this study, were grown in a greenhouse at the Institute of Oil Crops, Fujian Agriculture and Forestry University, Fuzhou, China. Based on the transcriptome expression data, we found that AhAPY2-1 was abundantly expressed in the pericarp. We selected a 2044 bp upstream region of the AhAPY2-1 gene for promoter cloning and characterization. The expression of the AhAPY2-1 gene in different tissues of peanut was checked by the qRT-PCR analyses. The promoter region of the AhAPY2-1 gene was cloned from the DNA template of peanut variety XHXL, and binary plasmid pMDC164 was used to construct the plant expression vector by the Gateway cloning method. Expression vectors were transformed into A. tumefaciens (GV3101) competent cells through the heat shock method. The floral dipping method was used to transform young Arabidopsis plants [84]. Positive transgenic plants were identified on a Hygromycin (HygR) selection medium (50 mg mL−1), and further verified by PCR amplification. Primers used in this study are given in Table S1. Our previous study gives a detailed procedure for qPCR and promoter cloning and transformation [85]. Eight positive plants (verified by HygR resistance and PCR amplification in every generation) were grown to T3 generation for functional characterization. Different tissues of transgenic Arabidopsis plants were used for GUS staining [86] to check the activity of the GUS gene under the control of the AhAPY2-1 promoter. Leaf, stem, flower, seedlings, siliques, and seeds were incubated in GUS staining solution for 12 h and then washed and decolorized with 75% ethanol. To achieve better staining results in embryo and cotyledons, the seeds of transgenic plants were ruptured before incubation. After that, cryostat sectioning was performed with the help of Leica CM1950 Cryostat Microtome (Leica Biosystems, Wetzlar, Germany). The images of stained tissues/organs were taken by Olympus microscope (BX3-CBH) (Olympus, Tokyo, Japan). The quantitative expression of the GUS gene in different tissues of transgenic plants was checked by qRT-PCR. Transgenic plants were also treated with different phytohormones; abscisic acid (ABA, 10 μg/mL), Brassinolide (BR, 0.1 mg/L), ethephon (ETH, 1 mg/mL), paclobutrazol (PAC, 150 mg/L), salicylic acid (SA, 3 mmol/L), and low temperature (4 °C). The expression of the GUS gene in response to these hormones and low temperature was analyzed by qRT-PCR at different time points. The qRT-PCR was performed for three biological replicates, and data were normalized by the 2−ΔΔCT method. The expression levels were expressed as mean ± standard errors. Statistical significance of expression levels at different time points was assessed by analysis of variance (ANOVA) with significance level α = 0.005 followed by LSD test. We investigated the Apyrase (APYs)/Nucleosied phosphatase (NTPs) family in cultivated peanut. Seventeen apyrase homologs were found in the genome of cultivated peanut, while eight homologs were also found in diploid peanut species (A. duranensis and A. ipaensis each). The genome-wide identification, phylogenetic analysis, structural and expression analysis, GO, and KEGG enrichment, and miRNAs prediction provided a theoretical base for future functional studies. This study highlighted some key genes that effectively respond to different stress agents. AhAPY1-1, AhAPY1-2, AhAPY6-1, and AhAPY6-2 showed upregulated expression against all hormone, water, and temperature treatments. These genes could be suitable candidates for drought and low-temperature resistance. AhAPY7-4 also showed increased expression against all treatments, while its expression was specifically high against drought treatment. This gene can also be a suitable candidate for drought resistance. Further, we functionally characterized a pericarp/pod-abundant expression promoter. The quantitative PCR analysis validated the transcriptome expression analysis. The quantitative and qualitative expression analysis of the GUS gene under AhAPY2-1P in transgenic Arabidopsis plants provided the practical significance of this promoter in deriving a gene in a pericarp-abundant manner

PMC10003108

Kazushi Yamamoto,Masashi Yamashita,Masataka Oda,Vindy Tjendana Tjhin,Hiroyuki Inagawa,Gen-Ichiro Soma

Oral Administration of Lipopolysaccharide Enhances Insulin Signaling-Related Factors in the KK/Ay Mouse Model of Type 2 Diabetes Mellitus

27-02-2023

glucose tolerance,adipose tissue,insulin resistance,lipopolysaccharide,oral administration

Lipopolysaccharide (LPS), an endotoxin, induces systemic inflammation by injection and is thought to be a causative agent of chronic inflammatory diseases, including type 2 diabetes mellitus (T2DM). However, our previous studies found that oral LPS administration does not exacerbate T2DM conditions in KK/Ay mice, which is the opposite of the response from LPS injection. Therefore, this study aims to confirm that oral LPS administration does not aggravate T2DM and to investigate the possible mechanisms. In this study, KK/Ay mice with T2DM were orally administered LPS (1 mg/kg BW/day) for 8 weeks, and blood glucose parameters before and after oral administration were compared. Abnormal glucose tolerance, insulin resistance progression, and progression of T2DM symptoms were suppressed by oral LPS administration. Furthermore, the expressions of factors involved in insulin signaling, such as insulin receptor, insulin receptor substrate 1, thymoma viral proto-oncogene, and glucose transporter type 4, were upregulated in the adipose tissues of KK/Ay mice, where this effect was observed. For the first time, oral LPS administration induces the expression of adiponectin in adipose tissues, which is involved in the increased expression of these molecules. Briefly, oral LPS administration may prevent T2DM by inducing an increase in the expressions of insulin signaling-related factors based on adiponectin production in adipose tissues.

Oral Administration of Lipopolysaccharide Enhances Insulin Signaling-Related Factors in the KK/Ay Mouse Model of Type 2 Diabetes Mellitus Lipopolysaccharide (LPS), an endotoxin, induces systemic inflammation by injection and is thought to be a causative agent of chronic inflammatory diseases, including type 2 diabetes mellitus (T2DM). However, our previous studies found that oral LPS administration does not exacerbate T2DM conditions in KK/Ay mice, which is the opposite of the response from LPS injection. Therefore, this study aims to confirm that oral LPS administration does not aggravate T2DM and to investigate the possible mechanisms. In this study, KK/Ay mice with T2DM were orally administered LPS (1 mg/kg BW/day) for 8 weeks, and blood glucose parameters before and after oral administration were compared. Abnormal glucose tolerance, insulin resistance progression, and progression of T2DM symptoms were suppressed by oral LPS administration. Furthermore, the expressions of factors involved in insulin signaling, such as insulin receptor, insulin receptor substrate 1, thymoma viral proto-oncogene, and glucose transporter type 4, were upregulated in the adipose tissues of KK/Ay mice, where this effect was observed. For the first time, oral LPS administration induces the expression of adiponectin in adipose tissues, which is involved in the increased expression of these molecules. Briefly, oral LPS administration may prevent T2DM by inducing an increase in the expressions of insulin signaling-related factors based on adiponectin production in adipose tissues. Lipopolysaccharide (LPS) is a glycolipid found in the outer membrane of Gram-negative bacteria. When LPS is injected into the body, it binds to Toll-like receptors (TLR4) in vivo, even at very low doses. This binding leads to the production of pro-inflammatory cytokines and, in turn, causes a strong systemic inflammatory response. This condition is called a cytokine storm state, which can induce shock symptoms such as fever and diarrhea and may lead to death [1,2,3,4]. Since the discovery of LPS, it has been called an endotoxin [5] and has been used as an inflammation-inducing substance for stimulating immune cells in vitro and inflammation models in animals (in vivo) by injection. Moreover, bacterial translocation has been observed in persistent inflammatory lesions in the intestinal tract and periodontal tissues, and persistent invasion of bacteria and LPS in living organisms induces systemic inflammation [6]. Based on these findings, LPS is considered a cause of chronic inflammatory diseases, including lifestyle-related diseases [7]. Specifically, many studies have reported that LPS is a causative agent of type 2 diabetes mellitus, one of the major lifestyle diseases. Type 2 diabetes mellitus is a chronic inflammatory disease of adipose tissues and is characterized by impaired glucose tolerance and insulin resistance. Several studies have suggested that LPS induces the onset of type 2 diabetes mellitus. For example, LPS injection was reported to decrease the protein and mRNA expression of Glucose transporter type 4 (Glut 4), the primary transporter for glucose uptake in adipose tissues, and induces symptoms of type 2 diabetes mellitus such as increased fasting blood glucose, impaired glucose tolerance, and insulin resistance [1,2,3,4]. However, in these reports, LPS was injected intraperitoneally or intravenously to induce pathological models of systemic inflammation deliberately. LPS exists within healthy individuals, yet inflammation was not induced [8]. A hundred trillion bacteria reside in the mucosa of animals, and approximately half of those are Gram-negative bacteria that contain LPS on their cell wall. Thus, LPS is permanently present in the mucosa and should not be considered toxic to living beings. Indeed, our group found that oral LPS administration does not induce inflammation, unlike its injections [9,10]. Furthermore, oral LPS administration was found to suppress inflammation induced by a high-fat diet, prevent dementia, and suppress atherosclerosis in senescence-accelerated mice (SAM-P8) and ApoE-deficient atherosclerotic mice fed a high-fat diet [11,12]. These findings suggest that the physiological role of LPS differs from that of inflammation exacerbation by injection. Therefore, we propose that orally administered LPS should not be viewed as an endotoxin that induces inflammation but as a potentially beneficial substance that merits further studies. Hence, this study aimed to establish this proposition by investigating the effect of oral LPS administration on type 2 diabetes mellitus using the KK-Ay mouse model, which is the standard animal model of type 2 diabetes mellitus [13,14]. As a result, we found that oral LPS administration improved fasting blood glucose levels and glucose tolerance index (HOMA-IR) without exacerbating inflammatory markers in KK/Ay mice with diabetic symptoms. In addition, for the first time, we found that adiponectin, an adipokine important for regulating glucose metabolic function, is induced in adipose tissues. To investigate the effect of oral LPS administration on type 2 diabetes mellitus, KK/Ay mice, a standard model for this analysis, were used because they exhibit impaired glucose tolerance and insulin resistance. Initially, an oral glucose tolerance test (OGTT) and measurement of blood glucose parameters were performed to confirm the condition of KK/Ay mice and compared it with the condition of non-type 2 diabetes mellitus model C57BL/6 mice. The OGTT results show that blood glucose levels were significantly increased in KK/Ay mice compared with those in C57BL/6 mice at 0, 30, 60, 120, and 180 min after oral glucose administration (Figure 1a). The area under the curve (AUC) of the OGTT was also significantly increased in KK/Ay mice compared with that in C57BL/6 mice (Figure 1b). In addition, the blood glucose parameters, such as fasting blood glucose level and hemoglobin A1C (HbA1c) test results, were significantly increased in KK/Ay mice compared with those in C57BL/6 mice (Figure 1c,d). Furthermore, blood insulin and HOMA-IR, an indicator of insulin resistance, were significantly increased in KK/Ay mice compared with those in C57BL/6 mice (Figure 1e,f).The abnormal glucose tolerance and insulin resistance results from these tests confirmed that KK/Ay mice had type 2 diabetes mellitus at the start of the study. KK/Ay mice with type 2 diabetes mellitus were divided into two groups: the LPS (−) group received distilled water, and the LPS (+) group received distilled water containing LPS. After 8 weeks, the effects of oral LPS administration on insulin resistance and glucose intolerance in KK/Ay mice were examined by performing an OGTT and measuring blood glucose parameters. In the OGTT, blood glucose levels at 60, 120, and 180 min after oral glucose administration were significantly lower in the LPS (+) group than in the LPS (−) group (Figure 2a), and the AUC of the OGTT was also significantly lower in the LPS (+) group than in the LPS (−) group (Figure 2b). Regarding blood glucose parameters, the fasting blood glucose showed a decreasing trend in the LPS (+) group compared with that in the LPS (−) group, and HbA1c decreased significantly in the LPS (+) group when compared with that in the LPS (−) group (Figure 2c,d). In addition, blood insulin levels appear to decrease in the LPS (+) group compared with those in the LPS (−) group, and HOMA-IR, a marker of insulin resistance, decreased significantly in the LPS (+) group compared with that in the LPS (−) group (Figure 2e,f). These results suggest that oral LPS administration has an ameliorating or inhibitory effect on insulin resistance and glucose intolerance in type 2 diabetic KK/Ay mice. Next, the OGTT and blood glucose parameters at the start (week 0) and end (week 8) of the study were compared to determine whether oral LPS administration had an ameliorating or inhibitory effect on type 2 diabetes mellitus. The AUC of the OGTT increased significantly in the LPS (−) group at the end of the study compared with that at the start of the study; however, no significant difference was found before and after the start of the study in the LPS (+) group (Figure 3a). Fasting blood glucose levels were not statistically different between the LPS (−) and LPS (+) groups; however, the fasting blood glucose level increased approximately 1.2-fold in the LPS (−) group, whereas it was almost unchanged in the LPS (+) group (Figure 3b). HbA1c increased significantly in both the LPS (−) and LPS (+) groups at the end of the study compared with that at the beginning of the study. However, the increase in HbA1c was approximately 1.6-fold in the LPS (−) group, whereas it was approximately 1.3-fold in the LPS (+) group, with the rate of increase also being lower in the LPS (+) group (Figure 3c). Blood insulin levels in both the LPS (−) and LPS (+) groups also increased significantly at the end of the study compared with that at the beginning of the study. The LPS (−) group had a 2.5-fold increase in blood insulin level, whereas the LPS (+) group had a 1.5-fold increase, with the rate of increase being lower in the LPS (+) group (Figure 3d). HOMA-IR increased significantly in the LPS (−) group at the end of the study compared with that at the beginning of the study, and no significant difference was observed in the LPS (+) group before and after the study (Figure 3e). These results indicate that oral LPS administration suppressed the progression of insulin resistance and glucose intolerance in type 2 diabetic KK/Ay mice, suggesting that oral LPS administration has a suppressive effect on type 2 diabetes mellitus. The analysis of body weight and adipose tissue changes in mice with and without LPS administration showed no significant changes in body weight, mesenteric adipose tissue weight, perirenal adipose tissue weight, peritesticular adipose tissue weight, or total adipose tissue weight (Figure 4a–e). On the contrary, the size of cells in adipose tissues was significantly reduced by oral LPS administration (Figure 4f,g). The adipose tissue is one of the tissues that plays a crucial role in type 2 diabetes mellitus, specifically its insulin signaling. The elevated insulin signaling in adipose tissues is involved in suppressing the progression of type 2 diabetes mellitus. Therefore, we hypothesized that the expression levels of insulin signaling-related factors are upregulated in adipose tissues of KK/Ay mice, in which blood insulin resistance suppression and blood glucose intolerance by oral LPS administration were observed. The expression levels of insulin signaling-related factors in adipose tissues indicated that mRNA and protein expression levels of Glut4, which is involved in insulin-mediated glucose uptake, were much elevated in the LPS (+) group than in the LPS (−) group (Figure 5a,b). In addition, the expression level of insulin receptor (Ir), which is involved in insulin signaling to upregulate Glut4 expression, showed an increasing trend in the LPS (+) group compared with that in the LPS (−) group (Figure 5c). Moreover, the expression levels of thymoma viral proto-oncogene (Akt) and insulin receptor substrate 1 (Irs1) were significantly elevated in the LPS (+) group compared with those in the LPS (−) group (Figure 5d,e). These results suggest that the expression levels of insulin signaling-related factors in adipose tissues are upregulated in KK/Ay mice, in which glucose intolerance and insulin resistance were suppressed by oral LPS administration. The induction of the expression levels of insulin signaling-related factors in adipose tissues is thought to involve adiponectin, a cytokine synthesized uniquely by adipocytes. Therefore, we hypothesized that when the expression levels of insulin signaling-related factors in adipose tissues were increased by oral LPS administration, adiponectin expression in adipose tissues would be also induced. The adiponectin gene expression and protein levels in adipose tissues were measured. The results show that adiponectin mRNA expression was significantly elevated in the LPS (+) group compared with that in the LPS (−) group (Figure 6a). In addition, the protein level of adiponectin was also significantly elevated in the LPS (+) group compared with that in the LPS (−) group (Figure 6b). Based on these results, we hypothesized that oral LPS administration induces adiponectin expression and upregulates the expression levels of insulin signaling-related factors in adipose tissues. Further investigations on adiponectin showed that the mRNA expression levels of adiponectin receptors (Adipor1 and Adipor2), which are located on the reaction pathway of adiponectin, were significantly increased in the LPS (+) group compared with that in the LPS (−) group (Figure 6c,d). Adiponectin directly induces increased Glut4 expression; however, whether it directly induces the expression levels of Ir, Irs1, and Akt2 is unclear. Therefore, to investigate whether adiponectin directly induces an increase in the expression levels of insulin signaling-related factors, we stimulated 3T3-L1 adipocytes in vitro with adiponectin (Figure 7a). The results showed that the mRNA expression of Glut4 tended to increase, and the expression levels of Ir, Irs1, and Akt2 mRNAs in 3T3-L1 adipocytes significantly increased upon adiponectin stimulation (Figure 7b–e). Thus, the upregulation of Glut4, Ir, Irs1, and Akt2 observed in the adipose tissues of KK/Ay mice orally treated with LPS may be due to adiponectin induction by LPS. Based on these findings, we speculated that oral LPS administration induces the expression of adiponectin in adipose tissues and that adiponectin directly induces the upregulation of insulin signaling-related factors in adipose tissues by oral LPS administration. Enteral LPS is responsible for the onset of obesity-related type 2 diabetes mellitus [15,16,17,18]. This perception is based on the fact that overeating and high-fat diets increase the amount of enteral LPS transferred into the blood [18,19]. In this study, glucose intolerance and insulin resistance are induced in a mouse model receiving continuous infusion of LPS using a subcutaneously implanted infusion pump [16]. However, previous reports have also demonstrated that intestinal LPS is incorporated into chylomicrons and transferred into blood and that chylomicron LPS is barely involved in disease induction [20,21,22]. Based on the reports, evidence is insufficient to support the hypothesis that LPS is the cause of type 2 diabetes mellitus. In this study, oral LPS administration suppressed the onset of type 2 diabetes mellitus in KK/Ay mice by increasing the expression levels of insulin signaling-related factors in adipose tissues. In our previous study, oral LPS administration to ApoE KO mice fed a high-fat diet and P8 (SAMP8), a mouse model of accelerated aging, reduced insulin resistance and AUC during a glucose tolerance test. This effect was observed at higher oral LPS doses (1 mg > 0.3 mg/kg/day) [11,12]. Based on these results, the LPS dose to be given orally in this study was set at 1 mg/kg/day. KK/Ay mice were used as experimental animals in this study. These mice were developed by crossing KK mice with C57BL/6-Ay mice carrying the Agouti gene (Ay) [23,24]. They exhibit hyperglycemia, high HbA1c levels, insulin resistance, and impaired glucose tolerance, so they are widely used as a standard mouse model of type 2 diabetes mellitus to investigate substances that are beneficial for type 2 diabetes mellitus and analyze the mechanism of action of type 2 diabetes mellitus [13,14]. Therefore, we determined that the KK/Ay mouse model was appropriate for this study to clarify the effects of oral LPS administration on type 2 diabetes mellitus. The initial state of KK/Ay mice was compared with that of naïve C57BL/6 mice, which were used as the non-type 2 diabetes mellitus model. At the beginning of the study, measurements of OGTT and blood parameters showed that KK/Ay mice had more advanced glucose tolerance and insulin resistance than C57BL/6 mice (Figure 1). Most of the studies using KK/Ay mice have concluded that KK/Ay mice had type 2 diabetes mellitus based on these results [25,26,27]. Therefore, we can say that KK/Ay mice had type 2 diabetes mellitus at the beginning of this study. The results of OGTT and measurements of blood parameters performed after 8 weeks of oral LPS administration were consistent with previous results from Apo E KO mice and SAMP8 [11,12]. Oral LPS administration led to a significant increase in the AUC of OGTT, fasting blood glucose, HbA1c level, and insulin resistance (Figure 2). These results suggest that oral LPS administration has an ameliorating or inhibitory effect on KK/Ay mice with type 2 diabetes mellitus. In this study, the effect of oral LPS administration on type 2 diabetes mellitus was further verified by comparing OGTT and blood parameters before and after oral LPS administration (Figure 3). The results were novel in that oral LPS administration has an inhibitory effect on type 2 diabetes mellitus. On the contrary, in a previous study, we reported that oral LPS administration to pre-diabetic (type 2) humans reduced fasting blood glucose and HbA1c levels compared with those before oral LPS administration, which are slightly different from the results of the present study [28]. However, in this previous study, LPS was orally administered in combination with Salacia tea, which has hypoglycemic effects. The oral LPS administration method was different from the method employed in the present study, in which only LPS was administered orally. This report also indicates that oral LPS administration enhanced the hypoglycemic effect of Salacia tea. Thus, LPS, when administered orally alone, has an inhibitory effect on type 2 diabetes mellitus; however, when taken in combination with other active ingredients or foods, it appeared to have an ameliorating effect on type 2 diabetes mellitus. Many studies have shown that the adipose tissue is one of the key tissues involved in the suppression of type 2 diabetes mellitus [29,30,31,32,33,34,35,36]. The mRNA expression levels of insulin signaling-related factors such as Ir, Irs1, Akt, and Glut4 declined in adipose tissues in the case of type 2 diabetes mellitus [31,34,36]. Furthermore, mice with adipose tissue-specific knockout of Glut4 mRNA have abnormal glucose tolerance and insulin resistance, even though the expression levels of insulin signaling-related factors in other tissues were comparable to those of wild-type healthy mice [37]. A study reported that glucose intolerance was also observed in mice with adipose tissue-specific knockout of Ir [38]. Conversely, glucose intolerance and insulin resistance were suppressed in mice with adipose tissue-specific enhanced expression of Glut4 [39,40]. These studies have suggested that increased expression levels of insulin signaling-related factors in adipose tissues are crucial in the suppression of type 2 diabetes mellitus. This study revealed that gene and protein expression levels of insulin signaling-related factors were elevated in KK/Ay mice, whose glucose intolerance and insulin resistance were suppressed by oral LPS administration (Figure 5). Therefore, these results suggest that oral LPS administration increases the expression levels of insulin signaling-related factors in adipose tissues of KK/Ay mice and suppresses insulin resistance and glucose tolerance. The expression levels of insulin signaling-related factors in adipose tissues are thought to be regulated by cytokines produced by adipose tissues [32,41]. Among these factors, adiponectin is a cytokine produced specifically by adipocytes and induces the expression levels of insulin signaling-related factors in adipose tissues [42,43]. For example, in vitro, adiponectin directly induces an increase in Glut4 mRNA and protein expression in adipocytes [43]. In vivo, mice with higher expression levels of adiponectin have increased Glut4 expression levels in adipose tissues and suppressed glucose intolerance and insulin resistance [42]. In this study, the expression of adiponectin in adipose tissues of KK/Ay mice, which showed suppression of type 2 diabetes mellitus by oral LPS administration, was increased, and the adiponectin receptor, a molecule in the pathway for adiponectin to induce increased the gene expression levels of insulin signaling-related factors, was also upregulated (Figure 6). Furthermore, in vitro adiponectin stimulation studies on 3T3–L1 adipocytes confirmed that adiponectin directly induces an increase in Glut4 expression, consistent with previous reports (Figure 7). In addition, adiponectin was demonstrated to directly induce increased mRNA expression levels of Ir, Irs1, and Akt2 (Figure 7). These results suggest that adiponectin induced by oral LPS administration upregulates the expression levels of insulin signaling-related factors in adipose tissues (Figure 8). LPS injection not only induces type 2 diabetes mellitus by decreasing insulin signaling in adipose tissues but also induces increased expression levels of inflammatory cytokines such as interleukin 1 beta (IL-1β), IL-6, monocyte chemotactic protein 1 (Mcp1), and tumor necrosis factor alpha (TNFα) and induces weight changes, hepatotoxicity, and dyslipidemia. However, oral LPS administration did not induce the mRNA expression levels of IL-1b, IL-6, IL-12b, Mcp1, or TNFα in adipose tissues of KK/Ay mice (Supplementary Figure S1). In addition, it increased the expression levels of insulin signaling-related factors in adipose tissues and suppressed type 2 diabetes mellitus. No effects were observed on body weight, adipose tissue weight, and blood Alanine transaminase (ALT) and aspartate transaminase (AST) levels, markers of hepatotoxicity (Figure 4 and Figure S2). Furthermore, the results of dyslipidemia markers, such as blood triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL), were in agreement with our previous reports [11,12], showing a significant decrease in TC and LDL, consequently a suppressive effect on dyslipidemia (Supplementary Figure S2). Dyslipidemia is suppressed by adiponectin [44], and the results of this study revealed that this effect may be related to the increase in adiponectin levels in adipose tissues induced by oral LPS administration. Furthermore, the results corresponded with our initial proposition that oral LPS administration induces an entirely different effect on organisms compared with LPS injection; thus, we proposed that the conventional idea that LPS is involved in the development of type 2 diabetes mellitus should be revised. The pathway by which orally administered LPS affects adipose tissues is unknown. Lu et al. found that mice with small intestine-specific TLR4 knockout had impaired glucose tolerance [45], suggesting that orally administered LPS acts starting from TLR4 in the small intestine in vivo. Furthermore, repeated low-dose LPS stimulations mimicking oral LPS administration in vitro do not induce adiponectin expression in 3T3-L1 adipocytes [46]. Thus, we hypothesized that orally administered LPS induces adiponectin expression through an indirect effect on adipose tissues. As possible mediators involved in this signaling process, we found that the membrane-bound Csf1 of blood monocytes is one of the second signaling molecules that transmits the signal of orally administered LPS to distal tissues [10]. In the future, we would like to clarify the mechanism of the inhibitory effect of orally administered LPS on type 2 diabetes mellitus, including analysis of the second signal in the control of adipose tissues. Male KK/Ay mice, aged 7 weeks, were purchased from CLEA Japan (Tokyo, Japan), and male C57BL/6 mice, aged 7 weeks, were purchased from SLC Japan (Hamamatsu, Japan) and maintained in a temperature- and humidity-controlled room under a 12 h light/dark cycle with unrestricted access to food and water. A mouse diet (low-fat diet (LFD); 16.1 kJ/g, 4.3% w/w fat and 0.005% w/w cholesterol; D12450B) was purchased from Research Diets, Inc. (New Brunswick, NJ, USA). All mice were acclimated for 1 week while fed on an acclimation diet (CE-2; CLEA Japan, Tokyo, Japan) and drank sterilized distilled water. KK/Ay mice were assigned to the LPS (+) and LPS (−) groups and fed an LFD for 8 weeks. C57BL/6 mice were assigned to one group (control group) and fed an LFD for 8 weeks. Purified LPS derived from P. agglomerans (obtained from Macrophi Inc., Kagawa, Japan) was dissolved in sterilized distilled water and applied at 1 mg/kg body weight (BW)/day. The LPS dose was estimated from previous in vivo studies, in which the dose required to achieve preventive effects was determined (0.1 ± 1 mg/kg BW/day) [9,10,11,12]. The drinking water was replaced weekly, and the concentration of LPS was adjusted according to the average BW and amount of water consumption. We previously confirmed that LPS degradation in drinking water in a week was not significant [11,12]. At the end of the experiment, the KK/Ay mice were anesthetized under isoflurane vapor and euthanized by decapitation. Whole blood was collected, and a portion was stored at −80 °C until assays were performed. The rest was centrifuged (2000× g for 20 min at 4 °C), and the resulting plasma or serum (supernatant) was stored at −80 °C until assays were performed. Mesenteric, perinephric, and epididymal adipose tissues were collected, weighed, and stored at −80 °C until assays were performed. At the end of the experiment, the C57BL/6 mice were anesthetized under isoflurane vapor and euthanized by decapitation. Serum or plasma was collected in the same manner as with KK/Ay mice and stored at −80 °C until assays were performed. The animal experiments were reviewed and approved by the Animal Care and Use Committee of the Control of Innate Immunity (approval number: CIITRA 02–08, CIITRA 02–09). This experiment was conducted according to the Law for the Humane Treatment and Management of Animal Standards Relating to the Care and Management of Laboratory Animals and Relief of Pain (Ministry of the Environment, Tokyo, Japan), the Fundamental Guidelines for Proper Conduct of Animal Experiments and Related Activities in Academic Research Institutions (Ministry of Education, Culture, Sports, Science and Technology, Tokyo, Japan), and the Guidelines for Proper Conduct of Animal Experiments (Science Council of Japan). Mice were fasted overnight and subjected to an OGTT by oral glucose administration (gavage with 2 g of D-glucose/kg BW). Blood samples were collected from the tail vein, and blood glucose levels were monitored using an Accu-Chek Aviva blood glucose meter with Accu-Chek Aviva test strips (Roche Diagnostics K.K., Tokyo, Japan) at 0, 30, 60, 120, and 180 min after glucose loading. The AUC was calculated using the trapezoid rule. TG, TC, LDL, HDL, glucose, AST, and ALT levels in the serum or plasma were measured using commercial enzyme kits (Wako Pure Chemical, Osaka, Japan) according to the manufacturer’s protocol. Insulin was determined using ELISA kits (Shibayagi, Shibukawa, Japan). HbA1c was measured by Oriental Yeast CO., Ltd. (Tokyo, Japan). Epididymal adipose tissue adiponectin levels were measured using ELISA kits (Proteintech Group, Inc., Tokyo, Japan). RNA was extracted using the RNeasy Mini Kit (QIAGEN, Hilden, Germany), and cDNA was synthesized by reverse transcription using ReverTra Ace qPCR RT Master Mix (TOYOBO, Osaka, Japan), according to the manufacturer’s instructions. RT-PCR assay was conducted using 5 μL of cDNA as the template and 10 μL of Power SYBR Green PCR Master Mix (Thermo Fisher Scientific, Tokyo, Japan) on the Stratagene Mx 3005P QPCR System (Agilent Technologies, Santa Clara, CA, USA). The primers are listed in Table 1. Data were analyzed based on the 2−∆∆Ct method and normalized by GADPH expression. The qPCR amplification was performed with an activation step at 95 °C for 10 min, followed by 40 cycles at 95 °C for 15 s (denaturation) and 60 °C for 1 min (annealing), and a dissociation stage at 95 °C for 15 s, 60 °C for 30 s, and 95 °C for 15 s for each gene. Western blot analysis was performed using antibodies that specifically recognize proteins, including Glut4 and glyceraldehyde-3-phosphate dehydrogenase (Gapdh). The epididymal adipose tissue was homogenized, proteins were extracted, and 15 μg of extracted protein was loaded for sodium dodecyl sulfate–polyacrylamide gel electrophoresis immunoblot analysis. Protein bands were then transferred to polyvinylidene fluoride membranes (Bio-Rad Laboratories, Hercules, CA, USA). After blocking the nonspecific sites, the membrane was probed with primary antibodies, followed by a horseradish peroxidase-conjugated secondary antibody (Cell Signaling Technology, Inc., Danvers, MA, USA). Detection of antibody reactions was performed with ECL Western blotting Detection Reagents (Advansta, San Jose, CA, USA). Each band was normalized using the corresponding value of Gapdh as an internal control. The antibodies used were Gapdh (primary antibody (mouse monoclonal, Abcam, Cambridge, UK) 1:4000 dilution, secondary antibody (rabbit polyclonal, Abcam) 1:4000 dilution) and Glut4 (primary antibody (rabbit monoclonal, Cell signaling) 1:1000 dilution, secondary antibody (rabbit polyclonal, Abcam) 1:4000 dilution). Reaction times were overnight at 4 °C for primary antibodies and 1 h at room temperature for secondary antibodies. Mouse embryo 3T3-L1 cell line was obtained from the American Type Culture Collection (Manassas, VA, USA). 3T3-L1 pre-adipocytes were cultured in Dulbecco’s modified Eagle medium (Wako) supplemented with 10% fetal bovine serum (Sigma-Aldrich, St. Louis, MO, USA) at 37 °C in 5% CO2. AdipoInducer Reagent (Takara Bio, Otsu, Japan) was used for the differentiation of 3T3-L1 pre-adipocytes. For the differentiation of 3T3-L1 pre-adipocytes to mature adipocytes, 3T3-L1 pre-adipocytes were induced with differentiation media (DMEM with low glucose content supplemented with 10% fetal bovine serum, 2.5 μM dexamethasone (DEX), 0.5 mM 3-Isobutyl 1-methylxanthine (IBMX), and 10 μg/mL insulin (days 0–2). On day 2, the medium was replenished with maturation media (DMEM with high glucose content supplemented with 10% fetal bovine serum and 10 μg/mL insulin) and maintained at a 37 °C and 5% CO2 environment. This medium was changed every 2 days until day 8. At this time, the cells exhibited characteristics of mature adipocytes. At day 8, the medium was replenished, and 3T3-L1 mature adipocytes were treated with or without recombinant adiponectin (20 μg/mL, Prospec, Ness-Ziona, Israel). Samples were collected at 24 h to extract RNA after adiponectin treatment. All statistical analyses were performed using Ekuseru Toukei 2012 (SSRI, Tokyo, Japan). Data are reported as the mean ± standard error of the mean (SE). Statistical analysis was performed by Student’s t test. A difference was considered significant at p < 0.05. This study showed for the first time that oral LPS administration has an inhibitory effect on type 2 diabetes mellitus. In addition, the study showed that LPS increases the expression levels of insulin signaling-related factors in adipose tissues, and the upregulator of these factors is adiponectin in adipose tissues.

PMC10003110

Seokwoo Lee,Myounghoon Cho,Byungkyu Park,Kyungsook Han

Finding miRNA–RNA Network Biomarkers for Predicting Metastasis and Prognosis in Cancer

06-03-2023

miRNA–RNA interaction,patient-specific network,differential correlation,cancer,prognosis,metastasis

Despite remarkable progress in cancer research and treatment over the past decades, cancer ranks as a leading cause of death worldwide. In particular, metastasis is the major cause of cancer deaths. After an extensive analysis of miRNAs and RNAs in tumor tissue samples, we derived miRNA–RNA pairs with substantially different correlations from those in normal tissue samples. Using the differential miRNA–RNA correlations, we constructed models for predicting metastasis. A comparison of our model to other models with the same data sets of solid cancer showed that our model is much better than the others in both lymph node metastasis and distant metastasis. The miRNA–RNA correlations were also used in finding prognostic network biomarkers in cancer patients. The results of our study showed that miRNA–RNA correlations and networks consisting of miRNA–RNA pairs were more powerful in predicting prognosis as well as metastasis. Our method and the biomarkers obtained using the method will be useful for predicting metastasis and prognosis, which in turn will help select treatment options for cancer patients and targets of anti-cancer drug discovery.

Finding miRNA–RNA Network Biomarkers for Predicting Metastasis and Prognosis in Cancer Despite remarkable progress in cancer research and treatment over the past decades, cancer ranks as a leading cause of death worldwide. In particular, metastasis is the major cause of cancer deaths. After an extensive analysis of miRNAs and RNAs in tumor tissue samples, we derived miRNA–RNA pairs with substantially different correlations from those in normal tissue samples. Using the differential miRNA–RNA correlations, we constructed models for predicting metastasis. A comparison of our model to other models with the same data sets of solid cancer showed that our model is much better than the others in both lymph node metastasis and distant metastasis. The miRNA–RNA correlations were also used in finding prognostic network biomarkers in cancer patients. The results of our study showed that miRNA–RNA correlations and networks consisting of miRNA–RNA pairs were more powerful in predicting prognosis as well as metastasis. Our method and the biomarkers obtained using the method will be useful for predicting metastasis and prognosis, which in turn will help select treatment options for cancer patients and targets of anti-cancer drug discovery. The past two decades have seen remarkable progress in cancer research and treatment. However, despite significant progress, cancer still affects millions of people and ranks as a leading cause of death in the world [1]. In particular, metastasis is the major cause of cancer mortality, which accounts for about 90% of cancer deaths [2,3]. Cancer is a complex and heterogeneous disease with many possible genetic and environmental causes. Many treatments are effective only for patients with specific genetic or epigenetic alterations that help tumor cells develop [4,5]. Therefore, finding genetic changes specific to individual patients is essential to selecting effective treatments for cancer patients [6]. In our previous studies [7,8], we have developed a method for constructing microRNAs (miRNAs) mediated RNA interaction networks specific to individual cancer patients and for finding prognostic miRNA–RNA pairs or lncRNA–miRNA–mRNA triplets. A miRNA is a small non-coding RNA molecule of ~22 nucleotides, which often represses the expression of a gene by binding to the gene [9]. Until recently, interactions between miRNAs and their target genes have not received much attention from cancer research scientists. The so-called competitive endogenous RNA (ceRNA) hypothesis proposed by Salmena et al. [10] suggests that miRNAs mediate a regulatory relation between long non-coding RNAs (lncRNAs) and mRNAs which share similar miRNA response elements (MREs) to bind to the same miRNA. Results of several experimental studies have supported the hypothesis and demonstrated that many miRNAs are key regulators in the initiation and development of cancer [11,12,13,14,15]. The ceRNA hypothesis focused on competing relations between lncRNAs and mRNAs only, but competition for miRNA-binding occurs not only between lncRNAs and mRNAs but also between lncRNAs or between mRNAs. Furthermore, many pseudogenes also act as ceRNAs, thereby regulating other genes. Motivated by the increasing amount of miRNA expression data, several studies have been conducted recently to construct ceRNA networks in cancer. Zhu et al. [16], for example, constructed a network of lncRNA–miRNA–mRNA triplets from miRNA–lncRNA associations and miRNA–mRNA associations. Jiang et al. [17] constructed a ceRNA network after calculating the correlation coefficients of miRNA-mRNA and miRNA–lncRNA pairs. However, most ceRNA networks constructed so far are intended to represent a general relation of RNAs present in multiple cancer samples rather than for a patient-specific relation of RNAs. The biological functions of the regulatory miRNAs are very diverse depending on the target molecules regulated by miRNAs. In particular, cancer is a very heterogeneous disease, so RNA interactions mediated by miRNAs can vary in different cancer patients. As an extension of our previous studies [7,8], we have developed a new method of finding biomarkers based on differential miRNA–RNA correlations to predict metastasis and prognosis in cancer. Unlike conventional molecular biomarkers, network biomarkers can capture the associations or regulations of molecules involved in complex diseases such as cancer [18]. A network-based approach is one of the emerging promising strategies, and the transition from molecular biomarkers to network biomarkers will help select treatment options tailored to individual patients. The rest of this paper presents our approach to deriving miRNA–RNA correlations specific to cancer patients and finding biomarkers for predicting metastasis and prognosis. Table 1 shows the number of tumor samples of each type and normal samples in 10 cancer data sets. In most cancer data sets, there were many fewer tumor samples with distant metastasis than tumor samples with lymph node metastasis. The RNAs of 4 biotypes (miRNAs, lncRNAs, mRNAs, and pseudogenes) obtained after removing those with low-expressions are shown in Table 2. The number of miRNA–RNA pairs left after each filtering process is shown in Table 3. The correlations of the miRNA–RNA pairs were used in our study to predict metastasis and prognosis. While our method uses PCCs of miRNA–RNA pairs as features, most learning-based methods for predicting metastasis use gene expressions as features. We compared the performance of prediction using three different types of features: PCCs of miRNA–RNA pairs, expressions of genes involved in miRNA–RNA pairs, and expressions of 191 metastasis-predictive genes found by Zhou et al. [19]. For a fair comparison, three methods with different features were evaluated in the same way. We partitioned the data sets randomly into training and test data sets with a ratio of 7:3. We used the training data set to optimize the hyperparameters of each model using a grid search with 5-fold cross-validation. We repeated the whole process of the data partition, training, and testing 10 times for the evaluation of the methods. Table 4 shows the average area under the curve (AUC) values of the three methods with independent data sets, which were not used in training the methods. Our method, which used PCCs of miRNA–RNA pairs, outperformed the other methods in all 10 cancer types. Figure 1 compares the average ROC curves of the three methods with independent data sets of COAD. It is interesting to note that the 191 metastasis-predictive genes were not predictive of prognosis in both distant metastasis and lymph node metastasis. The results demonstrate that PCCs of miRNA–RNA interactions are more powerful than gene expressions in predicting lymph node metastasis and distant metastasis. Detailed results of 5-fold cross-validation and independent testing of the three methods are available in Appendix A. We performed the univariate Cox regression analysis with respect to values of miRNA–RNA pairs to explore the overall survival of patients. Table 5 shows the top miRNA–RNA pairs with the lowest p-value of the log–rank test in each type of cancer. As shown in the table, several lncRNAs and pseudogenes are included in the top miRNA–RNA pairs, which corroborates the assertion that miRNAs play an important role in cancer through the interaction with lncRNAs and pseudogenes as well as with mRNAs [20,21]. If the higher of a miRNA–RNA pair is associated with a longer survival time, its hazard ratio (HR) < 1. In contrast, HR of a miRNA–RNA pair > 1 if the higher of the pair is associated with a shorter survival time. Figure 2 shows Kaplan–Meier plots and risk tables for the top miRNA–RNA pairs in LUAD and PRAD. In the Kaplan–Meier plots, the red line represents a group of patients with higher than the threshold value. In contrast, the blue line represents a group of patients with lower than the threshold value. The risk table below the Kaplan–Meier plot shows the number of patients at risk at a specific time point. We examined how many of the miRNA–RNA pairs with an adjusted p-value < 0.01 in the log–rank test (available in Appendix B) are supported by existing experimental results or previously predicted using computational methods. For this comparison, we extracted miRNA–RNA interactions in humans from the RNAInter database [22], which provides a comprehensive RNA interactome resource, including miRNA–target RNA interactions. Among the 2322 miRNA–RNA pairs of Appendix B, 53 pairs were found as experimentally validated miRNA–RNA pairs in RNAInter, and 90 pairs were found as previously predicted pairs in RNAInter. Except the 143 pairs (53 experimentally validated pairs and 90 predicted pairs), most miRNA–RNA pairs found in our study were not found in RNAInter. This implies that our approach can be useful in finding previously unknown miRNA–RNA interactions. With the miRNA–RNA pairs, we constructed star-shaped networks centered on common miRNAs, and selected the networks with C-index > 0.6, and adjusted p-value < 0.01. Two networks were found in BLCA, 14 in BRCA, 10 in COAD, 34 in ESCA, 1 in HNSC, 39 in LUAD, 1 in LUSC, 19 in PRAD, 2 in STAD, and 31 in THCA. The networks were named after their center nodes (e.g., network_MIR645 in LUAD, network_MIR4666A in PRAD). Table 6 shows the top prognostic network biomarkers with the lowest p-value in the log–rank test. MIR145, which is present in the potential prognostic network biomarker of BLCA, is known as a potential biomarker of cancer migration and invasion [23]. MIR645 in the potential prognostic network biomarker of LUAD, is known to promote the proliferation of non-small cell lung cancer cells by targeting TP53I11 gene [24]. MIR760 in the prognostic network biomarker of STAD has been reported to function as a tumor suppressor and inhibit cell migration in gastric cancer in several studies [25,26]. MIR138 found for THCA is known to act as a tumor suppressor by targeting several genes that are related to the proliferation and invasion of cancer cells [27]. Figure 3 shows the network biomarkers for LUAD and PRAD and the results of a survival analysis with the network biomarkers. The network_MIR645 (Figure 3A) consisting of 12 nodes (1 miRNA, 3 mRNAs, 6 lncRNAs, and 2 pseudogenes) revealed the lowest p-value in the log–rank test in LUAD. The network_MIR4666A (Figure 3B) includes 8 nodes (1 miRNA, 2 mRNAs, 2 lncRNAs, and 3 pseudogenes) showed the lowest p-value in the log–rank test and the highest C-index in PRAD. Detailed results of survival analysis with potential prognostic networks are available in Appendix C. As an example of miRNA–RNA correlation networks, Figure 4 shows a network composed of the miRNA–RNA pairs left after the Wilcoxon test in PRAD. The network consists of 5036 edges between 4121 nodes (125 miRNAs, 2330 mRNAs, 1169 lncRNAs, and 479 pseudogenes), and each edge represents PCC of a miRNA–RNA pair. In the network, 19 potential prognostic network biomarkers of PRAD are enclosed with rounded boxes. We compared the prognostic power of the networks with that of miRNA–RNA pairs and individual genes in the networks in terms of the p-value of the log–rank test and C-index. Survival analysis with individual genes was based on the expression of the genes. For a fair comparison, we carried out the log–rank test for individual genes with an optimal threshold determined by the cutp function, as in the networks and miRNA–RNA pairs. We then selected individual genes with an adjusted p-value of the log–rank test < 0.01. Figure 5 shows the distribution of p-values of the log–rank test and C-index values of networks of miRNA–RNA pairs, miRNA–RNA pairs, and individual genes. In most cancer types, the best p-values, and C-indices were observed in network biomarkers, followed by miRNA–RNA pairs. In particular, the superiority of network biomarkers was prominent in C-index. For more comparison, we selected the best network biomarker, miRNA–RNA pair, and gene and compared them in terms of the p-value of the log–rank test and C-index (Table 7). In all cancer types except BRCA and HNSC, networks of miRNA–RNA pairs were better than miRNA–RNA pairs and individual genes both in p-values and C-index. In BRCA and HNSC, miRNA–RNA pairs were the best, followed by networks of miRNA–RNA pairs. Overall, network biomarkers showed stronger prognostic power than miRNA–RNA pairs or individual genes in most cancer types. We further compared the predictive power of our network biomarkers with the prognostic genes in the Human Protein Atlas (HPA) [28], which provides the results of the log–rank test with TCGA data sets, the same data sets used in our study. Since HPA does not provide C-index values of prognostic genes, we computed them with TCGA data sets. Table 8 compares 10 network biomarkers with the prognostic genes of HPA in terms of the p-values of the log–rank test and C-indices. Both the network biomarkers and the prognostic genes of HPA are the ones with the highest C-index in each type of cancer. A comparison of prognostic markers in ESCA was not made because HPA does not provide prognostic genes in ESCA. As shown in the table, the network biomarkers found in our study were better than prognostic genes of HPA not only in p-values but also in C-indices, with the exception of the p-value in BRCA. In the Cancer Genome Atlas (TCGA), we selected the data sets which have at least 50 tumor samples with lymph node metastasis (LNM) and 10 normal samples. Distant metastasis (DM) was not included in the selection criteria due to the small number of samples with distant metastasis. Among the 33 cancer data sets of TCGA, 10 cancer data sets satisfied the selection criteria: urothelial bladder carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head-neck squamous cell carcinoma (HNSC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and thyroid carcinoma (THCA). The tumor samples in the selected cancer data sets were classified into four types based on the Tumor, Node, Metastasis (TNM) stage index in the clinical supplement data of TCGA. Samples with no metastasis (nonM): T stage of 1–4, N stage of 0, and M stage of 0 Samples with lymph node metastasis only (LNM_only): T stage of 1–4, N stage of 1–3, and M stage of 0 Samples with distant metastasis only (DM_only): T stage of 1–4, N stage of 0, and M stage of 1 Samples with both lymph node metastasis and distant metastasis (LNM&DM): T stage of 1–4, N stage of 1–3, and M stage of 1 We obtained RNA-seq gene expression data from the Genomic Data Commons (GDC) data portal [29]. After filtering out the genes with the average raw read counts , a total of 42,692 genes were left. Using the annotation file obtained from the Ensembl project [30], we classified the remaining genes into 4 biotypes: miRNAs, lncRNAs, mRNAs, and pseudogenes. There were 42,692 genes used (477 miRNAs, 13,731 lncRNAs, 18,937 mRNAs, and 9547 pseudogenes) across 10 types of cancer. We then normalized raw read counts of the genes into counts per million (CPM) values using the trimmed mean of M values (TMM) method [31] in the R package edgeR [32]. Our approach to predicting metastasis and prognosis is based on correlations of miRNAs and their target RNAs, which include mRNAs, lncRNAs, and pseudogenes. The correlations of miRNAs and their target RNAs were computed separately in each type of cancer. For every pair of miRNA and their target RNA in n normal samples, we computed the Pearson correlation coefficient (PCC) using Equation (1). In the equation, is the CPM value of miRNA X in sample i, and is the mean CPM value of miRNA X in n samples. Likewise, represents the CPM value of RNA Y in sample i, and is the mean CPM value of RNA Y in n samples. Our method for predicting metastasis is composed of two prediction models: one model for predicting lymph node metastasis () and another model for predicting distant metastasis (). In , LNM_only ∪ LNM&DM samples are positive, and nonM samples are negative. In , DM_only ∪ LNM&DM samples are positive, and nonM ∪ LNM_only samples are negative. In each of the positive and negative sets, miRNA–RNA pairs with < 0.4 were removed because their correlations are not strong enough to be used in predicting metastasis. Those miRNA–RNA pairs common to the positive and negative data sets were also removed. After adding a single tumor sample to the n normal samples, we recomputed and obtained by subtracting from . reflects the difference in miRNA–RNA correlations between the n normal samples and the single tumor sample. Using the values, we performed the Wilcoxon test [33] between positive and negative data sets, and selected the miRNA–RNA pairs with the p-value < 0.01 in the Wilcoxon test. The miRNA–RNA pairs left after the Wilcoxon test represent those miRNA–RNA pairs with significantly different correlations (i.e., of a miRNA–RNA pair) in cancer patients. Gene expressions observed in lymph node metastasis are often different from those in distant metastasis, so predicting both types of metastasis with a single model is difficult [34]. Thus, our method is composed of two prediction models: one model for predicting lymph node metastasis () and another model for predicting distant metastasis (). Both models use PCC values of miRNA–RNA pairs as features, but the dimension of feature vectors was reduced by performing the principal component analysis (PCA). The models are ensemble learners with two base learners: support vector machine (SVM) with the radial basis function (RBF) as a kernel and logistic regression (LR). Using LR as a secondary learner, we combined the base learners by stacking to improve predictive accuracy [35,36]. The data sets were randomly partitioned into training and test data sets with a ratio of 7:3. The training data set and the test data set are disjoint. The test data set was used in independent testing. Due to the randomness of the data partition and the small and imbalanced data sets, the whole process of the data partition, training, and testing was repeated 10 times when evaluating the models. The hyperparameters of SVMs and LRs were optimized with a grid search with 5-fold cross-validation of training data sets. The models take a patient sample as input. If both models classify the sample as negative, no metastasis is predicted for the patient. If the sample is classified as positive by but negative by , only lymph node metastasis is predicted for the patient. Similarly, if the sample is classified as negative by but positive by , only distant metastasis is predicted for the patient. If both models classify the sample as positive, both lymph node metastasis and distant metastasis are predicted for the patient (refer to Figure 6). The overall workflow of constructing the prediction models and running them is illustrated in Figure 6. Constructing the models involves data collection, classifying samples, deriving miRNA–RNA pairs, computing differential correlations of miRNA–RNA pairs, and training the models. We used the miRNA–RNA pairs derived for predicting metastasis in finding prognostic biomarkers. The workflow of finding prognostic biomarkers is illustrated in Figure 6. We derived two types of prognostic biomarkers: miRNA–RNA pair and subnetwork centered at a common miRNA of miRNA–RNA pairs. We carried out the univariate Cox regression analysis [37] with values of miRNA–RNA pairs and computed the concordance index (C-index) of every miRNA–RNA pair. The C-index for every pair in patient samples i and j is defined using Equation (3), where is an observed survival time of i and is a predicted score of i. could be predicted survival times, or hazards, etc. In this study, partial hazard values predicted with the Cox regression model were used as [38]. where = 1 if j is uncensored, and 0 otherwise. = 1 if , and 0 otherwise. The C-index ranges between 0 and 1, 1 being the best value. We also performed the log–rank test for each miRNA–RNA pair. When dividing patient samples into two groups (high group and low group), we used the cutp function in the R package survMisc [39]. The cutp function determines an optimal cut point for a continuous variable based on the statistical results of the Cox regression analysis. We adjusted the p-values of the log–rank test using the Benjamini–Hochberg procedure [40], and selected the miRNA–RNA pairs with an adjusted p-value < 0.01 as potential prognostic miRNA–RNA pairs. The miRNA–RNA pairs with an adjusted p-value < 0.01 were sorted in increasing order of p-values. Starting with the miRNA–RNA pair with the smallest p-value, we combined up to 15 miRNA–RNA pairs with common miRNAs. The combined miRNA–RNA pairs form star-shaped networks centered at common miRNAs. For every patient sample i, we computed the risk score of the star-shaped networks using Equation (4). In Equation (4), j denotes a miRNA–RNA pair in a network. represents the values of miRNA–RNA pair j in sample i. is the regression coefficient from the Cox regression analysis of miRNA–RNA pair j. The risk score was used in classifying patient samples into two groups, the high-risk group and the low-risk group. Again, the cutp function was used to determine an optimal threshold for classification. Finally, the networks with a C-index > 0.6 and adjusted p-value < 0.01 were selected as potential prognostic biomarkers. So far, many computational methods for predicting prognosis in cancer have focused on survival rates without considering metastasis. There are a few methods developed for predicting lymph node metastasis, but few attempts have been made to predict distant metastasis mainly due to the difficulty of the problem and the small number of publicly available samples with distant metastasis. We developed a new method for predicting both lymph node metastasis and distant metastasis using differential correlations of miRNAs and their target RNAs in cancer, which were derived from a large amount of RNA-seq data and clinical data. Testing our method on several types of cancer demonstrated that differential correlations of miRNAs and their target RNAs are much more powerful than gene expressions in predicting distant metastasis as well as lymph node metastasis. With the differential correlations of miRNAs and their target RNAs, we found network biomarkers for predicting the prognosis of cancer patients. The network biomarkers derived from metastasis analysis were more predictive of survival rates than correlations of individual miRNA–RNA pairs or gene expressions of individual genes. The results of our study showed that network biomarkers based on correlations of genes could be more powerful than typical molecular biomarkers of individual genes in predicting prognosis as well as metastasis. The method developed in this study, and its results will be useful in selecting treatment options for cancer patients and a target of anti-cancer drug discovery.

PMC10003111

Ivana Raffaele,Serena Silvestro,Emanuela Mazzon

MicroRNAs and MAPKs: Evidence of These Molecular Interactions in Alzheimer’s Disease

01-03-2023

microRNAs,MAPK,Alzheimer’s disease,neurodegeneration

Alzheimer’s disease (AD) is a neurodegenerative disorder known to be the leading cause of dementia worldwide. Many microRNAs (miRNAs) were found deregulated in the brain or blood of AD patients, suggesting a possible key role in different stages of neurodegeneration. In particular, mitogen-activated protein kinases (MAPK) signaling can be impaired by miRNA dysregulation during AD. Indeed, the aberrant MAPK pathway may facilitate the development of amyloid-beta (Aβ) and Tau pathology, oxidative stress, neuroinflammation, and brain cell death. The aim of this review was to describe the molecular interactions between miRNAs and MAPKs during AD pathogenesis by selecting evidence from experimental AD models. Publications ranging from 2010 to 2023 were considered, based on PubMed and Web of Science databases. According to obtained data, several miRNA deregulations may regulate MAPK signaling in different stages of AD and conversely. Moreover, overexpressing or silencing miRNAs involved in MAPK regulation was seen to improve cognitive deficits in AD animal models. In particular, miR-132 is of particular interest due to its neuroprotective functions by inhibiting Aβ and Tau depositions, as well as oxidative stress, through ERK/MAPK1 signaling modulation. However, further investigations are required to confirm and implement these promising results.

MicroRNAs and MAPKs: Evidence of These Molecular Interactions in Alzheimer’s Disease Alzheimer’s disease (AD) is a neurodegenerative disorder known to be the leading cause of dementia worldwide. Many microRNAs (miRNAs) were found deregulated in the brain or blood of AD patients, suggesting a possible key role in different stages of neurodegeneration. In particular, mitogen-activated protein kinases (MAPK) signaling can be impaired by miRNA dysregulation during AD. Indeed, the aberrant MAPK pathway may facilitate the development of amyloid-beta (Aβ) and Tau pathology, oxidative stress, neuroinflammation, and brain cell death. The aim of this review was to describe the molecular interactions between miRNAs and MAPKs during AD pathogenesis by selecting evidence from experimental AD models. Publications ranging from 2010 to 2023 were considered, based on PubMed and Web of Science databases. According to obtained data, several miRNA deregulations may regulate MAPK signaling in different stages of AD and conversely. Moreover, overexpressing or silencing miRNAs involved in MAPK regulation was seen to improve cognitive deficits in AD animal models. In particular, miR-132 is of particular interest due to its neuroprotective functions by inhibiting Aβ and Tau depositions, as well as oxidative stress, through ERK/MAPK1 signaling modulation. However, further investigations are required to confirm and implement these promising results. Alzheimer’s disease (AD), with more than 50 million people affected worldwide, is the most common form of dementia and poses a major public health burden for patients and their families [1]. This pathology manifests itself with memory loss and behavioral changes up to the loss of daily life activities that force the patient to become completely dependent on family or caregivers. Therefore, AD is a devastating and deadly disease and represents a major challenge for researchers [2]. The causes that induce AD are partially clear. However, genetics, environment, and lifestyle play an important role in AD pathogenesis, and certainly, aging remains the main risk factor. Extracellular deposition of amyloid-beta (Aβ) and neurofibrillary tangles (NFT) produced by hyperphosphorylated Tau protein (p-Tau), together with neuronal loss, are the hallmarks of this pathology [3,4]. The pathogenesis of AD depends on several factors, including apolipoprotein E (APOE) genetic variants, the APOE phenotype, and oxidative stress, which can promote damage to both DNA and RNA, including non-coding RNA (ncRNA) [5]. Among ncRNAs, microRNAs (miRNAs) are known to contribute to disease processes in AD [6,7]. Indeed, miRNAs are small ncRNAs of approximately 22 nucleotides that regulate messenger RNA (mRNA) expression, playing a crucial role in different biological processes [8]. The aberrant expression of specific miRNAs, such as miR-34a, miR-125b, and miR-155, has been previously associated with central nervous system (CNS) diseases [9,10,11,12,13]. In this regard, Prendecki et al. 2019 [5] highlighted that plasma levels of miR-107 and miR-650 in AD patients, quantified by quantitative PCR (qPCR), may be related to APOE genetic variants and clinical characteristics, including the age of onset and severity of dementia. Age of onset in AD patients, symptom severity, and APOE genetic variants may influence the regulation of APOE, miR-107, and miR-650 levels. The strongest relationship between APOE level and miRNA appears in patients with onset at 60–69 years of age and in patients with the APOE E3/E3 genotype. Thus, altered levels of plasma APOE, miR-107, and miR-650 may be a marker of the neurodegenerative process in the course of AD, associated with Aβ metabolism and disordered cell cycle [5]. According to several studies, many other miRNAs have the potential as biomarkers of disease since their deregulation has been found in the serum, plasma, and cerebrospinal fluid (CSF) of AD patients compared to healthy controls [14,15]. However, the effects of miRNA aberrant expression are still not entirely clear. MiRNAs’ dysregulations have been found in different neuropathological processes, including protein aggregation and inflammation [16,17,18]. Thus, several alterations may affect a number of molecular signaling pathways. In this context, recent data have reported that aberrant Mitogen-activated protein kinases (MAPKs) levels might be associated with cognitive dysfunction and could accelerate AD progression [19,20]. According to the literature, MAPKs may represent potential targets for AD. Indeed, their inhibition could prevent Aβ deposition, Tau hyperphosphorylation, neuronal apoptosis, and memory impairment [21]. The modulation of MAPK signaling by miRNA was previously evidenced, especially in cancer [22,23,24,25], but the interplay between miRNAs and MAPKs in neurodegenerative disease remains to be elucidated. Thus, exploring the possible effects of miRNA deregulation on MAPK signaling during AD would be an interesting chance in the diagnostic and therapeutic field. MAPKs are serine and threonine protein kinases expressed in both neuronal and non-neuronal cells of the mature CNS [26]. In response to several external stimuli, such as growth factors, glutamate and hormones, cellular stress, and pathogens [27], MAPKs mediate cell proliferation, differentiation, and survival [28]. Among the different MAPK enzymes, the most studied are extracellular signal-regulated kinases 1 and 2 (ERK1/2), ERK5, c-Jun amino-terminal kinase (JNK) 1 to 3, and p38 MAPK (α, β, γ, and δ) [29]. JNK and p38 MAPK are also known as stress-related protein kinases because they are strongly activated in several disease processes, including AD-associated β-amyloid neurodegeneration [28,30,31,32]. In this review, we provide an overview of evidence that evaluates the molecular interactions between miRNAs and MAPK pathways using in vitro and in vivo experimental AD models. In particular, the pathophysiology of AD will be illustrated, detailing the potential role of miRNAs and MAPKs in this condition. Furthermore, the biogenesis and structure of miRNAs and the role of MAPKs in AD will be mentioned. In order to select the manuscripts, we proceeded to search on PubMed and Web of Science using the following keywords “miRNAs” and “MAPK” or “map kinase” and “or “p38” or “jnk” or “ERK” and “Alzheimer’s disease”; publications ranging from 2010 to 2023 were selected. AD is a neurodegenerative disorder characterized by neuron loss and tissue damage, with progressive cognitive impairment [33]. The presence of amyloid plaque and NFT in different regions of the brain are considered the hallmarks of AD, as well as glia activation and endosome enlargement [34]. The extracellular accumulations of Aβ are responsible for triggering a complex of the pathological network that causes neuronal damage [35]. Aβ peptide is generated by the enzymatic proteolysis of the amyloid precursor protein (APP), a protein that physiologically has a key role in brain homeostasis [36]. In healthy subjects, APP is cleaved by an α-secretase and generates the soluble peptide APPα (sAPPα), a molecule involved in neuronal plasticity and survival and protection against cytotoxicity [37,38]. α-secretase-mediated APP processing represents the non-amyloidogenic pathway. However, Aβ peptide is produced following a β- and γ-secretase-mediated amyloidogenic pathway in AD subjects [39]. APP undergoes a first cleavage induced by the enzymatic cleavage of β-secretase 1 (BACE1), which generates the soluble peptide APPβ (sAPP-β) and a fragment consisting of 99 amino acids. sAPP-β is further cleaved by γ-secretase, generating a peptide of 40 amino acids and a peptide of 42, called Aβ1–40 and Aβ1–42, respectively [40,41]. The latter is more hydrophobic, amyloidogenic, and toxic [42,43]. After releasing in extracellular space, Aβ1–42 peptides form the “amyloid plaque” due to their higher propensity to aggregate compared to physiological products [44]. Of note, another key player in AD is Tau, a protein that stabilizes microtubules and promotes vesicular-mediated transport [45]. In physiological conditions, the Tau protein is in perfect balance between phosphorylated and dephosphorylated forms. In patients with AD, hyperphosphorylation leads to the formation of NFT in the cell body of neurons with consequent destabilization and neuronal death [46]. The presence of Aβ and Tau depositions have been associated with synaptic and neuron loss and, as a consequence, with the development of AD symptoms [4]. Therefore, Aβ and Tau interact with each other, promoting pathogenesis and neurodegeneration through different mechanisms that can involve MAPK signaling [47]. Moreover, several pieces of evidence proved the main role of oxidative stress in the early stages of AD by inducing modifications in the cerebral tissue before the formation of Aβ-plaques and NFT [48,49]. The brain is particularly predisposed to oxidative damage due to its high oxygen consumption, high lipid content, and low levels of antioxidant enzymes [48]. Reactive oxygen species (ROS), including peroxide oxygen (H2O2) and hydroxyl radicals, can induce cell death and senescence. It has been observed that the alteration in miRNA expression levels, induced as a response to ROS, can play a potential role in the pathogenesis of AD. Growing evidence has proven the role of neuroinflammation in the pathogenesis and progression of AD through the activation of microglia [50]. Indeed, neuroinflammation plays an important role in the onset and progression of neurodegeneration and neuronal loss in neurodegenerative diseases [51]. If prolonged over time, the inflammatory response can be deleterious because of the release of toxic substances by chronically activated microglia [52]. Neuroinflammation seems to play a critical role also in the dysregulation of mitochondrial and synaptic processes, which has been strongly correlated with AD pathogenesis [50,53]. However, the specific mechanisms of AD pathology are still not entirely clear. In terms of clinical manifestations, memory deficit is the most common symptom, although other important impairments involve language, visuospatial function, and executive function [44]. The loss of two or more cognitive domains is referred to as dementia [54]. Importantly, at present, there is no cure or treatment that can stop the progression of dementia. Despite the efforts to find potential targets, no medication has ever been approved following a clinical trial. The current drugs, which are acetylcholinesterase inhibitors and N methyl D aspartate receptor antagonists, can only slow the onset of the symptoms [55]. Indeed, AD is estimated to become one of the most devastating diseases of this century, in terms of costs and mortality, since it is the main cause of dementia worldwide [56]. Although AD usually occurs in a sporadic form in people > 65 years of age, a small percentage of patients develop earlier onset associated with mutations in different genes, including APP, PSEN2, and PSEN1 (encoding, respectively, amyloid precursor protein, presenilin-1, and presenilin-2) [57]. PSEN1 and PSEN2 are A proteases that regulate the functions of the γ-secretase enzyme, responsible for cutting the amyloid protein. Thus, mutations due to these genes cause the accumulation of Aβ. Instead, late-onset AD is mainly associated with a polymorphism in the APOE gene encoding APOE, a protein involved in lipid metabolism [58,59]. In particular, the APOE4 isoform may influence the pathogenesis of AD by promoting the conversion of Aβ into a fibrillar form and its deposition [60]. However, exploring other risk factors and/or biomarkers of AD could be helpful. In the last decade, researchers have highlighted the role of the intestinal microbiota in the pathogenesis of neurological and metabolic disorders [61,62,63]. The microbiota–gut–brain axis is a bidirectional communication system between the CNS and the gastrointestinal (GI) tract [64,65]. Natural bacteria living in the GI are involved in the modulation of immune responses and digestive processes, such as carbohydrate fermentation and vitamin synthesis [66]. On the other hand, intestinal dysbiosis could contribute to different stages of AD pathogenesis through the secretion of neuroactive molecules [67,68,69,70] and harmful metabolites, such as lipopolysaccharide (LPS). LPS is a bacterial endotoxin that triggers the release of pro-inflammatory cytokines and superoxide [71,72]. Furthermore, LPS has been shown to cause increased levels of APP and phosphorylated Tau in a PC12/THP-1 cell model [73]. In particular, gut-derived compounds can increase intestinal permeability, leading to the transport of harmful metabolites across the gut–brain axis to the brain. Thus, the gut microbiome seems to be involved in neurodegenerative diseases, including Parkinson’s disease and AD, but also in neuropsychiatric disorders such as depression and autistic spectrum disorders [69,74,75]. Previous studies demonstrated that the composition and diversity of the gut microbiota are altered in AD patients compared to cognitively normal controls [76]. However, evidence using AD animal models showed positive effects after treatment with antibiotics, probiotics, diet modification, or after fecal microbiota transplantation [63,77]. Thus, modulation of the gut microbiota could be a possible therapeutic and preventive intervention to alleviate symptoms or slow down the progression of AD [78,79,80]. In most cases, the first stages of pathology remain asymptomatic for many years, while the development of the disease depends on several risk factors, such as age and sex. Thus, the diagnosis of AD is complex and requires various analyses, including neurological and physical tests and above all, brain imaging [81]. The most accurate diagnosis is still the post-mortem histological examination, through which the characteristic lesions of AD can be identified [82]. Over recent decades, research has focused on the discovery of biomarkers that may promote both preclinical diagnosis and novel treatments for AD. Early identification of patients with AD could facilitate therapeutic intervention even before cognitive impairment. Indeed, the discovery of new molecular targets during the first stage of neurodegeneration may help to stop the pathogenesis of AD [83,84]. MiRNAs are small ncRNAs (~19–24 nucleotides), which typically lead to gene silencing by driving Argonaute (AGO) proteins to bind specific sites in the 3′UTR of mRNAs [85]. However, other target sites have been detected in the 5′UTR, in the coding sequence, and even in promoter regions. The miRNAs either block translation or degrade the target mRNA by process of “hetero-silencing”. The same miRNA can target different mRNAs; conversely, a single mRNA can be regulated by multiple miRNAs. The transcription of miRNAs takes place, especially by the work of RNA polymerase II, towards which they show a particular affinity thanks to the presence in the primary transcript of promoters that contain typical characteristics of RNA polymerase II [86]. The miRNAs originate from a long double-stranded transcript, the primary miRNA (pri-miRNA), which is recognized in the nucleus by the protein DGCR8 (Drosha’s partner). This protein is associated with Drosha, also called Ribonuclease III (RNase III), and directs its Drosha catalytic domain by cutting pri-miRNA and thus obtaining miRNA precursors (pre-miRNA) [87]. Pre-miRNAs are then carried to the cytoplasm by exportin-5, an export receptor which requires ras-related nuclear protein-Guanosine-5′-triphosphate (Ran-GTP) proteins for cargo binding. The nuclear export of pre-miRNAs is a crucial step in miRNA biogenesis. In particular, exportin-5 can recognize the double-stranded RNA of pre-miRNAs in a sequence-independent manner [88,89,90]. In the cytoplasm, pre-miRNA is further processed by RNase III endonuclease Dicer which removes the terminal loop, resulting in a mature RNA molecule of approximately 22 nucleotides called miRNA. Following cleavage, one RNA strand is degraded. The other strand is loaded, from the 5′ or 3′ end, into AGO protein to form ‘miRNA-induced silencing complex’ (miRISC), where mature miRNAs bind and regulate specific mRNAs. The name of mature miRNAs, 5p or 3p, depends on the directionality of the miRNA strand [91,92]. Post-transcriptional gene silencing can occur following different mechanisms depending on the complementarity between the miRNA and its mRNA target. One mechanism involves deadenylation by cap removal and exonucleolytic digestion of mRNA, a process that occurs when miRNAs bind perfectly complementary areas of their target mRNA. Instead, when miRNAs bind mRNA with imperfect complementarity, a translation block occurs, which can happen by repression of translation during the initial phase or during the elongation phase. Repression of translation by miRNAs can also occur, inducing premature ribosome detachment (Figure 1) [93]. However, in certain circumstances, miRNAs have also been reported to promote gene upregulation [94]. In addition, it has been revealed that miRNA abundance in the organism depends, at least in part, on their stability [95]. Indeed, the miRNAs secreted in extracellular fluids, such as blood, CSF, or saliva, may have potential as biomarkers for many diseases. MiRNA function is essential to promote development and biological processes, and their deregulation has been related to several pathological conditions [94]. In particular, these molecules are highly expressed in the CNS, which is involved in the development and homeostasis of the brain. Overall, miRNAs are essential for many biological functions within the neurons, including proliferation, apoptosis, and synaptic plasticity [96,97,98]. The aberrant expression of many miRNAs has been linked to impaired cognitive functions and memory loss in experimental models. The role of miRNAs in the neuropathogenesis of AD has been proved in several studies. However, further research is needed to also confirm in vitro and in vivo results in the human brain [99,100,101]. The dysfunction of miRNAs could affect AD progression by modulating neurodegeneration, neurotoxicity, and synaptic loss. Indeed, miRNA deregulation has been observed in the brain of AD patients compared to healthy controls, but their exact implication in AD pathogenesis is still unclear [102,103]. Of note, miRNA dysregulation could influence MAPK signaling during AD. Therefore, the use of miRNAs to regulate different genes involved in pathologies could be an interesting strategy to regulate neuronal homeostasis and allow neuronal circuits to respond adequately to environmental insults [104]. The miRNA’s ability to bind multiple mRNAs aroused interest as a potential therapeutic treatment. AD as a complex disorder could require a multi-targeted approach in order to inhibit different aspects of pathology. Growing data also suggest that miRNAs are critical regulators of pathophysiological processes [105,106]. However, the use of miRNAs could create potential problems due to their ability to modulate molecular pathways that could improve some pathological conditions but also have an influence on non-deregulated pathways [107]. Because they differ from conventional drugs, such as small molecule and protein drugs, which are also known to act primarily on protein targets, RNA-based therapies are considered to be the next generation of therapeutics [106,108]. First, RNA aptamers can produce pharmacological effects by blocking the activity of a particular protein target [109]. Second, to control a specific disease, antisense (asRNA), small interfering RNAs (siRNA), and miRNA can be created to specifically target functional mRNAs or ncRNAs [110]. Third, to treat a monogenic condition, guide RNAs (gRNAs) can be used to precisely alter the target sequences of a particular gene [111]. Currently, the mutual regulation between miRNAs and their target genes represents a challenge. Thus, in vivo studies on gene regulations mediated by miRNAs may have important implications for their clinical use [112]. Thus, RNA therapies have the potential to increase the number of therapeutic targets. At present, several pharmaceutical and biotech companies are working on possible therapeutics based on suppressing or re-establishing the concentration of specific miRNAs using, respectively, antagomiR (anti-miR) or miRNA mimics [113]. However, the use of miRNAs could increase significantly in subsequent years, which will contribute to the development of successful precision medicine and more personalized therapies. MAPKs are serine-threonine kinases that mediate cellular response to external stimuli through different transduction signals. MAPKs are ubiquitously expressed and evolutionarily conserved in eukaryotes [114,115]. The MAPK signaling pathway transduces signals through downstream phosphorylation of proteins from the membrane receptor to the cytoplasm and nucleus [116]. Activation of a MAPK cascade occurs in the form of consecutive phosphorylations, i.e., a Mitogen-Activated Protein Kinase Kinase Kinase (MAP3K) activates a Mitogen-Activated Protein Kinase (MEK), which then, in turn, activates a MAPK [114,115,117,118]. Phosphorylation events of MAPKs can be inactivated by MAPK phosphatases (MKPs) which dephosphorylate both phosphothreonine and phosphotyrosine residues present in MAPKs [117,119]. In mammals, three main groups of kinases have been characterized: ERK, JNK, and p38 MAPK. In general, ERK is activated by growth factors, while JNK and p38 are induced by cellular stress. Canonical activation of the ERK1 and ERK2 isoforms begins following the binding of a ligand to a receptor tyrosine kinase (RTK) present on the plasma membrane, followed by the activation of the small G protein, Ras. Next, Ras recruits and activates serine/threonine protein kinase Raf, a MAP3K, which activates MEK, which, in turn, phosphorylates both threonine and tyrosine residues within the TEY (Thr-Glu-Tyr) motif of MAPK and ERK1/2 [120,121]. Instead, p38 MAPK isoforms are activated by both stress and cytokines and play a key role in inflammatory responses [122,123]. In response to stress or cytokines, tumor necrosis factor receptor-associated factor (TRAF) 2/3/6 or Rho proteins activate a MAP3K, such as MEK kinase 1 (MEKK1), apoptosis signal-regulating kinase 1 (ASK1), or transforming growth factor-β-activated kinase 1 (TAK1). MAP3K, in turn, phosphorylates a MEK, MAP kinase kinase 3, or 6 (MKK3 or MKK6), which subsequently phosphorylates the TGY (Thr-Glu-Tyr) motif of the p38 MAPK isoforms (Figure 2) [124,125]. Thus, MAPKs are involved in many biological activities, including cell proliferation, differentiation, apoptosis, and survival [126,127,128,129,130]. The ERK/MAPK pathway sends developmental signals from upstream activators to downstream effectors, cytoplasmic and nuclear substrates, which also regulate several stages of neurodevelopment, such as neural induction, neural patterning, neurogenesis, and neurite outgrowth [131,132,133]. Therefore, due to the pleiotropic functions of the MAPK signaling cascade, its aberrant activations are known to be involved in numerous pathologies, including neurodegenerative diseases. Literature data suggest that ERK, JNK, and p38 MAPK are all implicated in AD, playing a role in various aspects of the disease, such as apoptosis, neuronal plasticity, neurotoxicity, and autophagy [134,135]. However, excessive ROS production occurs during early stage AD due to mitochondrial dysfunctions in neurons. It has been seen that MAPKs can be activated by oxidative stress in a number of different cell types [48,136]. Moreover, Aβ accumulation and Tau hyperphosphorylation, which affect neurons in AD, as well as neuroinflammation, have been associated with the MAPK cascade in several studies. ERK overactivation is known to increase Aβ production, while inhibition of the JNK pathway blocks c-Jun, caspase-2 (CASP-2), and caspase-3 (CASP-3) activation. In addition, p38 MAPK inhibition has shown neuroprotective effects against neuronal damage, suggesting its potential as a strategic treatment for AD [21,135,137,138]. Several pieces of evidence have proven that miRNA deregulation in AD may promote Aβ and Tau pathology by modulating the MAPK pathway [139,140]. On the other hand, some studies have reported that the aberrant activation of MAPKs led to miRNA dysregulation with consequent neuronal damage [141,142]. Thus, the mechanisms through which miRNAs and MAPKs modulate each other, contributing to AD development, are still not entirely clear. In this regard, miR-148-3p reduced expression levels have been associated with the elevation of p38 MAPK by targeting Phosphatase and tensin homolog (PTEN) in the AD mice model [143]. Among MAPKs, p38 MAPK is known to be involved in Tau phosphorylation [144]. Thus, Zeng et al. [143] suggested that miR-148a-3p downregulation may increase Tau phosphorylation via the PTEN/p38 MAPK pathway in vivo. The authors showed that miR-148-3p levels were decreased in the serum of AD patients, but also in amyloid precursor protein/presenilin-1 (APP/PS1) and SAMP8 (senescence-accelerated mouse prone 8) transgenic mice brain tissue. The APP/PS1 and the SAMP8 mice were characterized by pathological AD typical features, β-amyloid production and cognitive decline, respectively [145]. However, the therapeutic potential of miR-148a-3p was also assessed by injection of miR-148a-3p mimics or PTEN siRNA in the cortex and hippocampus of APP/PS1 mice. Interestingly, Zeng et al. also found that miR-148a-3p overexpression improved AD cognitive deficit and decreased p-Tau. This neuroprotective effect was also confirmed in vitro using the APPswe cell (SH-SY5Y cells transfected with the Swedish mutant form of human APP) model: the upregulation of miR-148a-3p reduced Aβ-induced injury by increasing cell viability and inhibiting Tau abnormal phosphorylation. Therefore, the data suggest the important role of miR-148a-3p in the progression of AD by indirect modulation of p38 MAPK signaling and Tau phosphorylation. The molecular mechanism induced by miR-148-3p could be used to ameliorate cognitive defects and neuronal degeneration [143]. Another significant deregulation is the overexpression of miR-342-3p, which has been identified in both post-mortem hippocampal samples from human AD patients and the murine AD model [146,147]. Fu et al. [148] proved that miR-342-3p upregulation exacerbated AD symptoms, as well as amyloid production and deposition in hippocampal tissues of triple transgenic AD (3xTg-AD) mice. This model is widely used to study AD since 3xTg-AD mice displayed both plaque and tangle pathology, as well as synaptic dysfunction, by expressing three dementia-related transgenes [149]. However, miR-342-3p inhibition with anti-miR improved cognitive deficit and decreased the Aβ-plaque burden in vivo, as revealed by immunohistochemical analysis. In accordance with the literature [140,150], Aβ stimulation increased JNK and ERK activation. It has been suggested that the miR-342-3p was acting as both target and modulator of Aβ-induced neuronal damage through JNK. However, miR-342-3p expression has been evaluated using different MAPK inhibitors after Aβ stimulation in HT22 cells. Only SP600125, a JNK inhibitor, could reverse miR-342-3p upregulation induced by Aβ exposure. Thus, Aβ might modulate miR-342-3p via the JNK pathway in vitro, but the increase in miR-342-3p levels could enhance JNK activation with a strong reduction of cellular vitality. In general, JNK is known to be involved in the regulation of apoptosis and survival signals in neurodegenerative diseases [151]. Therefore, data from this study confirm that hippocampal signal transduction derangement and neuronal apoptosis in AD result from the increased Aβ burden and chronic activation of the JNK cascade in a miR-342-3p-dependent manner. Consequently, intrahippocampal miR-342-3p inhibition could be a useful strategy to reduce Aβ plaques and improve learning and memory in AD patients [148]. According to another study, miR-125b, which is one of the most upregulated miRNAs in the brain of AD patients [152,153,154,155], interacted with MAPK signaling by inhibiting Dual Specificity Phosphatase 6 (DUSP6), also called MAPK phosphatase in vivo [156]. Thus, miR-125b overexpression led to enhanced phopho-p44/42-MAPK (p-ERK1/2) levels. Elevated p-ERK1/2 protein levels have been reported in the brain of both mice and humans with AD. Since ERK1/2 is known to phosphorylate Tau proteins on multiple sites through the Cyclin-dependent kinase 5 and its regulatory subunit p35 (cdk5/p35), the overactivation of these kinases may promote Tau pathology in AD. Based on the results, miR-125b overexpression exerted neurotoxic and pro-apoptotic effects, increasing memory and learning impairment, as shown in two behavioral assays of C57BL/6 wild-type (WT) mice. This suggests that the miR-125b/ERK axis may also lead to cognitive deterioration of cognitive functions in human patients with AD. The inhibition of miR-125b could be a new promising approach for AD management, but potential adverse side effects due to the reduction of miR-125b levels under baseline conditions should be investigated in future experiments [156]. The aberrant activation of ERK/MAPK was associated with Aβ pathology, as well as Tau phosphorylation, in other studies [150,157]. Growing evidence agrees that the miR-132/212 cluster is implicated in the neurophysiological process, including synaptic plasticity and memory formation [158,159,160]. Moreover, miR-132/212 was found to be downregulated in AD [161,162,163]. Hernandez-Rapp et al. [164] observed that the genetic deletion of the miR-132/212 cluster promoted amyloid aggregation and deposition in cortical and hippocampal tissues 3xTg-AD mice compared to the WT control, as well as the upregulation of ERK2 (MAPK1), Sirtuin 1 (Sirt1), and Tau proteins. In particular, MAPK1 was identified as a target of miR-132. These results were confirmed in vitro: the miR-132 overexpression caused the decrease of these genes’ expression in mouse Neuro2a cells expressing the Swedish mutant of APP and Δ9 mutant of PSEN1 (Neuro2a APPswe/Δ9) and human HEK293 cells expressing the Swedish mutant of APP (HEK293-APPswe), with the consequent reduction of Aβ. Thus, the loss of miR-132/212 enhanced Tau phosphorylation, Aβ pathology, and cognitive impairment. Interestingly, miR-132 was found to be downregulated in human post-mortem tissues of AD cases compared to non-dement controls. Therefore, the miR-132/212 network could control various mechanisms of AD pathogenesis by also regulating Tau and Aβ pathology through ERK signaling. Indeed, ERK has been suggested to act upstream of Aβ generation by regulating BACE1 [164]. Another study [165] confirmed the neuroprotective effects of miR-132 by negatively regulating BACE1 and ERK activity in APP/PS1 mice. The use of a miR-132 mimic was proposed as a potential strategy to ameliorate AD progression. The strong link between miR-132, ERK1/2, Aβ, and Tau pathology has been assessed in the hippocampus of AD mice but also in the human AD cortex. Consistently, miR-132 downregulation has been verified. However, the authors did not find a direct correlation between miR-132 and Tau with respect to the article mentioned above. MiR-132 has been suggested to affect Tau phosphorylation in an indirect manner by inhibiting 1,4,5-triphosphate 3-kinase B (ITPKB) and ERK1/2 activity. It has been suggested that miR-132 downregulation was both a cause and a consequence of AD pathology. Therefore, the use of miR-132 mimics could be an interesting strategy to mitigate the ongoing neurodegenerative process in AD patients. Indeed, Aβ and Tau levels were found to decrease after intracerebral ventricular (ICV) injection with miR-132 mimic in AD mice [165]. On the other hand, Nagaraj et al. [166] identified miR-483-5p as a possible blood-based biomarker because it was found to be upregulated in the plasma of AD patients and also from the first symptoms, so-called prodromal AD patients. Using an in silico approach, miR-132-3p and miR-483-5p were compared. MiRNA molecular targets involved in the neuroprotective mechanisms were identified and subsequently confirmed in vitro using HEK293 and SK-N-MC cellular-based models. miR-483-5p upregulation may protect against AD pathology since it decreases Tau phosphorylation by reducing ERK1 and MAPK1 mRNA levels. CRISPR/Cas9-mediated genomic deletion in neonatal fibroblasts supported miR-483-5p binding to ERK1. This could represent a novel target for AD, but further experimental research is needed to better understand the miR-483-5p/ERK1/Tau interaction [166]. Moreover, ERK signaling modulation was also associated with another miRNA called miR-126 [167]. The overexpression of miR-126 increased Aβ1-42 toxicity in Tg6799 mice, a familial model of AD, through the downregulation of ERK and growth factor/Phosphatidyl Inositol 3-Kinase/Protein kinase B (PI3K/AKT) signaling. According to Kim et al. [168], even a small increase in miR-126 expression might affect growth factor activities in both normal neurons and neurons with disease-associated mutations. It must be considered that ERK signaling is involved not only in Tau phosphorylation but also in neuronal functionality and aging [169,170,171]. The inhibition of miR-126 has been associated with neuroprotective effects without compromising normal cell functions. Thus, miR-126 dysregulation has been suggested as a potential promoter of metabolic dysfunctions and toxicity during aging or neurodegenerative diseases by modulating PI3K and ERK signaling [168]. It has been suggested that miRNAs deregulated by oxidative stress may contribute to AD development by regulating protein ubiquitination and phosphorylation through the MAPK signaling pathway [172,173,174,175]. According to Shunjiang Xu et al. [172], several miRNAs were upregulated in primary cultured hippocampal neurons after stimulation with H2O2, including miR-708, miR-296, miR-200c, miR-377, and miR-1190. The significantly increased expression of miR-708 was related to the process of cell apoptosis in gene ontology enrichment. Bioinformatics analysis revealed five target genes of miR-708 (Map3k13, Kras, Rap1b, Nras, and Csf1) that were predicted to affect MAPK signaling. Given its role in cell differentiation, synaptic plasticity, and learning, it was suggested that the deregulation of MAPK induced by miR-708 might contribute, at least in part, to synaptic loss during AD progression [172]. Using the same in vitro model, Zhang (2014) [173] showed other neuronal miRNAs that were modulated by oxidative stress in primary hippocampal neurons as well as the hippocampus of senescence-accelerated mice (SAM), SAMP8 and SAMP10 mice, respectively. These mice strains are widely used as models of AD, differing for some age-related pathological features such as memory and learning impairment or neurodegeneration. In this case, microarray results have proved that miR-329, miR-193b, miR-20a, miR-296, and miR-130b were upregulated after H2O2 stimulation. The authors suggested a correlation between miRNAs altered levels and the downregulation of neuronal genes in the AD brain. Indeed, enrichment analysis showed that miRNA upregulation could interfere with several biological processes, including cell growth or apoptosis. However, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of pathway enrichment revealed that miRNA alteration induced by oxidative stress could mainly impair the MAPK pathway, leading to synaptic loss and neuron death during AD. In this context, miR-20a is of particular interest: it could be involved in brain development by targeting markers such as Mitogen-activated protein kinase kinase kinase 12 (MAP3K12), influencing aging. In both studies, KEGG enrichment analysis provided that MAPK signaling was one of the main pathways to be impaired by oxidative stress-induced miRNAs. However, these results suggested that ROS production led to the dysregulation of both miRNAs and MAPK pathways, contributing to the pathology of AD [173]. Interestingly, miR-34c has been identified to be dysregulated in the hippocampus, plasma, and cerebrospinal fluid of patients with AD [176]. In this context, Shi et al. [175] investigated the expression patterns of miR-34c in oxidative–stressed hippocampal neurons and SAMP8 mice. The results showed that miR-34c was overexpressed in neurons treated with H2O2 or Aβ1–42, as well as in cortical and hippocampal regions of SAMP8 mice with aging. ROS production promoted JNK phosphorylation, which stimulated p53 protein accumulation and activation in vitro. It is well known that p53 activation leads to neuron loss during AD and that miR-34c is upregulated after p53 activation [177,178,179]. Consistently, miR-34c inhibition promoted cognitive decline and memory function by reducing Aβ-induced synaptic damage in SAMP8 mice. Thus, miR-34c was upregulated through the ROS-JNK-p53 pathway in the development of AD [175]. Other studies, suggested that several miRNAs can modulate oxidative stress by targeting different genes [180,181]. A study revealed that miR-132 could decrease oxidative stress and improve cognitive functions by targeting MAPK1 in AD rat models obtained after ICV injection with Aβ25–35 [174]. The overexpression of miR-132 was reported to reduce Nitric oxide synthase (iNOS) levels. Indeed, miR-132 expression was decreased in the hippocampus of rats with AD, while MAPK1 was upregulated as well as iNOS. It has been demonstrated that miR-132 overexpression or MAPK1 silencing decreased ROS and iNOS expression but upregulated superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) levels in the serum of AD rats. Thus, miR-132 could stimulate the antioxidant system and reduce the apoptosis rate by inactivating the MAPK pathway. The inhibition of MAPK1 interfered with p38 MAPK signaling, which has been associated with neuron apoptosis as a response to excessive ROS production. Indeed, p38 MAPK is known to play a role in cell death through the activation of several proteins, including p53, c-Jun and c-Fos, Bax, and CASP-3. The authors suggested that miR-132 may ameliorate cognitive functions, exerting neuroprotective effects by decreased p38 MAPK activity, oxidative stress, and, consequently, cognitive decline. These results may be used to better understand the molecular mechanisms of miR-132 in the pathogenesis of AD in order to develop novel clinical strategies [174]. Different studies showed that miRNAs modulate the inflammatory response of activated microglia and neuronal apoptosis via targeting the MAPK signaling pathway [182,183]. Using both BV-2 and HT22 cells stimulated with Aβ as an in vitro AD model, Shang et al. [184] found that miR-590-5p mimic injection restored cell viability by improving proliferation. In addition, miR-590-5p levels were found to be reduced in the serum of both AD patients and APP/PS1 transgenic mice. miR-590-5p downregulation was suggested to contribute to the pathogenesis and progression of AD through the activation of the TNF Receptor Associated Factor 3 (TRAF3)/p38 MAPK pathway. According to the findings, the anti-apoptotic effect of miRNA might partly be due to the inhibition of Pellino-1 (PELI1), which increased TRAF3 but decreased the expression as well as the phosphorylation of p38 MAPK and ERK1/2. Consistently, activation of the p38 MAPK pathway has been previously found in the brain tissue of AD cases [184]. Several findings proved the importance of cell cycle suppression for neuronal survival [185,186,187]. Although mature neurons inhibit the cell cycle in physiological conditions, it could be induced again by neurotoxic agents such as Aβ42 [188]. Aβ42 can promote cell cycle re-entry by promoting aberrant MEK-ERK signaling in neurons [189]. This excessive activation leads not to cell mitosis but to DNA replication and apoptosis. Modi et al. [190] evidenced that the MEK-ERK hyperactivated pathway led to overexpression of CyclinD1 by reducing miR-34a levels in a Tap73-dependent manner. In silico analysis revealed that miR-34a targeted the 3′UTR region of the CyclinD1 gene, showing neuroprotective effects by suppressing cell cycle re-entry and apoptosis in vitro. Interestingly, miR-34a expression was altered in Aβ42-induced cortical neurons from rats or APP/PS1 mice. Furthermore, its expression was previously found to be higher during neuronal differentiation, supported by p53 family member Tap73. However, cell cycle re-entry has been mainly studied in Alzheimer’s since it may contribute to neuron loss in patients [191]. Based on the finding data, cell cycle-related neuronal apoptosis (CRNA) may be regulated by miR-34a and ERK signaling in neurons [190]. In another study, miR-326 was found to reduce apoptosis by inactivating the JNK signaling pathway via Vav Guanine Nucleotide Exchange Factor 1 (VAV1) in the APPswe/PS1 double transgenic mice model of AD. The authors provided that miR-326 ameliorated AD progression and enhanced cell viability since miR-326 overexpression or/and JNK inhibition decreased Aβ1–40 and Aβ1–42 contents in brain tissues of AD mice. These results suggested that miR-326 could reduce Aβ deposition and Tau phosphorylation by inhibiting the JNK signaling pathway. Indeed, miR-326 mimic lentiviral vector or/and SP600126 injections improved cognitive deficit in AD mice compared to WT control, as revealed by the Morris water maze test. All findings have been predicted by bioinformatics analysis and subsequently confirmed experimentally [192]. According to different studies, miR-155 exerts pro-inflammatory activity by modulating certain components of the innate immune system [193,194]. MiR-155 has been associated with neuroinflammation, which occurs in the early stages of AD. Indeed, Guedes et al. showed that the c-Jun transcription factor (c-Jun) could regulate neuroinflammation by increasing miR-155 expression before extracellular Aβ deposition in vivo. Aβ production, has been associated with JNK activation and, as a consequence, with the downstream effector c-Jun. However, miR-155 upregulation induced by intracellular Aβ peptides was associated with glial cell activation and higher levels of cytokines in the hippocampal and cortical regions of 12-month-old 3xTg AD mice. The results were also confirmed in vitro by measuring miR-155 levels in Aβ-treated N9 microglia and astrocyte primary cultures. Thus, the authors proposed c-Jun silencing as a potential strategy to control AD pathogenesis and progression. Furthermore, modulation of miRNA expression in the brain by targeting glial cells with the aim of decreasing miR-155 levels could be an interesting strategy being explored in the context of AD [195]. Microglia have a central role in the maintenance of the CNS, but Aβ deposition can stimulate apoptosis in these cells [196]. Wan et al. demonstrated that miR-191-5p transfection in microglial cells reduced ERK1/2 and p38 MAPK activity by targeting the upstream MAP3K12 effector, which has been related to neuron stress response apoptosis and AD neurodegeneration. In particular, miR-191-5p overexpression was associated with BACE1 and Tau-5 (AD’s markers) downregulation, with a consequent decrease in the apoptosis rate in microglial cells. Indeed, miR-191-5p was found to be downregulated in hippocampal sections from APP/PS1 mice, suggesting that the deregulation of this miRNA may play a role in AD progression. However, miR-191-5p seems to alleviate microglial cell injury by targeting the MAP3K12/MAPK signaling pathway, but further experiments should be performed in vivo in order to validate the results seen in vitro [197]. The results are summarized in Table 1, which includes in vitro and in vivo evidence of miRNAs and MAPKs interaction in AD, as shown in Figure 3. Experimental studies have proven that miRNAs or MAPK signaling deregulation can contribute to AD progression by modulating Aβ and Tau pathology, oxidative stress, neuroinflammation, and neuron death. Moreover, the modulation of the MAPK pathway using miRNAs mimic injection or silencing may improve cognitive decline and neurodegeneration, as revealed in AD animal models. Thus, miRNAs are involved in MAPK signaling modulation, and the molecular interactions between miRNAs and the MAPKs pathway seem to have a potential for both diagnostics and therapeutics of AD. The molecular interactions between miRNAs and MAPKs during AD may provide new research insights for understanding AD pathology. This review summarizes a number of recent findings which provide promising results on the therapeutic side. Based on obtained data, it was found that miR-125b upregulation led to memory and learning impairment by increasing p-ERK levels. At the same time, miR-132 showed neuroprotective effects by influencing ERK/MAPK1 activity, with the consequent reduction of both Aβ and Tau pathology hallmarks, as well as oxidative stress in AD animal models. Additionally, several pieces of evidence suggest that interaction between miRNAs and the JNK pathway may contribute to neuron death in AD. Whereas miRNAs have a multi-targeting ability, the modulation of MAPK signaling by acting on miRNA expression seems to improve cognitive decline in AD animal models. Using bioinformatics technologies and in vivo strategies could facilitate the development of novel approaches in both diagnostics and therapeutic fields for AD. However, further investigations should be conducted to better investigate these molecular interactions in order to replicate and, possibly, translate them into clinical applications.

PMC10003116

Yashendra Sethi,Neil Patel,Nirja Kaka,Oroshay Kaiwan,Jill Kar,Arsalan Moinuddin,Ashish Goel,Hitesh Chopra,Simona Cavalu

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review

23-02-2023

precision medicine,cardiology,precision cardiology,hypertension,heart failure,myocardial infarction

Cardiac diseases form the lion’s share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced “omics”. These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the “omics”, involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review Cardiac diseases form the lion’s share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced “omics”. These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the “omics”, involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach. Over the past three decades, cardiovascular diseases (CVDs) have preponderated global disease burden––93% prevalence, 54% mortality, and 60% in disability-adjusted life years (DALY) [1,2,3]. This is further exacerbated by disparities in the inter- and intra-continental disease burden, costing USD 216 billion and USD 147 billion annually for healthcare and productivity loss, respectively [4,5,6]. The rectitude of medicine has always emphasized treating the patient rather than the disease. Today’s medicine is honing itself to be more precise and patient-centric. Precision medicine is an innovative clinical approach that uses individual genomic, environmental, and lifestyle information to guide medical management. It has already revolutionized oncology [7]; CVDs form their current epicenter owing to their heterogeneity and multi-causality, which leads to altered responses to treatment for each patient. The long-old treatment principles are succored by technological evolution in the “omics”—genomics, transcriptomics, epigenomics, metabolomics, proteomics, and microbiomics— which, together, help frame the position for future medicine [8]. “Omics” is aided by advanced “big data” analysis, which has helped in the development of in-depth clinical, biological, and molecular phenotyping, promoting better-integrated healthcare with early diagnosis, enhanced risk stratification, and disease management with the least possible side effects [9]. Most CVDs stem from a complex interplay of modifiable and non-modifiable factors which aggravate the set “omic” predisposition. In contemporary cardiology, most diagnostic criteria and therapeutic approaches rely on population-based studies, with less focus on approaches tailored to individualize patient treatment [10]. As such, a comprehensive analysis of phenotypes and the “omics” can help cluster patient groups sheathing disparities, simultaneously reinforcing patient-centric clinical care. Further, it will enhance patient quality of life (QOL) and help reduce complications via novel biomarkers, improved AI-assisted diagnostics, targeted therapeutics, and appropriate long-term risk assessment [11]. With technological advancements in data science and machine learning, the applicability of precision medicine in CVDs seems within reach, especially with the significant evolving literature in the pipeline over the past decade. As such, we aim to: 1. pool evolving clinically relevant information on precision medicine in cardiology, and 2. provide a comprehensive synthesis of the relevant literature to date. Thus, this will help with the evidence-based precise management of cardiac diseases and identification of possible challenges. The advent of precision medicine has the potential to revolutionize the future of cardiovascular disease (CVD) healthcare via its application through “omics” in cardiology (Figure 1). It empowers a physician to treat cardiac diseases on an individual basis—based on the patient’s unique profile. Recent times have seen a growing body of literature underlining the application of precision medicine in cardiology. Table 1 presents a compilation underlining the clinical significance of all “reviews” published over the past decade regarding the same, while Table 2, Table 3 and Table 4 present an omic-stratified and disease-specific compilation of the literature for myocardial infarction, hypertension, and heart failure, respectively. As such, precision medicine in cardiology promises to improve health and revolutionize the management previously manifested in oncology. The evolution of precision medicine in cardiology has been remarkable (Figure 2). Its applicability can have the best impact if enacted on the diseases with the highest impact (associated with the highest DALY), these include—myocardial infarction, hypertension, and heart failure. Myocardial infarction (MI) is the leading cause of death globally—16% of total deaths. Its pathogenesis is peculiar in terms of its heterogeneous causality and largely varied genetic predisposition. MI is a critical medical emergency, true to its scientific adage “Time is equal to Myocardium”. An opportune diagnosis with sensitive markers, optimal intervention, and the prevention of complications and recurrence is extremely consequential. Precision medicine may find its applications in all these areas (Table 2) and may guide research and drug development to add to the pharmacotherapeutic armamentarium for this disease [29,30]. The association between an individual’s metabolic profile and MI has been explored a lot recently. Svati Shah et al. demonstrated an independent association between peripheral blood metabolites and the presence of CAD (coronary artery disease). They showed that simple metabolites such as factor 4 (branched-chain amino acid metabolites) and factor 9 (urea cycle metabolites) can help diagnose CAD [48,50]. Many new metabolites have recently been associated with CAD, including but not limited to: medium-chain acylcarnitines, short-chain dicarboxylacylcarnitines, long-chain dicarboxylacylcarnitines, long-chain acylcarnitines, short-chain acylcarnitines, medium-chain acylcarnitines, ketone related, cholesterol, lipids, fatty acids, glucose, and branched-chain amino acids [49]. Another recent observational study by Tanzilli G et al. found that low serum albumin levels are associated with adverse events in STEMI patients [46]. Uchino Y et al. and Ijichi C et al. showed that supplementing patients with BCAAs (branch-chain amino acids) showed increased serum albumin levels [51,52]. The combination of one or more newer metabolic markers can aid the diagnosis for a certain subset of patients, personalizing their care and increasing the sensitivity of MI detection. Metabolomics can improve treatment options in addition to its predictive and diagnostic capabilities. Currently, the mainstay of acute coronary syndrome treatment is revascularization via emergency percutaneous coronary intervention (PCI). Tanzilli G et al. proposed ways to improve PCI by using early and prolonged glutathione infusions to blunt the inflammatory response via a chain of processes: 1. reduced NOX2 activation; 2. hsCRP generation; 3. TNF- levels; 4. cTpT release; 5. reduced neutrophil generation to protect myocardial cells; and 6. prevention of aberrant cardiac remodeling, allowing better left ventricular size and function post-PCI [46]. Advances in genomics are helping the knowledge gained to be incorporated into the treatment and diagnosis of MI. An RCT by Scott R et al. discovered six genes (CNR2, DPP4, GLP1R, SLC5A1, HTR2C, MCHR1) that could be potentially used to develop drugs to treat type 2 diabetes or obesity without incremental CVD risk [45]. At present, post-PCI, dual antiplatelet therapy (DAPT) is initiated to reduce the risk of thrombosis or MI. DAPT usually consists of aspirin and clopidogrel. However, patients with loss-of-function CYP2C19 mutation have elevated chances of ischemic events if treated with standard DAPT therapy [44]. Pereira N et al. showed that the genotype CYP2C19-guided selection of P2Y12 inhibitor was superior to standard treatment concerning thrombotic events and resulted in a lower incidence of bleeding. They also proposed that a genotype-guided P2Y12 inhibitor such as ticagrelor should be selected for such patients [43]. The development of biomarkers in precision medicine has been astounding and is still evolving. Mangion K et al. suggested the use of computational modeling to provide precise diagnostic care to patients and improve individual risk prediction. Computed biomechanical parameters such as contractility, stiffness, myofilament kinetics, strain, and stress provide information about LV function, thus determining the extent of cardiac damage and future prognosis [37]. Crea F et al. established biomarkers such as myeloperoxidase and hyaluronidase-2 to identify plaque erosion among ACS patients [35]. The CD44v6 splicing variant of the hyaluronan receptor was significantly higher in patients with plaque erosion than in plaque fissures, which can help detect silent myocardial infarctions. Adding to the evidence of the benefit of therapy individualization, Pasea L et al. concluded that the decision to prolong DAPT therapy should be assessed individually for each patient [38]. For assessment, prognostic models should look at demographics and behavior, cardiovascular history, non-cardiovascular history, biomarkers, and drugs. Tong G et al. explored the use of basic fibroblast growth factor (bFGF) in myocardial ischemia injury [33]. Oxidative stress plays a major role in myocardial injury, and bFGF can reduce oxidative stress by promoting the activation of NrF2 via the Akt/GSK3b/Fyn pathway, which reduces cardiomyocytes apoptosis and thus the infarct size to a larger extent, ultimately alleviating the heart injury. More studies are being conducted to study the cardioprotective effect of bFGF, which is certainly a novel preventive tool to treat MI. Further, Oni-Orisan A et al. found that epoxyeicosatrienoic acid (EET) elicits potent anti-inflammatory, vasodilatory, anti-apoptotic, pro-angiogenic, fibrinolytic, and smooth muscle cell anti-migratory effects with-in the cardiovascular system [41], and thus can be used in the treatment of acute MI. Wen Z et al. investigated the application of telmisartan-doped co-assembly nanofibers (TDCNfs), dual-ligand supramolecular nanofibers that synergistically counter-regulate RAS through targeted delivery, and presented it as an option for combined therapy against cardiac deterioration post-MI [32]. It reduces apoptosis, alleviates inflammatory response, and inhibits fibrosis to potentially mitigate post-MI outcomes [32]. Aside from MI, the treatment for myocardial infarction with no obstructive coronary arteries (MINOCA) also requires an investigation of cause to determine the patient-specific treatment [36]. Collectively, precision medicine helps to individualize the therapy by blending various diagnostic modalities such as ECG, cardiac enzymes, other biomarkers, echocardiography, coronary angiography, coronary vasomotion, and intravascular imaging techniques. Hypertension (HTN) is a major modifiable risk factor for cardiovascular morbidity and mortality. Globally, it forms a major share of NCD (Non-communicable diseases); about 1.28 billion adults aged 30–79 years have HTN [53]. Due to its insidious onset, the majority of HTN cases remain unidentified and run a silent but catastrophic course. Early detection and optimal control can considerably reduce the cardiovascular burden associated with it. The pathophysiology of hypertension includes an interplay between genetic, physiological, biochemical, and environmental factors, which vary amongst individuals [54]. Precision medicine in hypertension can specifically identify patient subgroups with distinct disease causation mechanisms and their differential responses to diverse antihypertensive treatments. A compilation of recent evidence for the application of PM in hypertension is listed in Table 3. Genetic polymorphisms and response to diuretics: Current evidence identifies maximum target polymorphisms in response to thiazide diuretics. As opposed to the findings of the GenHAT study, the homozygous carriers of ACE I/D polymorphisms, ACE II, showed a small reduction in blood pressure response to hydrochlorothiazide, compared to homozygous carriers of ACE DD alleles [72,75]. Another study reported the response to thiazide diuretic in African Americans with SNP rs7297610 CC located on chromosome 12q15 [76]. Other genetic association studies showed that PRKCAA allele carriers had a better blood pressure response than GG homozygote patients. Another study targeting the UMOD gene polymorphism showed differential BP response to loop diuretics in hypertensives. They divided patients into two groups: 1. UMOD group (AA genotype), which showed a good response to loop diuretics, and 2. “Low” UMOD group, which exhibited a lower BP response to loop diuretics [70]. Genetic polymorphisms and response to other antihypertensives: Blood pressure regulation in humans involves at least 70 genes and presents with a complex set of individual differences. The human beta (1)-adrenergic receptor (ADRB1) has two common functional polymorphisms (Ser49Gly and Gly389Arg), which are associated with varied responses to metoprolol in essential hypertension. Furthermore, 49Ser389Arg/49Ser389Arg and 49Ser389Arg/49Gly389Arg polymorphisms have been seen as good responders, whilst 49Ser389Gly/49Gly389Arg and 49Ser389Gly/49Ser389Gly polymorphisms have been seen to be non-responders [77]. ADRB1 polymorphisms further revealed that C allele homozygotes showed a better response to metoprolol than G allele carriers [78]. Another study reported a possible link between nephrin (NPNS1) gene variants and a good response to the angiotensin receptor antagonist, losartan, in hypertensive patients [79]. Other less commonly studied genetic polymorphisms include GRK4 polymorphisms, namely R65L, A142V, and A486V. Studies have revealed that homozygote double variants of 65 L and 142 V require more aggressive antihypertensive therapy than the homozygous single variants or heterozygous carriers to achieve a target mean arterial blood pressure [71]. Another study aimed at finding rare and common variants associated with hypertension identified 31 novel genetic regions—rare missense variants in RBM47, COL21A1, and RRAS [67]. These allelic variations can lay the foundation for newer drug targets. Furthermore, by using polygenic risk score (based on the total number of genetic loci required to be assessed to estimate the risk of developing a disease), five potential loci (PKD2L1, SLC12A2, CACNA1C, CACNB4, and CA7) have been reported as novel therapeutic targets for hypertensive therapy. More than 1000 hypertension-associated loci have now been identified, with drug-target genes expected to expand in the future [65]. Loganathan et al. identified other hypertension-associated loci and SNPs (Single Nucleotide Polymorphisms) such as RAAS signaling and Cytochrome P (CYP) genes, which govern individual and population differences in drug tolerance [61]. In 2018, the GWAS catalog found seven candidate genes with an established pathophysiological role in hypertension, namely ACE1, ACE2, ADRB1, ADRB2, MME, CACNA2D2, and UMOD [63]. Recently, newer drugs such as Rostafuroxin have disrupted the binding of mutant alpha-adducin and the ouabain-activated Na-K pump with the Src-SH2 domain, in rats as well as in human cell cultures, posing as potential antihypertensives [80]. Evidence also suggests that riboflavin, a co-factor for MTHFR, also has an antihypertensive effect via the MTHFR 677TT genotype-specific mechanism [81]. Another potential choice is aldosterone, which targets the epigenetically modified sodium channel epithelial 1α subunit (SCNN1A). It hypomethylates the histone protein (H3) at lysine 79 (H3K79) at subregions of the promoter in a subgroup of hypertensives [68]. The effect of metabolomic factors in hypertension is another limb to study for the precision medicine domain. The most commonly identified metabolomic factors include sex, gender, race, and plasma renin activity; their response to antihypertensives was studied. A growing body of literature found that hypertensive women have lower plasma renin activity as opposed to men, and thus were more responsive to diuretics and Calcium Channel Blockers (CCB) as compared to angiotensin-converting enzyme inhibitors (ACEI) and beta blockers [82]. Another study comparing renin profiling-guided (plasma renin activity) treatment to clinical judgment in uncontrolled hypertensive patients showed equal or better hypertension control while using the renin profile-guided treatment approach [83]. Adverse drug events following antihypertensive medications were more common in females, though a notable exception was aldosterone antagonists [56]. It has been shown that African Americans respond to diuretics and CCBs better than ACEIs, probably due to their RAAS genes and increased plasma level in conjunction with suppressed plasma renin activity. These factors are hypothesized to cause variations in drug responses, Additionally, the African race is predisposed to severe hypertension, courtesy of their enhanced vascular contractility and salt-retaining capacity [59]. Furthermore, a raised sympathetic tone amongst obese patients responds better to beta blockers [57]. Ongoing clinical trials are investigating biochemical pathways, pharmaco-metabolomics, and pharmacogenomics in antihypertensive drug responses. A recent experimental study by Bazzell et al., on hypertension transcriptomics, measured mRNA transcripts in the human urine supernatant to detect mineralocorticoid receptor activation and predict its response to mineralocorticoid receptor antagonists in hypertensive patients. The results of the RNA sequencing of urine extracellular vesicles match those of the human kidney. Alterations in mRNA in urine supernatant were associated with changes in human endocrine signaling (MR activation). These findings can aid in individualizing pharmaceutical therapy in patients with mineralocorticoid signaling abnormalities, such as resistant hypertension. These findings could be utilized to noninvasively discover possible indicators of abnormal renal and cardiorenal physiology [74]. In light of the current evidence available, it can be concluded that what we know about the pharmacogenomics of hypertension is only the tip of the iceberg, and finding more precise targets and therapies is imperative. Heart failure (HF) is one of the most challenging cardiovascular disorders to manage. Despite recent advances in symptom management and the possibility of halting disease progression, the structural and functional impairment associated with HF is irreversible. It is a disorder with heterogenous causality and a strong genetic predisposition. Thus, risk assessment, prevention, and early screening are key in its management. Precision medicine poses to fill the existing gap in preventive medical management and risk stratification (Table 4). The relevance of common genetic variation in the susceptibility to and heritability of HF has recently been investigated through large-scale genome-wide techniques. F Dominguez found that DCM (dilated cardiomyopathy) caused by mutations in BAG3 has high penetrance in carriers >40 years of age and increases the risk of progressive heart failure [103]. Shah S et al. found that loci KLHL3 and SYNPOL2–AGAP5 are implicated in HF, and also BAG3 and CDKN1A are associated with LV systolic dysfunction [104]. Maurer, MS et al., documented that tafamidis reduced death and hospitalizations associated with cardiovascular events in patients with transthyretin-associated cardiomyopathy [85]. Dumeny et al. found that NR3C2, which codes the target protein of spironolactone, or CYP11B2, which is involved in aldosterone synthesis, was associated with better spironolactone response in diastolic HF patients [84]. Glick D found that among older adults without HF with initially low cardiac troponin T(cTnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP), the long-term trajectory of both biomarkers predicts systolic dysfunction, incident HF, and CV death [93]. Pozsonyi et al. defined that copeptin predicted 5-year all-cause mortality in heart failure patients. Drum et al., found that plasma TB4 is elevated in women with HFpEF, which predicts mortality independent of clinical risk factors and NT-proBNP in women with HF [92]. Feng SD et al. found that β-endorphin (β-EP) and brain natriuretic peptide BNP have both high specificity and sensitivity to detecting early acute left heart failure and atrial fibrillation in patients [89]. Pellicori et al., investigated the effects of spironolactone on the serum markers of collagen metabolism and cardiovascular structure and function in people at risk of developing HF, as well as the potential interactions with a marker of fibrogenic activity, galectin-3 [88]. G Michael Felker found that Hs-cTnT was elevated in the majority of acute heart failure (AHF) patients. Baseline, peak, and peak change hs-cTnT were associated with worse outcomes, mainly 180-day cardiovascular mortality [91]. Shah et al. found that MR-proANP seems accurate in diagnosing acute decompensated heart failure (ADHF), whilst both mid-regional pro-atrial natriuretic peptide (MR-proANP) and mid-regional pro-adrenomedullin (MR-proADM) acclimatize prognosis [50]. Sjoukje I Lok found that growth differentiation factor 15 (GDF) levels are increased in patients with HF and correlate with the extent of myocardial fibrosis, hence they are used as a biomarker for cardiac remodeling [95]. Natalia Lopez-Andrès et al. found that increased galectin-3 (Gal-3) and N-terminal propeptide III procollagen (PIIINP), and low metallic metalloproteinase-1 (MMP-1) are associated with adverse long-term heart failure outcomes [96]. Julio Núñez et al. suggested that CA125 is a surrogate of fluid overload, hence it is potentially valuable for guiding decongestion therapy, and a CA125-guided diuretic strategy improved eGFR in patients with acute heart failure with renal dysfunction [87]. Hanna K Gaggin et al. found that the soluble suppression of tumorigenesis (sST2) measurement identifies patients with chronic heart failure in whom higher beta-blocker doses may be beneficial [94]. Metabolomics is the study of tiny, organic compounds within metabolic pathways. With the improvement of technology, nuclear magnetic resonance, gas chromatography, and mass spectrometry have enabled the discovery and analysis of enormous databases of metabolites implicated in heart failure. The molecular pathways implicated in cardiac failure show that a metabolic transition occurs in the failing myocardium. Metabolic profiles of patients with systolic heart failure have been developed by examining patient serum and breath. These profiles can be used clinically for diagnosis and prognosis in this population [105]. Du Z et al. suggested that 3-hydroxybutyrate, acetone, and succinate were elevated in patients with HFrEF and can predict outcomes in patients with HF [99]. Additionally, Hunter WG et al. found that levels of metabolites in medium- and long-chain acylcarnitines and ketone bodies are higher in patients with HFpEF compared to patients with HfrEF [98]. Wang Li et al. suggested that patients with HFrEF with ischemic causes had higher levels of lactate, alanine, creatinine, proline, isoleucine, and leucine in plasma than healthy subjects [100]. Desmoulin F et al. found that an increased ratio of plasma lactate to total cholesterol is a significant predictor of 30-day mortality in patients with acute decompensated HF (ADHF) [101]. Ahmad T et al. found that increased circulating long-chain acylcarnitine metabolite levels in patients with chronic HF were associated with adverse clinical outcomes [106]. Treating patients with end-stage HF with long-term mechanical circulatory support resulted in significantly decreased circulating long-chain acylcarnitine levels, suggesting that levels of long-chain acylcarnitine can be used to prognosticate HF outcomes. Olivotto I et al. found that treatment with mavacamten, a small molecule modulator of β-cardiac myosin, improved exercise capacity, LVOT obstruction, NYHA functional class, and health status in patients with obstructive hypertrophic cardiomyopathy [97]. W H Wilson Tang et al. suggested that high trimethylamine N-oxide (TMAO) levels were observed in patients with HF, and elevated TMAO levels portended higher long-term mortality risk [102]. The genetic basis of aortic diseases has long been known. Twenty percent of patients with thoracic aortic aneurysms and aortic dissection either have a family history or are associated with a syndrome such as Marfan syndrome, vascular Ehlers–Danlos syndrome, and Loeys–Dietz syndrome. Mutations of ACTA2, MYLK, and MYH11 have been found to be associated with aortic disease [107]. Furthermore, genetic variants of genes FBN1, SMAD3, and ACTA2 have also been shown to cause either syndromic or non-syndromic thoracic aortic aneurysm and dissection [108,109]. The recent updates have added evidence to support the role of pathogenic variants in COL3A1, FBN1, MYH11, SMAD3, TGFB2, TGFBR1, TGFBR2, MYLK, LOX, and PRKG1, predisposing to hereditary thoracic aortic disease. The above insight into the genes associated with aortic diseases can be added to the clinical database. Patients with clinical suspicion can be tested for genetic predisposition, and the results can be saved on their EHR (electronic health records) to help personalize their treatment [109,110]. The evolution in tools of artificial intelligence (AI) and machine learning models has made it possible to incorporate multimodal and multidimensional omics, which promise enhanced diagnosis and treatment modalities for tomorrow. AI has the potential to usher in the next medical revolution and enhance precision medicine to stratify patients according to their phenotypic characteristics. The incorporation of AI into laboratory medicine and diagnostics can aid in better performing screening and confirmatory tests. AI can be used to generate insights by integrating powerful computing and analysis, thus allowing the system to think, learn and empower clinical decision-making with augmented intelligence [111]. The advances in artificial intelligence and data science have allowed for the automation of various critical thinking processes in medicine, including diagnosis, risk classification, and management, easing the workload of doctors and decreasing the possibility of making errors. It has many different uses in the workplace and the care of patients, from making doctors’ life easier to facilitating research. As a field that relies heavily on abstract reasoning and interpretation, cardiology is a natural fit for the introduction of AI. Clinical evaluation, imaging interpretation, diagnosis, prognosis, risk stratification, precision medicine, and therapy for various cardiac diseases have all benefited from the use of artificial intelligence. Clinical diagnostic accuracy, especially for pediatric cardiac diseases, has been bolstered by the application of neural networks and machine learning. AI has helped increase the diagnostic utility of imaging modalities such as cardiac magnetic resonance imaging, echocardiograms, computer tomography scans, and electrocardiograms. In pediatric cardiac surgeries, the introduction of AI-based prediction algorithms greatly improves post-operative outcomes and prognosis. Important clinical results can be used with suitable computer algorithms for risk classification and predicting treatment outcomes [112]. Although artificial intelligence has made medicine more precise and accurate, it still has a long way to go and has some serious limitations. The acceptability is hampered by difficulties such as a lack of adequate algorithms and their infancy, a lack of physician training, a concern of over-mechanization, and dread of missing the “human touch”. The generalizability of algorithms developed in standardized research environments employing high-quality data to heterogeneous real-world populations must be rigorously evaluated. Biases in training data, model overfitting, insufficient statistical correction for multiple testing, and limited accountability around the processes by which deep learning algorithms reach their outcome (“black box” systems) are just a few of the pitfalls of AI that can have serious consequences for the patients, and they necessitate careful consideration by researchers, clinicians, and regulatory bodies. Despite the challenges, we believe that AI will be the perfect assistant to clinicians in directing adult and pediatric cardiology in the future [112,113]. Table 5 underlines the clinical applicability of AI in Precision cardiology. The clinical trials help us judge and predict drug outcomes with the best representative samples that evolve with phases of clinical trials, but the genetic variations, environmental factors, and idiosyncrasies are still strong enough to cause a fair number of adverse events and treatment failures. The evolving approach of precision medicine advocates the individualization of therapy, directed by local regulations and guidelines based on novel markers and gene targets, which can help us define reasons for failure, thus evolving a better tailored patient-centric approach to curing diseases. Numerous examples of genetic diversity and DNA variants determining the response to a drug are already in common parlance and are continually used to modify treatment. For instance, warfarin, the most commonly prescribed anticoagulant medicine, has a narrow therapeutic window and has shown wide inter-individual variations [114,115]. Studies document around 10% to 50% variability in warfarin dose requirements per the patient genotype, notably SNPs in CYP2C9 (CYP2C9*2, CYP2C9*3) and VKORC1 (rs9923231) [115,116,117]. Additionally, genetic variants have been identified that show differences in the response to β-blockers (ADRB1, ADRB2, GRK5, GRK4); angiotensin-converting enzyme inhibitors (ACE, AGTR1); diuretics (ADD1, NPPA, NEDD4L); and Calcium Channel Blockers (CACNB2, CACNA1C) [26]. Further, clopidogrel, an antiplatelet medicine, is a P2Y12 inhibitor, and it shows great inter-individual variability–the clopidogrel non-responders [106,118,119]. The genetics purported behind this involve loss-of-function alleles in CYP2C19 (CYP2C19*2 and CYP2C19*3), which is thought to be associated with poor drug responsiveness, whilst the gain-of-function allele CYP2C19*17 is associated with increased bleeding risk [119,120]. Now, the COAG (Clarification of Optimal Anticoagulation through Genetics) trial and the EU-PACT (European Pharmacogenetics and Anticoagulant Therapy-Warfarin) have produced RCTs advocating genotype-guided drug dosing for warfarin, which prescribe dosing based on CYP2C9 and VKORC1 genotyping [121,122]. Precision medicine aided by pharmacogenomics and pharmacogenetic profiling poses to refine this area, bringing in next-generation care using enhanced phenotyping for disease stratification [123]. Cardiovascular research is increasingly a part of the vast, digital, data-driven world made possible by the plethora of molecular, physiological, and environmental data generated by a variety of “omics” technologies. Clinical research and practice will advance from focusing on the “typical patient” to gaining a more sophisticated understanding of specific individuals and populations [124]. With this review, we underline the key areas where the domains of precision medicine (Figure 3) can be implemented in cardiology diagnostics, stratification, therapeutics, and prognostics, and compare its novelty to the existing norm. Precision medicine empowers a physician to treat cardiac diseases individualistically, based on the patient’s unique genetic, metabolic, proteomic, or symptomatic profile. The strength of precision medicine lies in the synthesis and analysis of “data” that is rapidly changing from standard clinical, imaging, and laboratory testing to next-generation sequencing, metabolomics, and proteomic studies [8]. Modern-day cardiology is evolving to adopt new genetic, molecular, metabolic, and proteomic tools. In the case of myocardial infarction, newer biomarkers such as bFGF, hsCRP, hs Troponins, and miRNAs have emerged, which have great potential for detecting disease processes with more accuracy and at an earlier stage. Additionally, recent advances have shown that metabolites (such as acylcarnitines, fatty acids, BCAAs) are strong predictors of cardiovascular diseases and can be paired with standard metabolomics such as troponin and lipid levels to promptly predict the occurrence of MI/death in patients with heart disease. Similarly for heart failure, various markers such as 3-hydroxybutyrate, acetone, succinate 2-oxoglutarate, pseudouridine alanine, creatinine, proline, isoleucine, and leucine in plasma have shown usability for the prediction of outcome; various genes have also been identified that can serve the purpose of early risk stratification in the near future [125]. Despite its applicability challenges, genomics has contributed greatly to our understanding of the variability of disease processes, risk propensity, and response to treatment. Future advancements in genetic data generation and tools of application will enable its implementation in the routine management of common diseases. Next-generation sequencing and genome-wide association studies using a variety of computational biology technologies offer hope for improving the diagnosis and treatment of cardiovascular diseases. The mass spectrophotometric characterization of human cardiac proteins may expand the applicability of proteomics methods to CVD. Furthermore, transcriptomics approaches reveal novel information about gene expression, and metabolomics represents the tail end of multi-omics efforts to tackle CVDs early on. The “omics” can thus play a core role in the individualization of therapy in cardiac diseases [125]. The rupture of atherosclerotic plaques appears to be the leading primary cause of CVD. Atherosclerosis, the leading cause of CVD, is a chronic inflammatory condition in which immuno-competent cells in lesions produce primarily pro-inflammatory cytokines. One key target for atherogenic immune responses is heat shock proteins, with other mediators being: pro-inflammatory cytokines, chemokines, and lipid mediators [126]. The evidence has evolved significantly in this domain, highlighting role of immune cells in various cardiac diseases. To cite an example, in the pathophysiology of heart failure, regulatory T cells (Tregs) play a role in immunoregulation and tissue healing. Tregs help the heart by limiting excessive inflammatory response and encouraging stable scar formation in the early stages of cardiac damage. However, Treg phenotypes and functions are altered in chronic heart failure by these cells being mutated into antiangiogenic and profibrotic cells. In addition, tumour necrosis factor (TNF)- and tumour necrosis factor receptor (TNFR1) expression rises in HF-activated CD4+ T cells. Immunotherapy for heart failure is now conceivable because of advances in next-generation sequencing and gene editing technologies [127,128,129,130,131]. The majority of pharmaceutical therapies have focused on changing hemodynamics (lowering afterload, regulating blood pressure and volume) or cardiac myocyte function. However, significant contributions of the immune system to normal cardiac function and damage response have lately emerged as attractive research fields. Therapeutic approaches that harness the strength of immune cells have the potential to open up new therapeutic pathways for various cardiac diseases, and these form important targets for providing individualized therapy by exploiting the “omics” and tailoring therapy in line with the immune makeup of the patients [126,131,132]. Various experts question the applicability and accessibility of precision medicine, believing that it lacks a global impact on cardiovascular disease management and will merely serve a small group of patients in the developed world, relegating its role to a selected niche only. However, this concern seems implausible due to the limited literature attesting to the validity of this claim [133]. Another challenge is the dearth of acceptability and neophobia to the growing methods both by the providers and the recipients. Precision medicine was historically considered complex, expensive, and inaccessible to underserved populations. Genomics has undoubtedly accelerated the discovery of mutations underlying cardiac diseases. Exploring genetic sequences, assembly, and the identification of genes is still evolving and seems to have a promising future, although the technology needed to translate this data into clinical interpretation and practice is still challenging. While major research work is focused on the exome (protein-coding DNA), another area of interest in present-day genetic sequencing is the non-protein-coding DNA and its impact on major clinical diseases, which are largely under-discovered. Moreover, the research/development of testing for genetic variants associated with the risk of developing a certain cardiac disease and its role in prevention is encouraging, but affordability and feasibility remain a concern even in developed countries [133,134]. Another challenge to PM in cardiology is the education and training of the stakeholders, including the providers and the general public [135,136]. Education must be aimed at training to use an integrated system approach, allowing healthcare providers and patients to be in congruency to accept and trust the new evolving techniques [136]. An added challenge is the apparent lack of available cohorts with relevant phenotypes to demonstrate statistically meaningful associations. Moreover, the absence of a replication cohort and differences in epigenomic patterns also make research difficult. Precision medicine is the future of medicine and holds promise for the more efficient management of cardiovascular diseases, owing to their gradual onset and heterogeneous, multimorbid, and chronic nature. The pathogenesis of these diseases may begin decades before any ultimate disease manifestation. Therefore, the use of precisely targeted tools for diagnosis and personalized treatment can revolutionize management by allowing the prevention, early diagnosis, and tailored treatment of cardiovascular diseases. Precision medicine is still an evolving field and many of the technologies needed for its implementation are in nascent stages. Moreover, the research and data on precision medicine are limited because of the ethical, social, legal, and economic issues, which may have produced an unavoidable bias in this review as well. This review explored the literature on precision medicine in cardiology and tried to outline and summarize the most clinically relevant sections of the evolving field. As we evolve in our capacity and infrastructure to employ tools exploring the genomics, proteomics, and metabolomics of cardiovascular diseases, we stand to see a future where a more precise therapy tailored to the needs, demands and limitations of an individual patient would no longer be a dream but a responsibility. The future of cardiology is here; we need to assimilate, adapt and make it more accessible by educating the providers about the evolving field and making infrastructure more equitable to the public.

PMC10003120

Long Chen,Na Geng,Taiwei Chen,Qingqing Xiao,Hengyuan Zhang,Huanhuan Huo,Lisheng Jiang,Qin Shao,Ben He

Ginsenoside Rb1 Improves Post-Cardiac Arrest Myocardial Stunning and Cerebral Outcomes by Regulating the Keap1/Nrf2 Pathway

06-03-2023

cardiac arrest,myocardial stunning,ginsenoside Rb1,cardiopulmonary resuscitation,mitochondria,Nrf2

The prognosis of cardiac arrest (CA) is dismal despite the ongoing progress in cardiopulmonary resuscitation (CPR). ginsenoside Rb1 (Gn-Rb1) has been verified to be cardioprotective in cardiac remodeling and cardiac ischemia/reperfusion (I/R) injury, but its role is less known in CA. After 15 min of potassium chloride-induced CA, male C57BL/6 mice were resuscitated. Gn-Rb1 was blindly randomized to mice after 20 s of CPR. We assessed the cardiac systolic function before CA and 3 h after CPR. Mortality rates, neurological outcome, mitochondrial homeostasis, and the levels of oxidative stress were evaluated. We found that Gn-Rb1 improved the long-term survival during the post-resuscitation period but did not affect the ROSC rate. Further mechanistic investigations revealed that Gn-Rb1 ameliorated CA/CPR-induced mitochondrial destabilization and oxidative stress, partially via the activation of Keap1/Nrf2 axis. Gn-Rb1 improved the neurological outcome after resuscitation partially by balancing the oxidative stress and suppressing apoptosis. In sum, Gn-Rb1 protects against post-CA myocardial stunning and cerebral outcomes via the induction of the Nrf2 signaling pathway, which may offer a new insight into therapeutic strategies for CA.

Ginsenoside Rb1 Improves Post-Cardiac Arrest Myocardial Stunning and Cerebral Outcomes by Regulating the Keap1/Nrf2 Pathway The prognosis of cardiac arrest (CA) is dismal despite the ongoing progress in cardiopulmonary resuscitation (CPR). ginsenoside Rb1 (Gn-Rb1) has been verified to be cardioprotective in cardiac remodeling and cardiac ischemia/reperfusion (I/R) injury, but its role is less known in CA. After 15 min of potassium chloride-induced CA, male C57BL/6 mice were resuscitated. Gn-Rb1 was blindly randomized to mice after 20 s of CPR. We assessed the cardiac systolic function before CA and 3 h after CPR. Mortality rates, neurological outcome, mitochondrial homeostasis, and the levels of oxidative stress were evaluated. We found that Gn-Rb1 improved the long-term survival during the post-resuscitation period but did not affect the ROSC rate. Further mechanistic investigations revealed that Gn-Rb1 ameliorated CA/CPR-induced mitochondrial destabilization and oxidative stress, partially via the activation of Keap1/Nrf2 axis. Gn-Rb1 improved the neurological outcome after resuscitation partially by balancing the oxidative stress and suppressing apoptosis. In sum, Gn-Rb1 protects against post-CA myocardial stunning and cerebral outcomes via the induction of the Nrf2 signaling pathway, which may offer a new insight into therapeutic strategies for CA. Sudden cardiac arrest (CA) carries a high burden of mortality and morbidity worldwide, despite the ongoing efforts to improve the “chain of survival” over the past 20 years [1]. A recent study showed that the global incidence of CA was around 3.7 million every year [2]. In America, the current survival rates of out-of-hospital CA are 11.4% and 10.4% for children and adults, respectively, contrasted with the rates for in-hospital CA, which are 41.1% and 25.8% for children and adults [3]. Of those survivors, up to 60% suffer from moderate to severe cognitive deficits, and 65% are attacked by post-arrest myocardial dysfunction, including left ventricular diastolic or systolic dysfunction, and low cardiac index [2]. In China, more than 500,000 new cases occur annually, and the prognosis, despite successful resuscitations and the return of spontaneous circulation (ROSC), is poor due to the limited options for treatment [4]. Paying attention to the pathogenesis of CA and searching for therapies that are more efficient and potent is thus, of the utmost importance. CA results in whole-body ischemia reperfusion (I/R) injury, which is related to myocardial dysfunction and neurological deficit. Notably, mitochondria destabilization and oxidative stress act as core pathological components of CA and I/R injury [5,6]. Mitochondria is a substantial source of reactive oxygen species (ROS), and it also represents a target for its deleterious effects. Excessive oxidative stress may cause mitochondria destabilization, which induces the enhanced production of free radical, thus triggering a vicious cycle that aggravates oxidative injury, and thereby, affects oxidative phosphorylation and energy metabolism [7]. Therefore, targeting the mitochondria and oxidative stress may hold promise for therapeutic treatments. Ginseng, a naturally occurring herb, has been widely used in East Asian countries such as China, Korea, and Japan for centuries to maintain body homeostasis and energy enhancement. Ginsenoside is the main bio-active component, which is extracted from ginseng. Currently, more than 100 ginsenosides have been identified [8], of which ginsenoside Rb1 (Gn-Rb1) is the most active and abundant monomer. A recent clinical study demonstrated the protective effect of Gn-Rb1 in chronic kidney disease, and the pharmacological mechanism involved anti-oxidative stress and anti-inflammation [9]. Previous works have observed the potential benefits of Gn-Rb1 in animal models of I/R settings for various organs including the heart [10,11,12], brain [13], spinal cord [14], intestine [15], and kidney [16]. Modern pharmacology researches have revealed multiple pharmacological properties of Gn-Rb1 on the cardiovascular system, including anti-oxidative, anti-apoptotic, and anti- inflammatory [10,11,12]. However, the effects of Gn-Rb1 against post-cardiac arrest syndrome, which is complicated by the whole-body I/R injury after ROSC following CA, has hitherto remained obscure. In the current study, we found that the administration of Gn-Rb1 during the early cardio-pulmonary resuscitation (CPR) period improved post-CA myocardial stunning and secondary brain injury. These findings provided new insights into the role of Gn-Rb1 in cardioprotection, which could pave the way for developing novel therapeutic strategies for post-cardiac arrest syndrome. A total of 256 mice were subjected to the sham operation (n = 35) or the potassium chloride-induced CA/CPR (n = 221). In the CA/CPR group, 30 mice were used to summarize ROSC-related characteristics. Of the other 127 successfully resuscitated mice, 100 survived for more than 3 h. The remaining 100 resuscitated mice were then randomly assigned to either the 72 h group (n = 40) or the 3 h group (n = 60) for the following investigation (Figure 1b). There were no differences in the resuscitation-related variables between the post-arrest mice treated with Gn-Rb1 or not, such as chest compression rate, ventilator parameters, body weight, heart rate, body temperature, and so on. Gn-Rb1 has been shown to protect the heart against I/R injury or ameliorate myocardial dysfunction in a different context [17,18,19,20,21]. However, the role of Gn-Rb1 in CA/CPR remains unknown. In the CA/CPR mouse model, no difference was observed in the ROSC rate between the CA group and CA+Rb1 group (53.3% vs. 66.7% and p = 0.248), whereas the time for ROSC was significantly improved in the Gn-Rb1 treated group (p < 0.05) (Figure 2b,c). The effect of Gn-Rb1 in impro ving the ROSC time suggested that Gn-Rb1 may be involved in the CA/CPR period. The effect of Gn-Rb1 on the post-resuscitation restoration of cardiac function was ascertained by transthoracic echocardiography. As shown in Figure 2d–g, CA/CPR induced severe depression of the LVEF, LVFS and CO during the first 3 h following the ROSC, which were significantly improved by the Gn-Rb1 treatment (32.65 ± 1.42% vs. 45.70 ± 1.36%, p < 0.05; 14.78 ± 2.78% vs. 22.01 ± 3.08%, p < 0.05, and 3.88 ± 0.46 vs. 6.76 ± 0.70, p < 0.05, respectively). Of note, the LVEF, LVFS, and CO did not differ significantly between the sham-operated mice and the 12 h post-arrest mice, regardless of treatment with Gn-Rb1 or not. The survival of mice in the CA group and CA+Rb1 group was monitored for 72 h (15%, 3 of 20 vs. 50%, 10 of 20, and p < 0.05, respectively). All ten mice in the sham group survived. The Kaplan–Meier survival curves indicated a rapid decline in survival within the first 12 h after ROSC (Figure 2h). Overall, these results indicate that Gn-Rb1 treatment during the early stage of CPR preserved the cardiac function and improved survival in CA/CPR mice. CA/CPR is known to trigger oxidative damage, which contributes to myocardial dysfunction [22]. To probe the mechanisms underlying the cardioprotection of Gn-Rb1, we examined the effects of Gn-Rb1 in regulating CA/CPR-induced myocardial oxidative stress. As shown in Figure 3a–f, CA/CPR remarkably induced the production of superoxide accumulation, as shown by DHE staining, as well as peroxide byproducts, such as 4 hydroxynonenal (4-HNE) and nitrotyrosine (NT). As predicted, Gn-Rb1 improved the deposition of CA/CPR-induced ROS in the myocardium. In addition, the changes in the antioxidant proteins SOD2 and oxidative markers gp91 were a partial remission by Gn-Rb1 (Figure 3g,h). As a potential site to drive the ROS production, NADH dehydrogenase was activated in cardiomyocytes during reperfusion [23]. Thus, we wondered what changes in NADH dehydrogenase would occur after CA/CPR. Our results indicated that CA/CPR activated NADH dehydrogenase, while Gn-Rb1 reduced its activity. In accordance, Gn-Rb1 inhibited the protein expression of some subunits of NADH dehydrogenase, such as NDUFS4, NDUFV1, and NDUFV2 (Figure 3i–k). Collectively, these data indicated that the improvement of cardiac dysfunction by Gn-Rb1 is partly due to its antioxidant properties. Multiple mechanisms underlying myocardial stunning have been reported, among which metabolic destabilization is one of the main culprits [24]. Mitochondrial homeostasis is a key mechanism contributing to energy metabolism. We therefore assessed the role of Gn-Rb1 on the mitochondrial dynamics and morphology, as well as ATP production, in the CA/CPR mice model. As shown in Figure 4a, the TEM analysis of the myocardial mitochondrial in CA mice revealed a substantial loss of matrix density, swelling, and cristae disruption. However, those pathological abnormalities were partially reversed by Gn-Rb1. Mitochondrial fusion and fission are considered the basic mechanisms for maintaining mitochondrial dynamics and morphology. As shown in Figure 4b,e, CA/CPR induced Drp1 translocation to the mitochondria and triggered phosphorylation of Drp1 at serine 616, whereas the Gn-Rb1 treatment prevented this effect. Notably, no significant differences were observed in the mitochondrial fusion proteins, such as OPA1 and MFN2. A reduction in the mitochondrial membrane potential (△ψ) and ATP production are hallmarks of mitochondrial dysfunction, shown in Figure 4f,g. However, Gn-Rb1 treatment improved the pathological status. Next, we investigated the molecular mechanisms of Gn-Rb1 protecting the myocardium. The Keap1/Nrf2 axis is the key for the cellular regulation of redox homeostasis, mitochondrial physiology, and metabolism [20,25]. Upon cardiac I/R injury (I/R), Keap1 is inactivated and NRF2 accumulates in the nucleus. Activation of Nrf2 attenuates myocardial I/R injury [26,27]. Studies have indicated that Gn-Rb1 may participate in the regulation of the Nrf2 signaling pathway to counteract I/R injury and oxidative damage [28,29]. Accordingly, we assumed that Gn-Rb1 attenuated oxidative stress and improved mitochondrial homeostasis, partly empowered by the activation of the Nrf2 signaling pathway. As shown in Figure 5a,b, Gn-Rb1 attenuated the CA/CPR-induced up-regulation of keap1, a main repressor of the Nrf2 signal. In parallel, Gn-Rb1 promoted the translocation of Nrf2 into the nucleus, while the level of Nrf2 in the cytoplasm was down-regulated accordingly. There was no difference in the HO-1 and NQO1 proteins and the Nrf2 downstream antioxidant genes in the CA group as compared to sham, while all of which were partly up-regulated by the Gn-Rb1 treatment. This detailed mechanism needs to be further explored. Next, we introduced siRNA to knock down the Nrf2 expression (Figure 5c,d). Of note, the Nrf2 knockdown partly attenuated the Gn-Rb1-induced HO-1 expression and NQO1 expression in the context of hypoxia/reoxygenation (H/R). Collectively, the activation of the Keap1/Nrf2 axis may, in part, explain the protective effect of Gn-Rb1 in CA/CPR-induced myocardial injury. To further substantiate the involvement of Nrf2 signaling in the protective action of Gn-Rb1 in the mouse CA/CPR model, NRCM were transfected with NC siRNA or Nrf2 siRNA. As shown in Figure 6a–c, the siRNA transfection decreased Nrf2 mRNA expression by ≥70% in NRCM. The intracellular ROS level was determined by DHE staining and a fluorescent probe (DCFH-DA). Superoxide within the mitochondrial was analyzed using the MitoSOXred reagent. Gn-Rb1 alleviated H/R-induced intracellular oxidative stress and mitochondrial ROS production, while the gene knockdown of Nrf2 partly abrogated the antioxidant effects (Figure 6d,e). Consistent with this, changes in gp91 and SOD2 protein expression were affected by the knockdown of Nrf2 (Figure 6f,g). In addition, we examined the protein levels of the subunits of NADH dehydrogenase. Among the five subunits, NDUFV1 was not affected by the Nrf2. However, the Nrf2 knockdown partly offset the effect of Gn-Rb1 on the NADH dehydrogenase activity (Figure 6h,i). Mitochondrial calcium overloading and the drop of the mitochondrial membrane potential (△Ψm) were hallmarks of mitochondrial dysfunction. Therefore, we measured mitochondrial Ca2+ with Rhodamine-2 (Rhod-2) and measured mitochondrial membrane potential with JC-1 staining. As shown in Figure 7a–d, the enhancement of mitochondrial Rhod-2 fluorescence and reduction in mitochondrial transmembrane potential after reoxygenation were improved partially by Gn-Rb1, while the gene knockdown of Nrf2 partly abrogated the protective effects. We next examined the impact of Nrf2 on mitochondrial morphology. Notably, Nrf2 regulated mitochondrial fission proteins, such as p-Drp1 (ser616) in total cell and Drp1 or Fis1 in mitochondrial, while it did not affect mitochondrial fusion proteins such as MFN2 and OPA1 (Figure 7e–h). Neurological damage is one of the major cause of disability and death after CA/CPR. As shown in Figure 8a, the neurological deficit scores were dramatically improved in the Gn-Rb1-treated group before 24 h following CA/CPR. However, the differences between the two groups were not statistically significant at 72 h. Gn-Rb1 improved CA/CPR-induced oxidative injury and cell apoptosis, as shown in DHE staining and TUNEL staining. The changes in the antioxidant proteins SOD2 and oxidative markers gp91, as well as apoptosis-related or anti-apoptosis-related proteins also support this point of view (Figure 8b–i). The present investigations offered the following new insights concerning the effects of Gn-Rb1 in post-CA myocardial stunning: (a) Gn-Rb1 significantly improved long-term survival during the post-resuscitation period, but did not affect the ROSC rate. (b) Gn-Rb1 ameliorated CA/CPR-induced mitochondrial destabilization and oxidative stress partially via the activation of Keap1/Nrf2 axis. (c) Gn-Rb1 improved neurological outcome after resuscitation, partially by balancing the oxidative stress and suppressing apoptosis. In summary, these findings provided the first evidence that Gn-Rb1 protected against CA-induced myocardial stunning through ameliorating mitochondrial destabilization and oxidative stress in a Nrf2-dependent manner. Our findings provide a valuable reference and great insight for developing new agents to treat CA. Previous researchers have suggested that post-CA myocardial dysfunction was reversible, and that the evolving process was consistent with myocardial stunning [30,31]. This is in agreement with clinical observations and our findings, to a certain extent. After a 12 h recovery period, the cardiac systolic and diastolic function largely returned to normal levels (Figure 2). Therefore, the effect of Gn-Rb1 on cardiac function, at this time point, was slightly less pronounced. However, insufficient cardiac output in the early post-resuscitation phase may worsen global I/R injuries, and contributes to the early deaths [32]. Accordingly, early improvement of myocardial stunning and increased support for the circulatory system are critical. We found that Gn-Rb1 significantly improved the cardiac contractility, output, and diastolic functions 3 h after the ROSC, compared with the vehicle group (Figure 2). Actually, an abundance evidence has supported the notion that Gn-Rb1 could improve cardiac function and remodeling in decompensated heart failure [19,20,33]. However, the role of Gn-Rb1 in post-cardiac arrest syndrome has not yet been identified. We demonstrated that Gn-Rb1 induced positive inotropic effects in CA/CPR mice, thus stabilizing or improving circulatory failure, resulting in a better post-resuscitation prognosis. CA is related to both global and focal I/R injuries of the heart, and one of the main pathological mechanisms of I/R injury is mitochondrial ROS burst. The vicious cycle of mitochondrial destabilization and oxidative stress is a well-known precipitating factor of post-cardiac arrest myocardial stunning [24]. Previously, multiple studies have demonstrated the therapeutic potential of Gn-Rb1 for cardiac I/R injury, and the underlying mechanisms were involved in antioxidant, antiapoptosis, and the regulation of mitochondrial homeostasis [10,34,35,36]. Therefore, we hypothesized that Gn-Rb1 protected against post-CA myocardial stunning by improving oxidative stress and mitochondrial destabilization. We found that Gn-Rb1 reduced the deposition of CA/CPR-induced superoxide and peroxide byproducts such as 4-HNE and NT (Figure 3a–f). In addition, the changes in the antioxidant proteins SOD2 and oxidative markers gp91 were a partial remission by Gn-Rb1 (Figure 3g–h). Gp91phox is the catalytic subunit of NADPH oxidase that triggers superoxide anions, and the superoxide contains the maximum burden of free radicals in I/R insult [37]. Superoxide dismutases (SOD), especially the manganese SOD (MnSOD, SOD2), is a mitochondrial antioxidant enzyme that is involved in the scavenger of superoxide [38]. NADH dehydrogenase is a key site to drive ROS production. Jiang et al. [10] reported that the inhibition of mitochondrial NADH dehydrogenase may elucidate the probable mechanism of Gn-Rb1 in alleviating cardiac I/R injury. As such, we examined the NADH dehydrogenase activity and the related subunit protein expression. Notably, Gn-Rb1 reduced the activity of NADH dehydrogenase, and some subunits showed corresponding changes as well, in the context of CA/CPR (Figure 3i,k). However, the expression of the subunits of NADH dehydrogenase may not necessarily be related to the activity of NADH dehydrogenase. In addition, the level of NADH dehydrogenase activity has complex concerns for the oxidation status post-CA and depends on the degree of mitochondrial electron transport chain dysfunction and organ-specificity. Therefore, further study is needed to explore these issues. All in all, our results supported the antioxidant activity of Gn-Rb1 in the CA/CPR context, which is consistent with the experimental results described in the literature [39,40]. Much of the studies in the literature have observed mitochondrial destabilization in the heart after CA/CPR, including morphologic alterations and dysfunctional disorder [41,42,43]. Actually, excessive oxidative stress triggers mitochondrial destabilization and then affects respiratory chain, ATP generation, and cell fate; while mitochondrial destabilization exacerbates oxidative injury in turn. The vicious cycle contributes to myocardial dysfunction. We found that CA/CPR triggered mitochondrial fission, while changes in mitochondrial fusion protein were not obvious (Figure 4d,e). This result was consistent with prior studies that argued for mitochondrial fission as the pathogenesis for post-CA myocardial stunning [44,45]. In addition, a reduction in ATP production and mitochondrial membrane potential (Δψ) is hallmark of mitochondrial defects. However, Gn-Rb1 treatment improves those pathological status. Gn-Rb1 has previously been reported to regulate energy metabolism in other disease settings, such as diabetic cardiomyopathy, heart failure, and I/R injury [10,19,20,21,34]. Here, we demonstrated the regulatory action of Gn-Rb1 on energy metabolism in the CA/CPR heart. Neurological damage is one of the major cause of disability and death after CA/CPR. Notably, multiple studies have demonstrated the efficacy of Gn-Rb1 in the treatment of cerebral ischemia–reperfusion injury [46,47,48]. However, whether Gn-Rb1 plays a role in CA/CPR-induced cerebral outcomes is yet to be determined. We found that Gn-Rb1 improved the neurological deficit scores in the mouse model of CA/CPR, and the pharmacological effects involved multiple mechanisms such as oxidative stress and apoptosis (Figure 8). The activation of the Keap1/Nrf2 axis might explain, at least in part, the beneficial effects of Gn-Rb1 on post-CA myocardial stunning. However, whether Gn-Rb1 functions similarly in the brain as is proposed in the heart remains unknown. Huang et al. [49] found that Gn-Rb1 had the effects against cerebral I/R injury, which were related to the antioxidative stress and Nrf2/HO-1 signaling pathway. Li et al. [50] suggested that Gn-Rb1 was capable of alleviating cerebral I/R injury in mice by the NF-κB pathway, oxidative stress pathway, and cytokine network pathway. As such, the Nrf2 signaling pathway may also explain the pharmacological effects of Gn-Rb1 on neurological damage following CA/CPR, but further study is required to unveil this issue. Nrf2, a master transcriptional regulator of redox regulation, activates adaptive responses against oxidative stress, autophagy, apoptosis, and inflammation, through the transcriptional induction of over 600 antioxidant enzymes [51]. Unstimulated, Nrf2 is sequestered by Keap1, and ubiquitinated and degraded in the cytoplasm [52]. Keap1 is inactivated under oxidative stress, allowing Nrf2 to be released from Keap1 and translocated into the nucleus. The activation of the Nrf2 signaling pathway is a major mechanism in the cellular defense against CA/CPR-induced myocardial stunning [53,54]. Our study has several limitations. First, CA was induced in healthy mice with no underlying coronary lesions or cardiac arrhythmia, which may have minimized its clinical relevance. In addition, Gn-Rb1 may exert different effects on cardiac arrest induced by structural heart disease and non-structural heart disease, and it may involve different mechanisms [55,56]. Second, the prognosis of CA was affected by systemic I/R injury, rather than single components. As such, the target organ, possibly Gn-Rb1-primary-specific, remains to be identified. Third, a well-established in vitro model mimicking CA/CPR situations is lacking currently, which disturbs the research of the underlying molecular mechanism. Fourth, we did not test the dose–response study on the mouse CA/CPR model. Fifth, whether Gn-Rb1 functions similarly in the brain as is proposed in the heart remains to be investigated in future. Thus, further investigations are needed to answer these questions. Gn-Rb1 was purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Antibodies against gp91phox, SOD2, 3-nitrotyrosine, 4 hydroxynonenal, DRP1, DRP1 (phospho S637), DRP1 (phospho S616), Mitofusin 2, OPA1, Fis1, Histone H3, caspases-3, cleaved caspases-3, and VDAC1 were obtained from Abcam (Cambridge, MA, USA). GAPDH, Bax, and Bcl-2 were obtained from Cell Signaling Technology (Beverly, MA, USA). Nrf2, keap1, NQO1, HO1, Ndufs1, Ndufv1, Ndufs6, Ndufs4, Ndufv2, and Ndufa12 were obtained from Abmart (Shanghai, China). Dihydroethidium (DHE) wasobtained from Beyotime (Jiangsu, China). Animal procedures were approved by the Institute’s Animal Ethics Committee of Shanghai Chest Hospital, Shanghai Jiao Tong University (Shanghai, China) (KS(Y)1839). Male C57 mice (8 weeks old) were obtained from Beijing Sibefu Biotechnology Co., Ltd. (Beijing, China) and housed at 25 ± 2 °C with 40–60% humidity under a normal 12 h light/dark cycle, with food and water available ad libitum. As described previously, the CA/CPR model was developed [53]. Briefly, mice were anesthetized using isoflurane (1.5% isoflurane/medical air mixture), and then intubated with a rodent respirator. The right jugular vein was cannulated with a polyethylene tube for fluid administration. ECG monitoring was obtained using limb electrodes. By injecting 0.08 mg of KCl/g body weight, CA was induced, and after an EKG was confirmed to be flat, the ventilator was turned off. Fourteen and a half minutes after onset of CA, mechanical ventilation resumed, and chest compression were delivered at a rate of 350–400 bpm for 15 min. After 20 s of chest compression, mice received 0.4 μg epinephrine/g body weight combined with Gn-Rb1 (50 mg/kg), or epinephrine only. This dose of Gn-Rb1 was given on the basis of previously published reports [10,17]. Additional doses of epinephrine were given at 1 min intervals until return of spontaneous circulation (ROSC) or after 5 min of CPR (Figure 1a). A total of 3 h after ROSC, mice were euthanized. Randomization was performed using simple randomization method via a random number table. The left ventricular apex tissues were embedded in OCT compound or kept in paraffin, and the residual heart tissues were then frozen at −80 °C for molecular analysis. Cardiac structure and function were determined using the Vevo770 system (VisualSonics, Toronto, Canada) at the indicated times of post-ROSC. The mice were anaesthetized by inhalation of 2% isoflurane, and M-mode images of the parasternal long axis were obtained to calculate left ventricular fractional shortening (LVFS), cardiac output (CO), and left ventricular ejection fraction (LVEF), as previously described [53]. Serial sections (5 µm) were prepared from formalin-fixed, paraffin-embedded left ventricular apex tissues. The 4 hydroxynonenal (4HNE) staining and 3-nitrotyrosine (NT) staining were used to evaluate the oxidative stress in myocardium. Quantitative image analysis of immunohistochemistry was performed using Image J analysis software [38]. The collected left ventricular apex tissues and brain tissues were embedded in OCT and cut into 6 μm sections. Cryosections were washed 3 times for 5 min using PBS and incubated with 10 μmol/L dihydroethidium for 30 min. After washing with PBS 3 times again, the slides were viewed under a fluorescence microscope (DM2500, Leica). The maximum excitation wavelength is 300 nm, and the maximum emission wavelength is 610 nm. The fluorescence intensity of DHE staining was measured using ImageJ software (version 2.0.0). Mitochondrial morphology was evaluated by transmission electron microscopy, as previously described [53]. Briefly, the left ventricles were fixed, dehydrated, embedded, and cut into ultrathin slices (70 nm), and then observed and imaged using TEM (Hitachi HT-7800, Tokyo, Japan). Extraction of cytoplasm and nuclear proteins was realized using Nuclear and Cytoplasmic Protein Extraction Kit (Beyotime, China). Total proteins were extracted from heart tissues, brain tissues, or primary cardiomyocytes according to product manual (Roche, USA). Protein concentration was quantified using a BCA protein assay (Thermo Fisher Scientific). The amount of protein was adjusted to 20 μg per lane. Proteins were separated using 7.5–12.5% SDS-PAGE and transferred onto 0.22 μm PVDF membranes. After being blocked with 5% BSA for 1 h and rinsed with PBS, the membrane was incubated for 12 h at 4 °C with the primary antibody. On the following day, the primary antibodies were removed with three rinses of PBS. The immunoblot bands were visualized using chemiluminescence (Millipore) via ImageQuant LAS 4000 Imager (General Electric, Pittsburgh, PA, USA.) after incubation with the corresponding secondary antibodies (ab288151, 1:10000, Abcam, Cambridge, UK) for 1 h at room temperature. The ratio of the gray value of the target bands to the internal reference band (GAPDH) was used as the relative expression of the protein. Total RNA from cells or tissues was extracted using TRIzol® reagent (Invitrogen, USA). Isolated RNA was reverse-transcribed and duplicated using PrimeScript™ RT Master Mix (Vazyme, Nanjing, China) and SYBR qPCR master mix (Vazyme, Nanjing, China) in iScript cDNA Synthesis Kit (Takara BIO, Otsu, Japan) and the Light-Cycler 480 Real-Time PCR System (Roche, San Francisco, CA, USA). Primers sequences are listed in Supplementary Table S1. The results were normalized to GAPDH and expressed as percentage of controls. TUNEL staining was performed using a TUNEL Apoptosis Assay Kit (Beyotime, Shanghai, China). TUNEL-positive nuclei were identified as apoptotic cells stained with FITC (green), and nuclei were simultaneously counterstained with DAPI. Images were captured using a Leica DMIRE2 fluorescence microscope. The excitation wavelength range was 450–500 nm, and the emission wavelength range was 515–565 nm. TUNEL-positive signals were normalized to the total nuclei signals for each field. Mitochondrial isolation from the hearts or NRCMs was performed using the Mitochondrial Isolation Kit (Beyotime, Shanghai, China) [25]. Briefly, cells and tissue were mechanically homogenized for 30 strokes using a tight pestle on ice in mitochondrial isolation buffer added with PMSF, and centrifuged at 600 g for 10 min at 4 °C, and then the resulting supernatant was centrifuged again at 11,000 g for 10 min at 4 °C to obtain mitochondria. The isolated mitochondria and cytoplasm were used for subsequent experiments. The neonatal rat cardiomyocytes (NRCMs) were isolated from heart ventricles of 1- to 3-day-old SD rats [57]. In brief, the ventricles were minced and digested with collagenase type II (Invitrogen) and pancreatase myocyte digestion buffer (Sigma-Aldrich, USA). After differential adhesion, the supernatants of primary cultures of myocardial cells were plated and then grown in DMEM with 10% FBS (fetal bovine serum, GIBCO, Billings, MT, USA), 100 U/mL penicillin, and 100 μg/mL streptomycin at 37 °C and 5% CO2 for 48 h. NRCMs at a density of 50–70% were transfected with Nrf2 small interfering RNAs (siRNAs, 50 nM, purchased from Genepharma, Shanghai, China) to silence Nrf2 using Lipo3000 (Invitrogen, Carlsbad, CA, USA). Sequences of the Nrf2 siRNA sequence were as follows: forward oligo, 5′-GGAUGAAGAGACCGGAGAAUU tt-3′, reverse oligo, and 5′-AAUUCUCCGGUCUCUUCAUCC tt-3′. We investigated the following groups after 72 h of transfection. Standard incubators were used to culture the blank group without transfection. Cells transfected with Nrf2 siRNA (Nrf2 siRNA group), or negative control siRNA (NC group) were exposed to hypoxia for 12 h and reoxygenation for 3 h, to simulate I/R injury. Based on Nrf2 siRNA group and NC group, Nrf2 siRNA+Rb1 group and NC + Rb1 group were treated with Gn-Rb1 (10 µM) during reoxygenation for 3 h [10,14,34]. Production of reactive oxygen species (ROS) was detected using DCFH-DA fluorescent probe kit (Beyotime, Shanghai, China). In brief, the plates were incubated in the dark for 20 min with DCFH-DA (10 M), and then cells were washed 3 times to remove DCFH-DA. Subsequently, cells were visualized using Leica DMIRE2 fluorescence microscope. We used 488nm excitation wavelength and 525 nm emission wavelength. mROS production was measured using MitoSOX Red (Invitrogen, USA). In brief, cells from different groups were washed 3 times with PBS and incubated for 30 min with 1 µM MitoSOX Red, and then counterstained with Hoechst. After washing 3 times with PBS, images of mROS level were obtained (Excitation/Emission 396/610 nm) using a fluorescence microscope (Leica DM400B, Leica Microsystems, Ltd., Wetzlar, Germany). A 12-point mouse neurologic scoring system was used to assess neurological deficits in mice after CA [58]. Six domains were evaluated with scores ranging from 0 (no response) to 2 (normal): righting reflex, motor-focal, breathing, spontaneous movement, paw pinch, and motor-global. For each domain, a blinded score was calculated and summed to obtain a neurologic score. The comparisons between the two groups were performed using unpaired t-test. Cellular ATP levels were measured using the Enhanced ATP Assay Kit (Beyotime, Shanghai, China). The cardiac tissues and treated NRCMs were lysed with ATP assay lysis buffer. The lysed cells were centrifuged in 12,000 g for 5 min at 4 °C, and then we collected supernatant. Afterward, we added ATP detection working solution to a 96-well black plate and incubated for 5 min, and then added supernatant to the plate quickly. The RLU of samples was detected by luminometer within 30 min. We normalized the luminescence signals to the protein concentrations in order to calculate the total ATP levels. A mitochondrial membrane potential assay kit with JC-1 (Beyotime, China) was used to detect the mitochondrial membrane potential. Briefly, cells were incubated with JC-1 working solution for 20 min, and then washed twice with JC-1 staining buffer. Cells were imaged using fluorescence microscope (Leica Microsystems). The potential gradient of the mitochondrial membrane potential (Δψm) was indicated by the ratio of green fluorescence to red fluorescence. For heart tissue, the isolated mitochondria were incubated with JC-1, as described previously. Green (488 nm excitation and 530 nm emission) and red (543 nm excitation and 590 nm emission) fluorescence were detected by Fluoromax-2 spectrophotometer (Horiba Jobin Yvon, Paris, France). NADH dehydrogenase activity assay was performed using the kit of Tong Wei (TW, reagent, Shanghai, China) according to the manufacturer’s instructions. Briefly, mash the tissue with an appropriate amount of normal saline, and then put it in 3000 centrifuge for 10 min to obtain the supernatant. In the micropores coated with NADH dehydrogenase antibodies, samples, standard samples, and HRP-labeled antibodies were added successively, incubated (37 ℃, 60 min), and washed thoroughly. The substrate TMB was used to develop color. The absorbance (OD value) was determined by enzyme-labeling instrument at 450 nm wavelength, and the activity of the sample was calculated. Protein concentration was determined by BCA method. The normality of data distribution was tested using the Shapiro–Wilk normality test. Normally distributed variables were presented as means ± standard deviation (SD), while categorical variables were presented as frequencies or percentages. To test for statistical significance, continuous variables following normal distribution were compared using Student’s t-test, while data that did not follow a normal distribution were analyzed by using non-parametric test. Comparisons among multiple groups were performed using one-way ANOVA. Categorical data were compared using the Chi-square test. For survival analysis, Kaplan–Meier survival analysis was used, and comparisons between groups were made using a log-rank (Mantel–Cox) test. P < 0.05 was considered statistically significant. All analyses were performed using Graph-Pad Prism 8 (GraphPad Software, LLC, San Diego, CA, USA). To sum up, our study provides the first evidence that Gn-Rb1 protects against post-cardiac arrest myocardial stunning, partly via alleviating oxidative stress and mitochondrial destabilization through the activation of the Keap1/Nrf2 signaling pathway, which sheds insight into the role of Gn-Rb1 as a new prospective agent against CA. Further studies, in particular clinical trials, will be important to confirm its therapeutic value in a clinical setting.

PMC10003123

Yanwen Liu,Yilong Yao,Yongsheng Zhang,Chao Yan,Mingsha Yang,Zishuai Wang,Wangzhang Li,Fanqinyu Li,Wei Wang,Yalan Yang,Xinyun Li,Zhonglin Tang

MicroRNA-200c-5p Regulates Migration and Differentiation of Myoblasts via Targeting Adamts5 in Skeletal Muscle Regeneration and Myogenesis

05-03-2023

miR-200c-5p,Adamts5,skeletal muscle,regeneration,migration,differentiation

Skeletal muscle, as a regenerative organization, plays a vital role in physiological characteristics and homeostasis. However, the regulation mechanism of skeletal muscle regeneration is not entirely clear. miRNAs, as one of the regulatory factors, exert profound effects on regulating skeletal muscle regeneration and myogenesis. This study aimed to discover the regulatory function of important miRNA miR-200c-5p in skeletal muscle regeneration. In our study, miR-200c-5p increased at the early stage and peaked at first day during mouse skeletal muscle regeneration, which was also highly expressed in skeletal muscle of mouse tissue profile. Further, overexpression of miR-200c-5p promoted migration and inhibited differentiation of C2C12 myoblast, whereas inhibition of miR-200c-5p had the opposite effect. Bioinformatic analysis predicted that Adamts5 has potential binding sites for miR-200c-5p at 3’UTR region. Dual-luciferase and RIP assays further proved that Adamts5 is a target gene of miR-200c-5p. The expression patterns of miR-200c-5p and Adamts5 were opposite during the skeletal muscle regeneration. Moreover, miR-200c-5p can rescue the effects of Adamts5 in the C2C12 myoblast. In conclusion, miR-200c-5p might play a considerable function during skeletal muscle regeneration and myogenesis. These findings will provide a promising gene for promoting muscle health and candidate therapeutic target for skeletal muscle repair.

MicroRNA-200c-5p Regulates Migration and Differentiation of Myoblasts via Targeting Adamts5 in Skeletal Muscle Regeneration and Myogenesis Skeletal muscle, as a regenerative organization, plays a vital role in physiological characteristics and homeostasis. However, the regulation mechanism of skeletal muscle regeneration is not entirely clear. miRNAs, as one of the regulatory factors, exert profound effects on regulating skeletal muscle regeneration and myogenesis. This study aimed to discover the regulatory function of important miRNA miR-200c-5p in skeletal muscle regeneration. In our study, miR-200c-5p increased at the early stage and peaked at first day during mouse skeletal muscle regeneration, which was also highly expressed in skeletal muscle of mouse tissue profile. Further, overexpression of miR-200c-5p promoted migration and inhibited differentiation of C2C12 myoblast, whereas inhibition of miR-200c-5p had the opposite effect. Bioinformatic analysis predicted that Adamts5 has potential binding sites for miR-200c-5p at 3’UTR region. Dual-luciferase and RIP assays further proved that Adamts5 is a target gene of miR-200c-5p. The expression patterns of miR-200c-5p and Adamts5 were opposite during the skeletal muscle regeneration. Moreover, miR-200c-5p can rescue the effects of Adamts5 in the C2C12 myoblast. In conclusion, miR-200c-5p might play a considerable function during skeletal muscle regeneration and myogenesis. These findings will provide a promising gene for promoting muscle health and candidate therapeutic target for skeletal muscle repair. Skeletal muscle, as the largest organ, occupied a profound role in the maintenance of physiological characteristics and homeostasis in mammals [1,2]. As is known, some factors, such as injury, stress, and exercise, can easily cause skeletal muscle damage [3]. After injury, skeletal muscle displays a remarkable regenerative capacity, which induces damaged parts to self-renew for repair [4,5]. However, it is incompletely clear for understanding the complex biological process of myogenesis and muscle regeneration. Therefore, exploring the regulatory factors and mechanisms of skeletal muscle regeneration is vital for the treatment of muscle health. So far, emerging studies have suggested that non-coding RNA affects skeletal muscle regeneration and myogenesis by regulating gene expression [6,7], such as microRNAs (miRNAs) [8,9], lncRNAs [10,11] and circRNAs [12,13,14]. Notably, miRNA is an important transcriptional or post-transcriptional regulator, exerting a crucial role in skeletal muscle regeneration and myogenesis. For example, down-regulated miR-204 enhances C2C12 myoblast proliferation and migration promoting skeletal muscle regeneration [15], and knockout of miR-223-3p results in impaired muscle regeneration [16]. As a new target, miR-155 affects the process of muscle regeneration by regulating the initial immune response [17]. Hence, miRNAs play profound effects concerning myocyte proliferation, migration, fusion, and differentiation in skeletal muscle regeneration. Our previous study has indicated that several miRNAs are differently expressed and involved in the regulation of skeletal muscle repair, especially miR-743a-5p [18]. In addition, miR-200c-5p is one of the important members belonging to the miR-200c family, the family closely associated with the proliferation, migration, and invasion of tumors and cancer cells. In particular, miR-200c-5p is considered as a new marker for the diagnosis of lupus nephritis [19]. In addition, miR-200c-5p has been identified as a prognostic indicator and therapeutic target for human hepatocellular carcinoma (HCC) patients [20]. Furthermore, researchers have demonstrated that miR-200c-5p inhibits the proliferation and metastasis of HCC via inhibiting the target gene MAD2L1 [21]. However, there are few reports on the roles of miR-200c-5p in skeletal muscle regeneration and myogenesis. In this study, we aim to elucidate the regulatory role of miR-200c-5p in skeletal muscle regeneration. The microarray results showed that miR-200c-5p is significantly down-regulated during C2C12 myoblast differentiation and it is highly expressed in skeletal muscle. In the process of skeletal muscle regeneration, miR-200c-5p expression first increased and subsequently decreased. Further, miR-200c-5p can promote myoblast migration and inhibit C2C12 myoblast differentiation in vitro. Mechanically, miR-200c-5p regulates the migration and differentiation of C2C12 myoblast via targeting the Adamts5 gene in skeletal muscle regeneration and myogenesis. This study will develop a promising gene for promoting muscle health and candidate therapeutic target for skeletal muscle repair. In previous microarray data, we determined that 39 miRNA expression levels were significantly down-regulated during C2C12 differentiation (Figure 1A). Notably, some of the miRNAs have been reported to play important roles in skeletal myogenesis, such as miR-743-5p [18], miR-324-5p [22], and miR-499-3p [23]. Interestingly, GO analysis of Targetscan results showed that the predicted target genes of miR-200c-5p were involved in skeletal muscle regeneration and skeletal muscle fiber development (Figure S1A). Moreover, miR-200c-5p is specifically highly expressed in the skeletal muscle of mice (Figure 1B) and highly conserved among different species (Figure S1B). Based on these results, we constructed a mouse model of tibial anterior (TA) muscle injury to study the role of miR-200c-5p in skeletal muscle regeneration (Figure 1C). The H&E staining results showed that most muscle fibers were dissolved with the severe inflammatory response after the first to third day of injury. After the seventh day of injury, new muscle fibers were formed. After the 14th day the injury, muscle fibers were almost completely repaired (Figure 1D). In addition, Pax7 as a marker gene for myosatellite cell activation was highly expressed at the early stage and the marker genes for myogenic differentiation (MyoD, MyoG, and MyHC) were highly expressed at the late stage during skeletal muscle regeneration (Figure 1E). Notably, miR-200c-5p displayed a similar or opposite expression pattern with these marker genes (Figure 1F). These results indicated that miR-200c-5p may be an important potential regulator for skeletal muscle regeneration and myogenesis. The migration, proliferation, and differentiation of skeletal muscle satellite cells determine the ability of skeletal muscle regeneration [24]. The qPCR results showed that the miR-200c-5p mimics up-regulated the expression of myoblast migration marker genes (Figure 2A), while the expression level of these marker genes was down-regulated after miR-200c-5p was inhibited (Figure 2B). It indicates that miR-200c-5p regulated the expression of marker genes involved in migration. Consistently, the wound healing assay was performed to verify the role of miR-200c-5p in C2C12 myoblast migration. The results showed that the wound width of the miR-200c-5p mimic group was significantly shortened (Figure 2C,D), but the miR-200c-5p inhibitor group was significantly wider at 12 and 24 h after scratch treatment (Figure 2E,F). In addition, the transwell assay showed that the number of C2C12 myoblast passing through the membrane of the well increased significantly after transfecting with miR-200c-5p mimics after 12 h (Figure 2G,H). However, the number of C2C12 myoblasts was significantly decreased after miR-200c-5p was inhibited (Figure 2I,J). The mRNA and protein expression of marker genes Ki67 and Pcna involved in proliferation were not affected after miR-200c-5p was overexpressed (Figure S2A,C,E) and inhibited (Figure S2B,D,F) on C2C12 myoblast. Similarly, the CCK-8 assay also demonstrated no difference in the proliferation of C2C12 myoblast after transfecting with miR-200c-5p mimics and inhibitor at 24 h, 36 h, 48 h, and 72 h (Figure S2G,H). These results suggested that miR-200c-5p regulates the migration, but does not affect the proliferation of C2C12 myoblast. Next, we analyzed the effect of miR-200c-5p on C2C12 myoblast differentiation. We used horse serum to induce the C2C12 myoblast differentiation for 0, 3, 5, and 7 days (Figure 3A). During the differentiation of C2C12 myoblast, the expression of miR-200c-5p was gradually decreased, which displayed an opposite expression pattern with MyHC (Figure 3B). It is consistent with the results of the microarray. Based on these results, we speculated that miR-200c-5p might be related to the differentiation of C2C12 myoblast. To certify this hypothesis, miR-200c-5p mimics and inhibitor were transfected into C2C12 myoblast. The qPCR results showed that the expression of MyoG and MyHC were down-regulated under the overexpression of miR-200c-5p (Figure 3C), while knockdown of miR-200c-5p had the opposite effect (Figure 3D). Moreover, Western blot and immunofluorescence assays revealed that overexpression of miR-200c-5p inhibits MyHC protein expression (Figure 3E,F) and myotube formation (Figure 3I,J), while interference of miR-200c-5p on the contrary (Figure 3G,H,K,L). These results indicate that miR-200c-5p modulates the differentiation of C2C12 myoblast. MiRNA functions by regulating the expression of target genes at the transcriptional and post-transcriptional level [25]. Adamts5 and Plxdc2 were identified as potential targets for miR-200c-5p based on microarray analysis and bioinformatic prediction using miRDB, TargetScan, and miRMAP programs (Figure 4A). It is noted that only Adamts5 was highly expressed in the skeletal muscle of mice (Figure 4B), while Plxdc2 expression was low (Figure 4C). During the differentiation of C2C12 myoblast, Adamts5 displayed an opposite expression pattern with miR-200c-5p. However, Plxdc2 expression did not change significantly (Figure 4D). Subsequently, we transfected miR-200c-5p mimics and inhibitor into C2C12 myoblasts and detected the expression of the Adamts5 and Plxdc2 to further confirm the target gene. The qPCR results showed that Adamts5 was down-regulated and up-regulated under overexpression and knockdown of miR-200c-5p (Figure 4E,F), respectively. However, the expression of Plxdc2 was not affected by miR-200c-5p (Figure 4E,F). In addition, the RIP assay also showed that Adamts5 was significantly enriched in the miR-200c-5p overexpression group (Figure 4G,H), while Plxdc2 was not enriched (Figure S3A). Furthermore, the vectors containing the wild-type sequence (Adamts5-3’UTR-WT) or mutated seed sequence (Adamts5-3’UTR-MT) were constructed to perform dual-luciferase assay (Figure S3B). The luciferase activity of the wild-type vector was markedly reduced under miR-200c-5p overexpression, but no changes in the mutation-type group (Figure 4I). Moreover, the protein expression of Adamts5 was consistent with its changes at the mRNA level (Figure 4J,L). Hence, these results suggested that Adamts5 is a direct target for miR-200c-5p. In the process of regeneration following skeletal muscle injury, we determined that the expression of Adamts5 was first decreased and subsequently increased at both mRNA and protein level (Figure 5A,B). Next, we used functional gain and loss to study the effects of Adamts5 on the proliferation and migration of C2C12 myoblast. The qPCR results showed that the expression of myoblast migration marker genes was down-regulated under the overexpression of Adamts5 (Figure 5C). On the contrary, these marker genes were up-regulated after Adamts5 was knocked down (Figure 5D). In addition, the wound healing experiment showed that Adamts5 overexpression significantly slowed down the wound healing (Figure 5E,F), but knocking down Adamts5 accelerated wound healing at 12 h and 24 h (Figure 5G,H). The transwell assay further demonstrated that Adamts5 overexpression inhibited C2C12 myoblast passing through the membrane of well (Figure 5I,J), while Adamts5 knockdown had the opposite effect (Figure 5K,L). In addition, the effects of Adamts5 on the proliferation of C2C12 myoblast were investigated by qPCR, Western blot, and CCK-8 assays. We determined that both overexpression and knockdown of Adamts5 did not affect the proliferation of C2C12 myoblast (Figure S4). Therefore, these results suggested that Adamts5 regulates the migration of C2C12 myoblast, but does not affect its proliferation. Adamts5 expression was down-regulated in both microarray results and the process of C2C12 differentiation (Figure 4D). In the subsequent assays, the mRNA expression of MyoG and MyHC were up-regulated through Adamts5 overexpression (Figure 6A) and down-regulated via Adamts5 knockdown (Figure 6B). Moreover, Western blot and immunofluorescence assays also verified that the overexpression of Adamts5 can promote the protein expression of MyHC and myotube formation (Figure 6C,D,G,H), while Adamts5 interference had the opposite effect (Figure 6E,F,I,J). These results suggested Adamts5 is involved in the differentiation of C2C12 myoblast which was consistent with the previous reports [26]. To further determine whether miR-200c-5p regulates C2C12 myoblast migration and differentiation through targeting Adamts5, we conducted the co-transfection assay of Adamts5 overexpression vector with miR-200c-5p mimics and mimics-NC, respectively. The results showed that miR-200c-5p overexpression can rescue the effects of Adamts5 on the myoblast migration marker gene expression at the mRNA level (Figure 7A). The wound healing assay demonstrated that overexpression of Adamts5 slowed down wound healing, while this effect was reversed by miR-200c-5p mimics (Figure 7B,C). In addition, miR-200c-5p overexpression can counteract the promoting effect of Adamts5 on MyoG and MyHC expression in C2C12 myoblast (Figure 7D–F). Overall, these results confirmed that miR-200c-5p regulates the migration and differentiation of C2C12 myoblast via targeting the Adamts5 gene. In this study, we determined that miR-200c-5p regulates the proliferation, migration and differentiation of C2C12 myoblast by targeting Adamts5 in skeletal muscle regeneration and myogenesis. Skeletal muscle regeneration in response to pathological stress and remodeling processes is critical for maintaining homeostasis [4,27]. As one of the ways of post-transcriptional regulation, miRNAs play an efficient regulatory role in skeletal muscle regeneration [8,28]. Here, we determined a critical novel candidate miRNA miR-200c-5p through miRNA microarray of C2C12 myoblast differentiation. Similarly, Hiroyuki Shibasaki et al. also illustrated miR-188 differently expressed in skeletal muscle cell differentiation concerning skeletal muscle regeneration by microarray analysis [29]. Then, we identified miR-200c-5p as specifically highly expressed in skeletal muscle through tissue profile. Importantly, several miRNAs have been reported to play an important regulatory role in skeletal muscle regeneration and myogenesis, which are also special and highly expressed in skeletal muscle, such as miR-1 [30], miR-133 [31] and miR-206 [32]. Functional miRNA expression is different during the process of skeletal muscle regeneration. For example, miR-26a and miR-24-3p are down-regulated from the first to third days after injury, and then increased accompanied by skeletal muscle repair [33,34]. In our results, miR-200c-5p rapidly responded to skeletal muscle regeneration and its expression reached to peak on the first day after injury. Thus, these results initially reflected that miR-200c-5p was a potential regulator involved in skeletal muscle regeneration and myogenesis. Accumulating studies showed that miRNA can regulate C2C12 proliferation, migration, and differentiation, and then affect skeletal muscle regeneration. For example, miR-127 promotes the differentiation of C2C12 myoblast and myotube formation, enhancing skeletal muscle regeneration ability [35]. In addition, the miR-17-92 cluster affected mouse skeletal muscle regeneration by regulating C2C12 myoblast proliferation and myotube formation [36]. In our results, qPCR, CCK-8, wound healing, Western blot and transwell experiments showed that miR-200c-5p promoted migration and did not affect the proliferation of C2C12 myoblast, accordingly. Moreover, miR-200c-5p inhibited the differentiation of C2C12 myoblast, which was similar to the differentiation effects of miR-200c-3p in C2C12 myoblast [37] and buccal mucosal fibroblasts [38]. Thus, our results, combined with previous reports and studies, directly and indirectly indicated that miR-200c-5p plays a vital role in skeletal muscle regeneration. However, miR-200c-5p suppresses cell proliferation and migration in human HCC cells [21]. It is inconsistent with our results. Similarly, miR-200c-3p belonging to the miR-200c family inhibits the migration and invasion in retinoblastoma and renal carcinoma cells [39,40,41,42,43]. On the contrary, miR-200c-3p promotes endothelial cell migration in pancreatic cancer [44]. In addition, miR-378 promotes proliferation in skeletal muscle myoblast [45] while suppressing the proliferation, migration, and invasion of colon cancer cells [46]. Therefore, the biological function differences of miR-200c-5p may be attributed to various cell types. Above all, these results suggest that miR-200c-5p plays multiple functions in the skeletal muscle cells and is involved in the regeneration of skeletal muscle. MiRNA functions by targeting mRNA 3’UTR of target genes [47,48]. We demonstrated that Adamts5 is a target gene for miR-200c-5p by dual luciferase and RIP assays. Adamts5 is a new metalloproteinase belonging to the ADAMTS family [49], which is associated with tumor proliferation and migration. Abnormal expression of Adamts5 is an effective marker of lymphatic invasion and lymph node metastasis in colorectal cancer [50]. In lung cancer, the expression of Adamts5 is up-regulated, which can promote the migration and invasion of tumor cells [51]. In human glioblastoma, Adamts5 also promotes cancer [52,53]. However, our results showed that overexpression of Adamts5 inhibited the migration of C2C12 myoblast and did not affect the proliferation of C2C12 myoblast. The function of Adamts5 in the skeletal muscle cells is inconsistent with these reports. However the previous studies also reported that Adamts5 plays an anticancer role by inhibiting migration, invasion, and angiogenesis of gastric cancer cells (GC) [54]. Adamts5 can also inhibit HCC cell migration and blood vessel formations by down-regulating VEGF expression [55]. It suggests that Adamts5 has various effects on the proliferation and migration of different cell types. As known, regeneration occurs due to proliferating myoblast migrating to their respective sites and aligning and merging to form multinucleated muscle fibers by membrane–membrane fusion [56]. Interestingly, Adamts5 overexpression significantly increases the adhesion between GC cells and ECM, and inhibits GC cell migration and invasion [54]. Therefore, we inferred that Adamts5 resulted in increasing adhesion between myoblasts and the stromal layer, and thus hindered myoblasts migration. In addition, microarray data showed Adamts5 expression is up-regulated during C2C12 differentiation and subsequent experimental results also proved that Adamts5 can regulate the differentiation of C2C12 myoblast which is consistent with the previous report. Moreover, the researchers proved that Adamts5 promotes C2C12 myoblast differentiation by encoding versicanase, which hydrolyzes skeletal muscle extracellular matrix (ECM) and promotes contact between cell membranes [26]. This finding further implies that Adamts5 inhibits C2C12 myoblast by increasing the adhesion between the myoblast and the stromal layer. However, this hypothesis needs to be verified in future studies. In addition, we also determined that overexpression of miR-200c-5p reversed the effects of Adamts5 on migration and differentiation of C2C12 myoblast in rescue assay. Therefore, it is concluded that miR-200c-5p regulates the migration and differentiation of C2C12 myoblast by directly targeting Adamts5 in skeletal muscle regeneration and myogenesis. However, we lack the results of skeletal muscle regeneration and myogenesis in miR-200c-5p and Adamts5 knockout mice. In this way, the regulatory effects of miR-200c-5p and Adamts5 on skeletal muscle can be further consolidated. We will complete this work in the future study. Our experiment type is animal experiment, and we conducted experiments related to animals. Eight-week-old C57BL male mice were purchased from the Guangdong Vital River Laboratory Animal Technology Co., Ltd (Guangzhou, China). and allowed to adapt to the environment for one week before experiments. The number of mice is 50. The grade of mouse is SPF. The specification of mouse is 25–30 g. All mice were housed at 26 °C constant temperature and 60% relative humidity with a 12 h light/12 h dark cycle and free access to food and water. All experimental animal procedures in this study were performed according to the guidelines of Good Laboratory Practice, and the animals were supplied with nutritional food and sufficient water. Animal feeding and tests were conducted based on the National Research Council Guide for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee at Huazhong Agricultural University (protocol code SYXK(e)2020-0084). We selected C2C12 myoblast and 293T cell from American Type Culture Collection (ATCC) and C57BL mice for in vitro and in vivo experiments. Firstly, we are devoted to the study of skeletal muscle. C2C12 is a common cell line in the laboratory and the preferred model for the proliferation and differentiation of myoblasts in vitro. It has the characteristics of rapid proliferation and strong myogenic differentiation ability. C2C12 is widely used in the study of myogenesis and skeletal muscle development, such as skeletal muscle regeneration [57], muscle fiber type transformation [58], and energy metabolism [59]. It indicated that the results from C2C12 are reliable and universal. The transfection efficiency of 293T cells is very high, and it is often used in dual luciferase experiments to study the targeting relationship between miRNA and target genes [60,61]. Secondly, mice are common experimental animals with low feeding costs, high genetic similarity with humans, and fast reproduction. Moreover, C57BL mice are inbred mice, and the gene similarity between different individuals is as high as 98.6%. Therefore, the differences between individuals are small, the experimental error is small, too, and the experimental results are more reliable. The results of C57BL were reliable. In addition, the mice reached sexual maturity at 6 to 7 weeks of age. The life health index of 8-week-old mice is great and all organs are mature, including skeletal muscle, which is suitable for the study of skeletal muscle development. The tibialis anterior muscle of C57BL male mice was injected with 20 μL of 10 μM cardiotoxin (MedChemExpress, New Jersey, USA) as previously described. The treated samples were collected at 0, 1, 3, 5, 7, and 14 days after injection under sterile condition. The tibialis anterior (TA) muscle of mice was embedded with OCT and solidified at low temperature. The frozen sections were prepared into 10 μm and fixed with 4% paraformaldehyde (Beyotime, Beijing, China) for 30 min. Then, the sections were stained according to the instructions of the hematoxylin and eosin (H&E) staining kit (Solarbio, Beijing, China). Finally, the sections were observed and photographed under a microscope. C2C12 myoblast and 293T cells were purchased from American Type Culture Collection (ATCC). The growth medium was Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, California, USA) containing 10% fetal bovine serum (FBS, Gibco, California, USA) and 1% penicillin–streptomycin (PS, Thermo Scientific, Massachusetts, USA), and the differentiation medium was DMED medium containing 2% horse serum (Bioind, Shanghai, China) and 1% PS. Then, the cells were cultured in a 37 °C cell incubator with 5% oxygen and 95% carbon dioxide. The transfection reagent was Lipofectamine™ 3000 (Thermo Fisher Scientific, Massachusetts, USA), operated according to its instructions. pcDNA3.1-Adamts5, GLO-Adamts5-WT, and GLO-Adamts5-MT were synthesized by Gene Create (Wuhan, China). The control plasmid pcDNA3.1 was obtained from our laboratory. Adamts5 siRNA, siRNA-NC, all miRNA mimics, mimic NC, miRNA inhibitor, and inhibitor NC were obtained from RiboBio (Guangzhou, China). All sequences are provided in Table S1. Cells or tissues were lysed with Triol (Invitrogen, Shanghai, China), extracted with chloroform, and denatured with isopropyl alcohol to precipitate RNA, then washed with 75% and 100% ethanol, respectively, and finally dissolved with DEPC water. The RNA quality and quantity were checked by NanoDrop 2000 (Thermo Fisher Scientific, Massachusetts, USA). The qualified RNA can be used for further study. According to the instructions, HiScript III 1st Strand cDNA Synthesis kit (+gDNA wiper) (R312-01, Vazyme, Nanjing, China) and miRNA 1st Strand cDNA Synthesis Kit (MR101-01, Vazyme, Nanjing, China) were used for cDNA reverse transcription synthesis of mRNA and miRNA, respectively. In addition, mRNA qPCR was performed using Fast ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China) in a total reaction volume of 20 μL, including 10 μL 2 × SYBR Master Mix, 0.4 μL PCR Forward Primer, 0.4 μL PCR Reverse Primer, 2 μL cDNA, and 7.2 μL Sterile enzyme-free water. The reaction conditions were 95 °C for 30 s, then 95 °C for 10 s, and 65 °C for 30 s for 40 cycles; the reference gene was Gapdh. For miRNA, qPCR was performed using miRNA Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China); the reaction system was the same as that of mRNA qPCR. The reaction condition was 95 °C for 5 min, then 95 °C for 10 s, 65 °C for 30 s for 40 cycles; the reference gene was U6. The relative expression levels of mRNA and miRNA were analyzed by the 2-ΔΔCT method. The sequence information of primers (Sangon Biotech, Shanghai, China) used for reverse transcription and quantification is shown in Table S2. Protein lysate was used to lysate cells or tissues. The lysate consisted of RIPA buffer (Thermo Scientific, MA: Massachusetts, USA), phosphorylase inhibitor (Roche 5892791001, Basel, Switzerland), protease inhibitor (Roche 04693132001, Basel, Switzerland), etc. The concentration of the obtained protein was measured by the BCA kit of Biyuntian. Sodium dodecyl sulfate (SDS, CWBIO, Beijing, China) was added and denaturated at 100 °C for 20 min. The 8% and 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels (EpiZyme, Shanghai, China) were selected, and the sample size was 10 µL or 20 µL. After electrophoresis, the prefabricated adhesives were transferred to 0.45 μm Hybridization Nitrocellulose Filter (NC) membrane (Merck, New Jersey, USA), which was sealed with 5% skim milk powder, and then the primary and secondary antibodies were incubated. Primary antibodies Adamts5 (1:1000, Abcam ab41037, Cambridge, UK), KI67 (1:1000, Bioss bs-23102R, Beijing, China), PCNA (1:1000, Abcam ab18197, Cambridge, UK), MyHC (developmental myosin 1:1000, DSHB MF20, Iowa, USA) and Gapdh (1:1000, Abcam ab9482, Cambridge, UK) were diluted by 1× Tween (TBST) buffer (EpiZyme, Shanghai, China). Secondary antibodies were derived from rabbits and mice. ImageJ software (NIH, Bethesda, Maryland, USA) was used to analyze the gray value of protein bands. C2C12 myoblast was seeded into 6-well plates 24 h before transfection. After transfection, when cell confluence reached 90%, the cells were scratched along a straight line with a sterile 200 µL pipette tip. Then, the wounds were observed at 0 h, 12 h, and 24 h, and photographed with a 40x microscope (Olympus, Tokyo, Japan). C2C12 myoblast was replaced with 1% dual antibody medium without serum after transfection for 12 h, and then starved for 12 h. After digestion, 1 × 105 cells were transferred to the upper chamber of Transwell (Corning, New York, USA), and 500 µL DMEM medium containing 10% fetal bovine serum and 1% PS was added to the lower chamber. The upper chamber medium was 100 µL DEME medium containing 1% PS without fetal bovine serum. Then, the transwell upper chamber was taken out 12 h later, cleaned with PBS, fixed with 4% paraformaldehyde, and stained with DAPI. Finally, cell migration was observed under a 100x microscope, and statistical analysis was performed using Image J software. C2C12 myoblasts were seeded into 96-well plates and harvested at 0 h, 24 h, 36 h, 48 h, and 72 h after transfection, respectively. The proliferation of myoblasts was measured using the Cell Counting Kit-8 (CCK-8) (Beyotime C0038, Beijing, China). CCK-8 reagent and complete medium were added to the 96-well plate in a mixture of 1:9 and incubated at 37 °C for 40 h. Every sample’s optical density (OD) at 450 nm was measured with a microplate reader, and the growth curve was drawn. The differentiated myoblasts were fixed with 4% paraformaldehyde (Beyotime, Beijing, China) at room temperature for 30 min. The cells were penetrated with 0.5% Triton-100 (Sigma, Shanghai, China) for 30 min and blocked with 5% bovine serum albumin (BSA) (Biofroxx, Berlin, Germany) for 1 h at room temperature. The primary antibody (mouse anti-myosin, MF-20-S, DSHB (1:500)) was incubated for 2 h at room temperature. The second antibody (anti-mouse, FITC, Servicebio (1:500)) was incubated at room temperature and shielded from light for 1 h. Finally, the nuclei were stained with DAPI (Beyotime, Beijing, China) for 10 min and then observed and photographed with a fluorescence microscope. C2C12 myoblasts were seeded into a T75 cell culture flask and transfected with miR-200c-5p mimics, and harvested cells after 48 h. RIP experiment was conducted according to the guidance of the Magna RIP™RNA-Binding Protein Immunoprecipitation Kit (Millipore, Bedford, MA, USA), and miRNA was pulled with anti-Ago2 antibody (Abcam ab186733, Cambridge, UK). Enrichment multiples of miR-200c-5p, Adamts5, and Plxdc2 were detected by qPCR. 293T cells were seeded on a six-well plate and co-transfected miR-200c-5p and miR-200c-5p-NC with Glo-Adamts5-WT by using Lipofectamine™ 3000 (Thermo Fisher Scientific, Massachusetts, USA) at 80% cell convergence. Another group co-transfected miR-200c-5p and miR-200c-5p-NC with Glo-Adamts5-MT. After 48 h, the cells were analyzed using the Dual-Luciferase Reporter Assay System Kit (Promega, Wisconsin, USA) on a GloMaxTM 20/20 Luminometer (Promega, Wisconsin, USA). The target genes of miR-200c-5p in mice were predicted by online miRDB (http://mirdb.org/, accessed on 21 September 2020), TargetScan (http://www.targetscan.org/vert_71/, accessed on 21 September 2020), and miRMAP (https://mirmap.ezlab.org/app/, accessed on 21 September 2020). The fusion index was determined as the percentage of myonuclear in myotubes (defined as cells with two or more nuclei) in comparison with the total number of nuclei in the field and analyzed using the ImageJ software (NIH, Bethesda, Maryland, USA). Image J was used to analyze the gray values of the protein bands according to the “Mean = IntDen/Area (Mean: Mean gray value; IntDen: Integrated Density)” formula. The operation process of Image J is as follows: (1) Open file; (2) Image-transform-rotate; (3) Image-Type-8-bit; (4) Analyze-Gels-Select First Lane; (5) Analyze-Gels-Plot Lanes; (6) Measure: use the “Line tool” to close the opening of the peak, use the “Magic wand” to click the peak in turn to obtain the gray value of the protein bands. Image J was also used to count the number of cells migrating in transwell assay. Image Pro Plus software (Media Cybernetics, Texas, USA) was used to analyze the width of the wound in wound healing assay. GraphPad Prism 5.0 software (GraphPad Software, La Jolla, California, USA) was applied to all statistical analyses. All experiments were repeated at least three times. t-test and ANOVA were used to assess statistical significance, and p < 0.05 was considered statistically significant. The results are presented as mean ± S.E.M. * p < 0.05, ** p < 0.01, *** p < 0.001, p ≥ 0.05: ns (Not significant). In conclusion, we determined that miR-200c-5p up-regulates in the early stage of skeletal muscle regeneration in mice, promotes migration, and inhibits differentiation of C2C12 myoblast. Mechanically, we demonstrated that miR-200c-5p regulates regeneration by affecting migration and differentiation of C2C12 myoblasts via targeting Adamts5. Our findings provide new insights into the role of ADAMTS family genes in skeletal muscle regeneration and myogenesis. Further, our study develops a promising therapeutic target and candidate gene for the muscular disease and animal genetics and breeding.

PMC10003129

Lin Fu,Xiaotong Zhou,Qian Jiao,Xi Chen

The Functions of TRIM56 in Antiviral Innate Immunity and Tumorigenesis

06-03-2023

TRIM56,innate immune response,antivirus,tumor

As a member of the TRIM (tripartite motif) protein family, TRIM56 can function as an E3 ubiquitin ligase. In addition, TRIM56 has been shown to possess deubiquitinase activity and the ability to bind RNA. This adds to the complexity of the regulatory mechanism of TRIM56. TRIM56 was initially found to be able to regulate the innate immune response. In recent years, its role in direct antiviral and tumor development has also attracted the interest of researchers, but there is no systematic review on TRIM56. Here, we first summarize the structural features and expression of TRIM56. Then, we review the functions of TRIM56 in TLR and cGAS-STING pathways of innate immune response, the mechanisms and structural specificity of TRIM56 against different types of viruses, and the dual roles of TRIM56 in tumorigenesis. Finally, we discuss the future research directions regarding TRIM56.

The Functions of TRIM56 in Antiviral Innate Immunity and Tumorigenesis As a member of the TRIM (tripartite motif) protein family, TRIM56 can function as an E3 ubiquitin ligase. In addition, TRIM56 has been shown to possess deubiquitinase activity and the ability to bind RNA. This adds to the complexity of the regulatory mechanism of TRIM56. TRIM56 was initially found to be able to regulate the innate immune response. In recent years, its role in direct antiviral and tumor development has also attracted the interest of researchers, but there is no systematic review on TRIM56. Here, we first summarize the structural features and expression of TRIM56. Then, we review the functions of TRIM56 in TLR and cGAS-STING pathways of innate immune response, the mechanisms and structural specificity of TRIM56 against different types of viruses, and the dual roles of TRIM56 in tumorigenesis. Finally, we discuss the future research directions regarding TRIM56. The tripartite-motif (TRIM) family of proteins, also known as really interesting new gene (RING)-B-box-Coiled-Coil (RBCC) region proteins, is composed of an N-terminal RING structural domain, one or two B-box patterns, and an α-helical coiled-coil domain, followed by a highly variable carboxyl structural domain from the N-terminus to the C-terminus [1,2,3]. TRIMs are a large family of proteins, and approximately 80 members of the TRIM family have been identified in humans [4,5]. Based on the highly variable C-terminal structural domains, TRIMs with RING structural domains can be classified into subfamilies I to XI (C-I to C-XI). The variable C-terminal regions include the PRY structural domain, the SPRY structural domain, the COS structural domain, the fibronectin type III repeat region (FNIII), the acid-rich region (ACID), the Meprin and TRAF-homologous structural domain (MATH), the ADP-ribosylation factor family structural domain (ARF), the filamine-type IG structural domain (FIL), the NHL structural domain, the PHD structural domain, bromodomain (BROMO), and the transmembrane region (TM) [3,6,7]. TRIM family members are involved in a wide range of cellular activities and biological processes, including DNA damage repair [8], RNA binding [9], autophagy [1,10], apoptosis [11], cell cycle [12], viral infection [13,14], immune activation [7,15], inflammatory processes [16], stem cell differentiation [17], and neurogenesis [18,19]. The aberrant expression of TRIM family members leads to the development of various diseases, including tumors and neurological disorders [19,20,21]. TRIM56 is a member of the TRIM family. TRIM56 was originally reported to regulate the intracellular double-stranded DNA innate immune response [22]. In recent years, an increasing number of studies have shown that TRIM56 is involved in the host response to viral infection. On one hand, TRIM56 acts by regulating host innate immune signaling. TRIM56 is able to cause the transcriptional induction of pro-inflammatory cytokines and type I interferon (IFN) by regulating the toll-like receptor (TLR) signaling pathway and the cyclic GMP-AMP synthase (cGAS)-stimulator interferon gene (STING) signaling pathway to limit viral transmission [23,24,25,26,27]. On the other hand, as a direct antiviral restriction factor, TRIM56 has been shown to have a direct antiviral effect on positive single-stranded RNA viruses of the Flaviviridae, Coronaviridae, and Retroviridae families. In addition, it is also effective against negative single-stranded RNA viruses (influenza A and B) and two DNA viruses [28]. The expression level of TRIM56 is not consistent among different tumor types, and its expression changes are closely related to tumor development and prognosis. This suggests that TRIM56 may play different pro- or anti-cancer functions in different tumor types. In recent years, many studies have revealed the function of TRIM56 in tumor development. TRIM56 is an oncogene in glioma, breast cancer, and Kaposi’s sarcoma [29,30,31,32], but it is a tumor suppressor in ovarian cancer, multiple myeloma, lung adenocarcinoma, hepatocellular carcinoma, and leukemia [33,34,35,36,37]. Here, we first describe the structural features and expression characteristics of TRIM56. Next, we focus on reviewing the role of TRIM56 in innate immunity and antiviral processes. We also summarize the role of TRIM56 in tumors. Finally, we discuss the future directions of TRIM56 research. Reviewing the antiviral and tumor regulatory functions and specific mechanisms of TRIM56 is beneficial to provide new ideas for developing novel antiviral drugs and enriching therapeutic strategies against tumors. TRIM56, also known as Ring finger protein 109 (RNF109), is an 81 kDa protein of 755 amino acids encoded by the TRIM56 gene on human chromosome 7. The protein contains three structural domains, a RING domain, a B-box domain, and a coiled-coil domain (Figure 1). Because it lacks a C-terminal structural domain, TRIM56 belongs to the C-V subfamily. The RING structural domain is a unique linear sequence of cysteine and histidine residues in a zinc finger structural domain that forms the catalytic center of the ubiquitinating enzyme. Ubiquitination is a very important post-translational modification process that plays roles in innate immune and tumorigenic development [38,39,40]. Ubiquitin is a 76-residue polypeptide. The key enzymes required for the ubiquitination process are ubiquitin-activating enzyme E1, ubiquitin-binding enzyme E2, and ubiquitin-ligase E3 [41]. Among them, E3 ubiquitin ligase can catalyze the covalent binding of ubiquitin molecules to substrates. E3 ubiquitin ligases can be classified into several groups according to their specific structural domains: the RING family, the family of homologous to E6AP C-terminus (HECT), RBR E3s, and those of unclassified type [42]. As we mention above, most members of the TRIM family have a RING structural domain, and most TRIM members have been identified as functional E3 ubiquitin ligases [43]. Notably, a few TRIM proteins do not contain any RING domain, such as TRIM14 and TRIM66 [6]. The B-box structural domain consists of small peptide sequences that contain finger-like protrusion. Although the B-box structural domain also contains a “zinc finger” structure, it generally does not exert E3 ubiquitin ligase activity. There are two distinct isoforms of the B-box, B-box1 and B-box2. Most TRIM proteins contain one B-box2 structural domain or two B-box structural domains, while a few TRIMs, such as TRIM69, do not have either structural domain [44]. The B-box structural domain is thought to be involved in the recognition of target proteins by TRIM proteins [4]. The coiled-coil structure domain of TRIMs can serve as a scaffold for mediating the homomeric and heteromeric assembly of TRIMs and other proteins. Additionally, it also exhibits enzymatic or nucleic acid binding activity [21,45]. TRIM56 can act as an E3 ubiquitin ligase that catalyzes the ubiquitination of Vimentin, DVL2 (Dishevelled-2), ERα, SAP18 (Sin3A associated protein 18), IκBα, STING, cGAS, and TGF-β-activated kinase 1 (TAK1) [23,31,32,33,36]. Interestingly, TRIM56 also has deubiquitinating enzyme activity and the ability to bind RNA [29,30,46]. The relationship between the exertion of these functions and the structure needs to be further investigated. TRIM56 is widely expressed in various tissues of adult mammals [47]. Similar to many other TRIM proteins, the expression of TRIM56 is regulated by type I IFN. The expression level of TRIM56 was significantly upregulated in cells after type I IFN treatment [22,48]. There are differences in the subcellular distribution of TRIM proteins [49]. Some TRIM proteins are widely distributed in the cytoplasm and nucleus, such as TRIM30 and TRIM32. Some are only present in the nucleus, such as TRIM19, and some are only present in the cytoplasm, such as TRIM29. In resting cells, the TRIM56 protein is only present in the cytoplasm and thus interacts with cytoplasmic proteins [47]. TRIM family members have direct and indirect antiviral effects, including direct interactions with virus-associated proteins or nucleic acids, or modulation of antiviral signaling pathways associated with host immune function [15]. In recent years, numerous studies have demonstrated that TRIM56 exerts antiviral effects. TRIM56 can affect viral replication by modulating signaling pathways of the innate immune response. In addition, TRIM56 can directly target viral components to affect viral replication or inhibit their function, thereby exerting antiviral effects. Here, we summarize the studies on the interaction between the TRIM56 protein and viruses, in particular the role of TRIM56 in the signaling of the innate immune response and the direct interaction between TRIM56 and viruses. Innate immunity is the first line of defense against pathogen invasion. Upon pathogen invasion, pathogen-associated molecular patterns (PAMPs) are recognized by the pattern recognition receptors (PRRs) of innate immune cells, including retinoic-acid inducible gene-I (RIG-I)-like receptors (RLRs), TLRs, and cell membrane DNA receptors [50,51]. The triggering of PRRs ultimately leads to the activation of various signaling pathways and the transcriptional induction of pro-inflammatory cytokines and type I IFN to limit viral transmission [52,53]. Type I and type III IFNs are potent antiviral agents. They efficiently induce the production of hundreds of interferon-stimulated genes (ISGs) via the JAK-STAT signaling pathway, establishing an antiviral state by controlling and limiting viral infection and replication [54]. By modulating the innate immune response signaling pathway, TRIM56 can regulate downstream interferons and ISGs to precisely exert antiviral immune responses (Figure 2). TLRs are the first-known PRRs capable of recognizing extracellular viral components that enter the cytoplasm by phagocytosis or endocytosis to induce type I IFN (IFN-I) and pro-inflammatory cytokines to counteract viral invasion. The TLR family contains 13 members [55]. Upon activation, all TLRs, except for TLR3, recruit adaptor molecule myeloid differentiation factor 88 (MyD88), which recruits kinase IL-1 receptor-associated kinase 1/4 (IRAK1/4) and E3 ubiquitin ligase TNF receptor-associated factor 6 (TRAF6). TRAF6 catalyzes its own ubiquitination. Ubiquitinated TRAF6 recognizes TAK1/MAP3K7 binding protein 2 (TAB2) and activates TAK1, ultimately leading to the activation of IκB kinase α/β/γ (IKKα/β/γ) and NF-κB [56,57]. TRIM56 catalyzes the M1-type ubiquitination modification of TAK1, which enhances the interaction of the TAK1-IKKα complex. The overexpression of TRIM56 enhances the TNF-α-induced activation of NF-κB signaling, whereas the knockdown of TRIM56 has the opposite effect. The C-terminus is the binding region of TRIM56 to TAK1, while the RING structural domain of TRIM56 is the active region of the E3 enzyme and is important for the ubiquitination of TAK1 [23]. Unlike other TLRs, TLR3 uses adaptor Toll-IL-1 receptor (TIR) domain-containing adaptor inducing IFN-β (TRIF) and then activates IRF3 via TBK1/IKKε-mediated phosphorylation. Phosphorylated IRF3 forms a dimer and then translocate to the nucleus, initiating IFN-I expression [58]. TRIM56 was found to interact with TRIF, which positively regulates the TLR3-mediated interferon pathway. This mechanism is independent of E3 ligase activity. The deletion of the C-terminus of TRIM56 abolished TRIM56-TRIF interaction and the enhancement of the TLR3-mediated IFN response [24] (Figure 2A). Furthermore, the overexpression of TRIM56 inhibits PEDV replication by positively regulating the TLR3-mediated antiviral signaling pathway [59]. cGAS, also known as MB21D1/C6orf150, is considered to be one of the most important cell membrane DNA sensors [60]. Upon recognition of viral DNA, cGAS synthesizes a second messenger molecule, cyclic GMP-AMP (cGAMP), which binds and activates STING and the transfer of STING from the endoplasmic reticulum (ER) to the Golgi apparatus via COPII-mediated vesicles [61]. Activated STING recruits and activates TBK1 and IKKβ, which promote the nuclear import of IRF3 and NF-κB, respectively, ultimately producing IFN-I and pro-inflammatory cytokines [62,63]. TRIM56 induces the Lys335 monoubiquitination of cGAS, resulting in a marked increase in cGAMP production, STING dimerization, and DNA-binding activity. TRIM56-deficient cells are defective in cGAS-mediated IFNα/β production during herpes simplex virus-1 (HSV-1) infection [25]. Tsuchida et al. found that the overexpression of TRIM56 enhanced IFN-β promoter activation after double-stranded DNA stimulation. TRIM56 interacts with STING and uses it as a substrate for lysine 63-linked ubiquitination. This modification induces STING dimerization, which recruits antiviral kinase TBK1 and induces IFN-β [22]. Ubiquitin regulatory X domain-containing proteins 3B (UBXN3B) can positively regulate STING signaling. Sting-/- mice and Ubxn3b-/- mice are highly susceptible to lethal HSV-1 and vesicular stomatitis virus (VSV) infections. UBXN3B interacts with STING and its E3 ligand TRIM56 and promotes STING ubiquitination, dimerization, translocation, and the subsequent recruitment and phosphorylation of TBK1 in the innate immune processes [26]. However, recent studies have shown that TRIM56 does not directly ubiquitinate STING. Wang et al. found that TRIM56 cannot add ubiquitinated signals to STING proteins using a two-step immunoprecipitation method. This suggests that TRIM56 may ubiquitinate a protein that can bind STING, rather than STING itself [64]. TRIM56 synthesizes ubiquitin chains that bind to NF-κB essential modifier (NEMO) and mediates the ubiquitination of NEMO to activate IKKβ, which is required for the activation of TBK1 and NF-κB [27,65] (Figure 2B). In the future, as technology advances, we believe that the relationship between TRIM56 and STING will eventually be determined. IFN exerts its antiviral effect by inducing the expression of hundreds of ISGs [66]. After IFNα treatment, Kane et al. found that the overexpression of TRIM56 increased the expression of many ISGs. In this way, TRIM56 could suppress the expression of late HIV-1 genes, thereby establishing an anti-HIV status [67]. In addition, the overexpression of TRIM56 greatly enhanced extracellular the dsRNA-induced expression of IFN-β and ISGs, whereas the knockdown of TRIM56 severely impaired IRF3 activation, IFN-β and ISGs induction, the establishment of the antiviral state of TLR3 ligands, and severely impaired TLR3-mediated chemokine induction after hepatitis C virus (HCV) infection [24]. The known activity of ISGs is still insufficient to explain the antiviral effect of IFN, suggesting that more ISGs with antiviral activity need to be discovered. IFN-I itself enhances the expression of TRIM56 [22,48]. This suggests that TRIM56 is also a potential ISG. By inducing a positive feedback regulatory mechanism, TRIM56 plays an important role in the innate immune process. Viruses are a serious threat to the health of living organisms. TRIM56 can act as a direct antiviral restriction factor against many types of viruses, such as positive single-stranded RNA viruses, negative single-stranded RNA viruses, and DNA viruses (Table 1). The N-terminal protease (N(pro)) of bovine viral diarrhea virus (BVDV) is a proviral interferon antagonist capable of degrading interferon regulatory factor 3 (IRF3) via the proteasome. Although TRIM56 overexpression does not affect the protein levels of N(pro) and IRF3, it still interferes with BVDV replication. The anti-BVDV viral activity of TRIM56 is dependent on its E3 ubiquitin ligase activity and the integrity of its C-terminal region and is not due to a general enhancement of the interferon antiviral response [47]. TRIM56 does not improve cellular resistance to yellow fever virus (YFV), dengue virus serotype 2 (DENV2), or human coronavirus (HCoV) OC43. The anti-flavivirus (YFV, DENV2, and BVDV) function of TRIM56 requires the E3 ligase activity located in the N-terminal RING structural domain and the integrity of its C-terminal portion, whereas anti-HCoV-OC43 restriction only depends on TRIM56 E3 ligase activity. TRIM56 inhibits YFV, DENV2, and BVDV replication by impairing intracellular viral RNA replication, whereas it inhibits HCoV-OC43 progeny production later in the viral life cycle by targeting the viral packaging and release phase rather than intracellular viral RNA accumulation [68]. The above studies suggest that different structural domains of TRIM56 are adapted for different antiviral mechanisms. Zika virus (ZIKV) infection is associated with microcephaly and other neurological disorders and is a serious threat to human health [69]. TRIM56 acts as an RNA-binding protein and binds to ZIKV RNA in infected cells. A recombinant TRIM56 fragment consisting of 392 C-terminal residues is able to directly bind ZIKV RNA in vitro. The overexpression of TRIM56, but not the E3 ligase-activating mutant or mutants lacking the short C-terminal portion, inhibits ZIKV RNA replication [46]. Thus, the C-terminus of TRIM56 interacts with ZIKV RNA, while the RING structural domain inhibits viral RNA replication. Porcine epidemic diarrhea virus (PEDV) infection causes severe enteric disease in lactating piglets, resulting in significant economic losses to the swine industry [70]. TRIM56 expression levels were upregulated in cells infected with PEDV. The overexpression of TRIM56 increased the protein levels of TRAF3, a component of the TLR3 pathway, and upregulated IFN-β, ISG, and chemokine expression, which significantly activated downstream IRF3 and NF-κB signaling. The overexpression of TRIM56 inhibited PEDV replication, and the RING domain, N-terminal domain, or C-terminal portion of TRIM56 failed to inhibit PEDV replication [59]. Human immunodeficiency virus (HIV), also known as the AIDS virus, is a retrovirus that causes defects in the human immune system [71]. TRIM56 alters the release of HIV-1 [72]. TRIM56 enhances the induction of ISGs by IFNα and suppresses late HIV-1 gene expression [67]. TRIM56 exerts direct antiviral effects against several positive single-stranded RNA viruses, including members of the Coronaviridae family. 2019-nCoV belongs to the same family of coronaviruses as HCoV-OC43 and causes Coronavirus Disease 2019 (COVID-19). COVID-19 patients were found to have higher levels of TRIM56 expression. There was also a strong positive correlation between the expression levels of TRIM56 and VEGF [73]. This suggests that TRIM56 may have an anti-2019 nCoV function. The antiviral activity of TRIM56 is virus-specific. TRIM56 was reported to be resistant to only seven positive single-stranded RNA viruses, including Flaviviridae YFV, DENV2, ZIKV, and BVDV; Retroviridae HIV-1; and OC43 and PEDV of the Coronaviridae family (Table 1). The overexpression of TRIM56 did not inhibit two positive single-stranded RNA viruses, encephalomyocarditis virus (EMCV) and HCV [47,68]. Whether TRIM56 affects other positive single-stranded RNA viruses remains to be investigated. Interestingly, the viral functions of anti-positive single-stranded RNA viruses are all dependent on the E3 ligase activity of TRIM56 [47,68]. Therapeutic approaches for influenza remain very limited, and genetically mutated drug-resistant influenza virus strains often emerge [74]. Understanding novel virus–host interactions that alter influenza virus adaptations may reveal new targets/approaches for therapeutic intervention [75]. TRIM56 is able to specifically inhibit the RNA synthesis of influenza A and B viruses (Table 1). Interestingly, anti-influenza virus activity was not associated with E3 ligase activity, or B-box or coiled-coil structural domain. In contrast, the deletion of the 63-residue long C-terminal tail of TRIM56 abolished the antiviral function. In addition, the expression of this short C-terminal tail was as effective as full-length TRIM56 in inhibiting influenza virus replication [76]. The antiviral activity of TRIM56 is virus-specific. The overexpression of TRIM56 has been reported not to inhibit three negative single-stranded RNA viruses, VSV, Sendai virus, and human parapneumovirus [47,76]. Whether TRIM56 affects other negative single-stranded RNA viruses remains to be investigated. TRIM56 expression is upregulated in IFN-treated HepG2 cells and Hepatitis B virus (HBV)-infected liver tissue. TRIM56 inhibits HBV replication with its RING and C-terminal structural domains. The C-terminal structural domain is essential for TRIM56 translocation from the cytoplasm to the nucleus during HBV infection (Table 1). TRIM56 ubiquitinates IκBα using the RING structural domain. This modification induces the phosphorylation of p65, which subsequently inhibits HBV core promoter activity, leading to the inhibition of HBV replication [77]. TRIM56 also promotes IFNα/β expression levels via the cGAS-STING signaling pathway and inhibits the replication of double-stranded DNA virus HSV-1 [25]. TRIM56-deficient mice show impaired production of IFNα/β and high susceptibility to lethal HSV-1 infection, but not to influenza A virus infection, because cGAS-STING-mediated immune responses are only directed against dsDNA and not against RNA viruses such as influenza A virus [25] (Table 1). The hallmark of Salmonella typhi infection is an acute intestinal inflammatory response, which is mediated by the action of secreted bacterial effector proteins [78]. Inflammation-promoting Salmonella effector SopA is an E3 ligase similar to HECT [79,80]. By targeting TRIM56 and TRIM65, SopA can stimulate innate immune signaling with two innate immune receptors, RIG-I and MDA5, respectively [69]. However, Fiskin et al. proposed the opposite mechanism. They found that endogenous TRIM56 and TRIM65 protein levels decreased under standard Salmonella infection conditions. SopA inhibited TRIM56 E3 ligase activity by occluding the E2 binding surface of TRIM56. At the same time, SopA ubiquitinates TRIM56, leading to proteasomal degradation during infection [81]. Whether TRIM56 plays a role in other types of bacterial infections remains to be investigated. By regulating various signaling pathways and proteins in an E3 ligase-dependent or -independent manner, TRIM56 plays different roles in different tumors. It inhibits ovarian cancer, multiple myeloma, lung adenocarcinoma, hepatocellular carcinoma, and leukemia; however, it promotes the development of glioma, breast cancer, and Kaposi’s sarcoma (Figure 3 and Table 2). Ovarian cancer is a gynecologic oncologic disease and one of the major female lethal cancers [82]. Epithelial-to-mesenchymal transition (EMT) leads to tumor metastasis, which accelerates tumor progression [83]. Vimentin is an important protein that regulates EMT and cancer progression in ovarian cancer [84]. TRIM56 is able to ubiquitinate and downregulate Vimentin. The TRIM56 inhibition of ovarian cancer migration and invasion in vitro occurs via an inhibitory effect on Vimentin [33]. TRIM56 expression is post-transcriptionally regulated at the translational level by RNA-binding protein poly r(c)-binding protein 1 (PCBP1) [85]. PCBP1 promotes ovarian cancer migration and invasion in vitro by inhibiting TRIM56 translation, reducing its protein levels, thereby inducing Vimentin expression [33,85]. Multiple myeloma (MM) is a group of plasma cell malignancies characterized by the extensive clonal proliferation of tumor plasma cells in the bone marrow [86]. MM accounts for approximately 10% of hematologic neoplastic diseases [87]. The bone marrow microenvironment and cytokines such as interleukin (IL)-6 and TNF (tumor necrosis factor)-α play an important role in the growth and survival of MM cells and are associated with the clinical presentation and prognosis of MM [88]. The expression of TRIM56 is significantly decreased in MM cells. TRIM56 inhibits cell proliferation and produces inflammatory cytokines by activating the TLR3/TRIF signaling pathway [34]. Huang et al. found that cell lines from early MM patients showed upregulated miR-9 expression, which promoted MM cell proliferation and reduced apoptosis. TRIM56 is a target protein of miR-9 that reverses miR-9-mediated proliferation and anti-apoptotic effects. Thus, miR-9 promotes MM development and progression with the regulation of the TRIM56/NF-κB pathway [89]. Lung cancer is the most common and lethal malignancy, with lung adenocarcinoma accounting for up to 40% of cases [90]. The reduced expression of TRIM56 in lung adenocarcinoma is associated with poor prognosis. The overexpression of TRIM56 inhibits the invasion and migration of lung adenocarcinoma cells [35]. In the treatment of advanced lung cancer, immunotherapy has achieved some success, but the problem of immunotherapy resistance cannot be ignored [91,92]. Exosomal circZNF451 was upregulated in patients with progressive disease compared with lung adenocarcinoma patients in partial remission after PD1 blockade therapy and was associated with a poor clinical prognosis. Exosomal circZNF451 was able to target RNA-binding protein FXR1 in macrophages and promote the ubiquitination of FXR1 via the E3 ubiquitin ligase TRIM56, which in turn activated the ELF4-IRF4 pathway, leading to M2 polarization and suppressive immune microenvironment in macrophages. Exosomal circZNF451 inhibits anti-PD1 therapy in lung adenocarcinoma by polarizing macrophages in complex with TRIM56 and FXR1 [93]. Thus, TRIM56 may serve as a potential therapeutic target and a novel predictive marker for PD1 inhibitor resistance in lung cancer. DVL2 is a key regulator of Wnt signaling, which stabilizes β-catenin by catabolizing the APC/Axin/CK1α/GSK3β degradation complex [94]. DVL2 expression levels are closely correlated with Wnt activity and tumor progression [31,95]. The TRIM56-mediated degradation of DVL2 inactivates Wnt signaling and thus inhibits tumor development. Nuclear paraspeckle assembly transcript 1 (NEAT1) localizes to the nucleus and is able to inhibit AML stem cell self-renewal and leukemogenesis by activating Wnt signaling [36]. Alternative splicing (AS) often alters the function of proteins, which in turn affects tumor development [96]. However, heterodimer NEAT1 is localized in the cytoplasm and is able to interact with TRIM56 and DVL2 by enhancing TRIM56-mediated DVL2 degradation, thereby inactivating Wnt signaling [36]. Targeting DVL2 using TRIM56- or DVL2-interacting NEAT1 truncators may be a potential strategy for the treatment of AML. Yang et al. found that downregulated TRIM56 in hepatocellular carcinoma (HCC) patient samples was strongly associated with pathological stage and prognosis [37]. TRIM56 negatively regulated key genes in Wnt signaling, β-catenin, c-Myc, RBM24, MMP-9, and cyclin D1, as well as Wnt. Among them, RBM24 was shown to be a downstream target gene of TRIM56. The overexpression of TRIM56 inhibited cell proliferation, whereas the knockdown of TRIM56 had the opposite effect. TRIM56 inhibited HCC proliferation by inactivating Wnt signaling and targeting RBM24 [37]. Hepatocellular carcinoma has been associated with viral infections of type B and C [97]. TRIM56 can inhibit the replication of HBV [77]. In addition, TRIM56 was able to promote the induction of TLR3-mediated chemokines after HCV infection [24]. TRIM56 expression is significantly increased in glioblastoma tissues and cell lines. High TRIM56 expression is associated with a poor prognosis in glioma patients [29,30]. TRIM56 can downregulate the ubiquitination level of cIAP1, thereby reducing the degradation of cIAP1 [30]. cIAP1 belongs to the inhibitors of apoptosis (IAP) family, which regulates the cell cycle and tumor development [98]. Several studies have shown that cIAP1 is highly expressed in various human cancers and plays a key oncogenic role [98,99]. In glioma, TRIM56 does not function as an E3 ligase but as a deubiquitinating enzyme to stabilize the expression of apoptosis inhibitor cIAP1, thereby promoting glioma progression [30]. Recurrent glioblastoma is characterized by resistance to radiotherapy or chemotherapy. TRIM56 increases FOXM1 protein levels and enhances FOXM1 by means of deubiquitination. TRIM56 inhibits the radiosensitivity of human glioblastoma by regulating FOXM1-mediated DNA repair. Targeting TRIM56 may be an effective approach to reverse radioresistance in glioblastoma recurrence [29]. Interestingly, TRIM56 in gliomas function as deubiquitinating enzymes rather than E3 ligases. Breast cancer is the most common cancer in women worldwide [100,101]. The knockdown of TRIM56 enhances the proliferation and metastasis of breast cancer cells. The expression of TRIM56 is positively correlated with ERα and PR in breast cancer samples and is associated with poor prognosis in patients treated with endocrine therapy. Approximately 60–70% of breast cancer patients are Erα-positive [102]. Estrogen-selective modulators, such as tamoxifen, are emerging as effective agents for controlling ERα breast cancer progression [103]. However, tamoxifen resistance develops during long-term treatment and cancer progression [104]. TRIM56 catalyzes the formation of K63-linked polyubiquitin chains of ERα, thereby prolonging the stability of the ERα protein [31]. Breast cancer proliferation requires transduction via the ERα signaling pathway. Therefore, TRIM56-targeted therapy may address treatment resistance, thereby inhibiting cancer cell proliferation. Kaposi’s Sarcoma (KS) is a common AIDS-associated cancer caused by KS-associated herpesvirus (KSHV) infection [105]. KSHV encodes viral FLICE inhibitory protein (vFLIP), a viral oncogenic protein. vFLIP promotes cell migration, invasion, and angiogenesis by downregulating the SAP18-HDAC1 complex. Specifically, vFLIP degrades SAP18 via the ubiquitin–proteasome pathway by recruiting E3 ubiquitin ligase TRIM56, which ultimately activates the NF-κB signaling pathway [32]. Interestingly, KSHV is closely associated with the development of KS, primary exudative lymphoma (PEL), and other diseases [106]. Moreover, the deletion of the TRIM56 gene has been found in PEL patients [107]. The relationship between TRIM56 and KSHV, and KSHV-related tumors needs to be further investigated. TRIM56 is aberrantly expressed in a variety of tumors. TRIM56 was lowly expressed in multiple myeloma [88], ovarian cancer [85], lung adenocarcinoma [35], and hepatocellular carcinoma [37]. TRIM56 was highly expressed in glioma [29,30]. Furthermore, by analyzing the data in the TCGA database, we found that the expression levels of TRIM56 were significantly low in lung squamous cell carcinoma, uterine corpus endometrial carcinoma, and uterine carcinosarcoma, and significantly high in pancreatic adenocarcinoma, glioblastoma, lower-grade glioma, and thymoma [108] (Figure 4). In addition to the above tumors, TRIM56 was highly expressed in living patients with muscle-invasive bladder cancer (MIBC) [109]. The function and regulatory mechanisms of TRIM56 in the above tumors remain to be investigated. In addition, the upstream regulatory mechanisms of TRIM56 are not well understood. In ovarian cancer, PCBP1 inhibits TRIM56 translation [85]. In multiple myeloma, mir-9 downregulates TRIM56 expression [89]. In lung adenocarcinoma, mir-542 and mir-627 have the potential to inhibit TRIM56 expression [35]. This review summarizes the role of TRIM56 in antiviral processes and the development of tumorigenesis. Elucidating the altered expression of TRIM56 and its potential mechanisms in the pathophysiology of cancer and other diseases may provide insights for the development of new and more effective therapeutic strategies. However, there are still no reports on the clinical applications of TRIM56 in small-molecule therapy. A further understanding of the crystal structure of TRIM56 and its ligand-binding complexes could refine the structure-based design for the development of specific small molecules targeting TRIM56, ultimately leading to therapeutic applications. As an E3 ubiquitin ligase, TRIM56 catalyzes the ubiquitination modification of substrates [23,26,31,32,33,36,61,77]. The fate of the substrate protein depends on the lysine used to form the ubiquitin molecule of the heteropeptide bond. Different ubiquitination chain lengths (monoubiquitination and polyubiquitination) and a wide variety of ubiquitination chain types (linked by Met1, Lys6, Lys11, Lys27, Lys29, Lys33, Lys48, and Lys63) play an extremely important role in protein activity, protein–protein interactions, and protein subcellular localization [39,110]. TRIM56 is able to catalyze the formation of K48, K63-linked, or M1-linked ubiquitination [111]. In addition, biological roles of TRIM56 independent of E3 ligases have been identified, including RNA binding and deubiquitinating enzyme activity [29,30,46]. The innate immune response is the first line of host defense and is characterized by the production of IFN-I and ISGs to limit viral infection and transmission [112,113,114]. Many studies have shown that TRIM56 plays a key role in the precise coordination of key signaling molecules and their associated pathways. Here, we discuss the current mechanisms regarding the involvement of TRIM56 in the regulation of TLRs, the cGAS-STING pathway, and downstream ISGs [23,26,61]. Whether TRIM56 regulates the RLRs pathway remains to be further investigated. In addition, TRIM56 is able to regulate innate antiviral signaling in a ubiquitination-independent manner, and the specific mechanisms of regulation remain to be explored. The C-terminal region of TRIM56 mediates protein–protein or protein–RNA interactions between TRIM56 and cellular viral proteins/RNAs and can inhibit viral RNA replication. In addition, the E3 ligase activity of TRIM56 may regulate post-translational modifications of viral proteins and/or host factors to inhibit the replication of positive-stranded RNA viruses. Although TRIM56 is widely expressed in many tissues, the highest expression levels of the protein were detected in the lung and stomach [47]. The presence of pathogenic microorganisms in the respiratory and gastrointestinal tracts, which are continuously exposed to the external environment, may account for the differences in tissue distribution [115]. TRIM56 has been reported to exert oncogenic or tumorigenic potential in solid tumors and hematological cancers [116,117]. The importance of exploring the function of TRIM56 in various malignancies comes not only from the understanding of the key mechanisms of tumor development but also from the important translational potential. In recent years, TRIM family proteins have made some progress in targeted cancer therapy, such as TRIM8-targeted approaches for chemotherapy-resistant colorectal cancer and TRIM24-targeted regimens for glioblastoma [118,119]. TRIM56 can affect tumor cell proliferation, apoptosis, and metastasis by regulating downstream molecules [29,30,31,32,33,34,35,36,37]. However, the effect of TRIM56 on tumor immunity is still unknown. TRIM56 can modulate the innate immune response and promote the production of type I IFNs and ISGs [23,24,25,26,27,65]. Notably, the innate immune response plays an important role in cancer immune escape [120,121]. Therefore, exploring the effect of TRIM56 on tumor immune response is a future research direction.

PMC10003131

Silvia De Siervi,Cristian Turato

Liver Organoids as an In Vitro Model to Study Primary Liver Cancer

25-02-2023

liver organoid,primary liver cancer,in vitro models

Primary liver cancers (PLC), including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are among the leading causes of cancer-related mortality worldwide. Bi-dimensional in vitro models are unable to recapitulate the key features of PLC; consequently, recent advancements in three-dimensional in vitro systems, such as organoids, opened up new avenues for the development of innovative models for studying tumour’s pathological mechanisms. Liver organoids show self-assembly and self-renewal capabilities, retaining essential aspects of their respective in vivo tissue and allowing modelling diseases and personalized treatment development. In this review, we will discuss the current advances in the field of liver organoids focusing on existing development protocols and possible applications in regenerative medicine and drug discovery.

Liver Organoids as an In Vitro Model to Study Primary Liver Cancer Primary liver cancers (PLC), including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are among the leading causes of cancer-related mortality worldwide. Bi-dimensional in vitro models are unable to recapitulate the key features of PLC; consequently, recent advancements in three-dimensional in vitro systems, such as organoids, opened up new avenues for the development of innovative models for studying tumour’s pathological mechanisms. Liver organoids show self-assembly and self-renewal capabilities, retaining essential aspects of their respective in vivo tissue and allowing modelling diseases and personalized treatment development. In this review, we will discuss the current advances in the field of liver organoids focusing on existing development protocols and possible applications in regenerative medicine and drug discovery. Numerous physiological, metabolic, and regulating processes, including bile secretion, glycogen and fat-soluble vitamin storage, drug detoxification, and the synthesis of plasma proteins and coagulation factors, are carried out by the liver [1]. As a result, pathogenic (genetic or acquired) alterations in liver tissue may have significant effects on an individual’s health. The basic hepatic structure consists of parenchymal cells, hepatocytes and cholangiocytes, and non-parenchymal cells, such as fibroblasts, stellate cells, Kupffer cells, and endothelial cells. In particular, hepatocytes, which are organized in lobules, account for more than half of total liver mass [2], while cholangiocytes are epithelial cells that line the bile ducts and the peribiliary glands and play an important role in the transport of bile constituents from the liver to the duodenum [3]. Primary liver cancers (PLC) are tumours that develop directly in the organ rather than as a result of metastasis [4] and include hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and combined hepatocellular-cholangiocarcinoma (CHC), a rare malignant neoplasm that shows features of both hepatocarcinoma and cholangiocarcinoma [5,6] (Figure 1). HCC, caused by a malignant transformation of the hepatocytes, accounts for about 85–90% of PLC cases and is one of the most common causes of cancer-related mortality worldwide [6,10]. The remaining 10–15% is represented by iCCA, which is less common than HCC and is caused by intrahepatic biliary tree epithelial alterations [6]. According to the site of origin, in addition to the aforementioned iCCA, CCA also includes a second form, the extrahepatic cholangiocarcinoma (eCCA), which develops outside liver parenchyma and is further classified as perilear cholangiocarcinoma (pCCA), accounting for 50% of cases, and distal cholangiocarcinoma (dCCA), observed in 30–40% of total CCA [11]. Infections with hepatitis B (HBV) and C (HCV) viruses, alcohol abuse (alcoholic liver disease, ALD), metabolic syndrome, obesity, type 2 diabetes (non-alcoholic fatty liver disease, NAFLD), and genetic or immune changes are among the main risk factors for the development of both HCC and CCA [12]. Other established and proven causes that contribute to the development of CCA are biliary tract diseases with resulting chronic infection, such as primary sclerosing cholangitis, cysts of the biliary duct, and parasitic infestations caused by trematodes [13]. The majority of patients receives diagnoses at an advanced stage of the disease, where there are limited and frequently inefficient treatment options, which contributes to the high mortality rate attributable to PLC [14]. Despite efforts, currently, there are no available treatments, and a large portion of the drugs tested over the past ten years are ineffective, failing to pass phase III of clinical trials [15]. The multikinase inhibitor Sorafenib [16] and the recently authorised Lenvatinib [17] are used as first-line therapeutic choices for HCC targeted therapy, while the only traditional first-line treatment option for patients with CCA at advanced stages of the disease is the combination of gemcitabine and cisplatin; otherwise, the use of folinic acid, fluorouracil, and oxaliplatin (FOLFOX) is used as CCA second-line treatment [18]. However, because of the limited efficacy of these options, there is an urgent need for new therapeutic strategies for PLC treatment. One of the most significant issues in the preclinical development of regenerative therapies is the lack of appropriate model-based systems that maintain the tumour’s morphologic and functional characteristics, such as three-dimensional architecture, cellular heterogeneity, and cell-cell interactions [19]. In this regard, reliable in vitro models are necessary to increase the knowledge of the molecular and cellular mechanisms underlying PLC progression and provide high-throughput experimental techniques to define biological processes and the efficacy of treatments [20]. As a result, in recent years, the limited clinical value of cell line translation has encouraged researchers to investigate other innovative models for PLC in vitro research. A few in vitro liver models that accurately mimic a working in vivo liver have been developed [21]. In this review, we aim to discuss the recent advances in the field of in vitro liver models with a major focus on liver organoids, a three-dimensional representation of the liver that exhibits accurate micro-anatomy and self-renewal capabilities [22]. In particular, we will analyse the potential innovative applications of liver organoids as a promising new tool for the study of the complexity of liver diseases and the discovery of novel therapies. We will also provide a detailed overview of current protocols and discuss potential novel approaches to address some of their limitations. Over the years, research has led to a greater understanding of crucial physiologic and pathological aspects of liver diseases. Overall, rodent models properly identified less than 50% of the therapeutic response and toxicity of clinically utilised drugs [22]. Therefore, in vitro human cell cultures are the most popular model for studying biological aspects of tumours [14,20], as well as pharmacological mechanisms, efficiency, and toxicity [22]. In the past and still today in vitro studies are based on the use of bi-dimensional cell lines (2D) derived from hepatoma and hepatocarcinoma, as well as 2D primary cultures, providing a useful tool for studying and characterizing molecular events at the base of disease onset and progression, and for obtaining information on the efficacy of treatments [23]. In particular, HepG2, a cell line derived from a liver biopsy of a Caucasian adolescent, is one of the most frequently employed preclinical experimental models for HCC research [14]. HepG2 exhibits typical hallmarks of a hepatic lesion, such as an increased α-fetoprotein (AFP) expression, and expresses distinct hepatic cell functions, such as glycogen synthesis, plasmatic protein and biliary acid synthesis, and cholesterol and triglycerides metabolization. Other cell lines commonly used in HCC research include HepaRG, which originated from a female with HCC, chronic HCV, and cirrhosis, and HuH-7, which are both viable models for studying drug metabolism and carcinogenesis [14]. On the other hand, in the last 40 years, more than fifty cell lines for CCA knowledge have been established [20]. The majority of preclinical research on CCA has been principally conducted in human eCCA cell lines, EGI-1 and TFK-1, and iCCA cells, RBE and HuCC-T1, derived from malignant ascites [20], all of which are representative of a single CCA subtype and thus insufficient for a comprehensive study of its molecular biology [13]. Although 2D cultures are still useful tools for biomarker discovery and drug screening, they have some significant limitations. At first, these cell lines grow in adhesion on a rigid surface with an elongated shape, creating a monolayer where interactions only occur between adjacent cells, and typical functions, such as signalling, proliferation, and migration, are altered [24]. Moreover, 2D cell cultures, which can only develop in two dimensions, have a higher proliferative capacity compared to in vivo conditions and are exposed to uniform concentrations of cell medium nutrients [25]. In addition, compared to patient-derived tissue, gene expression analysis of immortalized cell cultures revealed a significantly limited sensitivity to drug treatment that can easily induce apoptosis. This frequently results in incorrectly promising several molecules that, when tested in vivo, fail to provide the desired results [24]. As previously mentioned, another crucial model for research on PLC is the primary 2D human cell cultures, directly derived from cancer patients’ tissue samples, which were developed to overcome some limitations of the conventional cell lines [19]. Due to their ability to retain representative hepatocytes characteristics, such as expression levels of metabolizing enzymes and liver-specific markers, primary cultures represent a more reliable tool for in vitro research on hepatic metabolism, drug toxicity, and viral infections liver-related [26]. However, primary hepatocytes have a limited lifespan in culture, lasting only a few days, leading to a decrease in hepatic function in vitro [26] and necessitating the expensive donation of fresh material [19]. Additionally, the process of derivation of primary cultures is laborious since it is possible to detect an unwelcome increase in healthy cell fractions that must be eradicated [20]. Despite several advantages, such as easy reproducibility and cheaper costs, 2D cell techniques remain a too simplified model of tumour tissue, which is, instead, excessively heterogeneous and characterized by a complex and dynamic microenvironment [27]. In recent years, research has focused on developing three-dimensional (3D) cell models that may be derived from both patient biopsies and commercially available 2D cell lines described above. As shown in Table 1, in comparison to conventional 2D cell cultures, 3D systems provide a more accurate preservation of the in vivo conditions, processes, and microenvironment in which the tumour arises and develops [24], allowing the evaluation of several biological aspects, including proliferation, morphology, and cell-cell and cell-microenvironment interactions [14]. One of the first discovered 3D systems is represented by spheroid, a three-dimensional cellular aggregate with a spherical shape enriched in stem-like cell population but with too low complexity to mimic tumour organization [27]. Spheroids can be produced from primary cultures or cell lines that have been cultured as single or multi-cell suspensions [28]. To enable the development of floating spheres, the single-cell suspension is typically maintained in the absence of a matrix, in ultra-low attachment plates [29], and in serum-free conditions [28]. The use of spheroid is extensive and includes drug screening, immune interaction modelling [30], and the possibility of setting up co-culture systems with both healthy and cancerous cells, which aims to implement the understanding of angiogenesis and tumour metastatic mechanisms. Wang et al. developed efficient and reproducible agarose hydrogel microwells to produce uniform-sized multi-cellular tumour spheroids, which offer better mimicry of traditional solid tumours and allow the evaluation of some anti-cancer drug candidates’ effects, starting from cells of HCC-patients with abnormally high expression of fibroblast growth factor receptor 4 (FGFR4) [31]. In another study, liver spheroids were established from iCCA cell lines HuCC-T1, CCLP1, and CCA4 and then characterized, revealing an increased expression of key genes involved in self-renewal, drug resistance and survival, as well as stem-like surface markers [32]. Another viable 3D cell culture method is represented by scaffold-based systems, which embedded cells into a physical matrix, allowing them to aggregate, proliferate, and migrate [14]. Scaffolds are made up of a multitude of materials with varying porosity, permeability, and mechanical stability, to replicate the microenvironment of the extracellular matrix (ECM) of tissues and tumours [33]. Among different existent scaffolds, the distinctive hydrogels can mimic the characteristics of the ECM, allowing soluble factors like cytokines and growth factors to pass through the gel tissue-like support [34]. Hydrogels are incredibly adaptable since their preparation could differ depending on the experiment being conducted. There are both natural hydrogels that are typically made from natural polymers such as fibrinogen, collagen, hyaluronic acid, gelatin, and alginates, and synthetic hydrogel, made with polymeric materials with chemically defined bases, such as polyethylene glycol (PEG), polylactate (PLA), or polyvinyl alcohol (PVA) [24]. A natural hydrogel widely used in 3D cell culture is Matrigel. This is derived from secretions of the Engelbreth-Holm-Swarm murine sarcoma and appears as a soluble material rich in collagen IV, laminin, proteoglycans, soluble heparan, and entactin that can solidify at 37°C and mimic the properties of the base membrane matrix [35]. Recently, Turtoi et al. aimed to create a new 3D cell model of HCC, seeding HepG2 cells in a hyaluronic acid-based scaffold, in order to evaluate the cytotoxicity and apoptotic response to the anti-tumour agent cisplatin [36]. They demonstrated that the hyaluronic acid-based system allowed cells to proliferate into larger aggregates, showing liver-like functions, expressing main hepatocyte-specific biomarkers, such as albumin, bile acids, transaminases, and sensitizing the hepatocytes to the anti-tumour effect of cisplatin [36]. It also fabricated scaffolds for 3D culture models of CCA, using a CCA cell line (KKU-213A), by combining silk fibroin with hyaluronic acid, heparin sulfate, and gelatin, which could yield cancer stem cells and more accurately mimic tumour behaviour better than 2D systems, in terms of cell proliferation, microenvironment representation, and drug sensitivity [37]. Among other in vitro 3D models, there are 3D bioprinting, and organs-on-a-chip, which are both technologies derived from the combination of cell biology with engineering and biomaterials technology [14]. Cell models created with 3D bioprinting are innovative platforms based on the use of bioinks containing living cells, decellularized ECM constituents, nutrients, growth factors, and biomaterials with the purpose of engineering 3D constructs with tissue-like architecture [38,39]. As a result, bioprinting technology may create systems that successfully replicate the ECM, improving cellular proliferation rates and responses to chemotherapeutic drugs compared to conventional 2D models [40]. In a recent research, authors developed a 3D model with HepG2 cells, using 3D-bioprinting technology, in order to demonstrate the different effects and pharmacodynamics of some anti-tumour drugs between 2D and 3D HepG2-derived systems [41]. Moreover, Xie et al. proved that 3D bioprinted models are capable of performing drug screening through the establishment of patient-derived HCC hepatorganoids [42]. Current advances in 3D bioprinting technology have motivated bioengineers and scientists to also create methods for “printing” in vitro tumour-mimicking models in order to study the molecular mechanisms behind tumour growth. An example is represented by the bioprinter platform made by Li et al., which includes in a single system both RBE (an iCCA cell line) and stromal cells, including human umbilical vein endothelial cells (HUVEC), fibroblasts (CCC-HPF-1) and human monocyte leukaemia THP-1, demonstrating how stromal cells affected the proliferation, invasion, stemness, and drug resistance of CCA cells. As a result, this 3D bioprinted CCA model could be employed to more accurately mimic the tumour microenvironment, potentially serve as a robust, clinically accurate platform for preclinical research and drug testing, and offer a viable substitute for animal models [43]. Moreover, organ-on-a-chip models simulate real synthetic microenvironments, integrating living cells that can mimic the in vitro functions of an organ. New studies have successfully replicated the connection of several organ-on-a-chips to create body-on-a-chip models that represent multi-organ interactions and study the metastasis process in cancer in a more thorough manner [27]. In addition, in order to investigate the dynamic evolution of the tumour through proliferation, angiogenesis, and intravasation processes, vascularized tumour-on-a-chip models were created [44]. In contrast to traditional 2D models and animal testing, liver-on-a-chip technologies enable more effective management of the cellular microenvironment, increasing hepatocytes activity, simulating cellular responses to medicines in vivo, and more closely simulating liver physiology [45]. In one study, induced pluripotent stem cells were used to reconstruct the liver acinus, including its vascularized form, in conjunction with the pancreas and adipose tissue; additionally, fluorescent protein biosensors were added to the device to assess insulin resistance and the production of reactive oxygen species [46]. Thanks to this system, authors can investigate liver-specific biomarkers, identifying the progression from NAFLD to steatohepatitis within an experimental timeline [47]. Organoids are an in vitro 3D model that recapitulates some structures and functions of the corresponding in vivo organ, not visible in 2D cultures, derived directly from the dissociation of specialized epithelial tissues, from embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs), all capable of self-renewal and self-organization [48]. It has been discovered that organoids are a powerful system for studying development and regenerative processes as well as for understanding some diseases [49]. These models also provide new tools for translational research, making them a promise for drug development and personalized treatments [50]. Organoids offer the following several benefits: they combine the tractability of in vitro cell cultures with the architecture and differentiation of in vivo models, making them comparable to standard 2D cell lines in terms of long-term culturing, cryopreservation, and genetic manipulation [51]. Unfortunately, some significant restrictions on the use of organoids have been described, most of which are related to laborious protocols; for example, the development of tumour-specific organoids has only been successful in patients with highly differentiated tumours with high proliferative rates, ruling out the possibility of using patients who are still in the early stages of their disease [23]. Furthermore, because cancer is characterized by a heterogeneous TME, in which both cellular (epithelial cells, fibroblasts, stem cells, endothelial, and immune cells) and non-cellular (ECM, cytokines, chemokines, and growth factors) components are essential for the development and progression of the tumour, the lack of all of these components in a single 3D system represents a significant limitation [27,52]. However, despite the lack of reliable experimental protocols and the high cost of implementation, these 3D systems provide innovative tools for understanding the mechanisms underlying tumour progression. Furthermore, thanks to their ability to show high levels of genomic stability and mimic the heterogeneity observed in real tumours, organoids can be propagated for long periods with few genetic variations. Another aspect is the employment of organoids may decrease the requirement for using animal models and, thus, any associated animal ethics issues [53]. The first experiments that enabled the development of organoids were based on the isolation, from murine intestinal epithelium, of single leucine-rich repeat-containing G-protein-coupled receptors 5 (LGR5) positive adult stem cell, capable of self-renewing. These cells LGR5+ were placed in suspension, embedded in Matrigel with a medium containing a variety of growth factors, in order to mimic the combination of signals that persist in the niche, giving rise to three-dimensional structures with a total cytoarchitecture that is similar to that observed in vivo [54]. Following these unexpected extraordinary results, in recent years, organoids derived from various types of tumours have been described, including the brain [55], prostate [56], pancreas [57], colorectal [58], breast [59], bladder [60], and liver cancer [23,61,62], starting to embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs) and adult stem cells (ASCs) [27]. Huch and colleagues have reported the discovery of the first system of intestinal organoids obtained from epithelial biliary LGR5+ cells that were isolated from hepatic injury mice models and placed in a cultured medium enriched with R-Spondin 1 (R-Spo1) and Wnt3a, both WNT pathway activators [61]. The organoids thus obtained, termed cholangiocyte-derived organoids (chol-orgs), are an accurate in vitro model that captures the main characteristics of the biliary epithelium in vivo in terms of morphology, functions, and markers expression. However, they also exhibit higher levels of foetal markers and lower levels of mature markers, indicating a partial differentiation of the cholangiocytes [19]. In contrast to chol-orgs, recently it is developed hepatocytes-derived organoids (hep-orgs), organoids derived from primary hepatocytes, which exhibit phenotypic properties of hepatocytes more accurately in terms of molecular expressions of particular markers, as well as functional characteristics [63]. Using an appropriate differentiation medium that includes some new factors, such as fibroblast growth factor-19 (FGF-19), DAPT (a Notch inhibitor), and dexamethasone, chol-orgs at early passages may be differentiated into cells with a hepatocyte-like phenotype that are able to secrete albumin and carry out a variety of hepatic functions [19,53]. As a demonstration of the hepatoblasts’ bipotential plasticity, from a single subpopulation of LGR5+ cells, both chol-orgs and hep-orgs can be produced [25,64]. Moreover, the culture environment, both in terms of signalling and cell type, has a crucial role in the development and maintenance of organoids [65]. The organoids resulting from the hepatic tumour may be established by adult tissues surgically exported [62] or, more recently, by needle biopsies of patients affected by HCC, CCA, and CHC [23]. ESCs and iPSCs are alternative sources for the in vitro generation of organoid models [66]. During organoid formation, the starting cell population begins to assemble in a specific signalling environment, where it is necessary to provide signals related to liver development in order to trigger self-organization [25,64] (Figure 2). Human liver organoids from adult tissues need the identification of mitogenic signals through a variety of factors, including epithelial growth factor (EGF), fibroblast growth factor (FGF), and hepatocytes growth factor (HGF) [61,67,68]. Forskolin (FSK), an activator of cyclic adenosine monophosphate (cAMP) and the inhibitor of TGF-β signalling, A8301, are also added to the culture medium to allow long-term expansion [61,67]. A few days after seeding, ROCKi, an inhibitor of the Rho-associated kinase protein (ROCK), is added to the medium to prevent the apoptotic process [61,69] (Figure 2). In addition, as described by Peng et al. approach, liver-resident macrophages release large amounts of inflammatory cytokines, including TNF-α, following liver damage to help in regeneration; based on these findings, hepatocytes growth was certainly aided by the addition of 100 ng/mL TNF-α to the hep-orgs culture medium [70]. According to the protocols from Huch [61], Broutier [71], and Nuciforo [23] laboratories, all factors, with their respective concentrations, added to the culture medium for liver organoids development are illustrated in Table 2. For human organoids generation from iPSCs, changes in the culture medium were applied, with the WNT signalling inhibition [53], and the addition of different nutrients, such as activin A, bone morphogenic protein 4 (BMP4), and phosphoinositide 3 kinase inhibitor (PI3Ki) that help the differentiation of iPSCs through stages, resembling human liver during its embryonic development [66]. To differentiate the hepatic progenitors into hepatocytes, HGF and Oncostatin M were also added in the medium [72]. To allow three-dimensional suspension growth, it is necessary to provide the organoids with structural support using hydrogels such as Matrigel or Cultrex Basement Membrane Extract (BME) [19] (Figure 2). At the level of Disse space, hepatocytes are located near the ECM, linked to collagen type I, fibronectin, and laminin, affecting cell proliferation, differentiation, and migration. In particular, biochemical signals, such as the composition of the matrix, and mechanical properties, such as rigidity, act on the differentiation of the liver progenitor cells toward the hepatocytes or cholangiocytes lines [73]. For this reason, it is crucial to replicate both the biochemistry and the biomechanics of the native ECM of the in vitro liver tissue. As mentioned above, Matrigel has an advantageous protective complexity that enables it to mimic the structure of basal membrane; on the other hand, its murine origin has an elaborate process that results in elevated batch-to-batch variations in terms of composition and rigidity that interfere in vivo applications [73]. Recently, it has been discussed new approaches that could replace the use of Matrigel with alternative biological hydrogels that are appropriate from a chemical and physical standpoint in the regulation of mechanical properties [74]. Based on these findings, it is possible to intervene by altering the component ratio of miscellaneous components or by reinforcing sticky gels with more stable mechanical and spatial structures [73]. This is especially significant when used in the organoids culture since they are significantly controlled through mechanotransduction [75]. Synthetic hydrogels’ use is also becoming more successful, but since synthetic polymers lack biological activity, ECM’s biological functions must be restored by including biomolecules. Decellularized ECM acquired from both human and animal donors has also been used to develop some organoids accurately recapitulating the composition, structure, and vascularization of native ECM. The particular ECM for the liver may be obtained from a portion of surgical resection of a patient’s damaged liver or unsuitable livers for transplantation [33]. Recently, Willemse et al. described the culture and the expansion of human cholangiocyte organoids in hydrogel derived from decellularized liver tissue, showing the preservation of the cholangiocyte-like phenotype and the expression of selected cholangiocyte markers [76]. Different available materials to mimic the ECM in the generation of liver organoids are listed in Table 3. According to Nuciforo and Heim, the success rate of the experiment varies significantly between the generation of chol-orgs and hep-orgs: one-fourth of all cholangiocytes can start a transformation into an organoid with extremely rapid proliferation and long in vitro expansion, while just one hepatocyte out of every 100 produces hep-orgs, which proliferates more slowly and divides every 50–75 days when derived from the adult liver [19]. Once obtained, it is possible to cryopreserve liver organoids for long-time periods that can reach as long as 1–2 years, allowing the creation of biobanks of heterogenous tumour organoids, in which each sample is representative and exhibits a variety of histopathologic and molecular PLC characteristics [23]. Following generation, PLC-derived organoids could be characterized both at the molecular level using whole genome sequencing or RNA sequencing in order to detect gene expression or compare the presence and maintenance of some mutations, and proteomic techniques, such as immunohistochemistry and immunofluorescence that enable the assessment of the potential presence/absence and the quantification of specific markers levels (Figure 2). The transmembrane glycoprotein epithelial cell adhesion molecule (EpCAM) is one of the markers that has received the most attention for characterizing CCA-derived organoids. In the liver, EpCAM is a biliary marker, often not detected in mature hepatocytes [77], which has a physiological role in mediating intercellular adhesion in epithelial tissues and occurs at an early stage of the neoplastic transformation of CCA cells [78]. Another potential biomarker for CCA is Sex Determining Region Y-box 2 (SOX2), a transcriptional regulator in maintaining regeneration for embryonic stem cells. Numerous malignancies depend on SOX2 for carcinogenesis and tumour growth, and in CCA, SOX2 over-expression was linked to poor overall survival, increased cell proliferation and invasion, and reduced cell apoptosis; however, its exact role in CCA must be clarified with more studies [78]. Other two PLC biomarkers that have been studied include cytokeratins 7 and 19 (CK7 and CK19), which are crucial for maintaining epithelial barriers, regulating innate immunity, and cell adhesion, proliferation, and differentiation [79]. It has been observed that these two molecules are useful histochemical markers for the differential diagnosis of HCC and iCCA [80], as well as potential post-operative prognostic factors for CCA [81]. Therefore, a greater sense of security regarding the true nature of cells cultured is provided by the presence of these molecules in tumour organoids. On the other hand, the most significant HCC markers are albumin (ALB), hepatocyte nuclear factor 4 (HNF4), and α- fetoprotein (AFP) [62]. This latter one represents a marker of liver function, such as synthesis and secretion, typical of differentiated hepatocytes [62], and its up-regulation is present in more than 40% of tumour samples [82]. Moreover, the panel of immunohistochemical markers composed of heat shock proteins 70 (HSP70), glypican-3 (GPC3), and glutamine synthetase (GS) was recommended for the differentiation of early HCC. In particular, the HSP70s family was revealed to have a critical role in the development and progression of various cancers, including HCC [83]. HSP70s are involved in protein synthesis and transport, in order to maintain protein homeostasis, and it was observed that an over-expression of several HSP70s in HCC is associated with the overall survival, tumour grade and cancer stage [84]. In addition, GPC3 is considered a potential early diagnostic marker, associated with poor prognosis, of HCC, due to its involvement in cell proliferation through WNT/β-catenin pathway activation [82]. Recently studies evidenced how GPC3 could be a potential drug target that has significantly reduced tumour growth and prolonged survival in Phase I clinical trials [85]. Finally, GS levels also gradually increase with the development of HCC and were observed in its involvement in promoting epithelial-to-mesenchimal transition (EMT) [86]. During the last decades, the presence of the nuclear antigen Ki-67, a marker of tumour cell proliferation capability, has also received considerable attention [87]. This protein undergoes a rapid degradation during the G1 phase of the cell cycle, causing a reduction in intracellular levels in cells that are quiescent or have limited proliferation [88] and an increment in tumour cells that have a rapid division [89], underlying a correlation between Ki-67, the severity of the tumour, and the likelihood of a favourable prognosis [90]. As a result of the ability to use liver tissue samples for the assessment of organoid cultures, research is moving toward the use of these 3D systems as disease models, in addition to being an extremely helpful tool for precision and personalized medicine [74] (Figure 3). Recent studies have shown that tumour-derived organoids are capable of retaining the morphological characteristics and biomarkers of the original tumour tissue while also preserving the patient-specific gene expression profile, even when cultivated for extended periods [23,62]. Using gene editing techniques, such as CRISPR/Cas9, it is thus possible to engineer organoids, introducing or correcting certain mutations that may be appropriately studied and assessed for their function and pathogenicity [91,92]. Additionally, thanks to their peculiar metabolic capacity, liver organoids are promising tools for the development of new treatments for clinical use. Indeed, due to their ability to be expanded in vitro for long periods and to be cryopreserved, biobanks have been developed to be used as platforms for high-throughput drug screening of anti-cancer treatments [19,93]. Biobanks of healthy organoids, on the other hand, can represent a useful predictive investigation tool for the in vivo toxicity of drugs [25]. As previously described, one of the main issues with organoids is related to the fact that these systems are characterized by a single cellular type of representative of the neoplastic epithelium and do not fully represent the typical multi-cellular tumour environment. One of the solutions is represented by the setting up co-culture systems of liver tumour organoids with a variety of cell types, including patient-derived immune cells or cancer-associated fibroblasts (CAFs), thus offering a promising tool for modelling the dynamic interactions between expanding cancer cells and the immune system [30,66]. Recent improvements in co-culture techniques make it possible to create ever-more complex and cutting-edge systems, such as vascularised liver organoids, and to research host-pathogen interactions in vitro, such as the host-HBV/HCV interactions, a key factor in the development of PLCs [94,95]. An example is represented by Natarajan et al. who developed a co-culture system to study adaptive immune responses to HCV, using patient-derived CD8+ T-cells specific for HCV non-structural protein 3 to generate liver organoids [96]. During recent years a technique known as “interface liquid-air” (ALI) has also been developed, allowing the combination of organoids with both epithelial and stromal cells using standard Boyden chambers. The functioning of this system is based on cells that are embedded in ECM gel and placed on the upper surface of cell inserts with a below porous membrane, directly exposed to oxygen, while nutrients and growth factors are supplied from the external medium by diffusion through the porous membrane on the lower surface [27]. Liver engineering organoids may be further used in the future to study the early stages of liver tumours, offering an innovative perspective on preventive therapy. The advantages of maintaining the molecular and structural abnormalities brought about by oncogenes make organoids an ideal in vitro model for understanding oncogenic processes during tumour development [1]. In recent years, additional advancements in the organoid model have resulted in the creation of the organoid-on-a-chip, a micro-fabricated, integrated system that combines the architectural and genomic recapitulation of organoids with the highly customised flexibility of organ-on-a-chip models [97]. Numerous issues with traditional organoid models are resolved by the organoid-on-a-chip, such as a major control over the organoids’ microenvironment. Moreover, the organoid-on-a-chip model may also contain vascular and immunological components, significantly enhancing its therapeutic relevance in drug screening and clinical trials. A vascularized cancer model is required for researching tumorigenesis and metastasis because abnormal angiogenesis is a key component of carcinogenesis [53]. Another interesting area is the possibility of using liver organoids as instruments to simulate significant chronic liver diseases, such as NAFLD and liver fibrosis [98]. Growing evidence indicates that NAFLD is becoming a dominant cause of HCC [99] and CCA [100], but the mechanisms of NAFLD progression are largely unknown. NAFLD is characterized by intracellular deposition of lipids in hepatocytes, often associated with a wide spectrum of metabolic abnormalities, such as dyslipidemia, hypertension, and insulin resistance. The disease then ranges to non-alcoholic steatohepatitis (NASH), a more severe condition that includes inflammation and additional hepatocyte damage and can progress to cirrhosis [101]. For example, by exposing liver organoids to free fatty acids (FFAs) in perfused 3D cultures over an extended length of time, it is enabled to define the pathological characteristics of NAFLD. In this way, liver organoids could show lipid droplet production and triglyceride buildup after FFAs induction, demonstrating increased expressions of genes linked to lipid metabolism and highlighting the aberrant lipid metabolic pathway in NAFLD [102]. In conclusion, a significant characteristic of tumour organoids is the ability to predict their potential for in vivo metastasis, in addition to maintaining the genetic model of the primary tissue [74]. The animal models receiving transplants of liver organoids have shown encouraging outcomes [63,69,70]. However, the protocols must be further improved, to increase the rate of engraftment and to promove circulation in patients for the delivery of oxygen and nutrients [103]. The final stage in making tissue engineering a reality for the treatment of liver disease is to find solutions to these problems [74]. Due to the lack of reliable in vitro models and available treatments for PLC, there is an urgent need for an improved preclinical tumour system that can mimic the genetic background and architecture of the primary tissue. Moreover, significant variations between human and mouse physiology, metabolism, size, and longevity are among the shortcomings of in vivo animal models [104]. The 3D organoid systems represent an enormous promise for solving these limitations, besides providing several practical applications that potentially change biomedical research, drug development, and disease modelling. Traditional 3D cultures have faced issues in order to accomplish the right control of organoid production and to realise the complex microenvironment of a specific organ due to the quick development and broad needs of organoid technology [1]. Until now, the use of organoid models has permitted the development of novel possible treatments as well as a better knowledge of the underlying mechanisms of disease onset and progression. For efficient diagnosis and therapy decisions, patient-derived organoids represent an innovative option, thanks to their strong advantage of retaining personalized genetic information [105]. Moreover, the creation of liver organoids by bioengineering has the potential to produce more physiologically realistic and biomedical useful specimens. The potential to reproduce in vitro liver epithelial cells has been improved by the ability of liver cells to produce liver organoids. Despite the fact that liver organoids are among the most advanced human cell-based 3D liver models, and organoid-based drug testing may accurately predict clinical outcomes in personalized medicine and drug toxicity and efficacy evaluation [105], there are still several issues that need to be addressed, such as increased costs, absence of highly reproducible results, lack of other TME cell types and 3D culture platforms to model their interactions, and use of animal-derived 3D-matrices [106]. In part, these limitations can be attributed to the current use of non-standardised and well-defined protocols, which introduces technical variability into in vitro organoid cultures and reduces their accurate representation of cancer’s intrinsic biological heterogeneity [106]. Recent advancements in microfabrication techniques offer the ability to standardise cancer organoid derivation, analysing how the size of the starting cell cluster affects the rate of organoid development, for example. These improvements in cancer modelling will be well complemented by the increased availability of methods that monitor and measure organoid proliferation at the cellular level [106]. In addition, creating multi-cellular liver organoids in which epithelial cells interact with endothelial, mesenchymal, and immunological cells is necessary for the disease modelling of PLC, where the microenvironment plays a crucial role [25]. Microphysiological systems represent a promising approach for building organoid/tumour-on-a-chip models with more tissue complexity, including the incorporation of mature vasculature [107]. Several microfluidic devices have been developed to simulate how cancer interacts with vascular networks, allowing the evaluation of cancer extravasation, drug delivery, and tumour growth [107]. Finally, the implementation of engineered matrices animal-free, using hyaluronic acid or PEG, for example [108], will represent a future opportunity for high batch-to-batch reproducibility, standardisation of organoid development and culture protocols, and for understanding the roles of the ECM in regulating patient-specific tumours. Because of the potential applications of these 3D models, in the future, organoids will open the road to the regeneration of injured or diseased organs, a proposal that was previously thought to be unlikely to be accomplished in medicine. The ability of liver organoids to regenerate diseased livers may be very promising, and for this reason, the goal of current research is the creation of organoid liver buds that can be delivered to patients who are in urgent need of a liver transplant via the portal vein [53]. In this way, a structured patient-based treatment system may require everyone to have organoid tissue maintained in large-scale biobanks in the future, improving the core strategies and tenets of personalized medicine. Furthermore, working closely with bioengineers to add blood vessels to liver organoids may be considered crucial, and doing so is a feasible solution to the problem of the limited nutrition availability that eventually affects the development of organoids [25]. In conclusion, the repeatability of organoid systems, the addition of cells from different functional lineages, and the use of gene editing techniques for the acquisition of complex organoids, therefore, opened up new research fields.

PMC10003136

Jun Ueda,Taiga Yamazaki,Hiroshi Funakoshi

Toward the Development of Epigenome Editing-Based Therapeutics: Potentials and Challenges

01-03-2023

epigenome editing,epigenetics,chromatin,chromatin plasticity,in vivo,drug delivery

The advancement in epigenetics research over the past several decades has led to the potential application of epigenome-editing technologies for the treatment of various diseases. In particular, epigenome editing is potentially useful in the treatment of genetic and other related diseases, including rare imprinted diseases, as it can regulate the expression of the epigenome of the target region, and thereby the causative gene, with minimal or no modification of the genomic DNA. Various efforts are underway to successfully apply epigenome editing in vivo, such as improving target specificity, enzymatic activity, and drug delivery for the development of reliable therapeutics. In this review, we introduce the latest findings, summarize the current limitations and future challenges in the practical application of epigenome editing for disease therapy, and introduce important factors to consider, such as chromatin plasticity, for a more effective epigenome editing-based therapy.

Toward the Development of Epigenome Editing-Based Therapeutics: Potentials and Challenges The advancement in epigenetics research over the past several decades has led to the potential application of epigenome-editing technologies for the treatment of various diseases. In particular, epigenome editing is potentially useful in the treatment of genetic and other related diseases, including rare imprinted diseases, as it can regulate the expression of the epigenome of the target region, and thereby the causative gene, with minimal or no modification of the genomic DNA. Various efforts are underway to successfully apply epigenome editing in vivo, such as improving target specificity, enzymatic activity, and drug delivery for the development of reliable therapeutics. In this review, we introduce the latest findings, summarize the current limitations and future challenges in the practical application of epigenome editing for disease therapy, and introduce important factors to consider, such as chromatin plasticity, for a more effective epigenome editing-based therapy. Genome-editing technologies, such as zinc-finger nuclease (ZFN), transcription activator-like effector (TALE) nuclease (TALEN), clustered regulatory interspaced short palindromic repeats (CRISPR)-associated protein (Cas) (CRISPR-Cas), and other related technologies, are rapidly developing. Combined with DNA-cleaving enzymes (such as Fok I and Cas proteins), which have RNA or protein domains that recognize target DNA sequences, these technologies more readily facilitate the repair or modification of target genes or genomic loci than do conventional gene-targeting methods [1,2,3,4,5]. In addition, these technologies are optimized to induce changes in target DNA sequences, which make them ideal for repairing genomic DNA or introducing mutations. Studies on the application of genome-editing technologies for treating human genetic disorders and infectious diseases, such as human immunodeficiency virus (HIV), are ongoing [6]. Genome-editing therapies have just begun clinical trials, and approved drugs have not yet been commercialized [7,8,9,10]. For genome editing to be applicable to humans, DNA repair must be complete, and the repaired genome must be error-free. However, these goals are currently difficult to achieve through the intrinsic DNA repair mechanism, as the DNA repair pathway is complex [11]. An alternative approach to regulate gene function is to rewrite the epigenetic landscape to control gene expression with no or minimal changes in the underlying DNA sequence. Epigenome editing is considered a potential therapeutic approach for various genetic diseases and certain cancers [12,13]. These genetic diseases mainly involve gain-of-function genes [14,15], as loss-of-function genetic diseases can be alternatively treated via conventional gene therapy [16]. Epigenome editing is also considered for the treatment of nonhereditary diseases (or nongenetic diseases), as the target gene expression can be increased or decreased by modifying the epigenome associated with the target gene [17,18]. Moreover, epigenome editing is a practical approach to artificially manipulate the chromatin structure of arbitrary genomic regions, thereby enhancing our understanding of the basic epigenomic research [19]. This review outlines the fundamentals of epigenetics and epigenome editing and focuses on the current status and potential of epigenome editing, including ethical considerations, in the treatment of various diseases. All cells in the human body have the same genetic information. However, during cell differentiation, dynamic chromatin remodeling sorts the necessary genes from unnecessary genes. The changes in chromatin structure ensure that the necessary genes are actively transcribed, and the unnecessary genes are not transcribed because of the formation of heterochromatin structures [20,21,22]. These structures and phenotypes are maintained after each cell division. This process is called epigenetics, and intimately involves the chemical modifications of DNA, histones, chromatin proteins, and noncoding RNAs (e.g., small interfering RNAs (siRNAs), microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs), and long noncoding RNAs (lncRNAs)) [23,24,25]. Except during DNA recombination in immune cells, the genomic DNA sequence of most cell types is retained, regardless of differentiation fate. In particular, when histone tails are acetylated, the chromatin structures become relaxed and accessible to RNA polymerases and basic transcription factors that activate the transcription of the gene [26]. On the other hand, when DNA is methylated, or histone tails undergo repressive post-translational modifications, the chromatin is condensed and inaccessible to RNA polymerases and other transcription factors; thus, gene expression is repressed [21]. For instance, lysine and arginine residues of histones H3 and H4 are known to be methylated, exhibiting different results depending on the site of modification (Figure 1). Specifically, methylation of the 4th (H3K4) and 36th (H3K36) lysine residues of H3 is closely related to transcriptional activation and elongation, respectively. In contrast, the methylation of the 9th or 27th lysine residue (H3K9 or H3K27) of the same H3 is involved in transcriptional repression and heterochromatin structure formation [27,28,29]. These differences are caused by the different “reader” proteins that recognize the methylation sites. Therefore, the chromatin state of the modification site is determined by the type of “reader” protein that binds during methylation and post-translational modification. Although the individual chemical modifications involved in epigenetics are reversible, the chromatin structure (the so-called “epigenome”) changes are often stable and robust once the cell has established its identity, largely due to the influence of the “reader” proteins [21,25,30]. Thus, the “reader” proteins ultimately determine the chromatin state. Specifically, the chromodomain (CD) of the heterochromatin protein 1 (HP1) recognizes H3K9 methylation [31], which is observed in the nuclear structure after the phase separation [32,33]. Epigenomic-modifying enzymes, such as histone acetyltransferases, DNA methyltransferases (such as DNA methyltransferase 3 (DNMT3) alpha (DNMT3A)), and ten-eleven translocation methylcytosine dioxygenase 1 (TET1), which is a methylcytosine dioxygenase that demethylates methylated DNA, play pivotal roles in altering the epigenome. However, with a few exceptions, such as PR/SET Domain 9 (Prdm9) [34], most epigenomic-modifying enzymes do not exhibit genome sequence-binding specificity, as they do not have a DNA-binding domain that determines a target sequence. Instead, their target specificity depends on the type of transcription factors with which they form complexes [35,36,37,38]. As transcription factors bind to several target genes (often hundreds to thousands) and the length of the target sequence of an individual transcription factor ranges from a few to a dozen bases [36,39,40], it is difficult to artificially turn on or off the expression of any gene of interest using an epigenome-editing enzyme with a transcription factor DNA-binding domain. Therefore, the DNA-binding domain of a transcription factor is not suitable for targeting epigenomic-modifying enzymes. Hence, for epigenome editing, a programmable RNA or protein domain that recognizes target DNA sequences (in most cases, a target sequence of approximately 20 bp) and the catalytic domain from epigenomic-modifying enzymes (so-called “EpiEffectors”) are fused to create an artificial enzyme [41,42] (Figure 2). By using these artificial enzymes, the EpiEffector can specifically modify the epigenome of the target site. In the next section, we will describe the different types of EpiEffectors which are used in epigenome editing. EpiEffectors are the enzymatic domain of a group of enzymes involved in epigenetic modifications of DNA and histone proteins that do not themselves bind to specific DNA sequences. Typical examples of EpiEffectors are shown in Table 1. The herpes simplex virus-encoded protein VP16 is involved in the post-translational modification (acetylation) of histone tails and contributes to transcriptional activation. TET1 demethylates methylated DNA, which is a well-known to repress transcription. In contrast, some EpiEffectors, including DNA methyltransferases, are responsible for transcriptional repression. Nevertheless, the chromatin structure is altered, but the DNA sequence is retained in both cases. Although several enzymes are involved in epigenetic regulation (Table 1), only a few EpiEffectors are currently used for epigenome editing in vivo (Table 2). As described in the next section, VP16 and VP64 (four VP16s) are commonly used as EpiEffectors that activate transcription, whereas Krüppel-associated box (KRAB), the transcriptional repressor domain of Kox-1 (also known as ZNF10); a mammalian de novo DNA methyltransferase, DNMT3A; and a bacterial DNA methyltransferase, MQ1, are commonly used for gene repression. In addition, attempts have been made to combine DNMT3A with DNMT3-like (DNMT3L), a stimulator of the catalytic activity of de novo DNA methyltransferases, to extend the duration of epigenome editing in the cell [70,84,85]. Furthermore, epigenome modification approaches, such as the use of synergistic activation mediators (SAM), CRISPRon, and CRISPRoff (single artificial genes containing multiple EpiEffectors), which simultaneously express multiple types of EpiEffectors, are more effective than those that express a single type of EpiEffector [54,70,97]. These EpiEffectors were selected based on their efficacy in vivo, their well-understood properties, and their small gene size favoring in vivo gene transfer (Table 2). For further details on the types of EpiEffectors in epigenomic-modifying enzymes, please refer to earlier reviews [37,41,43,44,45]. Early studies using epigenome-editing enzymes with target sequence specificity were performed using zinc-finger and TALE domains that were originally used for genome editing [37,41,43]. Both are artificial enzymes that fuse the EpiEffector molecule with a DNA-binding domain that recognizes the target sequence. Several examples of epigenome editing at the cellular level have previously been reported [41,44], whereas those at the organismal level have been increasing in recent years (Table 2) [12]. In particular, Garriga-Canut et al. used zinc-finger and KRAB to specifically repress the mutant huntingtin gene (htt) in the brain tissue from an animal model of Huntington’s disease [14]. Zeitler et al. also used zinc-finger and KRAB to specifically suppress the mutant htt gene in cells derived from patients with Huntington’s disease, as well as in an animal disease model [15]. In contrast, Yamazaki et al. fused the gene encoding for the CpG methyltransferase from Mollicutes spiroplasma (M. SssI, strain MQ1) with TALE and successfully methylated repeat sequences in the pericentromeric region of chromosomes in early mouse embryos [42,87]. This study demonstrates the possibility of epigenome editing in a wide genome region (i.e., genomic DNA size that can be observed under an optical microscope). As transposon activation is a problem in the xenotransplantation [105], inactivation through epigenome editing of numerous repetitive sequences and transposons in the genome may become an important research area in the future. Although these approaches using zinc fingers and TALEs have some advantages (discussed in later sections), they have not yet been widely adopted by the scientific community because of the long period of time required to synthesize target sequence recognition domains [106]. In addition to zinc-finger and TALE systems, CRISPR systems have been developed using dead Cas (dCas) proteins that do not cleave DNA (“dead,” as the Cas protein has lost its endonuclease activity), but possess a programmable DNA-binding activity. The CRISPR-Cas system uses RNA for target site recognition, which makes it easier to recognize target DNA sequences compared with zinc-finger and TALE systems. The advent of these systems has changed the landscape of genome editing [45,106,107]. Among the dCas proteins, dCas9 was first explored for the CRISPR-Cas system, and methods were developed to manipulate the epigenome using dCas9 to achieve various effects and actions. The following is a brief description of the applications of the CRISPR/dCas system in epigenome editing. First, the direct effector fusion approach uses the effector-fused dCas9 to interfere with transcription through sterically inhibiting RNA polymerase binding and transcription elongation [108,109]. This strategy has been successfully applied in prokaryotes, which reduced the mRNA expression approximately 300-fold when targeting dCas9 using a single guide RNA (sgRNA) and up to 1000-fold when two sgRNAs are combined to inhibit transcription elongation [108,109]. However, in mammalian cells, only an approximately two-fold reduction in transcription levels was achieved [109]. For dCas9 to potently regulate gene expression in mammalian cells, specific effectors, such as transcriptional activation (VP64 and P65) and repression domains (KRAB and Sin3a-interacting domain (SID)) are required. Either of these active or inhibitory domains is then genetically fused with dCas9 to produce a single functional recombinant protein [110]. The dCas fusion proteins that activate or repress transcription are called CRISPR activation (CRISPRa) [111,112,113] or interference (CRISPRi) proteins, respectively [109,113,114]. The second approach, called indirect effector recruitment, incorporates an additional effector protein-recruiting motif into the basic design, of which the SUperNova tag (SunTag) is a representative example [115]. The third approach, called spatiotemporal control of activity, uses split-dCas9 or split-dCas9-effector proteins [116]. In this approach, DNA-binding complexes assemble and function under various conditions, such as chemical or light induction [117,118]. Using these approaches, the therapeutic applications of epigenome-editing have been studied in animal models of genetic diseases (Table 2) [45]. In particular, Matharu et al. successfully treated haploinsufficiency disease in mice through increasing target gene expression to normal levels using Streptococcus pyogenes dCas9-VP64 [100]. Thakore et al. also combined Staphylococcus aureus dCas9 with the transcriptional repressor KRAB to suppress the expression of the target gene Pcsk9, which regulates cholesterol levels, in the liver. In this study, the effect of a single dose of dCas9-KRAB lasted for up to 24 weeks [67]. Furthermore, Horii et al. successfully used dCas9-SunTag and single-chain fragment variable (scFv)-TET1 antibody to generate animal models of Silver–Russell syndrome, which is a disease related to genomic imprinting disorders [93]. More recently, Bohnsack et al. used dCas9-P300 to activate the activity-regulated cytoskeleton-associated protein (Arc) expression and observed the attenuation of adult anxiety and excessive alcohol use disorder in rats [55]. When considering the application of platforms used in genome editing to disease treatment, CRISPR-Cas systems are uniquely DNA- or RNA-based therapies because of the use of guide RNA, whereas epigenomic-modifying enzymes based on zinc fingers or TALEs are applicable as protein drugs and can be administered similarly to available commercial drugs. As protein-drug immunogenicity has been studied more widely than gene therapies, the availability of zinc fingers and TALEs as protein drugs could be a major advantage in developing epigenomic-modifying enzymes as therapeutic drugs [119,120]. Moreover, epigenome editing technologies using CRISPR-Cas and TALE are potentially immunogenic in that they contain non-human materials [121]. In contrast, zinc-finger-based technologies have the advantage of being less immunogenic than CRISPR-Cas and TALE because they are composed of polypeptides encoded in the human genome. In any case, one of the challenges for the future will be determining how to reduce the immunogenicity of the components of epigenome editing technologies. The main feature of epigenome editing, which is the preservation of the nucleotide sequence, has been considered to be both a weakness and strength, as the disease-causing gene is not altered. Instead, epigenome editing suppresses the expression of disease-causing genes or increases the expression of checkpoint genes, such as cell cycle and other suppressed genes. Therefore, except for the different target specificities, epigenomic-modifying enzymes are similar to the available molecularly targeted drugs against epigenomic-modifying enzymes, such as the DNA methyltransferase inhibitor, azacitidine (trade name Vidaza), and the histone deacetylase inhibitor, vorinostat (trade name Zolinza) [122,123]. Molecular drugs that target epigenomic-modifying enzymes deliver therapeutic efficacy by inhibiting the activity of specific enzymes. As they inhibit all functions involving the enzyme, they affect the entire genome (i.e., “epigenome remodeling” of treated cells) and result in substantial side effects in the patient [124,125]. In contrast, epigenome remodeling via an epigenome-editing strategy may result in fewer adverse effects, as it targets only one or a few sequences within the genome and does not act on the epigenomic-modifying enzymes. Furthermore, the modified chromatin structures are maintained after cell division, as they employ the endogenous epigenetic maintenance mechanism within the cells [12]. Consequently, epigenome editing may be suitable for the treatment of dominant genetic diseases, such as those caused by gain-of-function type mutations. Aside from epigenomic-modifying enzymes, miRNAs and siRNAs that target RNA transcripts are being developed as drug candidates for the treatment of genetic diseases, some of which have begun clinical trials for the treatment of dominant genetic disorders, such as Huntington′s disease [126,127]. Another advantage of epigenome editing is its reversible effects compared with the irreversible DNA sequence changes in genomic editing. Accordingly, as with existing drugs, such as molecularly targeted drugs, the dosage, duration of administration, and other factors in epigenome editing may be adjusted according to the patient′s condition. In the treatment of various diseases, including hereditary diseases, epigenome editing is applied to regulate the transcription of target genes without causing substantial side effects [17,18]. To achieve this, five factors must be considered: the off-target effects, undesired genomic mutations caused by the treatment, nuclear structure, cell types, and method of administration. This section summarizes the status of these challenges and possible approaches to overcome them. In recent years, the problem of specificity in epigenome editing has been gradually addressed. Although the risks are small, potential problems must be carefully minimized for a successful clinical application. Unlike genome editing that targets coding regions (e.g., exons), epigenome editing targets the transcriptional regulatory regions with similar sequences in several genes, thereby making it relatively difficult to find sequences unique to a specific gene [38,128]. Moreover, most genes are simultaneously and synergistically regulated and controlled by a common set of transcription factors during development and differentiation [36,38,128,129]. In particular, the transcription factors OCT4 and NANOG synergistically form the inner cell mass of the blastocyst [130]. Together with SOX2, these transcription factors regulate several thousands of genes in mouse embryonic stem (ES) cells [36]. This suggests that DNA-binding protein domains and RNAs that recognize target DNA sequences should be designed for longer target sequences when used for epigenome editing. Therefore, instead of the widely used type II CRISPR-dCas9 system [1], the type I-E Cas3 complex, which recognizes a 27 bp target sequence (longer than that in Cas9), may provide advantages in terms of specificity in epigenome editing [131,132,133]. This may be especially useful when applying the dCas3 system to ex vivo studies. However, when EpiEffector targets a transcriptional regulatory region of about 20 nucleotides, it should be noted that the effect of epigenome editing may become local, and the gene may be transcribed normally through alternative splicing and alternative promoter mechanisms [134]. Accordingly, the possibility of such splicing should be considered when applying this technology. Although CRISPR/dCas systems are widely used for epigenome editing because of their easily designed target sequences, the potential for dCas systems to alter genomic sequences remains a concern [135,136]. Laughery et al. reported dCas9 binding and R-loop formation as the main causes of background mutations caused by the dCas9 system. dCas9-induced mutations were particularly prominent when targeting the antisense strand of a gene. Several of the induced mutations resulted from cytosine deamination events induced by dCas9 on the nontarget strand of the R-loop, whereas the other mutations were related to homopolymer instability or translesion DNA synthesis. The results indicate that DNA binding by dCas9 is mutagenic, which is possible because dCas9 induces the formation of R-loops at its target sites [135]. As TALEs and zinc fingers only bind to DNA and have no enzymatic activity to cleave DNA, another cause of background mutation unique to the dCas system could be the residual DNA cleavage activity of dCas proteins. Therefore, if dCas proteins are to be used for human epigenome editing, their DNA-cleaving activity must be eliminated. The plasticity of the nuclear structure (genomic organization) of a cell is lost as cell differentiation occurs, and certain diseases are known to have abnormal nuclear structures [137,138,139,140]. During differentiation, the cells change their nuclear structure and translocate transcribed genes (i.e., genes that are used by the cell) to the euchromatic region near the center of the nucleus. Genes that are not transcribed (i.e., genes that are not used by the cell) are translocated near the nuclear periphery, where they become part of the heterochromatin and consequently, are inaccessible to the molecules necessary for transcription, such as RNA polymerases and basic transcription factor machinery. DNA and the histone proteins that fold DNA undergo various chemical modifications, which are eventually recognized by different “reader” proteins, as described previously. Once formed, the chromatin and nuclear structures are maintained and difficult to reverse. In epigenome editing, the epigenomic-modifying enzymes must be applied in cells with loose nuclear structure and dynamic and plastic chromatin, such as in early embryos and stem cells. This is because nuclear structures and chromatin are likely to be fixed in differentiated cells (Figure 3 and Figure 4A) [137,138,139,141,142], and a single epigenomic-modifying enzyme alone is insufficient to alter nuclear structures and chromatin [47,59]. Furthermore, the simultaneous introduction of several factors is necessary to change the expression state or epigenome of a gene of interest [47,54,70]. In addition, the nucleosome structure may affect the epigenome editing [143]. Specifically, heterochromatin reorganization requires the cooperation of numerous energy-consuming factors, including ATP-dependent chromatin-remodeling factors, to release the heterochromatin state [144,145]. This indicates that epigenome editing in differentiated cells has a poorer therapeutic effect than that in stem cells and thus, is not sustainable. Repeated dosing or increasing the dose of the epigenomic-modifying enzyme may address this problem. Repeated dosing has been applied in existing drugs, such as those targeting epigenomic-modifying enzymes (e.g., azacytidine). Nevertheless, it is important to consider the chromatin structure of the cells to be treated, as the therapeutic effects (including side effects) of the epigenomic-modifying enzyme may depend on the cell type. Notably, conventional gene targeting was made possible by the development of ES cells [146]. One of the most important characteristics of ES cells is their high chromatin plasticity [137,141]. Accordingly, chromatin plasticity must be considered in human epigenome editing studies. It is important to increase the target sequence specificity of epigenomic-modifying enzymes. It is also equally important to consider the cell types subjected to epigenome editing (Figure 4A). Specifically, to suppress the expression of a target gene through epigenome editing in the cell where that gene is strongly expressed, it is likely that transcription of the entire chromosomal region where the target gene resides will be activated. Although gene expression is suppressed by a target-specific epigenomic-modifying enzyme, the enzyme may not be sufficient, and the effect may not be sustained. Therefore, when the target gene is in the transcription factory, and its expression is active, a large-scale chromatin remodeling is required to suppress its expression, and a single epigenomic-modifying enzyme without chromatin remodeling may not be sufficient. Conversely, a target gene within an inactivated chromosome and heterochromatic region would be inaccessible for expression. Accordingly, the type I CRISPR-dCas3 system possesses epigenomic-modifying and helicase enzymatic activities and can edit long regions of genomes (0.5–100 kbp). Furthermore, compared with conventional systems, the CRISPR-dCas3 system may be more suitable as an epigenomic-modifying enzyme once the problem of genome size is addressed (Figure 4B) [131,133]. Alternatively, the SunTag system, in which multiple EpiEffector molecules are assembled in a scaffold to amplify the epigenomic-modifying enzymatic activity (Figure 4C) [115], is more effective for epigenome editing than a single EpiEffector domain [90,93,94,99,102,147]. Another approach related to the SunTag system is to combine different EpiEffectors to enhance transcriptional activation or repression, which is shown to be successful in vivo (Figure 4D) [54,58]. Finally, targeting multiple loci within the target gene using epigenomic-modifying enzymes may be effective in modulating the epigenome (Figure 4E) [98,99]. Overall, the chromatin plasticity of the target cells for epigenome editing must be sufficiently high to allow alterations to the chromatin. If the chromatin plasticity of the cells to be treated is lost, several epigenomic-modifying enzymes are necessary; however, this may result in off-target effects. Consequently, cell type must be considered when opting for epigenome editing as a therapy. Epigenome editing requires more components than genome editing. This inevitably increases the overall genome size of the gene transfer vector. Accordingly, the methods for delivering epigenome editing-based therapeutics to target cells, tissues, and organs, including miniaturization, must be optimized [17,148,149,150,151,152,153]. The application and function of drug delivery systems via viruses, lipids, compressed DNA nanoparticles, or gold nanoparticles must be improved to deliver engineered epigenomic-modifying enzymes to target cells before their terminal differentiation (specific somatic stem cells in which the chromatin structure is not fully immobilized) [12,150,154,155,156,157,158]. As discussed in the previous section, if epigenome editing can be performed on cells with high genomic plasticity, the treatment may be developed with fewer EpiEffectors, which can potentially address the problem of genome size. In gene delivery, it is also important to consider the method of transferring epigenomic-modifying enzymes into specific cells with higher genomic plasticity. When epigenome editing is applied to humans in situ, the size of the epigenome-editing system is critical for successful delivery. Among the developed systems, the adeno-associated viruses (AAVs) have attracted significant attention (Table 2). Specifically, the AAV type 2 vector has lost the site-specific insertion into human chromosome 19 via mutation. Site-specific insertion is a major characteristic of AAVs, possibly because the gene encoding for the Rab-escort protein-1 (REP1) is removed from the vector plasmid [159]. In this regard, AAV vectors have attracted particular attention as gene carriers for epigenomic-modifying enzymes. However, although the gene may be incorporated into the chromosome of the transduced cell, the probability and degree of such incorporation are considerably reduced. Furthermore, the expression of the gene of interest can be maintained for a long period of time [12,67,160]. In addition, AAVs are ideal delivery systems because of their low immunogenicity, high serotype abundance, and ability to preferentially infect specific tissues. A limitation of using AAVs for gene delivery is that the suitable gene size for epigenome editing must be less than 4.7 kbp (including promoter regions) [161]. However, for several epigenome editing systems, such as the type I and II CRISPR-Cas, consisting of large genome sizes, AAVs are not suitable gene delivery methods. Several approaches have been developed to overcome this limitation. Specifically, instead of using S. pyogenes Cas9, smaller dCas9 orthologues, such as SaCas9, SadCas9, CjCas9, and NmeCas9, and Casφ, originating from large phages, have been developed and shown to be successfully incorporated into AAVs [67,69,100,162,163,164,165,166]. In addition, because the size of EpiEffector molecules is generally large, it will be necessary to downsize and optimize EpiEffector molecules in future studies. Regarding the size limitation, various systems have been studied to allow the delivery of larger genomes. These include the dual/triple vector, concatamerization/trans-splicing, overlapping, hybridizing, protein trans-splicing, single vectors, and mini-gene strategies [167,168,169]. Another approach to overcome the size limitations is to use split inteins. Split inteins are a pair of naturally occurring polypeptides that mediate protein trans-splicing, similar to introns in pre-mRNA splicing when located at the terminus of two proteins [170]. In 2015, Fine et al. [171] discovered the split-intein, SpCas9, which exhibits a moderate genome editing rate in HEK293T cells compared with full-length SpCas9. In 2016, Chew et al. [172] developed an spCas9-AAV toolbox that retains the gene-targeting ability of full-length SpCas9. This set of plasmids includes the AAV-Cas9C-VPR for targeted gene activation. Split inteins are also used to express base editors. Another approach is nanotechnology-based delivery, such as the use of gold nanoparticles or quantum dots, which have been applied to the CRISPR/Cas9 system [173]. Nanocarriers, such as liposomes, polymers, and inorganic nanoparticles, have also been used for gene delivery of CRISPR/Cas gene-editing systems, which suggests that small particles are a viable alternative for large gene transfer [174,175]. However, when using nanoparticles in humans, the risk of epigenetic alterations must be considered [176]. Other possible methods are ex vivo epigenome editing, in which somatic stem cells or other cells are extracted from the patient, epigenome-edited, and then returned to the body of the patient [12,177]. In this case, it is easier to introduce epigenomic-modifying enzymes into the cells, which may be advantageous, depending on the type of disease. Collectively, the application and function of drug delivery systems via viruses, lipids, compressed DNA nanoparticles, or gold nanoparticles must be improved to successfully deliver engineered epigenomic-modifying enzymes to target cells before their terminal differentiation (specific somatic stem cells in which the chromatin structure is not fully immobilized) [12,150,154,155,156,157,158]. In addition, since epigenetics is reversible, repeated administration of epigenomic-modifying enzymes may be necessary if the target gene needs to be repressed or activated for an extended period. Accordingly, a dosage form that allows repeated administration is also desirable and should be taken into consideration. Epigenome editing has several important applications in basic research and offers potential novel treatments for various diseases. Although it is still in its infancy, several experimental studies have demonstrated the capability and promise of this technology. In addition, as the size of EpiEffector molecules responsible for the enzymatic activity in epigenome editing is generally large, it will be necessary to downsize and optimize EpiEffector molecules in future studies. Several challenges in epigenome editing have been discussed: improving target specificity, selecting optimal cell types for epigenome editing, avoiding undesirable genomic mutations, considering nuclear structure, and selecting optimal administration methods. Once these challenges are addressed, and if highly effective epigenomic-modifying enzymes can be delivered to target cells, epigenome editing poses a huge potential for application in human therapies, such as in improving therapeutic efficacies and extending drug responses. Directing epigenomic-modifying enzymes to target sequences is beneficial for the development of therapeutic agents with a lower risk of side effects than existing drugs, such as molecularly targeted drugs. Thus, epigenomic-modifying enzymes could be a promising option for the treatment of various diseases, including genetic diseases. In addition to epigenome editing of single disease-causing genes, future studies on epigenome editing that stabilizes or alters the entire chromosome structure are also important for the treatment of diseases associated with genome instability and chromosomal structural abnormalities [178]. As epigenome editing is relatively safer than genome editing, especially when targeting transposons or repeat sequences that are present in the genome in thousands of copies, further investigations are necessary. Finally, because epigenome editing does not involve modification of the genome itself, it is currently considered to have a lower impact on germ cells than genome editing. Thus, epigenome editing has the potential to overcome important scientific and ethical issues of concern with genome editing. However, because of the uncertainties associated with new medical technologies, deliberation is essential on how to clear social and ethical issues and develop safe and appropriate strategies and policies [179].

PMC10003139

36794404

Shereen A. Sabry,Amal M. Abd El Razek,Mohamed Nabil,Shaimaa M. Khedr,Hanan M. El-Nahas,Noura G. Eissa

Brain-targeted delivery of Valsartan using solid lipid nanoparticles labeled with Rhodamine B; a promising technique for mitigating the negative effects of stroke

15-02-2023

Valsartan,solid lipid nanoparticles,stroke,factorial design,transmission electron microscopy,photon imaging

Abstract The brain is a vital organ that is protected from the general circulation and is distinguished by the presence of a relatively impermeable blood brain barrier (BBB). Blood brain barrier prevents the entry of foreign molecules. The current research aims to transport valsartan (Val) across BBB utilizing solid lipid nanoparticles (SLNs) approach to mitigate the adverse effects of stroke. Using a 32-factorial design, we could investigate and optimize the effect of several variables in order to improve brain permeability of valsartan in a target-specific and sustained-release manner, which led to alleviation of ischemia-induced brain damage. The impact of each of the following independent variables was investigated: lipid concentration (% w/v), surfactant concentration (% w/v), and homogenization speed (RPM) on particle size, zeta potential (ZP), entrapment efficiency (EE) %, and cumulative drug release percentage (CDR) %. TEM images revealed a spherical form of the optimized nanoparticles, with particle size (215.76 ± 7.63 nm), PDI (0.311 ± 0.02), ZP (-15.26 ± 0.58 mV), EE (59.45 ± 0.88%), and CDR (87.59 ± 1.67%) for 72 hours. SLNs formulations showed sustained drug release, which could effectively reduce the dose frequency and improve patient compliance. DSC and X-ray emphasize that Val was encapsulated in the amorphous form. The in-vivo results revealed that the optimized formula successfully delivered Val to the brain through intranasal rout as compared to a pure Val solution and evidenced by the photon imaging and florescence intensity quantification. In a conclusion, the optimized SLN formula (F9) could be a promising therapy for delivering Val to brain, alleviating the negative consequences associated with stroke.

Brain-targeted delivery of Valsartan using solid lipid nanoparticles labeled with Rhodamine B; a promising technique for mitigating the negative effects of stroke The brain is a vital organ that is protected from the general circulation and is distinguished by the presence of a relatively impermeable blood brain barrier (BBB). Blood brain barrier prevents the entry of foreign molecules. The current research aims to transport valsartan (Val) across BBB utilizing solid lipid nanoparticles (SLNs) approach to mitigate the adverse effects of stroke. Using a 32-factorial design, we could investigate and optimize the effect of several variables in order to improve brain permeability of valsartan in a target-specific and sustained-release manner, which led to alleviation of ischemia-induced brain damage. The impact of each of the following independent variables was investigated: lipid concentration (% w/v), surfactant concentration (% w/v), and homogenization speed (RPM) on particle size, zeta potential (ZP), entrapment efficiency (EE) %, and cumulative drug release percentage (CDR) %. TEM images revealed a spherical form of the optimized nanoparticles, with particle size (215.76 ± 7.63 nm), PDI (0.311 ± 0.02), ZP (-15.26 ± 0.58 mV), EE (59.45 ± 0.88%), and CDR (87.59 ± 1.67%) for 72 hours. SLNs formulations showed sustained drug release, which could effectively reduce the dose frequency and improve patient compliance. DSC and X-ray emphasize that Val was encapsulated in the amorphous form. The in-vivo results revealed that the optimized formula successfully delivered Val to the brain through intranasal rout as compared to a pure Val solution and evidenced by the photon imaging and florescence intensity quantification. In a conclusion, the optimized SLN formula (F9) could be a promising therapy for delivering Val to brain, alleviating the negative consequences associated with stroke. Stroke is the most common cause of permanent disability in adults worldwide and the second greatest cause of death in industrialized countries (Tapeinos et al., 2017). It has been found that stroke is accompanied by an increased level of angiotensin II and angiotensin II type-1 (AT1) receptor, and the outcome of stroke is determined by the volume of the ischemic core, the extent of secondary brain damage which manifested by brain swelling, and impaired microcirculation and inflammation (Barakat et al., 2014). Angiotensin receptor blockers (ARBs) have been shown to ameliorate peripheral and central actions of angiotensin II, mediated by AT1-receptors, and also to stimulate unopposed angiotensin II type 2 (AT2) receptors that are up-regulated in ischemic area (Barakat et al., 2014; Pai et al., 2016). Additionally, it has been confirmed in large clinical trials, that ARBs demonstrate an essential role in preventing both primary and secondary stroke (Dahlof, 2009). The blood-brain barrier (BBB) is a highly effective system that separates the central nervous system (CNS) from general circulation. The capacity of a certain molecule to cross BBB is a critical prerequisite in the formulation of any drug targeting the CNS. Basically, it promotes selective transport of essential molecules for brain function (Morsi et al., 2013). Therefore, screenings that predict BBB permeability of candidate compounds are indispensable for enhancing the field of drug discovery and finding effective therapeutics for many CNS related diseases. Although, there is a lot of ongoing research to evaluate BBB permeability, yet it is time-intensive and inefficient (Tang et al., 2022). Valsartan (Val) is one of ARBs that is available in both solution and tablet dosage forms, however, it is a tetrazole derivative that is slightly soluble in water with bioavailability of about 25% and a volume of distribution of 17 liters. This indicates that Val does not distribute extensively into tissues (Michel et al., 2013), and as a result, it either crosses the BBB to a very low extent or not at all (Michel et al., 2016). Hence, there was a strong demand for enhancing Val delivery to brain. One possible approach for circumventing the BBB is through the use of SLNs (He et al., 2019). It is among the safest and most cost-effective drug carriers, allowing for the nontoxic and successful treatment of neurological illnesses. SLNs are simply made up of a drug encapsulated within a lipid core and a surfactant in the outer coat. Accordingly, SLNs are considered an excellent alternative to polymeric systems with minimal possible toxicity (Ghorab et al., 2015). The intranasal route allows drugs to be delivered directly to the CNS. So, drugs loaded into SLNs can directly penetrate the BBB from the nasal cavity (Duong et al., 2020). This work attempted to improve Val aqueous solubility and enhance its transport across the BBB by loading it into SLNs designed to be delivered through the nasal cavity. The efficiency of the drug being delivered to the brain was explored by tracing fluorescently labeled nasal Val-SLN with rhodamine b. (Rh-B). Namely, drug deposition in the brain was detected by imaging and quantifying fluorescence intensity (Photon Imager optima - Bio space lab, France, Software version: 3.5.10.1464). The procedure was modeled using a three-factor two-level (23) full factorial design (8 runs), design was employed to investigate the impact of three independent variables, namely lipid concentration (X1), surfactant concentration (X2), and homogenization speed (X3), on four dependent variables, namely particle size (PS-Y1), zeta potential (ZP-Y2), entrapment efficiency % (EE-Y3), and cumulative drug release % (CDR). Valsartan (Val) was obtained as a gift sample from Servier Egypt Industries, Egypt. Glyceryl monostearate (GMS), Poloxamer 407 (P407), and egg lecithin were kindly provided by Egyptian International Pharmaceutical Industries Co., (EIPICO.), Egypt. Rhodamine B (Rh-B) was purchased from Lab vision Trade Company, Egypt. Chloroform, acetone, disodium hydrogen phosphate, and potassium dihydrogen phosphate were purchased from El-Gomhouria Company for trading chemicals and medical appliances, Cairo, Egypt. Valsartan loaded SLNs were prepared by emulsification solvent evaporation process (Palei & Das, 2013) with slight modifications (volume and type of organic solvent and stirring rate). Briefly, Val (1% w/v) was dissolved in a mixture of chloroform: acetone (5 ml: 2 ml) in which GMS and egg lecithin were previously dissolved by stirring at 40 °C using a magnetic stirrer. This oily phase was then dripped into 25 ml of an aqueous P407 solution kept at the same temperature (40 °C) and emulsified by homogenization for 15 minutes to prepare O/W emulsion. The formed dispersion was stirred continuously at 700 rpm for 3.5 h using a mechanical stirrer to assure complete evaporation of the organic solvent residue. The lipid was precipitated out in the aqueous medium, resulting in SLN formation. Thereafter, the formulations were sonicated for 4 minutes by a pan sonicator and kept at room temperature overnight. Then, they were stored in the refrigerator for further studies. Plain SLNs were prepared by the same procedure mentioned above, but without the addition of the drug. These plain SLNs were used as a blank. To prepare Val-SLNs coupled with Rh-B for in-vivo fating, Rh-B (1 mg/100 mg lipid) was added at the lipid phase step, and the procedure was completed in the same way as previously mentioned (Topal et al., 2020). Eight formulations of SLNs (F1 to F8) were prepared according to 23 full-factorial experimental design as represented in Table 1. The particle size, PDI, and zeta potential of different SLN formulations were measured by dynamic light scattering (DLS) technique (Malvern Zetasizer Nano–ZS90). A fixed volume of each SLN formulation was diluted with distilled water and then injected into a clear disposable zeta cell (Kaur et al., 2016a; Ibrahim et al., 2019). Results were presented as mean values ± standard deviation (SD). A dialysis technique was employed to separate the free drug from Val-loaded SLNs. A certain volume of SLNs dispersion equivalent to (40 mg) Val was placed into a dialysis bag (molecular weight cutoff 12,000–14,000 Da) previously soaked in Sörensen phosphate buffer solution (PBS) of pH 6.4 overnight and then immersed in a screw-capped bottle containing 100 ml of PBS (pH 6.4). The entire system was kept at 25 °C with continuous stirring in a thermostatic shaker water bath (Kotterman Shaker D3165 Hangisen, W-Germany) at 100 rpm. The free drug was dialyzed for one hour each time against 100 ml of PBS (pH 6.4) and assayed at λ max of 242 nm for Val content. The procedure was repeated till there was no Val in the medium, and the total free Val is the sum of all readings (Tamizharasi et al., 2009). The percentage of EE of SLN formulations was determined using the following equation (Alajami et al., 2022). In-vitro Val release study was conducted for pure Val solution in PBS (pH 6.4) and all formulations of SLNs for 72 hours, using the dialysis bag technique (Misra et al., 2016; Chandana et al., 2021). Dialysis bags were soaked in PBS (pH 6.4) overnight before use. Fixed volume of pure drug solution and SLN formulations equivalent to (40 mg Val) were transferred to dialysis bags, the two ends firmly sealed and then suspended in a preheated receptor medium (100 ml PBS of pH 6.4) at 37 ± 0.5 °C under stirring at 100 rpm in a thermostatic shaking water bath. An aliquot of the dissolution medium (3 ml) was withdrawn at different time intervals, passed through a 0.22 µm filter, and replaced with an equal volume of fresh medium to maintain a constant volume. The drug concentration in each aliquot was analyzed by UV spectroscopy at 242 nm. All measurements were performed in triplicate, and the cumulative drug release percent (CDR%) was represented as mean ± SD. The release data of all SLN formulations were subjected to explore the mechanism of release kinetics according to the following models: zero order model (Qt = Ko.t), first order model (log Qt = log Qo – K.t/2.303), Higuchi release model (Qt = KH.t0.5), Korsmeyer-Peppas model (Qt/Q∞ = Kk.tn) and Hixson–Crowell model (Qo1/3 – Qt1/3 = Ks.t); where, Qt: amount of drug released, t: time interval, Qo: initial drug amount, Q∞: the amount of drug released at time infinity (∞), Ko, K, kH, Ks, Kk: release rate constants and n: release exponent (El-Nahas, 2010; Sheshala et al., 2019). The highest correlation coefficients (R2) referred to the drug release order, which was further confirmed by the release exponent value (n) of the Korsmeyer-Peppas model (Ibrahim et al., 2021). All prepared SLNs formulations were stored at refrigerator temperature (4 °C) for 4 months. At the end of this period, the means of PS, PDI, and ZP were measured (Palei & Das, 2013). Student’s t-test and one-way ANOVA were adopted to assess the significance of the difference between different formulations using Graph-Pad Prism version 5.02. Values were represented as the mean ± SD (Hasan et al., 2020; Hassan et al., 2020; Nair et al., 2021). Formula optimization was conducted by factorial design software. The optimization strategy was reliant on the preferred target of each response (P.S = 150 nm, ZP = −20 mV, EE% = 60, and CDR% = 90). The values suggested by the software to prepare the optimized formulation (F9) were 4.9379% w/v lipid, 0.6507% w/v SAA, and 10000 rpm as homogenization speed. The melting and crystallization behavior of pure Val, P407, egg lecithin, GMS, and optimized Val-loaded SLN (F9) were studied by DSC (DSC-60; Shimadzu Corporation, Tokyo, Japan). For each measurement, accurately weighed samples (2 mg) were sealed in aluminum pans and analyzed over a temperature range of 0-250 °C under a nitrogen purge (50 ml/min) with a heating rate of 10 °C/min. FTIR analysis was performed for the same components as in DSC analysis. An FTIR spectrometer (Perkinelmer 1600 FTIR spectrophotometer, USA) was used to record the FTIR spectra between 4.000 and 500 cm−1 using the KBr. The encapsulation of the drug inside the nanoparticles was further confirmed by XRD (Ultima IV; Rigaku Corporation, Tokyo, Japan, using a Goniometer PW18120 as a detector). Samples were exposed to Cu·Kα radiation (40 kV, 25 mA, k = 0.15418 nm) and analyzed at (2θ) from 10° to 80°. Bragg’s equation was used to transform the data from scattering angle to the spacing of lipid chains. The morphology of F9 with and without Rh-B coupling was investigated using TEM (Model JEM-1230, JOEL, Tokyo, Japan), in which a few drops of the formula were mounted on a carbon-coated grid, left for 2 minutes to allow better adsorption on the carbon film, excess liquid was removed with a filter paper, and then a drop of phospho-tungstic acid (1%) was added (Kurakula et al., 2016; Al Ashmawy et al., 2021). Male albino mice (weighing 25 ± 3 g) and aged 12 weeks were obtained from VACSERA (Giza, Egypt). Nude mice were chosen to allow the detection of faint light signals (Mannucci et al., 2020). Mice were accommodated for one week prior to the start of the experiments, which were conducted totally under the supervision of veterinary microsurgery and with the agreement of Zagazig University’s Animal Ethics Committee (ZU-IACUC) under approval protocol No, ZU-IACUC/3/F/106/2020. For ethical reasons, a small but statistically significant number of mice were used (Mannucci et al., 2020). Twenty mice were divided into four groups (5 mice per group). Group 1 received a vehicle (control group). Group 2 received the optimized Val-loaded SLN (F9), group 3 received blank SLN (F10), and group 4 received a pure Val solution (F11). All in-vivo tested formulations (F9, F10, and F11) were pigmented by Rh-B, as previously mentioned to be able to be tracked in the brain under in-vivo optical imaging (Aboud et al., 2016). Twenty microliters of each formulation were administered intranasally to mice, which was equivalent to 10 mg of valsartan per kg of mice (Sironi et al., 2004; Hadi et al., 2015). The permanent stroke of the distal middle cerebral artery was induced using an electrothermic coagulator, as previously described by Llovera et al. (2014). For surgical proceedings, the mice were anesthetized by i.p. administration of ketamine/xylazine cocktail at a dose level (0.1 ml and 0.1 ml/100 g body weight, respectively). Mice were shaved gently on the back area of the skull and an antisepsis of the area was performed with 4% alcohol-based iodine. At the place of the operation, a small incision was induced, then gently removing a piece of the skull to expose the middle cerebral artery and allow for the electro cautery drill. Post-surgically, all the animals were kept separately in their cages, and the wounds were cleaned daily without any dressing or covering over the wound. All formulations were administered by micropipette into both nostrils, following the protocol discussed by Hanson and coworkers, three days before stroke induction and continuing for another three days after stroke. At the end of the third day after stroke, mice were sacrificed ethically through an isoflurane overdose according to IACUC (Institutional Animal Care and Use Committee) recommendations. After perfusion, both lung and brain were excised and imaged (Hanson et al., 2013; Mannucci et al., 2020). The noninvasive detection and quantification of fluorescence distributed throughout the isolated organs (brain and lung) were performed by (photon Imager optima - Bio Space Lab, France, Software Version: 3.5.10.1464), allowing the evaluation of the biodistribution of fluorescently labeled formulations (Mannucci et al., 2020). Fluorescent images were obtained for dissected brain and lung isolated from all groups at λex = 539 nm and λem= 615 nm. Results of PS, PDI and ZP are showed in Table 2. The particle size (Y1) of all formulations was in the range of 98.28 nm to 1925.60 nm for F5 and F3, respectively. The influence of independent variables and their interactions on particle size could be identified by the following polynomial regression equation: From the obtained results, it was observed that, when increasing the lipid concentration from 3 to 5 (% w/v), there was a strong significant negative correlation with particle size (Pearson coefficient (r) = −0.426 and P value = 0.014) (Gardouh et al., 2010). The particle size decreased from 138.33 ± 1.89 nm to 101.89 ± 2.84 nm (F2, F6), 1925.60 ± 75.075 nm to 394.10 ± 18.37 nm (F3, F7), and 639.46 ± 39.71 nm to 213.63 ± 0.503 nm (F4, F8) as elucidated in Figure 1a and Table 2. These results were in harmony with Steiner and Bunjes, who related this behavior to the non-linear increase in the viscosity of the continuous phase, which is inversely proportional to the droplet size (Steiner & Bunjes, 2021). Another explanation might be that the size of SLN is affected by the number of carbon atoms in the fatty acid chain of the lipid. GMS had a smaller number of carbon atoms on its fatty acid chain, resulting in a smaller SLN. Therefore, increasing Glyceryl mono-stearate concentration resulted in the formation of small sized SLN (Gamal et al., 2020). Increasing SAA concentration from 0.5 to 1.5 (% w/v) showed a strong significant positive correlation on particle size (r = 0.584 and P value < 0.0001). These results were in accordance with Soma et al. (2017). By the increase of SAA concentration from 0.5 to 1.5 (% w/v), a significant increase in particle size was noticed from 99.05 ± 4.62 nm to 1925.60 ± 75.075 nm (F1, F3), 138.33 ± 1.89 nm to 639.46 ± 39.71 nm (F2, F4), 98.28 ± 5.63 nm to 394.10 ± 18.37 nm (F5, F7) and 101.89 ± 2.84 nm to 213.63 ± 0.503 nm (F6, F8) as obvious in Figure 1b. These results were matched with Alajami and coauthors, who attributed these findings to the accumulation of excess SAA molecules at the nanoparticle surface or due to the expansion of the interfacial film by increasing SAA concentration (Asasutjarit et al., 2007; Alajami et al., 2022). Another justification for increasing particle size by increasing SAA concentration is the dehydration of propylene oxide and ethylene oxide blocks within the poloxamer molecule during emulsification and hot homogenization, leading to a reduction of steric repulsion (Gamal et al., 2020). Results in Figure 1c verified that, when homogenization speed was increased from 10,000 to 15,000 rpm at constant lipid and SAA concentration, particle size decreased significantly from 1925.60 ± 75.07 nm to 639.46 ± 39.71 nm (F3, F4) and 394.10 ± 18.37 nm to 213.63 ± 0.503 nm (F7, F8). This result might be due to inefficient speed to reduce the particles at a lower speed. Whereas, the high-speed homogenization was sufficient to decrease the particle size through the high intensity of the shearing force acting on the particles (Kushwaha et al., 2013). Polydispersity index is a measurement of the broadness of the particle size distribution. Values which less than 0.5 are usually accepted by researchers, while 0.3 and below are most favorable (Hassan et al., 2020). PDI values of all SLNs ranged between 0.191 ± 0.036 and 1 ± 0.00 for F7 and F4, respectively as shown in Figure 2. F4, F5, and F6 had PDI< 0.3, indicating a homogeneous population of lipid vesicles (Danaei et al., 2018). Figure 2a clarified that, increasing the lipid concentration from 3 to 5%, led to a significant decrease in PDI from 0.358 ± 0.03 to 0.259 ± 0.08 (F1, F5), 0.528 ± 0.02 to 0.195 ± 0.03 (F2, F6), 0.716 ± 0.07 to 0.191 ± 0.03 (F3, F7), and from 1 ± 0.00 to 0.556 ± 0.03 (F4, F8). This could be due to the reduction in particle size upon increasing lipid content. This was in accordance with Suhaimi and coworkers, who found that a decrease in the particle size was associated with a reduction in PDI values (Suhaimi et al., 2015). The increase in SAA concentration from 0.5 to 1.5%; resulted in an increase in PDI from 0.358 ± 0.03 to 0.716 ± 0.07 (F1, F3), 0.528 ± 0.02 to 1 ± 0.00 (F2, F4), and 0.195 ± 0.03 to 0.556 ± 0.03 (F6, F8), as demonstrated in Figure 2b. These results confirmed that the larger the particle size, the greater the PDI, and vice versa (Kaur et al., 2016a). Increasing PDI values upon increasing SAA% might be related to increasing the viscosity of the aqueous phase, which affected the emulsification efficiency during SLN preparation. As a result, particles of varying sizes were formed that contributed to a higher PDI (Hassan et al., 2020). Increasing the homogenization speed from 10000 to 15000 rpm; resulted in an increase in PDI from 0.358 ± 0.03 to 0.528 ± 0.02 (F1, F2), 0.716 ± 0.07 to 1 ± 0.00 (F3, F4), and 0.191 ± 0.03 to 0.556 ± 0.03 (F7, F8) as distinct in Figure 2c. Similar findings were obtained by Anarjan and coauthors, who found that the PDI of the nanodispersion systems was increased by increasing the speed of the homogenization process (Anarjan et al., 2015). Zeta potential is the overall charge of the particles, which helps to assess the formulation stability during storage (Radwan et al., 2019). The obtained results showed a non-linear correlation between ZP values and the independent variables, as observed in the following polynomial equation: All SLN formulations showed ZP values with negative charges, which indicated the stable nature of nanoparticles (Remya & Damodharan, 2018). The negative charge of SLNs might be attributed to the fatty acids released from GMS hydrolysis and the negative phospholipids from lecithin (Schuh et al., 2014; Emami et al., 2015). As demonstrated in Table 2, Val-loaded SLNs showed ZP ranges between −15.36 ± 0.51 mV and −22.06 ± 0.67 mV for F4 and F8, respectively. This ascertained better stability and dispersion in the medium (Shah et al., 2017). Regression analysis equation that interprets the effect of independent variables on EE% (Y3) is represented as following: From the obtained results in Figure 3a, it was evident that an increase in the lipid ratio from 3 to 5% w/v led to increased EE% from 13.3 ± 0.521% to 59.2 ± 1.37% (F1, F5) and 38.56 ± 0.34% to 42.8 ± 0.99% (F3, F7) at constant SAA% and homogenization speed. These results might be contributed to excessive drug accommodation within lipid core with high lipid concentration (Emami et al., 2015). Similar results were obtained by Emami et al., and Soma et al., who found that, increasing the lipid content, led to increasing the viscosity of the medium and faster solidification of nanoparticles, thus preventing drug diffusion into the external phase (Emami et al., 2015; Soma et al., 2017). As observed in Figure 3b, there was a significant positive correlation between SAA concentration and EE%. Increasing P407% from 0.5 to 1.5% w/v led to a significant increase in EE% from 13.3 ± 0.521% to 38.56 ± 0.347% (F1, F3), 42.88 ± 1.17% to 47.2 ± 1.536% (F2, F4), and 39.95 ± 0.79% to 48 ± 0.92% (F6, F8). These results might be attributed to, increasing the surface coverage of SLNs by increasing the SAA% and thus preventing drug leaching from the lipid matrix and consequently increasing the EE% (Kushwaha et al., 2013; Maqsood et al., 2022(. On the other hand, the combinatory effect caused by the simultaneous increase in the concentration of P407 in the aqueous phase decreased the EE% of Val from 59.2 ± 1.37% to 42.8 ± 0.99% (F5, F7) upon increasing SAA% from 0.5 to 1.5% w/v at (5% lipid and 10000 rpm). This was also observed by Da Silva et al. (2011) and Emami et al. (2015), who found that P407 might favor the solubilization of Val in the aqueous medium. The obtained results in Figure 3c detected that, the increase in homogenization speed from 10000 to 15000 rpm at constant lipid and SAA %, led to a significant increase in EE% from 13.3 ± 0.52% to 42.88 ± 1.17% (F1, F2), 38.56 ± 0.34% to 47.2 ± 1.53% (F3, F4) and 42.8 ± 0.99% to 48 ± 0.92% (F7, F8). These results were also reported by Mai et al. (2018). The in-vitro release of Val from pure drug solution and all SLN formulations was studied for 72 hours using the dialysis bag method in a BPS medium (pH 6.4). Pure Val showed a rapid release of about 90% in the first six hours, as observed in Figure 4. The effect of the independent factors on CDR% is illustrated in the following polynomial equation: The release pattern of most SLN formulations was noticed to be biphasic, with an initial burst release within the first four hours, this might be attributed to the drug on the surface of SLNs and its solubility in the selected medium (Kaur et al., 2016b; Rana et al., 2020), followed by sustained release over 72 hours (Yassin et al., 2010; Remya & Damodharan, 2018). The sustained release might be due to increasing the diffusional path length and hindering effects attained by the surrounding lipid core (Alajami et al., 2022). There was a negative correlation between X1, X2, and X3 on CDR% as indicated by Pearson correlation coefficients (-0.418, −0.523 and −0.430), respectively. For most formulations, increasing the lipid concentration, maintaining the drug release up to 72 hours by restricting the entry of medium and inhibited fast immobilization of Val from the lipid core and thus, extended the release % (Parvez et al., 2020). In another explanation, the diffusion distance from the lipid matrix decreased with the increase in lipid concentration (El-Say & Hosny, 2018; Bhattacharyya & Reddy, 2019). As seen in Table 3, the Higuchi model had a higher R2 value for in-vitro drug release of all SLN formulations than the Hixson-Crowell model. In addition, R2 value for the first order model was higher than that of zero order. These findings established that the drug release from all formulations followed the diffusion mechanism (Ibrahim et al., 2021). The n value of the Korsmeyer-Peppas model provided additional confirmation about the type of diffusion (Bibi et al., 2022). As detected in Table 3, n-value was found to be less than 0.5, indicating that the drug release mechanism was quasi-Fickian diffusion (Basak et al., 2008; Olejnik et al., 2017). Color change, particle aggregation, or phase separation were not seen in stored SLN formulations. According to the findings in Table 4, the particle size of certain formulations decreased significantly after being stored at refrigerator temperature. The decrease in particle size was correlated with the increase in the ZP as observed in F1, F3, and F7 respectively. Decreasing the particle diameter on storage at refrigerator temperature might be attributed to the microviscosity phenomenon, which is a property of the surfactant that prevents particle agglomeration and is a temperature-dependent factor that increases at refrigerator temperature (Shah et al., 2014; Makoni et al., 2019). As obvious in Table 5, the particle size of the optimized formulation (F9) without Rh-B coupling was higher than predicted (215.76 ± 7.47 nm to150 nm, respectively), but this value is still acceptable for brain targeting of SLNs, as demonstrated by Neves and coauthors, who reported that the particle size of most successfully used nanoparticles for drug delivery across the BBB ranged from 150-300 nm (Neves et al., 2015). However, particle size of (F9) which was loaded with Rh-B and administered in animals for in-vivo experiments was 166 ± 5.33 nm. Other measurements (PDI, ZP, and CDR%) were in good harmony with the predicted values as detectable in Table 5, which clarifies that the experimental design closely predicted the relationship between the dependent and independent variables and successfully assisted in setting up a model for optimizing Val-loaded SLNs (Gupta et al., 2016). FTIR was performed to investigate the possible type of interaction between pure Val and optimized formula components by elucidating the reduction, shifting, or disappearance of absorption bands of the studied samples. Figure 5 compares the FTIR spectra of the pure Val, the optimized formula, and its raw materials. In agreement with Chandana et al., Val showed characteristic peaks at 2963 cm−1 and 2932 cm−1 (C-H stretching, alkane), 1732 cm−1 (acidic C = O stretching), 1603 (ketonic C = O stretching), and 3430 cm−1 (carboxylic group, -COOH) (Chandana et al., 2021). The spectrum of GMS showed absorption bands at 3398 cm−1 for O-H stretching from the unesterified hydroxyl group of the glyceryl moiety, 1734 cm−1 (C = O, stretching), and 2918 cm−1 for C-H stretch in CH2 groups in the acyl chain of the fatty acid (Patel et al., 2014). In the case of the optimized formulation (F9), the characteristic peaks unique to the drug were not observed, indicating drug encapsulation into the nanocarrier (Ghorab et al., 2015; Omwoyo & Moloto, 2019). As well, there was a slight increase in the (O-H) band of GMS, which might be due to the formation of a hydrogen bond between Val and GMS. DSC patterns of Val, P407, egg lecithin, GMS, and optimized SLN (F9) were shown in Figure 6. It was clear that the melting peaks of bulk GMS and pure Val were at 61.1 °C and 101.62 °C, respectively. The sharp peak of Val crystals (101.62 °C) was absent in the thermogram of Val-loaded SLN (F9), which confirmed drug solubilization in the lipid matrix. Moreover, the endothermic peak of GMS in F9 was broadened and shifted to 69.1 °C compared to bulk GMS (61.1 °C), which indicated SLN formation (Sharma et al., 2021). The same manner was seen by Song and coworkers, who attributed this shift to the small particle size effect (nanometer range), their high specific surface area, and the presence of surfactant (Song et al., 2016). The XRD spectra of pure Val, optimized SLN (F9), and its components are represented in Figure 7. The diffraction spectra of pure Val showed characteristic peaks at a diffraction angle of 2θ degrees of 13.696, 14.194, 17.393, 21.775, and 25.182. These results were in great agreement with Sharma & Jain (2010), Zaini et al. (2017), and Abbaspour et al. (2021). Glyceryl monostearate is high crystalline in nature with characteristic peaks at 2θ of 18.823, 19.137, 21.146, 22.676, 23.23 and 36.51 with the highest intensity peak at 19.137 representing the β-crystal form (Su et al., 2016). The intensity of crystalline peaks of Val was reduced in the SLN formulation, which provided additional support that the drug was encapsulated within the carrier system (Parmar et al., 2011). The intensity of lipid peaks was also decreased in the SLN formulation which confirmed the decreased crystallinity of lipid in the SLN formulation (Parmar et al., 2011; Kushwaha et al., 2013; Rohit & Pal, 2013; Gupta et al., 2016; Behbahani et al., 2017). The shapes of the optimal Val-loaded SLN formulation (F9) with and without Rh-B coupling are shown in Figures 8 and 9. The particles examined were spherical and homogenous in shape, with a coating encapsulating the nanoparticles. TEM images showed slightly smaller particle sizes of nanoparticles compared to those measured with a Zetasizer instrument based on dynamic light scattering (Rubab et al., 2021). The fluorescent formulations were administered intranasally in mice, and fluorescence was investigated in the brain and lung to verify whether the drug was successfully distributed to the brain or not. The fluorescence intensity-per-area was identified by a color ranging from dark blue (low accumulation) to red (maximum accumulation) (El-Mezayen et al., 2018). Measurements were done by tracing a region of interest (ROI) on the fluorescent images, utilizing (PhotoAcquisition M3Vision analysis software) for photon quantification. These measurements were performed for lung and brain for all in-vivo tested formulations (Mannucci et al., 2020). The obtained results in Figure 10 showed that mice received the optimized formulation (F9) showed an apparent red fluorescence signal at the brain site, reflecting higher drug accumulation in the brain and successful delivery of Val loaded nanoparticle formulation across the BBB, as compared to the mice received the pure drug solution (F11), which showed a blue fluorescence at the brain site indicated the poor permeability of the pure drug across the BBB. These results were additionally confirmed by quantifying the fluorescence intensity in the brain and the lung. The obtained results in Figure 11 depict that the optimized SLN formulation (F9) showed significantly higher fluorescence intensity in the brain as compared to the pure Val solution (F11). Furthermore, there was a non-significant difference (P > 0.05) in florescence intensity between F11 and the control group which confirmed poor delivery of pure Val to brain. The organ distribution study revealed a higher accumulation of optimized formula in the brain as compared to free drug solution, confirming the successful delivery of Val-loaded SLN formulation to the brain. The results of various experiments led to the conclusion that the optimal SLN formula (F9), as suggested by full factorial design (23) was at a lipid concentration of 4.9379% w/v, 0.6507% w/v P407, and 10,000 rpm, demonstrated acceptable particle size, EE%, and sustained drug release over three days, which could be beneficial in decreasing dose frequency and increasing patient compliance. In-vivo photon imaging and fluorescence intensity quantification in dissected brain and lung of all animal groups indicated that the optimized Val-loaded SLN successfully delivered Val to the brain. Finally, Val-loaded SLNs could be a promising strategy for mitigating the negative effects of stroke with high efficacy and low side effects.

PMC10003142

Ekaterina V. Novosadova,Oleg V. Dolotov,Lyudmila V. Novosadova,Lubov I. Davydova,Konstantin V. Sidoruk,Elena L. Arsenyeva,Darya M. Shimchenko,Vladimir G. Debabov,Vladimir G. Bogush,Vyacheslav Z. Tarantul

Composite Coatings Based on Recombinant Spidroins and Peptides with Motifs of the Extracellular Matrix Proteins Enhance Neuronal Differentiation of Neural Precursor Cells Derived from Human Induced Pluripotent Stem Cells

02-03-2023

composite coatings,recombinant spidroins,fused peptides with ECM motifs,induced pluripotent stem cells,neural precursor cells,dopaminergic neurons

The production and transplantation of functionally active human neurons is a promising approach to cell therapy. Biocompatible and biodegradable matrices that effectively promote the growth and directed differentiation of neural precursor cells (NPCs) into the desired neuronal types are very important. The aim of this study was to evaluate the suitability of novel composite coatings (CCs) containing recombinant spidroins (RSs) rS1/9 and rS2/12 in combination with recombinant fused proteins (FP) carrying bioactive motifs (BAP) of the extracellular matrix (ECM) proteins for the growth of NPCs derived from human induced pluripotent stem cells (iPSC) and their differentiation into neurons. NPCs were produced by the directed differentiation of human iPSCs. The growth and differentiation of NPCs cultured on different CC variants were compared with a Matrigel (MG) coating using qPCR analysis, immunocytochemical staining, and ELISA. An investigation revealed that the use of CCs consisting of a mixture of two RSs and FPs with different peptide motifs of ECMs increased the efficiency of obtaining neurons differentiated from iPSCs compared to Matrigel. CC consisting of two RSs and FPs with Arg–Gly–Asp–Ser (RGDS) and heparin binding peptide (HBP) is the most effective for the support of NPCs and their neuronal differentiation.

Composite Coatings Based on Recombinant Spidroins and Peptides with Motifs of the Extracellular Matrix Proteins Enhance Neuronal Differentiation of Neural Precursor Cells Derived from Human Induced Pluripotent Stem Cells The production and transplantation of functionally active human neurons is a promising approach to cell therapy. Biocompatible and biodegradable matrices that effectively promote the growth and directed differentiation of neural precursor cells (NPCs) into the desired neuronal types are very important. The aim of this study was to evaluate the suitability of novel composite coatings (CCs) containing recombinant spidroins (RSs) rS1/9 and rS2/12 in combination with recombinant fused proteins (FP) carrying bioactive motifs (BAP) of the extracellular matrix (ECM) proteins for the growth of NPCs derived from human induced pluripotent stem cells (iPSC) and their differentiation into neurons. NPCs were produced by the directed differentiation of human iPSCs. The growth and differentiation of NPCs cultured on different CC variants were compared with a Matrigel (MG) coating using qPCR analysis, immunocytochemical staining, and ELISA. An investigation revealed that the use of CCs consisting of a mixture of two RSs and FPs with different peptide motifs of ECMs increased the efficiency of obtaining neurons differentiated from iPSCs compared to Matrigel. CC consisting of two RSs and FPs with Arg–Gly–Asp–Ser (RGDS) and heparin binding peptide (HBP) is the most effective for the support of NPCs and their neuronal differentiation. Tissue engineering aims to develop functional biological substitutes that restore, maintain, or improve broken tissue function by combining matrices, cells, and biologically active macromolecules. However, despite the notable successes of modern developments in the creation of various tissue engineering constructs, the task of obtaining matrices with optimized properties that improve the differentiation of NPCs into the desired types of neurons, the survival of transplanted neural cells and the high rate and degree of their vascularization and innervation required to ensure sufficient blood supply and normal functioning of the reconstructed nervous tissue still remain unsolved [1]. One of the attractive materials for such matrices are spidroins, which make up the frame filaments (dragline silk) of the spider web of orb weaving spiders. These proteins are characterized by unique mechanical properties—a combination of the highest values of strength and elasticity, which leads to high values of energy of rupture; they are also resistant to high and low temperatures and aggressive chemical influences [2]. Recombinant analogues of spidroins (RSs) have been obtained and their properties are largely close to natural [3]. Aside from high mechanical properties, RSs are biocompatible with any tissues of animals and humans, non-immunogenic, non-allergenic, and biodegradable to amino acids. Due to their self-assembly ability, RSs can form various supramolecular structures such as hydrogels including microgels, transparent elastic films, highly porous spongy 3D scaffolds, nonwoven materials, etc. [4]. In addition, the positive surface charge of these proteins and all devices based on them is very important for the adhesion of any cells including nerve cells to the substrate [5]. Another advantage of RS-based matrices is the possibility of introducing various biologically active peptides (BAPs) including motifs of the extracellular matrix (ECM) proteins into their structure. This allows obtaining matrices with unique predetermined properties, which are superior to synthetic and natural materials in terms of their breadth of application and the set of useful properties [6]. For tissue engineering, the sources of human nerve cells are also important. Significant progress in the technology of their production is associated with the creation of a reprogramming methodology, allowing for the transformation of the somatic cells of adult organisms into induced pluripotent stem cells (iPSCs) [7]. Various cocktails of small molecules and growth factors are used for directed neuronal differentiation of iPSCs, and the substrate on which this differentiation occurs is also extremely important. Currently, one of the most commonly used substrate is Matrigel (MG), derived from the basal membrane of Engelbreth–Holm–Swarm mouse sarcoma, which is rich in various ECM proteins including laminin, collagen IV, proteoglycans, heparin sulfates, and growth factors. However, this matrix cannot be used for regenerative medicine due to its oncogenic origin and potential for pathogen contamination [8]. Among the currently used matrix materials, RSs appear to be among the most promising for dealing with neuronal differentiation of cells derived from iPSCs in vitro. Some RSs have been shown to be effective agents in brain repairing after stroke due to the presence of multiple repeats of the GRGGL sequence recognized by NPC [9]. RS-based matrices support the proliferation and neuronal differentiation of neural stem cells. They have a more suitable surface charge (positive over the entire range of physiological pH values) and stiffness to support NSC growth than matrices made from silk fibroin or polylysine [10]. Previously, it has also been shown that the nonwoven matrix based on RSs rS1/9 and rS2/12, polycaprolactone and platelet-rich plasma, supports growth and neuronal differentiation of human NPCs [11]. The aim of this study was to evaluate the suitability of novel CCs containing RSs rS1/9 and rS2/12 in combination with the first time obtained by genetic engineering fused proteins (FPs) containing SUMO, RS rS1/9 “monomer”, and some BAP of the ECM proteins, for the growth of NPCs derived from human iPSCs and their differentiation into dopaminergic (DA) neurons. The following CCs were used in this work: SP1: rS2/12 + FP(RGDS); SP2: rS2/12 (control for SP1 and SP5); SP3: rS1/9 + rS2/12 + FP(RGDS) + FP(HBP); SP4: rS1/9 + rS2/12 (control for SP3); SP5: rS2/12 + FP(GRGGL), where FP(RGDS) is the fused protein with the RGDS motif; FP(HBP) is the fused protein with the heparin binding peptide (HBP) motif; and FP(GRGGL) is the fused protein with the GRGGL motif. The Matrigel coating (MG) was used as the positive control. In the first stage of the work, we evaluated the ability of five different variants of CCs based on RSs rS1/9 + rS2/12, both individually and in combination with FP, to support the growth and proliferation of NPCs obtained by the directed differentiation of human induced pluripotent cells (iPSCs). The MG coating served as a comparison. A schematic of the experiment is shown in Figure 1. Nerve cells derived from iPSCs at different stages of differentiation (NPC, IDN, and DN) were initially characterized using qPCR by the level of transcription of early and late neuronal markers in them. It was shown that as neuronal differentiation proceeds, the expression level of early neuronal markers (NESTIN, PAX6, SOX2) decreased in the cells, while the expression level of late ones (TUBB3), in contrast, increased (Figure 2). Next, the ability of NPCs and IDNs to proliferate when cultured on CCs compared with the MG coating was assessed (Figure 3). As can be seen from the histograms in Figure 3a, the proliferation of NPCs is reduced when cultured on all CCs compared to MG with the exception of SP3. At the same time, the observed decrease in IDN proliferative activity when cultured on SP3 was minimal compared to the other variants including MG. The adhesive properties of most of the studied CCs for NPS and IDN were also decreased compared to MG, the only exception being SP3 (Figure 3). To evaluate the effect of different CC variants on NPC differentiation, the expression levels of mRNA specific for early (PAX6, SOX2 and NESTIN) and late (TUBB3) neuronal genes were analyzed in these cells using qPCR. NPCs were dispersed onto coating-treated culture dishes and cultured for 5 days. We found that the expression level of early and late neuronal marker genes did not differ significantly by cultivation NPCs on all of the analyzed coatings (Table 1). Analysis of early neuronal marker expression at the protein level using immunocytochemical staining showed that the NPC stage contained more than 75% SOX2-positive cells in the population (Figure 4). The number of such cells was not statistically different when cultured on different CCs and MG, which confirms the data from the qPCR analysis (Figure 4a). Given the fact that NPCs can differentiate in both the neuronal and glial direction, we estimated the number of spontaneously differentiated glial cells and showed that they represented less than 1% of the total population (Figure 4a). Figure 4b shows the representative photos of the immunocytochemical staining of the resulting cell population. Next, we analyzed the effect of cultivation on different CCs on IDN differentiation from the NPCs. For this purpose, the NeuN protein, which is a nuclear protein present in postmitotic neurons, was used as a marker protein. We found that the number of NeuN-positive cells did not differ between different cells up to 41 days of cultivation (Figure 5). The dopaminergic (DA) neurons play an essential role in maintaining the human brain’s normal sensation, voluntary movement, emotion, and cognition [12]. The previously described protocol was used for the directed production of DA neurons from NPCs [13]. In IDN and DN obtained by the cultivation of NPS on different CCs, we performed a comparative study of the mRNA expression levels of the genes’ characteristic of DA neurons—tyrosine hydroxylase (TH) and the aromatic L-amino acid decarboxylase (AADC) (Figure 6). As can be seen from Figure 6, there was a significant increase in the expression of TH and AADC genes specific to DA neurons in DNs formed by cultivation on different CCs. This suggests that these CCs are very effective in affecting differentiation when using our protocol of the directed differentiation of NPCs into DA neurons. Using immunocytochemical analysis with anti-TH antibodies, we showed that in DNs, despite a significant increase in TH gene transcription, this change was less significant at the protein level (about 40%) and was observed only when cells were cultivated on the SP3 and SP5 coatings (Figure 7). Figure 8 shows the representative photographs of DN cultured on different CCs. The study of the transcription of marker genes responsible for synaptogenesis showed that the expression of the SNAP25, STX1A, SNPT, SYN2, and SYN3 genes did not differ significantly from all the CCs and MG used for the cultivation NPCs (Table 2). Further differentiation of NPCs into IDNs when cultivated on all CCs (except SP4) resulted in the increased expression of the synapse-specific genes SNAP25, STX1A, SYN2, and GSG1L compared to MG. By day 45 of differentiation, the expression levels of the studied genes in DN generally leveled off. There was only an increase in SNPT expression in DNs when they were cultivated on SP1 and SP5 (Table 3). Synapsins (SYN, SYN2, and SYN3) are also important markers of cellular synaptogenesis ability. As can be seen from Table 4, only IDNs showed a marked increase in the transcription of individual genes of this family when cells were cultivated on CCs. Thus, we can conclude that the studied coatings based on RSs and FPs compared to MG contribute to the enhancement of synaptogenesis in the process of neuronal differentiation of NPS into IDN. The main difference in the expression of genes involved in synaptogenesis mainly occurs with coatings with BAP (SP1, SP3 and SP5). To establish the role in synaptogenesis of BAPs included in SP1, SP3, and SP5 coatings (RGDS, RGDS + HBP and GRGGL motifs, respectively), as part of FP, the effect of these CCs was compared with that of the CCs without BAPs (SP2 and SP4). SP2 consisting only of rS2/12 was used as the internal controls for SP1 and SP5, and SP4 coatings consisting only of a mixture of two RSs (rS1/9 + rS2/12) were used as a control for SP3. For this purpose, we compared the expression levels of genes involved in synaptogenesis in the IDNs and DNs obtained by cultivating on different controls with their internal controls. Table 5 and Table 6 present the data of the qPCR analysis of the transcription of various genes involved in synaptogenesis as ratios of the gene expression levels in IDN and DN cultured on the coating with added FPs (SP1, SP3, SP5) to SP2 and SP4 not containing these proteins. In the intermediate stage of neuronal differentiation (IDN), all coatings with BAP showed an increased expression of the synaptogenesis marker genes GSG1L and SYN2. The expression in the STX1A gene was enhanced in IDNs obtained when the cells were cultured on SP5, and the expression of the SNAP25 gene was enhanced in IDNs obtained on the SP3 coating. At the same time, the maximum difference in expression was observed with the SP3 coating compared with MG (Table 6). Thus, we can conclude that the presence of BAP in the coatings contributes to the enhancement in the expression of a number of genes involved in synaptogenesis in IDNs. The maximum activation of the transcription of these genes was observed when cells were cultured on the SP3 coating containing BAPs both with RGDS and HBP motifs. Next, we investigated the effect of the coatings analyzed on the expression in the IDNs and DNs of neurotrophic factor (NTF) genes, which are necessary for normal differentiation and the maintenance of neuronal viability. When cultured on all coatings in the IDN intermediate stage, there was a significant increase in the expression of the BDNF, GDNF, and NGF genes, while in contrast, the NT3 gene decreased its expression (Table 7). At the same time, in DNs cultured on CCs, the NTF expression levels were commensurate with the cells cultured on MG. The protein amounts of BDNF and GDNF were assessed in DNs differentiated on different CCs using commercial enzyme-linked immunosorbent assay (ELISA) kit. It was found that when cells were cultured on the SP1, SP3 and SP5 coatings, the levels of both BDNF and GDNF in the cell lysates were many times (more than 10-fold) higher than when MG was used as a coating (Figure 9). At the same time, BDNF and GDNF were not detected in the conditioned media collected from the corresponding cultures. Since the SP1, SP3, and SP5 coatings contain FPs with BAPs, the results indicate that peptides of ECM proteins contribute to the enhancement of NTF synthesis in CC-forming DNs. Cell therapy for neurodegenerative diseases requires the creation of functionally active neuronal constructs that can be used for transplantation. This goal, first of all, requires the selection of NPCs as well as the selection of matrices that allow these cells to grow and differentiate into mature neurons. The task of the present study was to find the optimal composition of RS-based matrices that would most effectively promote the growth and directed differentiation of human iPSC-derived NPCs into the desired neuronal types and provide increased survival of transplanted nerve cells after their transplantation. Our previous experience of using RSs in the form of microgels, highly porous spongy like 3D scaffolds, isotropic and anisotropic nonwoven matrices indicates that these materials are effective for neuronal cell growth and differentiation and can induce neoangiogenesis and neoinnervation when transplanted into the lesion area in the animal body, which is crucial for damaged tissue regeneration. The choice of RSs as a base material for such matrices is associated with the previously obtained results of successful applications of these proteins for the cultivation of various types of cells and in experiments on laboratory animals. For example, a layer of isolated neonatal rat cardiomyocytes was grown on a nonwoven matrix of RS rS1/9, rS2/12, and rS2/12-RGDS obtained by electrospinning and not containing any additional biologically active compounds. Optical excitation mapping proved that the cells do indeed form syncytium, and the excitation impulse travels through the grown tissue, causing synchronous cell contraction, as in in vivo cardiac tissue [14,15]. In experiments on laboratory animals, it was found that bioengineered microparticles from RS perform not only the function of a framework for cells, but are themselves capable of influencing the immune response and have pro-regenerative properties [16]. It was also shown that rS1/9-based anisotropic nonwoven matrices in combination with platelet-rich plasma are a suitable biocompatible substrate for reprogrammed NPCs when implanted into the brain and spinal cord of rhesus macaques [11]. BAPs with ECM motifs have long been utilized in the creation of scaffolds for neural tissue cells as components of matrices [17]. Cultivation of NPCs on anisotropic matrices based on rS1/9 PC and BAPs with motifs from ECM proteins (RGD from fibronectin, IKVAV laminin pentapeptide, and VAEIDGIEL motif from tenascin-C) mainly preserved their stemness in the growth medium [18]. It was demonstrated that different motifs have different effects on neurogenesis: the RGD motif promotes the formation of a smaller number of neurons with longer neurites, whereas the IKVAV motif is characterized by the formation of more NF200-positive neurons with shorter neurites. In experiments with nonwoven matrices made of RS with oriented fibers, they have been shown to direct the migration of Schwann cells and accelerate axonal growth from mouse dorsal ganglia as well as induce the migration of smooth muscle and aortic endothelial cells [19]. The present work is a logical continuation of our series of studies on the effect of RS-based matrices and their derivatives on the growth and differentiation of human and animal nerve cells in vitro and in vivo. In contrast to previous studies, the object of the present work was NPCs derived from human iPSCs. To study the growth and differentiation of NPS in vitro, a mixture of previously genetically engineered RS (rS1/9 and rS2/12) and FPs with three BAPs was used as a coating: RGDS tetrapeptide from fibronectin that recognizes the integrins of most cells; the GRGGL pentapeptide, which is recognized by NCAM and provides good adhesion of neural precursors, and heparin-binding peptide (HBP). HBP is part of laminin, which is a major component of the basal membrane surrounding the brain and blood vessels throughout the CNS [20], and is also present in the ventricular zone of the developing neocortex. Laminins have been shown to promote the expansion, migration, and differentiation of NSCs in vitro [21,22]. In addition, HBPs have been found to be involved in the binding of various growth factors and to interact with syndecans in the cell membrane [23]. Cultivating NPS and NDN on most of the studied CCs revealed a decrease in the adhesive properties and ability to support cell proliferation compared to MG, the only exception being SP3 coatings (Figure 3). At the same time, we found no change in the expression levels of early and late neuronal marker genes in cultivated NPCs on all the analyzed coatings (Table 1). However, a further comparison of the effect on the growth and differentiation of NPCs when they were cultured on CCs and standardly used MG, showed a marked advantage of the former. It was shown that in the DA neurons formed on CCs, there was a multiple increase in the expression of the AADC and TH genes characteristic of this cell type (Figure 6). These data were partially confirmed by immunocytochemical staining with antibodies to tyrosine hydroxylase: in particular, there was an increase in the number of DA neurons on the SP3 and SP5 coatings (Figure 7). Thus, we can conclude that these CCs are more effective than the MG coating for the directed differentiation of NPCs into DA neurons. In addition, IDNs cultured on CCs (Table 4 and Table 5) showed a marked increase in the transcription of certain genes involved in synthapogenesis compared to cells cultured on the MG coating (Table 3 and Table 4). This may indirectly indicate the acceleration of neuronal differentiation on the studied CCs. The maximum number of genes that changed their expression at this differentiation stage was observed when the cells were cultured on CCs SP1, SP3, and SP5. At the stage of DN, an increase in the expression of the SNPT gene was noted when cells were cultured on SP1 and SP5. To assess the role in the synaptogenesis of BAPs included in the FPs of the SP1, SP3, and SP5 coatings, the effects of these coatings were compared with the effects of CCs without BAPs (SP2 and SP4). It was found that all BAPs, to varying degrees, caused the upregulation of the studied genes. The maximum number of upregulated genes (SNAP25, SNPT, PSD95, SYN2, and GSG1L) was observed for SP3. The cultivation of cells on SP5 led to increased expression of STX2, SYN2, and GSG1L, and on SP1, only SYN2 and GSG1L. The secretion of NTFs, secretory dimeric proteins that have a significant influence on all biological processes of neurons during pre- and postnatal ontogenesis, is essential for the normal development and viability of neurons. In the developing nervous system, neurotrophins regulate cell division, cell migration, differentiation, establishment, and maintenance of intercellular contact activity as well as the initiation of apoptosis [24,25,26]. It was shown that the expression of most of the studied NTF genes (BDNF, GDNF, NGF) was enhanced at the NDN stage, the only exception being NT3, whose expression, in contrast, was decreased in all CC variants compared to the MG coating (Table 7). The maximum difference was observed for the SP1, SP3, and SP5 coatings, while for these same CCs, the increased expression of these genes persisted in DN, which was confirmed for BDNF and GDNF at the protein level (Figure 9). The fact that the increased expression of most of the studied genes involved in neuronal differentiation was observed for the SP5 variant containing the GRGGL sequence, in contrast to the SP2 variant that does not contain this sequence, which indicates the effect of GRGGL on the differentiation process. At the same time, a significant increase in the expression of the studied genes was found when the cells were cultivated on the SP5 coating compared to SP4 containing the rS1/9 protein, which includes 18 repeats of the GRGGL sequence [27]. This can be explained by the lower availability of GRGGL for contact with NCAM in the cell walls compared to the same in SP5, where it was exposed above the surface of the coating due to the presence of a 14-mer linker (SGG)4S, which ensures the binding of this peptide to the rest of FP and gives it extra mobility. The found influence of various BAPs on the differentiation of neural progenitors through the activation of the expression of the studied genes normally involved in differentiation is associated with the known role of these peptides in cell activation. This activation is mediated via various pathways of interaction of the BAPs with cells: RGDS interacts with integrins, BAP interacts with syndecans, GRGGL interacts with NCAM. A positive effect on the expression of genes involved in neuronal differentiation was already observed for individual BAPs (RGDS and GRGGL in SP1 and SP5, respectively). At the same time, the maximum effect, as expected, was found for the SP5 coating containing all three BAPs used in the work (GRGGL in the rS1/9 protein, RGDS, and HBP). These results are in good agreement with the known literature examples of the use of similar BAPs for the adhesion, proliferation, and differentiation of neuronal cells [28,29,30]. Thus, certain newly created RS- and FP-based CCs with ESM motifs promote NPC differentiation into DN by enhancing the expression of genes involved in synaptogenesis, stimulating the synthesis of a number of NTFs and contributing to the production of human DA neurons. We used two RS—rS1/9 and rS2/12, whose genes we previously cloned in Saccharomices cerevisiae [14,27]. The rS1/9 molecule has a molecular mass of 94 kDa and consists of nine so called monomers, consisting of four initial repeats. Each of them contains GGX tripeptides (X = L, Y, Q) and one poly-Ala cluster consisting of five to eight Ala residues. This protein also contains 18 repeats of the NCAM-binding sequence GRGGL, which is a signal for binding neuronal cells. The rS2/12 molecule has a molecular mass of 113 kDa and consists of 12 so called monomers, consisting of five initial repeats. Each repeat contains pentapeptides GPGGY and GPGQQ and also one poly-Ala cluster consisting of five to eight Ala residues. These poly-Ala clusters form β-sheets, which, in turn, form crystallites that provide a unique stability to the materials based on spidroins [27]. Yeast biomass production, RS isolation, and purification by ion-exchange chromatography using a HiPrep 16/10 SP FF column (GE Healthcare, Chicago, IL, USA) and an ACTA purifier TM chromatograph (GE Healthcare, Chicago, IL, USA) with pH exchange (pH 4.0–pH7.0–pH4.0) were carried out in accordance with previously published protocols [18]. The RSs were eluted from the column and dialyzed against deionized water and then frozen and lyophilized as described. FPs containing different BAPs were designed according to the same scheme: H6-SUMO-rS1/1-G(SGG)4S-[BAP], where H6 is the his-tag for ease purification of FPs on a Ni-column; SUMO (Small Ubiquitin Like Modifier) is a peptide product of the yeast Smt3 gene [31], which, according to the literature [32] and our experience, increases the yield of the product in E.coli cells (can dramatically improve protein solubility, achieve native protein folding, and increase total yield by improving expression and decreasing degradation); rS1/1—monomer of rS1/9, which acts as an “anchor” in the interaction with full-sized RSs; G(SGG)4S is a neutral linker that promotes the exposure of biologically active peptide (BAP) over the matrix surface; BAP—any of the cloned BAP. We chose the following polypeptides as BAPs: RGDS, a tetrapeptide from fibronectin that recognizes the integrins of most cells [33,34]. GRGGL is a pentapeptide that is recognized by NCAM, interacts with neuron surface receptors, and upregulates NCAM expression in primary cortical neurons from embryonic day 18 (E18) Sprague–Dawley rats [9]; HBP—heparin binding peptide (GGGGSPPRRARVTY) [35], which is involved in the binding of various growth factors and interacts with syndecans in the cell membrane [23]. The genes of all three FPs were designed and chemically synthesized. The codons in the sequences were optimized to facilitate the synthesis of the construct: the rarest codons in E. coli were removed. The resulting constructs were cloned in the pET-28a-Novagen expressive vector (Novagen, Merck KGaA, Darmstadt, Germany) at the NcoI and XhoI restriction sites and transformed into the E. coli strain BL21(DE3) (Novagen, Merck KGaA, Darmstadt, Germany)) using the same vector. As a result, three strains, producing FPs: FP(RGDS), FP(GRGGL), and FP(HBP) were obtained. To isolate FPs, the strain producers were grown in a 10 L fermenter in a growth medium (20 g/L soy peptone Amresco 140 (VWR Life Science AMRESCO, Cambridge, MA, USA); 10 g/L yeast extract Maisons-Alfort, France; 5 g/L glucose (Acros Organics, Waltham, MA, USA); 5 g/L NaCl (Scharlab, Sentmenat, Barcelona, Spain); 0.5 g/L kanamycin (VWR Life Science AMRESCO, Radnor, PA, USA)); up to stationary phase; induction was carried out with lactose as part of the feed (20 g/L soy peptone Amresco 140; 10 g/L yeast extract; 30 g/L glucose; 5 g/L NaCl; 0.5 g/L kanamycin). The process was carried out at 28 °C, pH 7.0 with a typical growth time of 16–18 h. Biomass was harvested by centrifugation (14,000× g at 4 °C for 30 min) and suspended in buffer (0.05 M Na-Pi buffer, pH 8.0; 0.2 M NaCl; 5% glycerin; 0.02 M imidazol) at a ratio of 9:1. Suspension was sonicated in 50 mL of buffer and clarified by centrifugation. To purify the FP, chromatography with the FPLC system ÄCTApurifierTM an ACTA (GE Healthcare, Chicago, IL, USA) with an installed HiTrap 5 mL of the NiNTA resin column (GE Healthcare, Chicago, IL, USA) was utilized. The elution was carried out stepwise using a decrease in pH to 6.0 and an increase in the content of imidazole (BioFroxx, Bruckberg, Germany) to 0.45 M in a buffer of the same composition. The desired proteins were detected using electrophoresis in 15% PAAG-SDS. The proteins after chromatographic purification were dialyzed against deionized water, frozen at −70 °C and freeze-dried. Protein concentrations were determined by spectrometry at 280 nm. After purification, the samples contained >95% of the target protein. Freeze-dried proteins (both full-length RSs and FPs) were dissolved in concentrated (99.7%) formic acid (Helicon, RF) to a final concentration of 400 mg/mL for 14–16 h until complete dissolution. Then, the protein solutions were mixed in such a way that the final total concentration of all proteins was equal to 400 mg/mL, while the total concentration of FP in each solution was 10% of the total protein. After that, each sample was diluted 100 times with deionized water. The final total protein concentration for all samples was 2 mg/mL, and the concentration of formic acid was 1%. Solutions were centrifuged at 18,000× g at 4 °C for 30 min to remove protein aggregates immediately prior to use. In the preliminary experiments, it was found that the optimal ratio between the full-size RSs and FPs was a ratio of 9:1 (by weight), so this ratio was used in all experiments. This meant that the total mass of full-sized RSs in the mixture was always 90%, and the total mass of FPs was 10%. At the same time, both rS1/9 and rS2/12 among themselves, and FP among themselves had always been in an equal ratio. Coating RS and FP mixtures were prepared immediately prior to use. To do this, we mixed the prepared solutions of each protein in the selected ratio. MG solution was prepared according to the manufacturer’s protocols (Corning Life Sciences, NY, USA). In this work, six variants of samples for the coating cups were used: SP1: rS2/12 + FP(RGDS) in relation to 9:1; SP2: rS2/12 (control for SP1 and SP5); SP3: rS1/9 + rS2/12 + FP(RGDS) + FP(HBP) in relation to 4.5:4.5:0.5:0.5; SP4: rS1/9 + rS2/12 (control for SP3) in relation to 5:5; SP5: rS2/12 + FP(GRGGL) in relation to 9:1; MG: (Matrigel, positive control). where FP(RGDS) is the fused protein with the RGDS motif; FP(HBP) is the fused protein with the HBP motif; and FP(GRGGL) is the fused protein with the GRGGL motif. The coating was carried out as follows: 1 mL of the prepared protein solutions was poured into a sterile Petri dish (d = 35 mm) and incubated in a laminar box for 30 min, the protein solution was removed and to stabilize the coatings, the samples were immersed in 96% (v/v) ethanol for 30 min to induce a β-sheet structure [36]. After that, the dishes were incubated for 30 min in sterile deionized water followed by 70% ethanol for 30 min and then in sterile deionized water. This procedure was repeated 10 more times. The cups were dried and used immediately, or wrapped with Parafilm and stored at +4 °C for a month. A standard cup coating procedure was used for the Matrigel. A total of 1 mL of the solution was poured into a sterile Petri dish (d = 35 mm) and incubated for 60 min. The treated cups were used immediately or wrapped with Parafilm and stored at +4 °C for a month. Immediately before use, the Matrigel was removed and washed once with DMEM medium containing penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation). The study complies with the World Medical Assembly Declaration of Helsinki—Ethical Principles for Medical Research Involving Human Subjects. This work was approved by the Ethic Committee of the Institute of Molecular Genetics of National Research Centre “Kurchatov Institute” (Protocol no. 3 from 19 February 2018). Donor provided a written informed consent. The work was carried out on the iPSC line (IPSHD1.1S) obtained from skin fibroblasts of a healthy donor using the CytoTune™-iPS 2.0 Sendai Reprogramming Kit. The reprogramming vectors included the four Yamanaka factors, Oct, Sox2, Klf4, and c-Myc, shown to be sufficient for efficient reprogramming. The obtained iPSC expressed the essential pattern of specific pluripotency-associated genes, possessed a normal karyotype, and were capable of producing the derivatives of embryonic threenic germ layers [37]. Cells were cultured in StemMACS iPS-BrewXF medium (Miltenyi Biotec, Nordrhein-Westfalen, Germany) on Matrigel (Corning Life Sciences, NY, USA) treated with Petri dishes. The medium was changed daily. iPSCs were cultured in CO2 incubator (5% CO2, 80% humidity and 37 °C) in iPS-Brew XF basal medium (Miltenyi Biotec, Nordrhein-Westfalen, Germany) until reaching an 80% confluent monolayer. The culture medium was replaced by the medium for neural progenitors. After 10–14 days of cultivation, neural rosettes with specific “ridges” were formed. Rosettes were mechanically transferred to a 24-well plate with ultra-low adhesion (Corning Life Sciences, NY, USA) and cultivated for 3–5 days until neurospheres were formed. Neurospheres were collected and treated with 0.05% trypsin (ICN Biomedicals, Hackensack, NJ, USA). After trypsin inactivation in DMEM supplemented with 10% FBS (HyClone, Waltman, MA, USA), cells were resuspended in growth medium for neural progenitors with 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA), and transferred to Petri dishes coated with Matrigel (Corning Life Sciences, NY, USA). NPs were cultivated to a dense monolayer, changing the medium every 48 h. After reaching the monolayer, NPCs were plated with 0.05% trypsin on new Petri dishes coated with Matrigel at a dilution of 1:4 or 1:5. Cells were cultured in a CO2 incubator (5% CO2, 80% humidity, and 37 °C). To study the effect of different matrices on the proliferation and differentiation of NPCs, cells of 2–3 passages were used. NPCs were dispersed onto Petri dishes pretreated with MG and RS. Culture medium for NPCs: Neurobasal medium (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), 2% serum replacement (Gibco, Carlsbad, CA, USA), 1% N2 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc., Hackensack, NJ, USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 10 μM SB431542 (Stemgent, Cambridge, MA, USA), and 80 ng/mL recombinant Noggin (Peprotech, Cranbury, NJ, USA). Culture medium for neuronal differentiation type I (NDN): Neurobasal medium A, (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), 2% serum replacement (Gibco, Carlsbad, CA, USA), 1% B-27 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc., Hackensack, NJ USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 100 ng/mL human SHH (Miltenyi Biotec, Nordrhein-Westfalen, Germany), 100 ng/mL FGF8 (PeproTech, Cranbury, NJ, USA), 10 μM purmorphamine (Sigma-Aldrich, Saint Louis, MO, USA). Culture medium for neuronal differentiation type II (DN): Neurobasal medium A, (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), 2% serum replacement (Gibco, Carlsbad, CA, USA), 1% B-27 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc, Hackensack, NJ, USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 20 ng/mL BDNF (PeproTech, Cranbury, NJ, USA), 20 ng/mL GDNF (PeproTech, Cranbury, NJ, USA), 200 μM ascorbic acid (StemCell, Vancouver, BC, USA), 4 μM Forskolin (Stemgent, Cambridge, MA, USA). The NPs were disseminated at 200,000 cells per cm² into Petri dishes pre-treated with MG and RS in neuronal precursor medium supplemented with 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA). The next day, the medium was replaced with medium for the differentiation of type I neurons. The cells were cultured for 10 days, with the medium changing every other day. After the cells reached a dense monolayer, they were disseminated to new 1:4 or 1:5 cups. On the ninth day of cultivation, the cells were removed from the substrate with 0.05% trypsin (Gibco, Carlsbad, CA, USA) and disseminated on a prepared culture dish at 400,000 cells per cm2 in medium for the differentiation of type I neurons with the addition of 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA). The next day, the medium was changed to medium for the differentiation of type II neurons and the cells were cultured for 14 days. The medium was changed every other day for the first 7 days and daily thereafter. Cells were cultured in CO2-incubator (5% CO2, 80% humidity, and 37 °C). The adherent cells on the Petri dish were washed with PBS, fixed with 4% para-formaldehyde in PBS (pH 6.8) for 20 min at room temperature (RT), and washed in PBS with 0.1% Tween 20 (Sigma-Aldrich, Saint Louis, MO, USA) three times for 5 min. Nonspecific antibody sorption was blocked by incubation in blocking buffer (PBS with 0.1%, Triton x100, and 5% fetal bovine serum (HyClone, Waltman, MA, USA)) for 30 min at RT. Primary antibodies (Table 8) were applied overnight at 4 °C, and then washed in PBS with 0.1% Tween 20 three times for 5 min. The secondary antibodies were applied for 60 min at RT, then washed in PBS with 0.1% Tween 20 three times for 5 min. After that, the cell cultures were incubated with 0.1 μg/mL DAPI (Sigma-Aldrich, Saint Louis, MO, USA) in PBS for 10 min for visualization of the cell nuclei, and washed twice with PBS. The cells were investigated using an AxioImager Z1 fluorescence microscope (Carl Zeiss, Oberhohen, Germany), and images were taken with AxioVision 4.8 software (Carl Zeiss, Oberhohen, Germany). For cell counting, the multiple fields that covered the whole dish surface were imaged. The obtained images were analyzed with ImageJ 1.49 software (NCBI, Bethesda, MD, USA) using the ITCN plugin (Center for Bio-image Informatics, Santa Barbara, CA, USA). The levels of BDNF and GDNF proteins were quantified using a sandwich ELISA. Culture media were collected at indicated time points, centrifuged at 14,000× g for 5 min at 4 °C, and the supernatants were stored at −80 °C. The cells were washed three times with cold PBS before being lysed in 1 mL of 100 mM PIPES lysis buffer, pH 7.0, containing 500 mM NaCl, 2% BSA, 0.2% Triton X-100, 0.1% NaN3, and protease inhibitors (2 μg/mL aprotinin, 2 mM EDTA, 10 μM leupeptin, 1 μM pepstatin, and 200 μM PMSF) [38]. The sister wells were treated with trypsin and viable cells were counted using trypan blue exclusion and a hemocytometer. After three freeze/thaw cycles, the cell lysates were centrifuged at 14,000× g for 5 min at 4 °C, and the supernatants were stored at −80 °C. The BDNF and GDNF concentrations in the cell supernatants and lysates were determined in duplicate using Human/Mouse BDNF DuoSet ELISA and Human GDNF DuoSet ELISA Kits (R&D Systems, Minneapolis, MN, USA), according to the manufacturer’s instructions. Total RNA was extracted from the cells with a Trizol RNA Purification Kit (Invitro-gen, USA) following the manufacturer’s instructions, with a subsequent DNA-Free DNA Removal Kit (Invitrogen, Carlsbad, CA, USA) treatment. cDNA was synthesized on 0.5–2 μg of total RNA using M-MLV Reverse Transcriptase (Evrogen, Moscow, Russian Federation) with random primers. The primer sequences are shown in Table 9. The cDNA obtained was amplified using a CFX96 Touch™ Real-Time PCR Detection System (Bio-Rad, Berkeley, CA, USA) set to the following reaction conditions: denaturation at 95 °C (3 min), cycles n = 40 (95 °C, 15 s; 60 °C, 20 s; 72 °C, 45 s). The qPCRmix-HS SYBR reaction mixture (Evrogen, Moscow, Russian Federation) was used and 18S rRNA was accepted as the reference gene. For the quantification of cell growth and viability, adhesive cell cultures were incubated for 4 h in culture medium containing 0.5 mg/mL MTT (Sigma-Aldrich, Saint Louis, MO, USA). Next, the medium was removed and the blue MTT–formazan product was diluted with DMSO (Panreac, Barcelona, Spain). After 2 h of incubation at RT on a shaker setting of 150 rpm/min, the absorbance of the formazan solution was recorded at 600 nm using a spectrophotometer (Metertech, Taiwan). Data were analyzed using GraphPad Prism software. Normality and homogeneity of variance were assessed by Shapiro–Wilk and Brown–Forsythe tests, respectively. Statistical analyses of the data were performed using the Student’s t-test or ordinary one-way ANOVA followed by Dunnett’s post hoc test wherever applicable, as indicated in the figures and tables legend. Results are presented as the mean ± SEM.

PMC10003143

36883905

Miao Tang,Xiao Zhang,Weidong Fei,Yu Xin,Meng Zhang,Yao Yao,Yunchun Zhao,Caihong Zheng,Dongli Sun

Advance in placenta drug delivery: concern for placenta-originated disease therapy

08-03-2023

Placenta,nanoplatforms,drug delivery,retention effect,pregnancy

Abstract In the therapy of placenta-originated diseases during pregnancy, the main challenges are fetal exposure to drugs, which can pass through the placenta and cause safety concerns for fetal development. The design of placenta-resident drug delivery system is an advantageous method to minimize fetal exposure as well as reduce adverse maternal off-target effects. By utilizing the placenta as a biological barrier, the placenta-resident nanodrugs could be trapped in the local placenta to concentrate on the treatment of this abnormal originated tissue. Therefore, the success of such systems largely depends on the placental retention capacity. This paper expounds on the transport mechanism of nanodrugs in the placenta, analyzes the factors that affect the placental retention of nanodrugs, and summarizes the advantages and concerns of current nanoplatforms in the treatment of placenta-originated diseases. In general, this review aims to provide a theoretical basis for the construction of placenta-resident drug delivery systems, which will potentially enable safe and efficient clinical treatment for placenta-originated diseases in the future.

Advance in placenta drug delivery: concern for placenta-originated disease therapy In the therapy of placenta-originated diseases during pregnancy, the main challenges are fetal exposure to drugs, which can pass through the placenta and cause safety concerns for fetal development. The design of placenta-resident drug delivery system is an advantageous method to minimize fetal exposure as well as reduce adverse maternal off-target effects. By utilizing the placenta as a biological barrier, the placenta-resident nanodrugs could be trapped in the local placenta to concentrate on the treatment of this abnormal originated tissue. Therefore, the success of such systems largely depends on the placental retention capacity. This paper expounds on the transport mechanism of nanodrugs in the placenta, analyzes the factors that affect the placental retention of nanodrugs, and summarizes the advantages and concerns of current nanoplatforms in the treatment of placenta-originated diseases. In general, this review aims to provide a theoretical basis for the construction of placenta-resident drug delivery systems, which will potentially enable safe and efficient clinical treatment for placenta-originated diseases in the future. Over 130 million infants are born globally every year (Keelan et al., 2015), during whose pregnancies more than 20% (>26 million per year) suffered from one or more pregnancy-related complications. The most common disorders are preeclampsia, fetal growth restriction, gestational diabetes, and preterm birth. Among the numerous pregnancy complications, placenta-originated pregnancy complications, such as preeclampsia and fetal growth restriction, arising from abnormal placental development and function, are the most difficult diseases to treat in obstetrics for the lack of safe and effective drugs (Tang et al., 2022). Timely delivery of the baby is the most effective strategy to treat preeclampsia or fetal growth restriction. However, about 81% of the newborns survived from early-onset fetal growth restriction (before 32 weeks), wherein 12% of the surviving babies are diagnosed with cognitive impairment and/or cerebral palsy (Pels et al., 2020). Every year, about 70,000 pregnant women and 500,000 fetuses or newborns die of preeclampsia worldwide (Rana et al., 2019). Moreover, placenta-originated disorders also increase the risks of cardiovascular and metabolic diseases of mothers and babies in the long term, potentially increasing serious health concerns. Deep knowledge of the placental function in transferring drugs and nutrients from the mother to the fetus will help researchers and clinicians make measures to improve maternal and fetal health (Al-Enazy et al., 2017). The placenta develops rapidly as a well-organized and functioning organ in early pregnancy to support fetal growth (Figueroa-Espada et al., 2020). In early pregnancy prior to the gestation of 10–12 weeks, the placenta is not completely developed to transfer nutrients proficiently (Figueroa-Espada et al., 2020; Koren & Ornoy, 2018). From the 10–12 weeks of gestation, the developing placenta has grown to supply nutrients, exchange waste products, and protect the fetus from exposure to some xenobiotics and toxic substances in the maternal circulation (Faber et al., 1992; Gude et al., 2004). From the aspect of maternal-fetal drug delivery, the placenta can be regarded as a crossing passage, flexibly and intendedly delivering therapeutics to treat pregnancy-related complications (Grafmueller et al., 2013; Joshi, 2017). Placental drug transfer depends on the physiological and pathological characteristics of the placenta and the physicochemical properties of drugs (Figueroa-Espada et al., 2020; Tuzelkox et al., 1995). The placenta has a high hemodynamic characteristic, which provides a guarantee for the delivery of nutrients from the mother to the fetus, and the various transporters in the placenta also provide opportunities for forward and reverse transport (Tetro et al., 2018). The physical and chemical properties of drugs themselves, such as drug molecular size, hydrophilic or lipophilic characteristics, also play an important role in their placental transportation. The placental transfer ability is affected by the molecular size of the therapeutic agent, which might be relatively impermeable when its molecular weight is greater than 1000 Da, and permeable when its molecular weight is less than 600 Da (Tuzelkox et al., 1995). Moreover, according to the like-dissolves-like principle, hydrophobic drugs can pass through the placental barrier more easily especially when they have a lower rate of protein binds and less ionization (Audus, 1999; Unadkat et al., 2004). In contrast, hydrophilic molecules are less permeable and cannot easily penetrate blood vessel walls and placenta. However, the most common forms of the drugs are chemical molecules with small sizes, which possess the possible procedures of easily crossing through the placenta (Syme et al., 2004), possibly causing severe fetal toxicity, such as abortion (Suarez et al., 2001), birth defects (Kulaga et al., 2011), and carcinogenicity (Venn et al., 2004) for the drug use during the pregnancy. For instance, a Dutch clinical trial of sildenafil for fetal growth restriction showed that sildenafil was associated with fetal pulmonary hypertension and fetal death (Hawkes, 2018). The most challenging problem of treating placenta-originated diseases is to take both efficacy and safety into therapeutic design considerations (Joshi, 2017). Compared to small molecule drugs, the design of nanoplatforms could target the lesions and lower unnecessary therapeutics delivered as the off-target effects. Recently, many researchers have reported that advanced nanotechnology would assist in the treatment of pregnancy complications with safety and efficiency (Table 1) (Nelson et al., 2021; Pritchard et al., 2021). The placental permeability of nanoparticles could be designed via the adjustment of their physicochemical properties. Meanwhile, well-designed nanoplatforms may vary in distribution according to the therapeutic condition to be confined in the maternal side, easily pass through the placenta and enter the fetal circulation, or retain in the placenta (Pritchard et al., 2021). For example, one study showed that targeting nanoplatforms loaded with doxorubicin could deliver drugs to placental tissue. It can improve the therapeutic effect of ectopic pregnancy and reduce systemic toxicity (Kaitu’u-Lino et al., 2013). Alternatively, for placenta-originated diseases such as preeclampsia and fetal growth restriction, they could be designed to retain in the placental surface, having functions on the syncytiotrophoblasts (SCT) where the pathogenic factors produce and cause the development of the disease (Figure 1). In general, nanotechnology is able to keep the efficacy and reduce the side effect during the therapy of placenta-originated disease. Nanotechnology has been clinically used to treat tumors and can overcome off-target effects and achieve targeted drug delivery. However, due to the high research cost, long research cycle, and safety issues, the application of nanotechnology in placenta-originated diseases is delayed (Tetro et al., 2018). Now, advances in the understanding of placental features have made it possible to realize the application of nanotechnology in placenta-related disease therapy. To provide a theoretical basis for the construction of placenta-resident drug delivery systems for placenta-originated disease therapy, this review summarizes the mechanism of nanoplatform transport in the placenta, and analyzes the physicochemical properties (including particle size, charge, and surface modification) of nanocarriers and pregnancy stages that affecting the placental retention of nanoplatforms. More importantly, we analyzed the advantages and attention issues of nanoplatforms in the treatment of placenta-originated diseases. In general, this review will provide guidelines for the construction of placenta-resident drug delivery systems and bring new hope for the therapy of placenta-originated diseases. The human placenta is a discoid monochorionic double-perfused organ (Figure 2C). The placenta develops primarily from the trophectoderm surrounding the blastocyst. With the progress of embryo implantation, trophectoderm cells gradually differentiate and develop into a variety of trophoblast cell subtypes with specialized functions. These cell types include villous cytotrophoblasts (VCT), syncytiotrophoblasts (SCT), extravillous trophoblasts (EVT), and trophoblast giant cells. In addition to trophoblasts, other cells that make up the placental environment include Hofbauer cells, fibroblasts, fetal endothelial cells, and decidual cells (Arumugasaamy et al., 2020). During pregnancies, maternal vasculature undergoes structural changes to allow efficient blood flow to the fetus (Figure 2A). Uterine arteries develop various branches; basal arteries end in the decidua or myometrium; and spiral arteries extend to the intervillous space (Brosens et al., 2019). When VCT arrive in the endometrium, their growth and proliferation become faster. External VCT cells fuze to develop multinucleated SCT that can produce enzymes that promote extracellular matrix (ECM) degradation and secrete factors that induce the apoptosis of endometrial epithelial cells for blastocyst implantation (Gupta et al., 2016). VCT with proliferative ability can grow toward the maternal decidua to form the cytotrophoblast cell column (CCC), and be anchored in the maternal decidua. VCT then differentiate into invasive extravillous trophoblasts (EVT) at the ends of CCC. Invasive EVT develop into interstitial extravillous trophoblasts (iEVT) or into intravascular extravillous trophoblasts (enEVT) (Ji et al., 2013; Roberts et al., 2017; Velicky et al., 2016). Eventually, iEVT enter the inner third of the myometrium as multinucleated giant cells, along with enEVT, altering arteries to ensure efficient blood flow and adequate nutrient supply (Burton et al., 2019). Special physiological conditions during pregnancy help nanodrugs to be trapped in the placenta (Valero et al., 2018). For one thing, the blood flow of the uterine artery increases sharply during pregnancy, and the resistance of flow in the blood vessel is reduced due to the distal segment expansion of the spiral artery. For another, due to the hemodynamic adjustment, maternal blood circulation volume and cardiac output increase (Burton et al., 2009). When nanodrugs were administered intravenously, high placental blood flow increased the transportation of the nanodrugs into the placenta. The nanodrugs reach the placental intervillous space through the spiral artery. The blood flow velocity in the intervillous space decreases rapidly to 10 times lower than that in the uterine artery, prolonging the contact time between the nanodrugs and the chorionic villi, as well as the SCT (Burton et al., 2009). The outer side of the apical membrane of the SCT is a brush-like structure with a large surface area, increasing the possibilities of nanodrugs internalization and local drug release (Arumugasaamy et al., 2020). Furthermore, transport proteins in the apical membrane, such as ATP-binding cassette (ABC) and solute carrier protein (SLC) transport proteins, might be utilized as efficient tools for the delivery or efflux of nanodrugs (Figure 2B) (Arumugasaamy et al., 2020). Overall, the nanodrugs may take advantages of the placental structure, the placental hemodynamics as well as the transporters for placenta-originated disease therapy. The key to treating placental diseases is to concentrate the drug into the placenta as much as possible to minimize the side effects to the fetus and mother. It is important to understand the delivery mechanism of nanoplatforms in the placenta before constructing a placenta-resident drug delivery system. In the placenta, nanoparticles can be transported by common transcellular transport mechanisms such as passive diffusion, active transport, and pinocytosis. The exact transport pathway may depend on the physicochemical properties of nanoplatforms (Al-Enazy et al., 2017; Shojaei et al., 2021). The following section will introduce the mechanism of nanoplatforms entering and exiting the placenta. More importantly, some strategies to enhance the accumulation of nanoplatforms in the placenta were summarized to provide new ideas for researchers to treat placenta-originated diseases. Paracellular pathway is a process by which substances are absorbed through the intercellular space. It is a passive mode of transport that consumes no energy. Studies reported that the placenta has various lipid pores (Kertschanska et al., 1997; Kurz & Fasching, 1968). Subsequently, Kertschanska et al. found that such placental pores extended from the basal trophoblast surface to the SCT. Alternatively, by using electron microscopic analysis, Kertschanska et al. reported that the lipid pore has approximately a diameter of 15 to 25 nm at normal intravascular pressure (Kertschanska et al., 1997). In addition, several studies have reported that the placental pores (channels) are continuous and curved from the fetus to the mother (Bosco et al., 2007; Kertschanska et al., 2000; Kurz & Fasching, 1968). Small hydrophilic compounds such as opioid peptides (Ampasavate et al., 2002) and nanoparticles smaller than 25 nm in diameter will be allowed to pass through the placenta by passive diffusion due to the presence of placental channels. The entry of the nanoplatforms through the pores into the placenta is known as paracellular absorption (Figure 3A). An in vivo study has shown that the injection of quantum dots smaller than 25 nm into pregnant mice was more likely to pass through the placenta than those larger ones, and the transferred number of quantum dots increased with the dose (Chu et al., 2010). In addition, small dendritic nanoparticles (5.6 nm) can cross the placenta via placental channels (Menjoge et al., 2011). These studies indicate that nanoplatforms with particle sizes less than 25 nm can enter the placenta through the paracellular pathway, but they can also easily cross the placenta through continuous placental channels. Therefore, the nanoplatforms with small particle sizes may not have a good placental resident effect, and may even affect fetal development. Notably, the development of stimuli-responsive aggregated nanoplatforms provides a new way to overcome this obstacle (Mura et al., 2013; Yu et al., 2020; Zhang et al., 2020). The main idea of this strategy is that small particle-size nanoparticles can specifically aggregate into large particle sizes in the placental environment, which can not only improve placenta-specific aggregation and long-term retention but also enhance the treatment effect of placental diseases. This strategy has been applied in the study of tumor-targeted drug delivery. A study showed that acid-responsive aggregated gold nanoparticles can specifically accumulate and retain in the acidic tumor microenvironment (Luan et al., 2022). The placenta and tumor are similar to some extent (King et al., 2016). Thus, such a strategy could be applied in the design of placenta drug delivery systems. Endocytosis is the process of transporting extracellular substances into the cell through the deformation movement of the plasma membrane, which is divided into phagocytosis and pinocytosis. Pinocytosis is the main pathway of nanoparticle uptake and can be classified into two categories: clathrin-mediated endocytosis and clathrin-independent endocytosis (Conner & Schmid, 2003; Zhang et al., 2019). Clathrin-independent endocytosis pathway includes macro endocytosis and caveolae-mediated endocytosis. There are many clathrin-coated regions in the trophoblast of the placental syncytium between microvilli (Zhang et al., 2019). Thus, nanoparticles can be absorbed by the trophoblast through pinocytosis (Figure 3B). Studies have shown that polymer nanoparticles with positive charges, as well as gold nanoparticles, can be internalized by SCT through clathrin-mediated endocytosis and caveolae-mediated endocytosis (Kaul et al., 2013; Myllynen et al., 2008; Rattanapinyopituk et al., 2014). In a 2018 study, pullulan acetate nanoparticles were internalized into BeWo B30 placental barrier cells via caveolae-mediated endocytosis (Tang et al., 2018). Rattanapinyopituk et al. in 2014 investigated clathrin- and caveolin-mediated transport of gold nanoparticles in the placenta by intravenous injection (Rattanapinyopituk et al., 2014). The results showed that gold nanoparticles increased the expression of caveolin in fetal endothelial cells, as well as the clathrin in SCT and fetal endothelial cells. In the study, gold nanoparticles could pass through the placenta and enter fetal circulation through clathrin- and caveolin-mediated endocytosis (Rattanapinyopituk et al., 2014). These results suggest that both clathrin- and caveolin-mediated cellular uptakes may be explored for placental targeting drug delivery. Based on this transport mechanism, researchers can modify clathrin or caveolin easily recognized molecules on the surface of nanoplatforms to achieve the purpose of placental delivery of drugs. Transporter-mediated uptake is divided into facilitated diffusion and active transport. Facilitated diffusion allows certain compounds to cross the placenta without energy. Active transport is an energy-dependent process that usually proceeds against a concentration gradient. The major superfamily of transporters found in the placenta are the SLC and ABC transporters (Al-Enazy et al., 2017; Staud et al., 2012). For instance, organic anion transporters are a family of transporters in the placenta, mediating transport in the maternal-fetal interface for metabolites, waste products, and hormones (Lofthouse et al., 2018). Similarly, transporters such as amino acid transporters, glucose transporters, and transferrin can deliver specific substrates across the placenta (Illsley, 2000; Parkkila et al., 1997). For example, iron is transported across the placenta through transferrin receptor-mediated endocytosis (Parkkila et al., 1997). Facilitated diffusion transport increases the transport rate of endogenous compounds, such as hormones and nucleosides, when passive diffusion cannot meet the functional and metabolic needs of the fetus. Transport of drugs via facilitated diffusion pathways appears to be rare (Syme et al., 2004), and there have not been any reports of nanoparticle-facilitated diffusion. Meanwhile, active transport mechanisms for placenta-specific substrate delivery have not been well studied for their utilization in drug delivery. At present, the active transport of nanomaterials through this mechanism is mainly focused on the field of cancer therapy. In one study, stealth liposomal systems modified with aspartate-polyoxyethylene stearate conjugate (APS) were designed to target ATB0,+ overexpressed human lung cells via transporter-mediated delivery (Luo et al., 2017). However, with the development of nanoscience, known placental transport mechanisms can be exploited for receptor-mediated drug delivery with high specificity into the placenta (Figure 3C). Our group has previously explored the transporters that highly expressed in the human placenta (Zeng et al., 2019), and confirmed that nucleoside transporters could mediate the entry of their substrate-modified liposomes into gestational trophoblasts (Fei et al., 2021). In conclusion, researchers can increase placental drug delivery by constructing nanoplatforms modified with high-affinity substrates for transporters in the placenta. Exocytosis is the process that transport vesicles release their contents into the extracellular matrix through fusion with the plasma membrane. After being ingested by cells, nanoparticles will undergo a series of pathways in the cell and eventually be transported out of the cell (Dahiya & Ganguli, 2019; Sakhtianchi et al., 2013). The transport of nanoparticles across placental tissue is mainly through exocytosis and can occur in two main ways (Figure 3D): (i) after endocytosis, nanoparticles are internalized into early endosomes. Early endosomes become mature and form into multivesicular bodies, then fuse with the plasma membrane and release nanoparticles from the trophoblast. Therefore, nanoparticles reach fetal circulation; (ii) early endosomes transport nanoparticles to lysosomes, and then exocytosis of lysosomes can also release the contents into the villus matrix and subsequently into fetal capillaries. From the mechanism of nanoplatform transferring out of the placenta, it can be seen that the construction of nanoplatforms that can achieve lysosomal escape can make nanoplatforms stay in the placental trophoblast cells for a longer time and reduce the amount of placental transmission. This section describes the mechanism of nanoplatform transport in the placenta. More importantly, based on these transport mechanisms, this review has summarized some strategies for the construction of drug delivery systems that are expected to improve the placental residence. These strategies are summarized in three aspects: the first aspect is to increase the affinity of the nanoplatforms with placental trophoblast cells, that is, to modify the substrate of cell membrane transporters on the surface of nanoplatforms; the second aspect is to achieve nanoparticle aggregation through the placental microenvironment and increase placental retention; finally, lysosomal escape of nanoplatforms could reduce the nanodrug leaving the placenta. It should be emphasized that these strategies are still in the theoretical stage, and follow-up studies are needed to confirm their feasibility. The permeability of the placenta to nanoparticles with different physicochemical properties varies widely. The nanoparticles are devised according to the therapeutic purpose to control their distribution on the maternal, placenta, and fetal sides. Nanoparticles can be designed to easily penetrate the placenta and participate in fetal circulation, or they can be designed to prevent drugs through the placenta and remain in the maternal compartment to maximize maternal drug concentrations while minimizing injurious effects on the fetus, or they can be designed to more precisely target the placenta and accumulate in its superficial layer, SCT, etc. for the treatment of placenta-originated diseases. The barrier imposed by the placenta to nanodrug transport is strongly affected by the physicochemical properties of the nanoparticles, including particle size, surface charge, nanomaterial type, and surface modification. Additionally, one must take into account how placental physiology and transport vary at different stages of gestation while designing nanoplatforms. After comprehensive research, it is easier to develop a satisfactory placenta-resident drug delivery system, enhancing the targeting effect and improving the bioavailability of drugs. The size is a major factor influencing the retention of nanoparticles in the placenta, and typically, the placental barrier is less restrictive for smaller-sized lipophilic nanoparticles. Therefore, nanoplatforms of larger size and hydrophilicity may be more suitable for the treatment of maternal or placenta-originated diseases to avoid drug transfer from the placenta to the fetus. Our research group prepared 80 nm, 200 nm, and 500 nm Cy 5-loaded liposomes and then studied their aggregation in the placenta (Tang et al., 2022). The results of fluorescence intensity and liquid chromatography-mass spectrometry analysis of placenta and fetal slices showed that the particle size of liposomes was positively correlated with the accumulation of liposomes in the placenta (Figure 4A–C). After 8 hours of administration, the Cy 5 concentration ratio of placenta to fetus was analyzed, and the ratio of 500 nm lipids was about 6 times higher than that of the 200 and 80 nm-sized liposomes, indicating that 500 nm liposomes were more suitable for placental drug delivery (Figure 4C) (Tang et al., 2022). Ali et al. found that the permeability of dexamethasone-loaded PLGA nanoparticles was halved when the size of PLGA nanoparticles was increased from 143 to 196 nm in an in vitro model of human placental cells (Ali et al., 2013). In another study, Refuerzo et al. tested whether silicone nanovectors (SNVs) at 519 nm, 834 nm, and 1000 nm would cross the placenta in pregnant rats (Refuerzo et al., 2011). They demonstrated that 1000 nm SNVs did not cross the placenta and remained in the maternal circulation, while smaller SNPs (close to 500 nm) could cross the placenta and participate in the fetal circulation. Huang et al. investigated whether fluorescently labeled carboxylate-modified polystyrene nanoparticles at 20, 40, 100, 200, and 500 nm could cross the placenta and affect trophectoderm function, ultimately finding that only 40 nm nanoparticles had prominent placenta ingestion and trophectoderm internalization (Huang et al., 2015). In general, the particle size of the nanoparticle will affect its placental retention in the placenta. When constructing the nanocarrier, selecting an appropriate particle size is necessary for placenta drug delivery, thus improving the safety and reliability of nanoplatforms for the treatment of pregnancy-related diseases. Surface charge is another property that determines whether nanoparticles will transfer from the placenta to the fetus. Cationic nanoparticles are more likely to cross the placenta than anionic nanoparticles because of the easier uptake of cationic nanoparticles by the negatively charged membrane of trophoblast cells (Zhang et al., 2019). In an in vitro blood-placental barrier model, Müller et al. verified that cation-coated superparamagnetic iron oxide nanoparticles (SPIONs) had the strongest ability to interact with BeWo cells and were predominantly retained in the BeWo/pericytic layer. In comparison, anionic and neutral surface-charged SPIONs could cross the cell layer more readily (Müller et al., 2018). Ho et al. demonstrated the effect of surface charge by simultaneously injecting anionic or cationic multimodal polymer nanoparticles in the first and third trimesters of pregnant rats, respectively. In the third trimester, cationic nanoparticles aggregated more easily than anionic nanoparticles in the chorionic plate of the rat placenta, while in the first trimester, both nanoparticles readily penetrated the placenta. The above results emphasized that electrical charge and different gestational stages affected the placental uptake of nanoparticles (Ho et al., 2017). It should be noted that positively charged nanoparticles are removed from the bloodstream faster than negatively charged nanoparticles due to increased tissue and cellular uptake, and they can induce hemolysis and platelet aggregation (Albanese et al., 2012; Nel et al., 2009). Di Bona et al. reported that cationic nanoparticles accumulated preferentially in the mouse placenta at high doses, but also increased the risk of maternal and fetal toxicity (Di Bona et al., 2014). Therefore, investigators must carefully control the surface charge of nanoplatforms to balance tissue toxicity and placental transport. Different materials of nanoparticles have different permeability extents in the placenta. For example, gold nanoparticles above 80 nm, silica nanoparticles above 300 nm, and polystyrene nanoparticles above 500 nm all remained in the placenta without entering the fetus (Aengenheister et al., 2021; Bongaerts et al., 2020). Even if the nanoparticles are of similar size, different materials produce different placental resident effects. In an ex vivo perfusion model, 4–8 nm TiO2 NPs were unable to pass through the placenta (Aengenheister et al., 2019), whereas 3–6 nm Au NPs were able to cross the human placental barrier and enter the fetal circulation (Aengenheister et al., 2018). Under the same particle size, organic nanomaterials can enter or cross the placenta more easily than inorganic nanoparticles, because organic nanoparticles always have deformability (elasticity) and they are more likely to enter the placenta through paracellular pathways. For instance, many studies reported that both 50–500 nm liposomes and 20–500 nm polystyrene nanoparticles could enter the placenta and accumulate in the fetus (Irvin-Choy et al., 2020). In comparison, 80 nm gold nanoparticles and silica nanoparticles over 300 nm aggregated very little in the placenta, and they were not detectable in the fetus. From this point of view, organic nanoparticles have broader particle size selectivity in placental drug delivery. Furthermore, vesicle-like nanocarriers such as liposomes and exosomes can also enter the placental barrier through membrane fusion. This type of nanocarrier is often used for drug delivery in placenta-originated diseases due to its superior placental aggregation ability (Tang et al., 2022). Notably, few inorganic nanocarriers have been used for drug delivery in placenta-originated diseases (Table 1). This is because inorganic carriers, such as silicon dioxide, titanium dioxide, etc., degrade slowly in the body and easily cause embryotoxicity. This is an even more important issue (safety of nanocarriers) than drug delivery, which would be discussed in the following pages. The surface functionalization of nanoparticles has many advantages, such as reducing toxicity and immune response, increasing the specificity and efficacy of the nanodrugs. For instance, ligands modified on the surface of the nanoparticles could increase the specificity and efficacy of the nanodrugs. Meanwhile, the surface modification could also help to change the efflux and penetration of nanoplatforms. The molecules used to modify the nanoparticles include small proteins, peptides, antibodies, aptamers, and oligosaccharides (Sanita et al., 2020). To better target the placenta, nanoplatforms can be surface modified by targeting ligands, such as peptides, antibodies, or aptamers that bind placenta-specific receptors (Whigham et al., 2019). The mechanism of placental targeted nanodrugs is that the ligands on the surface of the nanoplatforms bind specifically to receptors on the surface of trophoblast cells or other placental cells. This bond is supported by intermolecular forces such as van der Waals forces, hydrogen bonds, etc. Such interacting forces allow the nanoparticles to stay on the surface or inside the target cells. Therefore, the nanoplatforms modified by targeting groups can show a good placental residence effect. Tumor-homing peptides, such as CGKRK and iRGD, whose receptors are expressed at high levels in the human placenta, have developed into feasible targets for placenta-specific drug delivery (Beards et al., 2017; King et al., 2016). When A. King et al. injected T7 phage displaying surface peptides CGKRK or iRGD intravenously into pregnant mice, the enrichment of CGKRK and iRGD was approximately 7- to 8-fold higher in the placenta compared with other organs. They observed that CGKRK- and iRGD-modified nanoparticles bound to murine decidual spiral arteries and the vasculature of the placental labyrinth, but not to the junctional zone adjacent to the labyrinth, at different gestation periods. Meanwhile, in the human placental explant model, CGKRK- and iRGD-modified nanoparticles could accumulate rapidly in the outer syncytium rather than permeating into the underlying cytotrophoblast. Subsequently, they used iRGD-modified targeted liposomes to selectively deliver insulin-like growth factor 2 to the mouse placenta, improving fetal body weight distribution in growth-restricted model mice. Tumor-homing peptides provide new ideas for developing placenta-specific therapies (King et al., 2016). The two placenta-targeting peptides were inspired by the similarity between tumors and the placenta. In the future, we can use the similarity between tumors and the placenta to develop more placenta-targeting nanodrugs (Table 2). Chondroitin sulfate A (CSA) is present in the placental SCT, and placental CSA-binding peptide (plCSA-BP) can specifically bind to CSA in the trophoblast. Zhang et al. showed that plCSA-BP conjugated nanoparticles efficiently bound to mouse placental maze trophoblast cells in vivo and ex vivo (Figure 5A,B). plCSA-BP conjugated nanoparticles were used as delivery vehicles for methotrexate (MTX). In the targeted therapy group, the MTX concentration in the placenta was 6-fold higher than that in the non-targeted therapy group at 24 hours, while MTX was undetected in the fetus. After 48 hours of dosing, MTX was detected only in the placenta of the targeted therapy group (Figure 5C). It shows that plCSA-BP conjugated nanoparticles can increase the accumulation of drugs in the placenta and prolong the action time of drugs (Zhang et al., 2018b). CNKGLRNK is a novel peptide sequence that selectively binds to the uteroplacental vascular system. CNKGLRNK peptide-modified liposomes could not enter fetal circulation and directly treated endothelial cells in the uterine spiral artery and placental labyrinth (Cureton et al., 2017). Another study found that three fluorescein-labeled elastin-like peptides (ELPs) ranging from 25 to 86 kDa (4.1 to 6.8 nm) were unable to cross the placental barrier when administered intravenously. The most prominent accumulation location of nanoparticles is the placental chorionic plate, and the accumulating concentration of nanoparticles increased with sizes (Kuna et al., 2018). ELPs are genetically encoded, which means that researchers have absolute control over the ELP sequence and molecular weight, and targeting peptides and therapeutic proteins can be easily added by modifying the DNA-encoding sequence. ELPs are biologically inert macromolecules, and ELP fusions can stabilize the protein, peptide, or small molecule cargoes in the body’s circulation. Tunability, long circulation, biodegradability, and non-immunogenicity make them ideal nanocarriers for drug delivery during pregnancy, delivering drugs to the placenta while preventing fetal drug exposure. Recently, researchers have identified exosomes as attractive candidate therapeutic agents and delivery nanoplatforms (Lu & Huang, 2020). Exosomes are lipid bilayer nanovesicles with different sizes (30 to 150 nm). The bioactive entities packaged in exosomes can be transferred between cells, resulting in changes in recipient cell phenotype (Vader et al., 2016). Compared with artificial nanoparticles, exosomes have multiple advantages as drug delivery vehicles: lower immunogenicity and toxicity, direct fusion with target cell membranes, stronger cellular internalization, fewer off-target effects, etc. (Zhang et al., 2019). Placental cells can communicate with maternal tissues through exosomes to regulate their biological functions, and exosomes are present in higher numbers in pregnancy complications such as preeclampsia and gestational diabetes (Salomon & Rice, 2017). The surface of exosomes derived from different tissues contains protein fragments that bind to the ligands of the tissue cells. Such ligand-receptor interaction mechanism can realize the specific aggregation of exosomes (Liang et al., 2021). Placenta-originated exosomes can target the trophoblast to deliver the payload directly to the placenta. Meanwhile, the exosomes can be modified with functional ligands to improve the stability of blood circulation, better localize to the target site, and increase the efficiency of intracellular delivery. In general, placenta-originated exosomes may be a targeted vehicle for the treatment of placenta-originated diseases. Surface-functionalized nanoparticles can promote placenta-specific drug delivery and reduce nanoparticle transfer to the fetus, thereby improving drug safety and efficacy. Polyethylene glycol (PEG)-coated liposomes were nearly impermeable to the placental barrier (Shojaei et al., 2021; Soininen et al., 2015). In an ex vivo placental perfusion model, Myllynen et al. demonstrated that PEG-coated 10–30 nm gold nanoparticles (Au NPs) were not able to penetrate the human placenta within 6 h of perfusion (Myllynen et al., 2008). PEG acted as a hydrophilic shell, repelling the adsorption of opsonins and other serum proteins to the nanoplatforms, and preventing macrophage clearance with ‘stealth’ properties (Suk et al., 2016). In another study, three surface modifications, namely ferritin with good biocompatibility, PEG with stealth effect, and stabilizing anionic material citrate, were used to decorate 13 nm Au NPs to evaluate the influence of surface function on the biodistribution of Au NPs in the maternal-fetal interface (Yang et al., 2012). Ferritin-modified or PEGylated Au NPs had similar levels of placental accumulation, in contrast to the significantly reduced fetal tissue uptake of citrate-terminated Au NPs. This suggests that the addition of stealth agents (e.g. PEG) to nanoparticles inhibits their ability to cross the placenta. However, it is worth noting that excess PEG also inhibits uptake by parent tissues and cells, thus requiring a balance between PEG surface modification, placental transport, and maternal cellular uptake. PEG is the most commonly used surface-modifying molecule for the pharmaceutical formulation, thus, existing studies have focused on the effect of PEG surface modification on the placental aggregation of nanodrugs. With the deepening of research, the effects of other commonly used surface-modifying compounds (Guerrini et al., 2018), such as zwitterionic ligands, lipid bilayer, and proteins, on the placental generation of nanodrugs should also be investigated. Overall, this aspect is still in its infancy, and more efforts need to be devoted to the development of nanoplatforms with placental aggregation capabilities. We have just mentioned some important key factors affecting the placental retention of nanoplatforms, including particle size, charge, material type, and surface modification. However, other factors such as the morphology of the nanoplatforms and physical conditions such as temperature and pH of the particles are also important, but information on their mechanisms affecting placental accumulation and penetration is lacking. More research is needed to gain a deeper understanding of these factors affecting nanoparticle placental retention. In addition, chemical structure modification of drugs and regulating the expression of transporters in placental cells are effective strategies to reduce placental drug efflux. In addition to the physicochemical properties of nanoplatforms, the gestational age of pregnancy is another key factor affecting the placental retention of nanoplatforms. The structure, cellular composition, function, and blood flow of the placenta vary with gestational age, thereby altering placental uptake and transport capacity. During early pregnancy, when the placenta is not yet filled with maternal blood, most drugs in the maternal blood enter the embryo by passive diffusion. By the end of the first trimester, the placental barrier can be as thick as 20 microns, and the placental retention ability is strong. The placenta thins to 2 to 5 microns at term, which means the fetus is more likely to be exposed to maternal drugs at this time. In addition, placental blood flow and surface area increase significantly with gestation time, which also enhances the likelihood of drug transfer to the fetus (Pritchard et al., 2021). Yang et al. evaluated the influence of gestational age and nanoparticle composition on placental transfer by maternal administration of nanoparticles in mice (Yang et al., 2012). Experiments showed that gold nanoparticles injected intravenously in early gestation (< E11.5) in mice had higher fetal accumulation compared to late gestation (E > 11.5). Pietroiusti et al. intravenously injected SiO2 nanoparticles of three different sizes (25, 60, and 115 nm) and two different surface functionalizations (NH2 and COOH) at three different gestational time points in pregnant mice (Pietroiusti et al., 2018). The results showed that only 60 nm negatively charged nanoparticles could produce fetal accumulation at all three stages, while larger nanoparticles could only cross the placenta in the third trimester. At mid-pregnancy, 25 nm nanoparticles were the only ones of the three nanoparticles that could pass through the placenta in both positively and negatively charged forms. The ratio of the concentration of negatively charged SiO2 nanoparticles in the placenta to that in the fetus was highest in the third trimester of pregnancy. That is, the accumulation of 115 nm SiO2 nanoparticles in the placenta was twice that of the fetus, and 60 nm SiO2 nanoparticles was three times higher. What’s more, 25 nm negatively charged SiO2 nanoparticles were only detected in the placenta (Pietroiusti et al., 2018). The in vivo transport process of drug delivery systems is complex and will affect the placental drug delivery efficiency. For instance, the reticuloendothelial system and plasma albumin complexation will accelerate the clearance of nanodrugs and reduce drug accumulation in the placenta. The drug released by nanodrugs at the placenta may also return to the maternal side or enter the fetal side through diffusion. That meant the placental resident effect of nanodrugs is also related to the loaded drugs. From the discussion in this section, constructing placenta-resident nanoplatforms is challenging. Given that the development of each field is gradual, we call for more attention and research to focus on the field of placental drug delivery to improve the maternal-fetal safety of drugs. Different types of nanocarriers have been successfully adopted in various nanodrugs, such as liposomes, albumin, and polymer nanoparticles. Because nanocarriers have unique properties, such as various shapes, sizes, and physicochemical properties that give them a high surface area to volume ratio, and the ability to carry therapeutically active compounds that eventually aggregate at the target site (Edis et al., 2021). When nanoparticles focus on placental drug delivery, their unique targeting properties combined with various strategies could distinguish them from traditional treatment during pregnancy. First and foremost, nanoparticles have flexible cargo encapsulation, widening their delivery of drug categories such as small molecule compounds, peptides, proteins, RNA, and DNA. Their large surface area and volume ratio also enable high loading capacity for drugs via different intermolecular forces. Therefore, nanoparticles can be designed by various construction options, suiting different pharmaceutical applications and cargo properties. Drug cargo would avoid degradation or metabolism with the help of protective encapsulation, keeping therapeutically active at the targeted site. Second, nanoparticles can penetrate the placental barrier flexibly via alterations of size, charge, and shape, enhancing on-site drug concentrations for disease therapy. Third, the versatile surface structure or surface charge of nanoparticles can control immunogenicity, inflammatory potential, and clearance. One example is the ‘stealth’ technology, where PEG is attached to the surface of nanoparticles. This surface modification can reduce the uptake by the mononuclear phagocyte system (MPS) to prolong the presence of PEGylated nanocarriers in the blood (Immordino et al., 2006). Finally, nanoparticles could be designed to improve placental drug delivery by different therapeutic mechanisms, such as active targeting through surface modifications and passive targeting by the placental microenvironment. The significant physiological changes that occur during pregnancy have created an urgent need to develop drug delivery technologies specifically for use during pregnancy, such as pregnancy-induced increases in circulating blood volume and cardiac output by nearly 50%. Pharmacokinetics, including blood clearance and biodistribution, were different compared to non-pregnant women (Gude et al., 2004; Tasnif et al., 2016). Most treatments used clinically are not tissue-specific, then the drug accumulates in maternal and fetal tissues, leading to off-target toxicity (Refuerzo et al., 2017). Therapeutic drugs are transported to the target site or organ in a controllable manner by drug delivery systems, maximizing the therapeutic effect while minimizing the off-target effects of the administered therapeutic agents. Thus, nanoparticles can be used to precisely control drug delivery during pregnancy and reduce the risk of fetal and maternal drug exposure. The placentas have many characteristics in common with solid tumors, such as rapid proliferation, avoidance of immune destruction, induction of angiogenesis, etc. (Lala et al., 2021). Zhang et. al compared placenta-specific methotrexate delivery with general methotrexate delivery by conjugating a placental targeted peptide or a scrambled peptide respectively to the nanoparticles. After intravenous administration of these nanoparticles to pregnant mice, they measured the cross-sectional areas of blood sinusoids in the placental labyrinthine region. It was reported that both targeted and non-targeted delivery of nanoparticles significantly decreased the mean blood sinusoid areas in the placenta, indicating that nanoparticles might take advantage of the enhanced permeability and retention (EPR) effect to improve the delivery of drugs to the placenta (Zhang et al., 2018b). Therefore, it might be reasonable to conclude that the abundant new blood vessels in the placental tissue make the placenta have a certain resident effect on the nanoparticles, making liposomes accumulate in the placental tissue similar to the tumor EPR effect. The drug delivery technology then enhances the placental retention of nanoparticles and reduces maternal-fetal drug exposure by manipulating the physicochemical characteristics of nanoparticles, including their size, surface charge, composition of the material, and surface modification, taking into account different stages of pregnancy (Figueroa-Espada et al., 2020). For example, hydrophobic and positive-charged particles can increase placental tissue uptake and reduce drug placental penetration compared to hydrophilic and uncharged particles (Keelan et al., 2015). Drugs can be attached to macromolecular carriers such as cyclodextrins (Andaluz et al., 2013), or placental penetration of drugs can be reduced by using colloidal drug delivery systems such as liposomes or dendrimers (Menjoge et al., 2011). Additionally, liposomes have been successfully used to encapsulate small molecular drugs such as valproic acid (Barzago et al., 1996), inulin (Tuzelkox et al., 1995), riboflavin (Tuzelkox et al., 1995), methotrexate (Tuzelkox et al., 1995), penicillin (Tuzelkox et al., 1995), and indomethacin (Refuerzo et al., 2015) to increase the accumulation of these drugs in the placenta. Nanocarriers with surface-modified conjugation, such as targeting peptides, accumulate in target organs, thereby maximizing drug delivery to the desired location (Whigham et al., 2019), reducing the risk of drugs interference with normal placental and/or fetal development, and ultimately increasing drug safety. Zhang et al. mixed siRNAs against nuclear factor-erythroid 2-like 2 (Nrf2) and Soluble fms-like tyrosine kinase 1 (sFlt-1) to construct nanoparticles and achieve the synchronous downregulation of Nrf2 and sFlt-1 in the placenta (Li et al., 2020a). The nanoparticles were constructed by the carboxyl-polyethylene glycol-poly (d,l-lactide) (COOH-PEG5K-PLA8K), cationic lipid 1,2-Dioleoyl-3-trimethylammonium propane (DOTAP), and a conjugating peptide. The surface modification by conjugating peptides targeting CSA enabled the nanoparticle to deliver drugs to the placenta accurately. The treatment effects and pregnancy outcomes in nanodrug-treated mice were significantly better than those observed with single gene inhibition. Stimuli-responsive nanocarriers have received a great deal of attention for their versatility. Nanocarriers are designed to modulate drug release at the target site by inducing their action through endogenous, including pH, temperature, enzymes, and oxidative reduction. For instance, the variation of glutathione concentration between the tumor microenvironment and normal tissues creates a platform for the generation of the redox-sensitive drug delivery system incorporated with disulfide bonds (Yang et al., 2022). Different pH between normal tissues and tumor microenvironment provides opportunities for pH-sensitive drug delivery systems (Sethuraman et al., 2021). Although the placenta microenvironment has not been connected to the design of nanodrugs, we may apply it as a reference for constructing placenta-specific drug release systems. It was reported that the extracellular microenvironment of the trophectoderm exhibits a lower pH due to hypoxia-induced lactate production (Kay et al., 2007). Hest et al. designed an ELP diblock copolymer that disassembled under mildly acidic conditions (Abdelghani et al., 2021). The safety of nanoparticles is paramount when considering the use of nanoparticles in reproductive medicine. The exposure of nanodrugs to unwanted tissue (maternal or fetal) must be reduced or eliminated, while still providing sufficient therapeutic benefit. Because of low maternal tolerance during pregnancy, any genetic or epigenetic changes in the fetus caused by nanoparticles in the uterus have the potential to cause long-term deleterious effects. The toxicity of nanomaterials is related to the chemical properties, transepithelial electrical resistance, particle size, surface modification, concentration, and paracellular permeability of nanomaterials (Ali & Rytting, 2014). The following are some examples of nanomaterials with maternal fetal toxicity and relatively safe nanomaterials. Yamashita et al. found significant adverse effects of silica nanoparticles on the placental barrier, such as decreased blood flow, spiral artery injury, and apoptosis of cavernous trophoblast cells (Yamashita et al., 2011). Another study found genetic dysregulation in the fetal cerebral cortex, olfactory bulb, and areas associated with the dopamine system after fetal exposure to TiO2 NPs (Umezawa et al., 2012). Maternal lungs exhibited morphologically emphysema-like changes after intravenous injection of 30 nm diameter AuNPs in pregnant mice (Yang et al., 2014), whereas 100 nm AuNPs were genotoxic to fetal liver and blood and cause miRNA dysregulation in fetal lung and liver (Balansky et al., 2013). In vivo administration of 80 nm chromium and cobalt nanoparticles resulted in abnormal fetal hippocampal neurodevelopment and increased DNA damage (Hawkins et al., 2018). Ag accumulation in the mother might affect the growth of placenta and embryos, and induce epigenetic alterations in the embryos, contributing to postponing the cognitive and physical development of the fetus (Ema et al., 2017; Zhang et al., 2015). Long-term accumulation of quantum dots in the mother may increase the risk of embryonic dysplasia (Žalgevičienė et al., 2012). High concentration of polystyrene nanoparticles decreased cell viability of choriocarcinoma cells (BeWo cell line) in vitro (Cartwright et al., 2012), which might be due to the positive correlation between high polystyrene dose and pro-inflammatory effects (Brown et al., 2001; Cartwright et al., 2012). Surface-modified polystyrene nanoparticles were not present in the fetus but accumulated in the liver, spleen or mesangium of pregnant mice with potential health risks (Kenesei et al., 2016). In the in vitro placental perfusion experiment, the placental transfer rate of polyamide dendrimers was significantly reduced compared with free drugs, and placental function was not affected (Menjoge et al., 2011). In vitro (BeWo cells and perfused placenta model), PEGylated doxorubicin liposomes exhibited lower placental penetrability than free doxorubicin and pH-sensitive liposomal preparations of doxorubicin, reducing fetal exposure (Soininen et al., 2015). Risks to the mother and fetus from the various inorganic, organic, or hybrid nanoparticles described above vary, and some reviews also focused on the safety of nanoparticles (Das et al., 2016; Ema et al., 2016; Hou & Zhu, 2017; Keelan et al., 2015; Muoth et al., 2016; Zhang et al., 2017). Inorganic nanoparticles have shown the ease of crossing the blood-placental barrier and induce multiple toxicological effects (Pereira et al., 2020). The direct toxicity of inorganic and organic nanoparticles to fetus might be avoided by nanoparticle retention in the placenta, but the toxicity caused by the deposition of inorganic materials in the mother is still a problem (Verougstraete et al., 2018). In this aspect, biodegradable organic nanoparticles might be more advantageous, and their current clinical application as drug carriers further proves their safety (Anselmo & Mitragotri, 2016). However, both inorganic and organic nanoparticles have also been considered to have indirect toxicity, which may cause maternal pro-inflammatory effects and reproductive endocrine disruptors and indirectly affect the growth and development of the fetus (Gualtieri et al., 2014; Hutz et al., 2014). Therefore, this nascent area deserves more investigation. Compared with inorganic nanoparticles, organic nanoparticles have the potential for better targeting selectivity and less toxicological effects (Kannan & Kannan 2017; Pereira et al., 2020). In general, both inorganic and organic nanoparticles would be able to have good function in placenta drug delivery as long as researchers take advantage of their properties and design nanoparticles skillfully. Surface functionalization of nanoparticles can interfere with the transplacental passage and facilitate placenta-specific drug delivery to reduce maternal-fetal toxicity. Biodegradable materials show less direct toxicity than slowly metabolized biomaterials, but the indirect toxicity of the drug carriers still needs long-term concern. In addition, researchers can pay more attention to biologically derived substances and use their natural targeting, immune tolerance, and other characteristics to design safer vectors, such as placenta-originated exosomes. Besides the toxicity, the bioavailability, solubility, and stability issues of nanoplatforms also deserve more attention in placenta-originated disease therapy. Drugs always cross the placenta to a certain extent after maternal administration (Tetro et al., 2018). When researchers construct placenta-resident drug delivery systems, they need to pay attention to the placental penetration of nanodrugs, because the drug will pass through the decidua-placental junction and adversely affect the fetus during organogenesis and organ maturation. As one of the earliest drug carriers, liposomes have been widely studied for their placental transfer. For instance, T4 thyroxine is a kind of water-soluble macromolecule, whose penetration is effectively blocked by the placenta. After being encapsulated by liposomes, it could penetrate the placenta through the active transport pathway and improve the placental permeability of T4 thyroxine (Bajoria et al., 1997). In an in vitro model, poly(lactic-co-glycolic acid)-encapsulated dexamethasone increased dexamethasone transfer to the fetal compartment (Ali et al., 2013). Moreover, compared with free drugs, liposomal encapsulated penicillin, inulin, methotrexate, and riboflavin in the research were more localized to the placenta and more transferred to the fetus (Tuzelkox et al., 1995). These results demonstrated that nanoplatforms in some conditions could alter the ability of drugs to cross the placental barrier. The above discussion reminds researchers to carefully consider the compatibility of nanomaterials and small molecule drugs. Rapid development and metabolic changes during pregnancy make the fetus more sensitive to external toxicants. Therefore, when preparing nanoplatforms, we should not only consider the function of nanomaterials (placental retention and placental targeting), and the safety of nanomaterials (for both maternal and fetal safety), but also pay attention to the different transport and metabolism conditions of drugs encapsulated in nanoparticles. As the transport and metabolism of the modified drugs are closely related to efficacy and safety, we must clarify the placental penetration of nanodrugs, minimize the potential effect of the drug delivery system on the fetus, and prevent the occurrence of conditions that affect fetal development. The semi-quantitative or quantitative results on the accumulation of nanoplatforms in the placenta versus in the fetus should be included to evaluate their placenta-penetrating effect. Moreover, multiple analytical methods are needed to quantify and/or visualize the pregnancy transfer of nanoparticles, such as liquid chromatography-mass spectrometry analysis, magnetic resonance imaging, ultrasound imaging, photoacoustic imaging, etc. (Bongaerts et al., 2020). A critical step in translating therapeutic and drug delivery technology to the clinic requires the use of animal models in vivo to assess therapeutic effects. The most commonly used animal model for preliminary preclinical studies is the mouse model. The mouse placenta shares a pivotal structural similarity with the human placenta in that both are choroidal placenta, which is characterized by direct contact between maternal blood and trophoblast tissue. Whereas there are several crucial differences between human and mouse placentas, as well as several pivotal differences in full reproduction, that must be taken into account when using mice as model organisms. Such as, mice have a particular inverted yolk sac or chorioflavin placenta. This critical difference can result in higher levels of toxicity to placental development in mice than that in humans when studying drug delivery techniques. In addition, the transport of therapeutic agents across the yolk sac placenta may differ from the human placenta and may have a stronger protective effect against certain foreign substances (Schmidt et al., 2015). The intraplacental anatomy is another important difference between the mouse placenta and the human placenta. The placenta of mice has junction areas and labyrinth areas, which are responsible for the endocrine function and maternal-fetal exchange respectively. In contrast, the human placenta contains two trophoblasts during early gestation, which evolve into a functional area containing lamellar trophoblasts with villi extending into the maternal blood lumen (Dilworth & Sibley, 2013). In conclusion, the mouse model does share similarities with the human placenta (the trophoblast and endothelium separate the maternal-fetal blood supply), but there are still significant differences in the structure, number of cell layers, and dispersion barrier thickness (larger in mice than in humans). Therefore, when assessing the potential, preclinical efficacy, and safety of transplacental delivery of nanoparticles, the results must make assumptions about the applicability to humans, and experimental studies can use a combination of in vitro, ex vivo, and in vivo models to make experimental results more reliable. The Centers for Disease Control and Prevention reports that approximately 70% of pregnant women take at least one prescription drug and 90% of women overall take at least one medication while pregnant (Joshi, 2017). Over the past three decades, the use of prescription drugs during the first trimester of pregnancy has grown by more than 60%, the usage of four or more medications during the first trimester of pregnancy has almost tripled, and the use of four or more medications at any point throughout the pregnancy has more than doubled (Joshi, 2017). Nevertheless, the risk-averse pharmaceutical company is understandably hesitant to engage in the evaluation and development of treatments for pregnant women, haunted by the ghost of thalidomide and the possibility of disastrous lawsuits. This truth is plainly demonstrated by data that pregnant women are purposefully excluded from 98% of medication administration studies (Shields & Lyerly, 2013). Among all pregnancy-related disorders, the therapy of placenta-originated disorders like fetal growth restriction and preeclampsia is particularly difficult. Because it is very difficult to concentrate the drug in the placenta while minimizing the drug permeation on the fetal side. The majority of commonly used medications are small molecules that can pass through the placental barrier by passive diffusion, resulting in substantial fetal toxicity such as miscarriage, deformity, and carcinogenicity. As a result, therapeutic progress for placenta-originated illnesses has been modest in recent decades, and new technology and fresh techniques are required to ameliorate the situation. Recent advances in nanoscience have made placenta-resident drug delivery systems a potential tool for the treatment of placenta-originated diseases, as the ability of nanodrugs to prevent drugs from crossing the placental barrier could greatly increase the number of drugs available to pregnant women. By adjusting the physicochemical properties of nanocarriers, the placenta-resident drug delivery system can optimize the speed and extent of drug transplacental transport and minimize unnecessary drug exposure to the fetus. To accelerate the achievement of constructing placenta-resident drug delivery systems, this review demonstrated the transport mechanism of nanodrugs in the placenta and analyzes the physical and chemical factors that affect the retention of nanoplatforms in the placenta. By reviewing the literature, we have obtained some important insights: (1) the uptake ability of placental trophoblasts to different kinds of materials or nanocarriers with different physicochemical properties varies greatly. Therefore, researchers must screen ‘fetal-friendly’ nanodrugs for the effective treatment of placenta-originated diseases through a sufficient amount of preclinical research; (2) organic carriers are safer in the field of placental drug delivery, and have a relatively wide range of particle sizes choose space; (3) based on the similarity between tumor and placenta, an inspiration from the nanodrug of tumor treatment would help researchers to quickly step forward to achieve placenta drug generation in the treatment of placenta-related complications. At the same time, it should be noted that this similarity does not represent consistency. The knowledge of placental microenvironment and pathophysiology should be deeply studied and differences should be detected, in order to explore the truly suitable materials; (4) as mentioned above, some small molecules may become easier to pass through the placenta and lead to fetal exposure due to the design of nanoplatforms. Therefore, we need to further consider the compatibility between carriers and drugs, as the distribution and metabolism of the nanoparticles are also important for efficacy and safety. More importantly, the advantages and concerns of nanoplatforms in the treatment of placenta-originated diseases are summarized for guiding researchers to construct more potential nanotherapeutics for placenta-originated disease therapy. The goal of placenta-originated disease therapy will take decades to become a clinical reality, and nanodrugs for maternal-fetal health are still in the early phases of development. Much effort is expected to optimize the various portions of the nanotherapeutics and bring the promise to realization. The biodistribution of nanotherapeutics during pregnancy will become more controlled or predictable as scientists continue to identify the ‘rules’ for the placental uptake and transport of nanodrugs. As a result, innovative technologies for treating pregnancy issues should thrive. We anticipate that the first nanotechnology-based pregnancy-specific medicinal formulations will be evaluated in the near future, with a view to developing new treatments for pregnant women and their fetuses.

PMC10003146

36880122

Jae Geun Song,Kshitis Chandra Baral,Gyu-Lin Kim,Ji-Won Park,Soo-Hwa Seo,Da-Hyun Kim,Dong Hoon Jung,Nonye Linda Ifekpolugo,Hyo-Kyung Han

Quantitative analysis of therapeutic proteins in biological fluids: recent advancement in analytical techniques

06-03-2023

Protein drugs,protein assays,LC-MS/MS,ELISA,chromatographic separation,quantitation

Abstract Pharmaceutical application of therapeutic proteins has been continuously expanded for the treatment of various diseases. Efficient and reliable bioanalytical methods are essential to expedite the identification and successful clinical development of therapeutic proteins. In particular, selective quantitative assays in a high-throughput format are critical for the pharmacokinetic and pharmacodynamic evaluation of protein drugs and to meet the regulatory requirements for new drug approval. However, the inherent complexity of proteins and many interfering substances presented in biological matrices have a great impact on the specificity, sensitivity, accuracy, and robustness of analytical assays, thereby hindering the quantification of proteins. To overcome these issues, various protein assays and sample preparation methods are currently available in a medium- or high-throughput format. While there is no standard or universal approach suitable for all circumstances, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay often becomes a method of choice for the identification and quantitative analysis of therapeutic proteins in complex biological samples, owing to its high sensitivity, specificity, and throughput. Accordingly, its application as an essential analytical tool is continuously expanded in pharmaceutical R&D processes. Proper sample preparation is also important since clean samples can minimize the interference from co-existing substances and improve the specificity and sensitivity of LC-MS/MS assays. A combination of different methods can be utilized to improve bioanalytical performance and ensure more accurate quantification. This review provides an overview of various protein assays and sample preparation methods, with particular emphasis on quantitative protein analysis by LC-MS/MS.

Quantitative analysis of therapeutic proteins in biological fluids: recent advancement in analytical techniques Pharmaceutical application of therapeutic proteins has been continuously expanded for the treatment of various diseases. Efficient and reliable bioanalytical methods are essential to expedite the identification and successful clinical development of therapeutic proteins. In particular, selective quantitative assays in a high-throughput format are critical for the pharmacokinetic and pharmacodynamic evaluation of protein drugs and to meet the regulatory requirements for new drug approval. However, the inherent complexity of proteins and many interfering substances presented in biological matrices have a great impact on the specificity, sensitivity, accuracy, and robustness of analytical assays, thereby hindering the quantification of proteins. To overcome these issues, various protein assays and sample preparation methods are currently available in a medium- or high-throughput format. While there is no standard or universal approach suitable for all circumstances, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay often becomes a method of choice for the identification and quantitative analysis of therapeutic proteins in complex biological samples, owing to its high sensitivity, specificity, and throughput. Accordingly, its application as an essential analytical tool is continuously expanded in pharmaceutical R&D processes. Proper sample preparation is also important since clean samples can minimize the interference from co-existing substances and improve the specificity and sensitivity of LC-MS/MS assays. A combination of different methods can be utilized to improve bioanalytical performance and ensure more accurate quantification. This review provides an overview of various protein assays and sample preparation methods, with particular emphasis on quantitative protein analysis by LC-MS/MS. Proteins-based therapeutics display diverse functions and high target selectivity in pathological conditions (Zheng et al., 2014a). Therefore, protein drugs are actively pursued for the treatment of various diseases, and the global pharmaceutical market for protein drugs is continuously expanding with new drug approvals (van den Broek et al., 2013). To expedite the identification and preclinical/clinical development of new protein drugs, sensitive and reproducible protein assays and analytical tools are essential to the pharmaceutical R&D process (van den Broek et al., 2013). In particular, a reliable quantitative assay for protein drugs in biological fluids such as plasma and urine can be instrumental in determining the pharmacokinetic profiles of therapeutic proteins (Russell et al., 2020, 2021). To date, diverse analytical assays are available for quantifying protein content in in vitro and in vivo samples, including UV absorption methods, colorimetric assays, immunoassays, and chromatographic analyses (Chang & Zhang, 2017; Kim et al., 2022a). These methods have their own advantages and disadvantages in terms of assay time, sensitivity, compatibility, specificity, and robustness. Of note, the severe interference from endogenous proteins and substances is often a big challenge in quantifying protein drug concentrations in biological fluids (Gillette & Carr, 2013). Analytical methods should be selected depending on the accuracy, sensitivity, and specificity required for determining protein concentration. Recently, liquid chromatography-tandem mass spectrometry (LC–MS/MS) has been widely adopted as a method of choice for the quantitative analysis of protein drugs in biological fluids owing to its high specificity and sensitivity (Plumb et al., 2012). The LC–MS/MS assay is moderately high-throughput, achieving high sensitivity and specificity for target proteins in complex biological matrices (Plumb et al., 2012). However, the optimization of LC-MS/MS conditions is not straightforward, and there are many factors to be considered in sample preparation, chromatographic separation, and optimizing mass spectrometry conditions. Despite these complications in optimizing LC-MS/MS conditions in regard to sensitivity, accuracy, and specificity, advances in instrument and analytical techniques have promoted LC-MS/MS as a more practical assay for monitoring therapeutic proteins and their potential metabolites in plasma during clinical development. In general, there are two approaches for protein quantitation by LC-MS/MS: bottom-up approach and top-down approach. Bottom-up approach involves the enzymatic protein digestion into smaller peptides and then one or more unique signature peptides are separated and analyzed by LC-MS/MS (Kang et al., 2020). On the other hand, top-down approach employs the direct measurement of intact protein by LC-MS/MS. While bottom-up approach is relatively fast and easy to implement, top-down approach shows the improved selectivity, enabling to characterize the hard-to-predict events such as coding polymorphisms, alternative splicing, and posttranslational modifications, simultaneously (Patrie & Cline, 2020). Nowadays, top-down approach is widely used for protein quantitation by LC-MS/MS. Given that the currently available protein assays have their own advantages and disadvantages, there is no single universal method suitable for all proteins; method selection should be based on the compatibility with the samples to be analyzed. For the best choice of an analytical assay, it is important to understand the working mechanisms, assumptions, and limitations of each analytical method. Therefore, this review will provide a brief overview of protein assays applicable for the quantification of protein drug concentration, with a focus on LC-MS/MS assays as recent advances in LC-MS/MS expand the applicability of this technique during the preclinical and clinical development of protein drugs. Proteins that contain aromatic amino acids such as tyrosine, tryptophan, and phenylalanine, exhibit strong UV absorption around 230–300 nm (Antosiewicz & Shugar, 2016; Yanti et al., 2021). In addition, the peptide bond in proteins has a strong absorption around 190 nm and a weak absorption between 210 and 220 nm (Prasad et al., 2017). Recent studies also suggest that proteins rich in charged amino acids (e.g. Lys, Glu, Arg) can display distinct UV absorption at 250–350 nm although they lack aromatic amino acids (Prasad et al., 2017). As UV absorption is proportional to chromophore content and total protein concentration, the measurement of UV absorption at specific wavelengths can be a simple and direct assay method for determining protein concentrations based on Beer-Lambert law. The measurement of UV absorption does not require any assay reagents. It is rapid, cost-effective, high-throughput, and does not affect the biological activity of proteins (Aitken & Learmonth, 2009; Kielkopf et al., 2020). Furthermore, it does not affect the biological activity of proteins. However, the UV absorption method is not applicable for protein mixtures and for samples containing non-protein contents that can absorb UV light. For example, nucleic acids have strong UV absorbance at 280 nm due to which the coexistence of nucleic acids will interfere with the protein assay by UV absorption (Kielkopf et al., 2020). Interference can also be caused by solvents and various components of biological buffers (Noble & Bailey, 2009; Reinmuth-Selzle et al., 2022). Therefore, interference from co-existing components in biological matrices should be carefully examined during sample preparation and the selection of optimal wavelength. The colorimetric reagent Coomassie Brilliant Blue G −250 dye (triphenylmethane dye) can be used to measure the total protein concentration in a sample as described by Bradford in 1976 (Bradford, 1976; Kielkopf et al., 2020). Although the precise mechanism of the Bradford assay is not fully defined, the main mechanism is the binding of Coomassie dye to basic amino acid residues (e.g. arginine, lysine, and histidine) under acidic conditions, leading to a color change from brown to blue (He, 2011; Reinmuth-Selzle et al., 2022). The protein-dye complex stabilizes the anionic form of the dye, resulting in a spectral shift from the reddish-brown form of the dye (maximum absorbance at 465 nm) to the blue form (maximum absorbance at 610 nm) (Olson, 2016; Filgueiras & Borges, 2022). Although the optimal wavelength is 595 nm, the amount of blue color (absorbance) can be measured at 575–615 nm if needed (Karimi et al., 2022). Among amino acid residues, arginine residues mainly interact with the Coomassie dye while other basic amino acids (lysine and histidine) only give slight responses (Reinmuth-Selzle et al., 2022). This may explain the wide protein-to protein variation in Bradford assays. Van der Waals forces and hydrophobic interactions may also influence protein binding to the dye (Reinmuth-Selzle et al., 2022). The Bradford assay is simple, economic, and fast (Reinmuth-Selzle et al., 2022). It is a sensitive technique that can detect a large range of proteins. In addition, it is compatible with buffers, solvents, thiols, metal ions, reducing substances, and chelating agents (Krohn, 2005). The Bradford assay can be performed in a test tube or in microplate format that may serve as a high-throughput assay. However, it also possesses some disadvantages. The Bradford assay is not suitable for quantifying low-molecular weight peptides or proteins (less than 3,000 Da) that do not produce color by binding with the Coomassie dye (Cohen & Walt, 2019). Nor is it applicable to proteins that are poorly soluble under acidic conditions (Olson, 2016). The assay is incompatible with various ionic and nonionic surfactants (e.g. SDS, Triton X), causing precipitation of the Coomassie dye reagent (Olson, 2016). Recently, modified Bradford assay kits are commercially available and show improved compatibility with certain surfactants and increased linearity of response (Scientific, 2013; Zhou et al., 2022). As described first by Lowry in 1951, copper-based protein assays depend on the biuret reaction as a first step. In the biuret reaction, proteins form a colored chelate complex with cupric ions (Cu2+) in the presence of sodium potassium tartrate. Biuret reacts with copper to form a light blue, tetradentate complex (Martina & Vojtech, 2015). Following the reduction of cupric cations (Cu2+) to cuprous cations (Cu+), the addition of the Folin-Ciocalteu reagent (phosphomolybdate-phosphotungstate) enhances the light blue color of the tetradentate copper-protein complex (maximum absorbance at 750 nm), increasing the sensitivity of the biuret reaction (Noble & Bailey, 2009; Goldring, 2012). Compared to the Bradford assay, the Lowry assay is compatible with most surfactants and exhibits less protein–protein variation (Hayes, 2020). It is more sensitive than the UV absorption method (Rodger & Sanders, 2017). However, this method requires more time and reagents than the Bradford assay. In addition, a high proline content will interfere with the protein-copper complex formation (Schaich, 2016). Since color development is not only due to the reduced copper-amide bond complex but also due to amino acid residues such as tyrosine and tryptophan (or cystine, cysteine, and histidine to a lesser extent), this assay exhibits variability according to protein sequence (Le et al., 2016; Schaich, 2016). Samples containing ammonium sulfate, free thiols, sucrose, chelating agents (EDTA), Tris-HCl, strong acids or strong bases, and Triton X could also compromise the sensitivity of this protein assay (Schaich, 2016). Consequently, modified Lowry methods have been proposed to use fewer reagents, increase the speed and stability of the color formation, improve the compatibility with some salt solutions, and provide a more linear response (Olson, 2016; Schaich, 2016). There are also many commercial sources of the modified Lowry assay. The BCA assay is a widely used method for the quantitation of total proteins in solution (Ahlschwede et al., 2022; Tran & Park, 2022). Similar to the Lowry assay, the BCA assay is a copper-based protein assay where Folin-Ciocalteu reagent in the Lowry assay is replaced by BCA. This method is based on two steps—protein-copper chelation and the secondary detection of the reduced copper (Walker, 2009). The first step is the biuret reaction, where proteins produce the blue chelate complex by reacting with cupric ions (Walker, 2009). Following the reduction of cupric cations (Cu2+) to cuprous cations (Cu+), the reduced cuprous cations (Cu+) react with a highly sensitive and selective colorimetric detection reagent, BCA, resulting in an intense purple BCA/copper complex (λmax = 562 nm) (Olson, 2016). The BCA/copper complex is water-soluble and its absorbance at 562 nm exhibits strong linearity with increasing protein concentrations. In addition to 562 nm, the purple color can be measured at any wavelength of 550 nm–570 nm with minimal (<10%) loss of signal. The BCA assay has many advantages over other protein assays. Compared to the Bradford assay, it is more sensitive and compatible with surfactants at concentrations up to 5%. In addition, it responds more uniformly to different proteins than the Bradford method, exhibiting lower protein-protein variation (Noble et al., 2007). In the BCA assay, the reagent is fairly stable under alkaline conditions and can be included in the copper solution, leading to a one-step process. It is applicable over a broad range of protein concentrations (0.5 μg/mL to 1.5 mg/mL). However, it also displays some disadvantages. Substances reducing or chelating copper will produce color, thus interfering with the accuracy of the protein quantitation (Noble et al., 2007). The accuracy of the results is also affected by the presence of acidifiers, reducing sugars, lipids, and phospholipids in the buffer. Variable colorimetric responses may arise due to differences in the compositions and structures of proteins, including amino acid sequence, isoelectric point, secondary structure, and side chain or prosthetic groups (Krohn, 2005). The intensity of the produced color also varies with the incubation time and temperature, requiring the optimization of assay conditions for each application (Krohn, 2005). At present, different BCA assay kits, including the micro-BCA protein assay, are commercially available. Fluorescence-based assays for protein quantitation have been developed to overcome the limitations of absorbance-based assays. In particular, fluorescence-based protein assays may be a better option for total protein quantitation where sensitivity or limited sample size might be an issue. These assays have superior sensitivity and lower background signals, requiring less protein sample for quantitation than colorimetric protein assays (An, 2009). They are suitable for high-throughput application with automation to quantify proteins in biological samples. Furthermore, they provide a wider dynamic range and lower protein-to-protein variability than colorimetric assays (An, 2009). Fluorescence-based assays detect the fluorescent signal from the dye attached to proteins, using a fluorometer or a microplate reader. In general, fluorescence-based protein assays adopt two different approaches: (i) using nonfluorescent but reactive dyes that covalently bind to the amine groups of proteins and form fluorescent adducts, or (ii) using dyes that exhibit fluorescence enhancement upon non-covalent interaction with hydrophobic regions of proteins or detergent-coated proteins (Jones et al., 2003). For both approaches, various fluorescence probes have been developed and are commercially available. For example, fluorescamine is nonfluorescent but interacts with primary amines, producing fluorescent adducts detectable at λex = 390 nm and λem = 475 nm (Jones et al., 2003). Similarly, o-phthaldialdehyde (OPA) and 3-(4-carboxybenzoyl) quinoline-2-carboxaldehyde (CBQCA) are nonfluorescent but react with primary amine groups of proteins (Bantan-Polak et al., 2001). CBQCA binds to primary aliphatic amines in the presence of cyanide or thiols, leading to the formation of a fluorescent adduct detectable at λex = 450 nm and λem = 550 nm (You et al., 1997; Bantan-Polak et al., 2001). OPA is also nonfluorescent but reacts with primary amines in the presence of 2-mercaptoethanol, producing an intense blue, fluorescent product detectable at λex = 340 nm and λem = 455 nm (Bantan-Polak et al., 2001; Jones et al., 2003). These reagents function well in the presence of lipids that normally interfere with protein estimations (Olson, 2016). They are also compatible with reducing agents, metal chelators, and detergents (Jones et al., 2003). However, they are not compatible with amine-containing buffers (e.g. Tris or glycine buffers), and the presence of free amino acids or other materials containing primary amines interferes with protein detection (Jones et al., 2003). The sensitivity of their assays depends on the number of amines in the protein analytes. In addition to these reagents, coating proteins with detergent and detecting detergent-protein complexes are also known to improve the detection and quantitation of proteins, since certain ionic detergents can coat proteins with near uniformity (Jones et al., 2003). At present, nonfluorescent dyes that become intensely fluorescent upon binding to detergent-coated proteins or hydrophobic regions of proteins are commercially available for protein quantitation in complex biological samples. The immunoassays are highly selective bioanalytical methods for the detection or quantitation of diverse biomacromolecules (Darwish, 2006). Owing to their high specificity and sensitivity, immunoassays can be used to quantify very low concentrations of proteins in biological samples. In addition, they can be used to analyze large numbers of samples at a time without exhaustive sample preparation, thus minimizing the turn-around time of analysis (Hsieh & Rao, 2017). Consequently, immunoassays have been widely used in the pharmaceutical development process of protein drugs for pharmacokinetic evaluation, bioequivalence studies, and drug monitoring. However, immunoassays for quantifying proteins in biological fluids may have a limitation linked to the interference from certain substances that may cause either false-negative or false-positive results. They often suffer from a lack of specificity and cross-reactivity with other molecules, including metabolites. In addition, suitable antibodies may not always be available. To improve the sensitivity, specificity, and throughput, there has been continuous effort to refine immunoassays along with the development of new reagents, systems, and methodologies. Monoclonal antibodies are now widely used in immunoassays, and the methodologies of labels and solid-phase components are much more sophisticated. Given that the major trend is to avoid radioisotopic labels and move toward fast, reliable, and automated solid-phase assays with nonisotopic labels, some immunoassays with nonisotopic labels will be covered in the following section. Enzymatic immunoassays are categorized into homogeneous enzymatic immunoassays and heterogeneous enzymatic immunoassays. In homogeneous enzymatic immunoassays, enzymes are inactivated while they bind to the antibody, eliminating the need for the washing step (Porstmann & Kiessig, 1992). They are easy to use but their application is limited due to high cost and low sensitivity. Compared to homogeneous enzymatic immunoassays, heterogeneous enzymatic immunoassays require washing steps to remove free, unbound antigen (Aydin, 2015) but are more commonly used due to their higher sensitivity (Aydin, 2015). In 1971, Engvall and Perlmann reported a simple, rapid, sensitive, and high-throughput, heterogeneous immunoassay technique, generally known as the enzyme immunoassay (EIA) or the enzyme-linked immunosorbent assay (ELISA) (Engvall & Perlmann, 1971). ELISA is a powerful method that is used to detect and quantitate very low concentrations of proteins, peptides, antibodies, and hormones in complex biological fluids with minimal interference. In principle, ELISA is a plate-based assay technique, where the antigen (target macromolecule) is immobilized on a solid surface and then complexed with a reporter enzyme-linked antibody (Hosseini et al., 2018). Detection occurs by measuring the activity of the reporter enzyme via incubation with the appropriate substrate to produce a measurable product. In this assay, horseradish peroxidase (HRP) and alkaline phosphatase (AP) are the most commonly used enzyme labels, although other enzymes, including β-galactosidase, catalase, glucose oxidase, and acetylcholinesterase, have also been used (Porstmann & Kiessig, 1992). In addition, various substrates are commercially available for ELISA. Substrates should be selected depending on the required assay sensitivity and the instrumentation for signal detection (e.g. spectrophotometer, luminometer, or fluorometer). For example, HRP conjugates with 5-amino salicylic acid and orthophenylenediamine produce brown complexes, while AP conjugates with sodium azide produce yellow complexes (Aydin, 2015). These enzyme-substrate reactions are usually completed within 30–60 min, and the absorbance is determined using a spectrophotometer at 400–600 nm depending on the characteristics of the conjugate used (Aydin, 2015). Several different ELISA formats have been developed to increase the specificity of measurement. Among them, the sandwich ELISA assay is the most widely used due to its high sensitivity and specificity. In the sandwich ELISA, the analyte to be measured is bound between two primary antibodies—the capture antibody and the detection antibody—that detect different epitopes of the antigen (Drijvers et al., 2017). Initially, the sample is added to the microplate wells coated with the antibody. Then, the plate is incubated and undergoes washing steps to remove unbound antigens. Following the washing step, antibodies that are specific to the antigen are added and incubated; these antibodies are tagged with the reporter enzyme. The enzyme substrate is then added to the medium for producing colored complexes. Currently, matched pairs are commonly used in the sandwich ELISA where the capture and the detection antibodies do not interfere with each another and have simultaneous binding capacity. ELISA is easy to perform due to the binding and immobilization of reagents to the solid surface. The immobilization of reactants to the microplate surface facilitates the separation of bound materials from unbound ones. Furthermore, the use of high-affinity antibodies and the washing away of nonspecific bound materials make ELISA a powerful tool for measuring specific analytes in a biological matrix. Furthermore, various ready-to-use ELISA kits are commercially available, allowing easy analysis of protein samples. Consequently, the ELISA is often a method of choice for quantifying protein concentrations in biological fluids owing to its speed, simplicity, specificity, and relatively low cost, even when proteins can be measured by other standard procedures. However, it also presents some drawbacks, including high cost, laborious assay procedures, antibody instability, insufficient blocking of immobilized antigens, and the possibility of cross-reaction (Shah & Maghsoudlou, 2016; Hosseini et al., 2018). Given that the detection step largely determines the sensitivity of immunoassays, the detection of antibodies can be done using fluorescent probes in addition to the use of immunoassays based on color intensity. Such assays are known as fluorescent immunoassays (FIAs) (Rizzo, 2022). The FIA is a variant of the ELISA, where the substrate used does not generate color but emits fluorescence. In addition to conventional FIAs, advancement in fluorescent labeling technologies and instruments has facilitated the development of various FIA-related methodologies, including fluorescence polarization immunoassays and time-resolved fluorescence immunoassays. Although standard fluorometric detection with conventional fluorophores is popular, it has several limitations: (i) a high background signal due to the simultaneous excitation/emission process, (ii) self-quenching due to relatively small Stokes shift (the difference between the maximum absorbance and emission wavelengths), (iii) a background signal from autofluorescent substances in biological matrices, and (iv) potential false positives due to fluorescent test compounds in high-throughput screening formats (Soini & Hemmilä, 1979; Hemmilä, 1985). In particular, background fluorescence from the sample can limit the utility of FIAs. To overcome these drawbacks, time-resolved fluoroimmunoassay techniques (TRFIAs) use chelates of lanthanides as fluorescent labels (Hagan & Zuchner, 2011). During standard fluorometric detection, the light emitted by the sample is measured while excitation occurs. However, in TRFIAs, lanthanide chelate labels allow the detection of the emitted light after excitation has occurred. Lanthanide chelates (e.g. europium, terbium, and samarium) have longer fluorescence lifetimes (µseconds–milliseconds) than the typical background fluorescence of biological matrices, enabling the measurement of fluorescence emission after any background fluorescence has decayed (Kricka & Park, 2014). In addition, lanthanide chelates have substantial Stokes shift, thus greatly increasing the signal to background ratio. Other unique characteristics of lanthanide chelates include the possibility of dissociating the label into a new, highly fluorescent chelate by pH shift and narrow emission peaks, which make the TRFIA a highly sensitive method associated with lower interference detection (Hagan & Zuchner, 2011; Rizzo, 2022). The fluorescence polarization immunoassay (FPIA) is also a widely used homogeneous FIA. The polarization of the fluorescence from a fluorescence-labeled antigen (tracer) is determined by its rate of rotation during the lifetime of the excited state in solution. Since the degree of depolarization depends on the size of the molecule (large molecules rotate more slowly), a fluorescence-labeled tracer in solution has a lower degree of polarization than an antibody-bound tracer having slower rotation (Hendrickson et al., 2020). Therefore, fluorescence polarization can be modulated by the competition between drugs in the sample and the fluorescence-labeled tracer for binding to the antibody, where the depolarization is related to the drug concentrations in the sample (He et al., 2018). At low drug concentrations, more tracer molecules are bound to the antibody, leading to a higher fluorescence polarization. Overall, the FIA is more sensitive than the ELISA and is used to determine low concentrations of proteins. It is also simple, easy to run, and rapid. The FIA is advantageous over the chemiluminescence immunoassay in terms of low cost, large signal intensity, and faster imaging speed (Ahmed et al., 2020). The basic principle of chemiluminescence immunoassays (CLIA) is similar to that of the ELISA, except that the substrate of the CLIA generates a luminescence signal in the presence of an enzyme, instead of developing a particular color. Chemiluminescence is the emission of light by a chemical reaction, where the enzyme used in CLIA converts the substrate to a reaction product emitting a photon of light (Rizzo, 2022). These chemiluminescent reactions can also be elevated by an enhancer that boosts the electronic activation and provides an intense light emission for a longer period, leading to highly enhanced analytic sensitivity (Cinquanta et al., 2017). Compared to ELISA, the CLIA shows higher sensitivity and shorter turnaround times. In addition, it has a wider dynamic range with a linear relationship between luminous intensity and the concentration of the measured substance. The key advantages of CLIA also include the absence of interfering emissions (high specificity), rapid acquisition of the analytical signal, and high stability of reagents and their conjugates. Different types of substrates are available for CLIAs, and activation of these substrates requires chemical or enzymatic reactions associated with the immunological reactions (Cinquanta et al., 2017). Most chemiluminescent substrates are HRP-dependent, although AP-based substrates are also available in certain cases (Rizzo, 2022). Luminol or its derivatives are the most commonly used substrates in the presence of HRP and a peroxide buffer (Rizzo, 2022). The electro-chemiluminescence immunoassay (ECLIA) is another type of a CLIA, using electrical current for oxidizing substrates. The ECLIA also has higher sensitivity and a shorter analysis time than the ELISA (Bolton et al., 2020). Technical advancement will continuously encourage the development of a new and automated analytical method based on the principle of CLIA, increasing the assay efficiency and steadily reducing cost. In recent decades, HPLC has become an indispensable method for the purification, separation, and quantitation of peptides and proteins, owing to its high resolution, reproducibility, selectivity, and high recovery (Aguilar, 2004). There are various separation modes of HPLC, including ion exchange chromatography (IEC), size exclusion chromatography (SEC), reversed-phase liquid chromatography (RPLC), and affinity chromatography (Wang et al., 2016b). Among them, RPLC, IEC, and SEC are most commonly used for protein analysis (Mant et al., 2007). RPLC is a powerful and widely used method for the analysis of both intact and fragmented proteins. It is performed with columns containing highly pure and inert silica-based particles (usually silica particles chemically bonded with octadecylsilyl groups) as the stationary phase. In particular, for the analysis of large, intact proteins, a surface-modified, highly pure, and wide-pore size silica (e.g. ≥300 Å) is used to improve the access of proteins to the stationary phase pores (Fekete et al., 2012). In RPLC, the separation of proteins depends on the difference in adsorption coefficient or binding affinity of each analyte to immobilized stationary phase, where the hydrophobicity of the analytes determines the elution order, with the least hydrophobic molecule eluting first (Aguilar, 2004). Furthermore, the binding affinity is affected by the structure of the analytes and the nature of the immobilized ligands. In the case of IEC, the retention mechanism depends on the surface charge of the proteins and the charge of the surrounding medium; therefore, choosing an appropriate pH value is important (Kopaciewicz et al., 1983). In SEC, the separation of molecules is based on the hydrodynamic radius and the shape of the analytes rather than adsorptive interactions between the analytes and the column support (Hong et al., 2012; Kim et al., 2020, 2022b). SEC is also referred to as gel filtration chromatography (GFC) if aqueous solutions are used as the mobile phase. Since the analytes are filtered through the porous network of the stationary phase, the SEC column works like an ‘inverse sieve’ where because larger molecules cannot move through the internal pores as deeply as smaller molecules, they elute earlier (Grotefend et al., 2012). Although LC-MS/MS has become increasingly popular for protein analysis in recent years, SEC is still widely used as a powerful, more cost-effective tool. In addition to different separation modes, HPLC offers various detection options, including UV or fluorescence detection and mass spectrometry, which may affect its sensitivity and specificity (Table 1). High recovery of proteins and peptides from the stationary phase is also important since it influence the sensitivity and reproducibility of HPLC assay (D’Atri et al., 2020). Various factors such as column dimensions, pore size, ligand type, mobile phase composition, temperature, and flow rate can greatly influence the sensitivity, specificity, and recovery in the chromatographic analysis of proteins and peptides (Josic & Kovac, 2010; Bobály et al., 2015). More details of these variables will be discussed in Section 3.2.1. Mass spectrometry (MS) measures the mass-to-charge ratio of ions to quantify drugs in the biological matrix. The key components of mass spectrometers include an ion source, a mass analyzer, and a detector that measures the intensity of ionized molecules using the mass-to-charge ratio (m/z) (Jonsson, 2001). Various ionization methods are available, including ion electron impact, chemical ionization, electrospray ionization (ESI), and laser desorption (Jonsson, 2001; Jeong et al., 2020). Among them, ESI is extensively used for quantitative protein analysis. ESI is the most effective and soft ionization technique, which produces ionized droplets without breaking chemical bonds and further fragmenting the peptides (Bolbach, 2005; Banerjee & Mazumdar, 2012). Different mass analyzers including quadrupole (Q), ion-trap (IT), time-of-flight (TOF), Fourier transform ion cyclotron resonance (FTICR), and Orbitrap are also available for the measurement of fragmented ions (Glish & Vachet, 2003). The combination of different analyzers (e.g. QTOF, triple-Q) can be used to improve the sensitivity, accuracy, and resolution of ions having similar m/z values in quantifying proteins or peptides (Neagu et al., 2022). However, if multiple substances having identical molecular masses exist in the sample mixture, chromatographic separation should be carried out prior to MS analysis (Karpievitch et al., 2010). Recently, a multidimensional LC strategy has been reported to improve the separation of peptides or proteins, including cation exchange and RPLC separation (CEX-RPLC) and hydrophilic interaction chromatography (HILIC)-RPLC separation (HILIC-RPLC) (Law et al., 2015; Stoll et al., 2018). In addition, Baghdady & Schug (2019a) evaluated different high pH volatile buffers and ion pairing reagents by using two different high pH resistant RPLC packing materials (silica- and polymer-based). They achieved the best chromatographic separation using triethylammonium bicarbonate at pH 10 and hybrid silica particles, suggesting that online coupling of high pH RPLC configuration to low pH RPLC for a comprehensive two-dimensional LC may be feasible for intact proteins (Baghdady & Schug, 2019a). However, multidimensional LC requires a larger amount of samples and more analysis time compared to using single LC (McDonald et al., 2002; Peng et al., 2003). Tandem mass spectrometry (MS/MS) combines two mass analyzers in a single instrument. After a sample is ionized and mass-analyzed in the first mass analyzer, a distinct ion of interest having a particular m/z-ratio is directed into a collision cell and undergoes fragmentation by various dissociation methods, including collision-induced dissociation, higher energy collision dissociation, electron-transfer dissociation, and electron-capture dissociation (van den Broek et al., 2008). Then, the generated fragments are separated by the second mass analyzer, based on their individual m/z ratios. To improve the selectivity and specificity, HPLC-based separation can be performed prior to MS/MS analysis, which is known as LC-MS/MS analysis. In current clinical practice, two representative methods for the quantification of target protein in plasma are ELISA and LC-MS/MS; the advantages and disadvantages of LC-MS/MS are summarized in comparison with ELISA in Table 3. Owing to the substantial sensitivity, selectivity, and high throughput, the LC-MS/MS assay often becomes a method of choice for the identification and quantification of proteins in complex biological samples. Selected examples for the application of LC-MS/MS in protein assays are summarized in Table 2. Accordingly, its application as an essential analytical tool is continuously expanded in the pharmaceutical R&D process. Therefore, this review will cover more details on the method development of LC-MS/MS for quantifying therapeutic proteins in biological samples such as serum and urine in the following sections. Sample preparation is a critical part of LC-MS/MS analysis for the quantitative determination of target proteins in biological fluids (Maráková, 2022). Various sample preparation methods have been developed for an efficient and reproducible LC-MS/MS analysis of protein samples. Each method has its own limitations, and no single method works for all diverse types of proteins. Furthermore, there is limited commercial availability of simple, economic, and non-immunoaffinity sample preparation options for intact proteins (Maráková, 2022). Since an efficient and robust sample preparation process allows faster and cleaner chromatographic separation prior to MS analysis, the quality of sample preparation can considerably affect the quality of data obtained from LC-MS/MS analysis. Therefore, the selection and optimization of the appropriate sample preparation method is essential to assure a highly sensitive, accurate, and reproducible LC-MS/MS analysis for protein quantitation. Some common sample preparation methods are illustrated in Figure 1 and their basic principles are briefly discussed in the following section. PPT is the most widely used plasma sample preparation method for LC-MS/MS analysis because of its simplicity, fast speed, and low cost (Zheng et al., 2014a; Yuan, 2019). It is appropriate for high protein matrices such as plasma and serum, utilizing the solubility difference between protein drugs of interest and many other macromolecules in biological fluids (Thomas et al., 2021). In principle, the change in pH or hydrophobicity by adding a precipitating reagent (e.g. organic solvents, acids, salts), alters the interactions between proteins and the aqueous environment, precipitating proteins out of solution (Zheng et al., 2014a; Lim et al., 2020). In addition, binding of metals to proteins causes the denaturation and the aggregation of proteins, promoting protein precipitation (Polson et al., 2003). Generally, the protein precipitant is separated either through centrifugation or filtration, and the supernatants are used for further analysis (Yuan, 2019). The PPT process can be automated using commercially available 96-well PPT plates that are also compatible with most LC/MS autosamplers. Generally, PPT does not require extensive method development and can be implemented with a simple generic method. In addition, PPT is very efficient, removing >90% of proteins from various animal plasma samples by using a 2:1 volume ratio of acetonitrile to plasma (Polson et al., 2003). However, it has some limitations, particularly when the plasma concentration of protein drugs is very low. If evaporation and re-constitution steps are omitted, the limit of quantitation (LOQ) of the assay may be compromised by dilution with precipitating reagents, leading to reduced assay sensitivity (Li et al., 2019). Furthermore, as various endogenous proteins or phospholipids/salts in plasma cannot be completely removed by PPT, they often interfere with the assay (Zheng et al., 2014a). PPT may also cause a loss of protein drugs during the precipitation of endogenous plasma proteins, due to protein binding or analyte stability (Zheng et al., 2014a). Thus, it is important to disrupt protein binding of the biomolecules from the biological matrices and maximize the drug recovery. Various strategies are employed to improve the drug recovery in PPT. Formic acid or ammonium hydroxide can be added into the organic solvents to reduce protein binding (Zhao & Juck, 2018). In addition, to improve the drug recovery, low volume ratios of precipitating solvents to plasma sample are preferred, generally 2:1 or even lower (Polson et al., 2003). However, it may reduce the efficiency of protein removal. To overcome these issues, PPT may be used in combination with other sample preparation techniques such as solid phase extraction or liquid-liquid extraction (Chambers et al., 2014; Miyachi et al., 2017). LLE is a method that can be used to selectively extract the analyte from biological matrices using differential distribution of biomolecules into a two‐phase solution system (typically an aqueous solution and a water-immiscible organic solvent or solvent mixture) (Chang et al., 2007). In LLE, the analyte of interest in biological fluids is partitioned by adding an organic extraction solvent with vigorous mixing, followed by additional steps such as evaporation and reconstitution (Vuckovic, 2020). For improving the recovery of analytes while minimizing the matrix effect, experimental variables such as the extraction solvent, extraction buffer, pH, and the volume ratio of the sample and extraction solvent should be carefully optimized (Yuan, 2019). In general, LLE is more efficient in removing endogenous proteins, lipids, and salts from biological samples than PPT (Yuan, 2019). LLE is simple, easy to run, and high‐throughput in a 96‐well plate format (Zheng et al., 2014b). It is also more cost-effective than solid-phase extraction (SPE). However, the application of the LLE method is mainly limited to hydrophobic proteins, as polar proteins are not efficiently extracted by typical water-immiscible organic solvents (Yuan, 2019). To overcome this issue and expand its application to hydrophilic proteins, salting‐out-assisted LLE (SALLE) has been developed as an alternative LLE (Tang & Weng, 2013). It employs the salting-out effect of a water-miscible organic solvent by the addition of a substance inducing phase separation from an aqueous solution, achieving the simultaneous extraction of target compounds into a separated organic solvent phase (Zhang & Xiong, 2019). As salts and extraction solvents have a great influence on the extraction efficiency and drug recovery, their selection should be carefully optimized (Zhang & Xiong, 2019). The most commonly used organic solvents for SALLE are acetonitrile, acetone, and isopropanol, while most commonly used salting-out agents include sodium chloride, calcium chloride, magnesium sulfate, and ammonium sulfate (Tang & Weng, 2013; Zhang & Xiong, 2019). Although SALLE offers an alternative for the extraction of hydrophilic compounds that are not efficiently extracted by conventional LLE, it is not limited to only polar drugs. Compared to PPT, SALLE is similarly simple but provides cleaner extracts due to the phase separation. It is also faster and more cost-effective than conventional LLE. In most cases, SALLE does not require evaporation and reconstitution steps, allowing subsequent LC-MS/MS analysis directly in the organic phase or after a simple dilution (Zhang & Xiong, 2019). Particularly, SALLE in 96-well automation can be easily integrated into the high-throughput LC-MS/MS assay to increase productivity. SPE is an efficient method providing more selective extraction of various compounds via chromatographic separation using cartridges packed with silica-based or polymer-based sorbents (Badawy et al., 2022). The selection of an appropriate SPE sorbent is critical for the successful extraction of target analytes and should be done by taking into account various physicochemical properties (e.g. polarity, basicity, charge) of analytes. Similar to HPLC columns, many stationary phase options are available such as reversed phase, ion exchange, normal phase, and mixed mode phases (Sentellas et al., 2020). Among them, the most commonly used SPE materials for the isolation of proteins and peptides are reversed-phase and ion-exchange materials. Dual retention modes combining different types of SPE are often used to improve the selectivity and sensitivity, particularly prior to the quantitative analysis of therapeutic proteins (Yang et al., 2007). For example, RP-SCX-SPE, which combines reversed phase-SPE (RP-SPE) with strong cation exchange-SPE (SCX-SPE), could remove the background peptides and other interfering substances in a biological matrix more efficiently than RP-SPE alone, thereby greatly reducing the background noise and improving the assay sensitivity of LC-MS/MS (Yang et al., 2007). SPE materials are also available in various formats including cartridges, plates, micropipette tips, and magnetic beads (Bladergroen & van der Burgt, 2015). Although SPE is a commonly used sample preparation method, it has issues including poor recovery and reproducibility, incomplete sample cleanup, and high matrix effect (Płotka-Wasylka et al., 2015; Badawy et al., 2022). To overcome these drawbacks, new microextraction techniques have been developed, including solid-phase microextraction (SPME), dispersive micro-SPE (DMSPE), and magnetic SPE (MSPE) (Chen & Bartlett, 2012). For example, micro-elution SPE is a miniaturized solid-phase extraction method, enabling minimal elution volumes to deliver concentrated samples for high-sensitivity analysis. In a conventional SPE plate or column, higher eluting solvent volumes may require an evaporation step to concentrate samples. However, micro-elution SPE containing a sorbent bed as little as 2 mg, requires typical sample volumes of 10–100 µL and elution volumes as low as 25 µL (usually <150 µL), diluting samples without losing sensitivity (Maráková et al., 2023). Micro-elution SPE technique also offers shorter operation time and lower cost. Moreover, it is suitable for hydrophobic proteins and the direct analysis of analyte without drying and reconstitution step (Maráková et al., 2023). Unlike HPLC, SPE is typically a low resolution and very low-pressure method that helps remove interfering substances or concentrate a sample, thereby improving assay sensitivity. SPE provides much cleaner extracts than PPT and uses significantly smaller volumes of solvent than LLE (Yuan, 2019). It can reduce harmful compounds introduced into the LC system, thereby extending the life-time of analytical columns and instruments. Furthermore, SPE can be automated in a 96‐well plate format that are directly coupled to LC-MS/MS analysis (Sentellas et al., 2020). As a result, SPE is widely used in pharmaceutical applications. However, compared to PPT and LLE, its cost is higher and the optimization of its experimental variables takes longer time (Zheng et al., 2014a). Compared to proteins, peptides are easier to fractionate by LC and are ionized and fragmented more efficiently. Thus, in the quantitative analysis of proteins in plasma or other biological fluids, protein digestion is actively employed to convert protein analytes to peptides mixture and then to quantify one or more of peptides as a surrogate by LC-MS/MS. Protein digestion can be done enzymatically or non-enzymatically (Angel et al., 2012). The enzymatic or chemical digestion of proteins cleaves the protein into smaller peptides having higher chemical tractability, lower molecular mass, and fewer charges, thus leading to more efficient chromatographic separation and better detection by the mass analyzer (Compton et al., 2011; Willems et al., 2021). The most widely used digestion methods employ sequence-specific proteases such as trypsin, chymotrypsin, endoproteinase Glu-C, and Lysyl-endopeptidase (Switzar et al., 2013). Among proteolytic enzymes, trypsin is a gold standard owing to its high specificity and low cost, cutting at the carboxyl side of arginine (Arg) and lysine (Lys) residues. It produces positively charged peptides with an average size of 700–1,500 Da, which are easily detectable by MS (Burkhart et al., 2012). Selection to perform in-solution or in-gel digestion depends on the sample amount and/or its complexity. In-solution digestion is generally advantageous for small sample volumes with low to moderate complexity and is more amenable to high throughput. In in-solution digestion, proteins typically undergo irreversible cleavage of disulfide bonds via reduction and alkylation, prior to digestion, to allow immediate access of trypsin to internal cleavage sites and achieve high protein sequence coverage during MS analysis (Medzihradszky, 2005). However, reduction and alkylation steps can be excluded if high sequence coverage is not required. Although trypsin is highly active and tolerant of many additives, tightly folded proteins can be resistant to trypsin digestion. Post-translational modifications also present a challenge for trypsin-based digestion since glycans can limit trypsin access to cleavage sites, and acetylation makes Lys and Arg residues resistant to trypsin digestion (Saveliev et al., 2007). In addition, if the distribution of tryptic cleavage sites is suboptimal, the obtained peptides may be too long or too short for MS analysis. To overcome these issues, various alternative proteases, including Glu-C, Lys-N, Lys-C, Asp-N, and chymotrypsin are commercially available, which complement trypsin and allow more efficient protein analysis with MS. Extraction of the protein prior to enzyme digestion and/or extraction of the surrogate peptide after enzyme digestion can also be employed to improve the selectivity and sensitivity of protein analysis (Li et al., 2011). As an alternative to enzymatic digestion, nonenzymatic digestion of proteins can be performed via chemical cleavage by dilute acid solutions (e.g. formic acid, hydrochloric acid, acetic acid), cyanogen bromide, 2-nitro-5-thiocyanobenzoate, and hydroxylamine (Crimmins et al., 2000; Switzar et al., 2013). In recent years, electrochemical oxidation-based nonenzymatic cleavage of proteins has been reported to allow specific cleavage at Tyr and Trp, exhibiting the advantages of rapid reaction and online coupling to an LC-MS system (Permentier et al., 2003). To enhance the digestion of diverse proteins, several approaches have also been explored, including the combined use of chemical and enzymatic methods (Choudhary et al., 2003) and multiple enzyme digestion strategy using the combination of enzymes having different specificity (Swaney et al., 2010). Similarly, immobilization of enzymes onto a solid surface can be used to increase enzyme stability and digestion efficiency (Massolini & Calleri, 2005; Yamaguchi et al., 2010) . In addition, various approaches such as elevated temperature, microwave, ultrasound, and high pressure have been used to accelerate digestion (Switzar et al., 2013). The physicochemical properties of protein samples are critical to determine how they are digested and prepared further for LC analysis. Filtration is often applied to samples containing particles such as undissolved salts. The experimental conditions for each method should be tailored to specific samples and MS techniques for optimal and reproducible results. High-abundance proteins (HAPs) present in serum, plasma, and other physiological fluids can hinder the identification and characterization of important low-abundance proteins (LAPs) by limiting the dynamic range for mass spectral analyses due to the masking effects of HAPs (Pietrowska et al., 2019). Therefore, depletion of HAPs in biological samples has become a routine strategy for enhancing the detection sensitivity of LC-MS/MS analysis. High abundant plasma proteins include albumin, IgG, antitrypsin, IgA, transferrin, haptoglobin, and fibrinogen (Millioni et al., 2011; Pietrowska et al., 2019). Depletion of these HAPs in biological samples has become a routine strategy for enhancing the detection sensitivity of LC-MS/MS analysis. Depletion of HAPs improves the dynamic range for LC-MS/MS analysis and the loading capacity, resulting in the simplification of a complex system and enabling the detection of low-level target proteins. Several fractionation methods are available for protein depletion, which are based on the separation of proteins by physicochemical properties (charge or size) or biochemical properties (immunoaffinity) (Ly & Wasinger, 2011). In particular, immuno-based depletion methods involve the selective binding of target proteins to the stationary phase using immobilized antibodies or other molecules with high affinity and specificity for the targets (Filip et al., 2015). As a result, they have high specificity and efficiency, achieving rapid purification or concentration of the analytes. An alternative strategy to isolate LAPs is based on an immobilized, combinatorial peptide ligand library (Righetti & Boschetti, 2015; Lee et al., 2019). Highly diverse hexapeptides are bound to a chromatographic support where each unique hexapeptide binds to a unique protein recognition site. In this approach, HAPs saturate their ligands and excess proteins are washed out during the process while LAPs are concentrated on their specific ligands. Several protein depletion kits are commercially available, simultaneously depleting multiple HAPs (approximately 7–20 HAPs). Depletion of HAPs by immunoaffinity columns may be followed by denaturation, reduction, desalting, and tryptic digestion of low-abundance target proteins to improve the accuracy and the precision of the assay (Shi et al., 2012b). Such an integrated sample preparation system can be further integrated with LC-MS/MS to achieve high-throughput protein quantification in biological samples. Immunocapture enrichment is widely used to isolate and enrich the target proteins or peptides from the biological matrices. It employs capture reagents (usually antibodies) for the specific and high affinity interaction with the target analytes, offering a highly selective sample cleanup and enrichment procedure (Zhao et al., 2018a). In addition, combination of immunocapture enrichment with LC-MS/MS analysis provides a viable option for the quantitative analysis of LAPs or signature peptides in biological matrices. Capture reagents are usually immobilized on a solid support. During the immunocapture process, the target analyte binds specifically and tightly to the capture reagent on a solid support but other matrix components that do not bind to the capture reagent are removed from the solid support by washing with a buffer (Zhao et al., 2018a). Then, the target analytes are eluted from the capture reagents by adding acids, followed by LC-MS/MS analysis. The immunocapture process produces a clean, enriched extract and greatly reduces matrix effect in LC-MS/MS analysis, thereby improving assay sensitivity. There are several critical factors in developing a reliable and robust immunocapture-LC-MS/MS assay, including reagent selection and designing of capture format. Particularly, capture reagents are the most crucial component in the immunocapture-LC-MS/MS analysis, since their quality directly affect the assay specificity, reproducibility, sensitivity, and robustness (Zhao et al., 2018a). Capture reagents are categorized into two groups; generic capture reagents and specific capture reagents. Generic capture reagents bind to various common regions (e.g. Fab or Fc) of proteins but have different binding affinities across protein species (Fung et al., 2016). Since the low specificity issues of generic capture reagents can be overcome by selective mass detection, generic capture reagents are useful in a wide range of applications. On the other hand, analyte-specific capture reagents (e.g. antipayload, antitarget, antipeptide antibodies) are required to improve the specificity of immunocapture, providing a more reliable and robust assay (Zhao et al., 2018a). Instead of proteins enrichment with antiprotein antibodies, an alternative approach involves immunocapturing a surrogate peptide of protein drugs using anti-peptide antibodies after enzymatic protein digestion (Anderson et al., 2004). This approach is commonly called, ‘Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA)’ (van den Broek et al., 2015). After adding a stable isotope-labeled surrogate peptide as an internal standard into digested samples, both the labeled and nonlabelled surrogate peptides are captured by a sequence-specific antipeptide antibody, then enriched and separated from biological matrices for LC-MS/MS analysis (Anderson, 2004). Compared to antiprotein immunocapture-LC-MS/MS assays, antipeptide immunocapture-LC-MS/MS assays provide higher sensitivity particularly for LAPs in plasma by minimizing potential interferences (Becker & Hoofnagle, 2012). Considering the labor-extensive immunocapture steps, automated immunocapture platforms are desirable to improve the assay throughput. Several immunocapture platforms are commercially available, including bead-based, cartridge/tip-based, and plate-based platforms (Neubert et al., 2020). Among them, magnetic bead-based platforms are commonly used due to their commercial availability, cost effectiveness, and application flexibility. The selection of platforms suitable for the assay may depend on the sensitivity requirement and availability of reagents. Reversed-phase HPLC (RP-HPLC) plays a central role in the quantitative analysis of protein-based drugs due to its versatility, sensitivity, and compatibility with mass spectrometry. In addition, RP-HPLC has high resolution capability to separate structurally similar proteins and peptides, facilitating its widespread use for protein analysis. Therefore, combination of RP-HPLC with highly selective and sensitive tandem MS allows high-throughput assay for the identification and the quantitation of low-abundance target proteins in complex biological samples (Donato et al., 2012). Various parameters in a workflow should be optimized for efficient LC-MS/MS analysis (Figure 2). Prior to mass analysis, the chromatographic separation should be optimized to provide high resolution, capacity, and fast turnaround time. In addition, various factors affecting MS detection should be optimized to produce highly accurate and reproducible results (Nehete et al., 2013). Some critical factors affecting the chromatographic separation and MS detection are briefly discussed in the following section. In RP-HPLC, proteins or peptides are adsorbed on the hydrophobic surface of the stationary phase (Neverova & Van Eyk, 2005; D’Atri et al., 2020). Owing to the large size of proteins, only a portion of the protein adsorbs to the hydrophobic surface of stationary phase and the greater part of the protein lies above the hydrophobic surface in contact with the mobile phase. When a specific concentration of organic solvent is reached, the protein desorbs from the surface and elutes from the column (Carr, 2016). Given that the separation of proteins via this adsorption and desorption process depends on the extent of interaction with particles packed in a column, the surface characteristics of the packing materials greatly affects the chromatographic separation of the protein samples (Issaq et al., 2003; Wang et al., 2016a). In RP-HPLC, silica particles are widely used as the stationary phase due to their physical robustness, stability, and diversity in pore size and particle diameter (Borges, 2015). Various functional groups are introduced to modify the silica surface to achieve different degrees of hydrophobicity (Corran, 1989). Among them, an octadecylsilyl (ODS) column filled with silica particles chemically bonded with ODS groups is most widely used in RP-HPLC. It is commonly used for the separation of peptides (typically less than 2,000–3,000 Da) after protein digestion. Similarly, silica surfaces with less hydrophobic attachment, including butyl (C4) or phenyl phases, are suitable for the separation of large or hydrophobic peptides (Zhou et al., 1991). The shape, pore size, and diameter of silica particles also affect the resolution in HPLC assays of complex biological mixtures containing proteins. While resolution can be improved by decreasing the particle diameter, the most commonly used particle diameters for analytical RP-HPLC are in the range of 3–5 µm (Aguilar, 2004). The pore size of packing materials is also an important factor to enhance the resolution. Generally, a silica column packed with porous materials having a pore size of ∼ 100 Å results in poor protein separation, since proteins cannot enter small pores (Kirkland et al., 2002). Only after protein digestion, the obtained small peptides can enter the small pores of the silica packing materials and interact with the hydrophobic surface. Therefore, silica columns having porous materials (pore size ≥300 Å) are commonly used for the separation of proteins with better resolution, since the diameter of solute molecules should be at least one-tenth the size of the pore diameter to avoid restricted diffusion of the solute and make the total surface area of the sorbent material accessible (Wei et al., 1997; Carr, 2016). Particles with 6,000–8,000 Å pores with a network of smaller pores of 500–1,000 Å have achieved rapid protein separations (Paliwal et al., 1996). In addition, the purity of the silica particles affects peak separation. Silica particles having metal ion impurities cause peak tailing and poor resolution (Zhang et al., 2014). Similarly, size (volume) and pH of the samples should also be considered in column selection, since they may determine the pore and particle size as well as the types of bonded phases in the column packing materials (Kromidas, 2008; Žuvela et al., 2019; Baghdady & Schug, 2019b). However, the column length does not seem to be critical in the separation of protein samples. Once proteins are desorbed near the top of the column, the interaction of proteins with the hydrophobic stationary phase is minimal as proteins move down the column (Carr, 2002; Fekete et al., 2021). ; Recently, Fekete et al. (2021) reported the utility of ultrashort columns for the high-throughput RPLC analysis of therapeutic proteins. They observed that ultrashort columns of only 5 mm length could separate antibody fragments and antibody-drug conjugates in less than 30 s, providing acceptable performance compared to regular columns (100–150 mm length). This short column has advantages including significantly shorten analysis time and less protein hydrolysis due to lower residence times. The selectivity and resolution of HPLC can be improved by tuning the mobile phase in terms of composition, elution mode, and flow rate (Aguilar, 2004). The mobile phase should make use of the highest purity water, solvents, and buffers to lower the background noise, since limits of detection and quantitation in LC-MS/MS analysis will be compromised by a high level of background noise. Based on eluent strength, viscosity, and polarity, organic solvents such as acetonitrile, methanol, and 2-propanol are commonly used for protein sample analysis (Corran, 1989). In addition to eluotropic effects, the organic solvent also influences the conformational change of proteins, providing an additional effect on the selectivity and the recovery of proteins (Aguilar, 2004). The mobile phase also contains ion-pair reagents such as trifluroacetic acid (TFA), phosphoric acid, and heptafluorobutyric acid, improving the resolution (McCalley, 2005; Dong, 2006). Given that TFA significantly decreases the MS sensitivity due to ion suppression effects during the electrospray process via the formation of ion pairs with analytes, the use of TFA should be minimized in LC-MS/MS analysis or replaced by an alternative (Mallet et al., 2004; Maráková et al., 2020). As an alternative acidic mobile phase additive, difluoroacetic acid (DFA) is promising for the analysis of peptides and proteins, effectively lowering pH to suppress deleterious silanol interactions. While it is a strong ion-pairing agent suitable to improve RPLC separations, it does not decrease MS sensitivity as much as TFA (Maráková et al., 2020). The mode of elution also has a significant impact on the resolution of protein samples. The stoichiometric displacement model (SDM) is an equilibrium model first proposed for RPLC, in which retention of proteins is a function of the number of solvent molecules required to displace a protein from the stationary phase ((Xindu & Regnier, 1984). When the solvating power of mobile phase is strong enough to break the multiple interaction between proteins and the stationary phase, proteins are desorbed and eluted from the stationary phase (Kopaciewicz et al., 1983; Xindu & Regnier, 1984; Regnier, 1987). In general, gradient elution provides higher resolution in the chromatographic separation of protein mixture than isocratic elution. The retention of proteins changes abruptly when the organic solvent reaches the concentration for desorption, providing sharp peaks of the protein analytes (Carr, 2016). Due to the large change in retention with small changes in organic solvent concentration, isocratic elution is seldom used with protein samples. In particular, the adjustment of the gradient slope is essential for optimizing the resolution of protein samples where a lower gradient slope or a slower rate of change in organic solvent concentrations provides better peak separation (Aguilar, 2004). Moreover, the selection and optimization of the gradient conditions primarily depends on the physicochemical characteristics of the target protein analyte. The separation of protein mixtures can be improved by longer gradient elution by increasing the residence time and mass transfer of the solute onto the stationary surface, but it may also accentuate the degree of denaturation (Kumpalume & Ghose, 2003; Burdette & Marcus, 2013). The flow rate should also be optimized to achieve rapid separation and analysis of proteins. In contrast to small molecules, large biomolecules having low diffusivity constants show band broadening with increasing flow rates (mass transfer effect) (Knox & Scott, 1983; Ghosh et al., 2013; Podgornik et al., 2013). At high flow rates, these large molecules cannot travel in and out of porous silica particles as fast as mobile phase elution rate, leading to insufficient time for interacting with the stationary phase and therefore, to broad peaks. Hence, it is necessary to optimize the flow rate of the mobile phase to avoid potential band broadening (Martin & Guiochon, 2005). Temperature plays an important role in optimizing the chromatographic separation of protein samples since it has a profound effect on the viscosity of the mobile phase and the diffusion of the analytes (target proteins). In general, the lower viscosity of the mobile phase and greater solute diffusivity at elevated temperatures result in more symmetrical and narrower peaks, improving the resolution (Zhu et al., 2004). In addition, the reduced viscosity of the mobile phase at elevated temperatures decreases the running time and achieves good efficiency at higher flow rates compared to those at ambient temperature, thereby increasing the speed of assay (Issaq et al., 2003). The conformational structure and the binding of proteins on the hydrophobic surface of the stationary phase can also be manipulated by changing the temperature, thus improving assay selectivity (Lazoura et al., 1997). Overall, temperature affects the chromatographic elution profiles of protein samples, whereby elevated temperatures may improve the selectivity and recovery of large or hydrophobic proteins. However, there should be caution that high temperature can affect the protein stability and cause the conformational change or thermal degradation of proteins (Staub et al., 2011). LC-MS/MS analysis has an inherent uncertainty from each process including extraction, pre-analytical sample treatments, chromatography, and mass detection. To minimize the variations resulting from sample preparation and analytical procedures, structurally related compounds have been used as internal standards (IS). In general, IS are added to the sample at the beginning of the sample preparation and go through the entire process with the target analytes. However, these conventional IS are chemically different from the analytes, thus behaving differently. Therefore, the analytical uncertainty is mitigated by using conventional IS but not fully compensated. Given that isotopic analogues of the analytes are chemically identical to the analytes but have different mass, isotope-labeled IS can mirror the analytes at each stage of the process while they can be distinguished from the analyte by the mass detection (Ciccimaro & Blair, 2010). Accordingly, stable isotope labeled (SIL) standards are employed in quantitative LC-MS/MS analysis, where some atoms of the analyte are replaced by their stable (non-radioactive) isotopes such as deuterium (2H or D), 13 C or 15 N. As with the conventional IS, SIL standards should be added to the sample at the beginning of the procedure. Since SIL standards are uniquely matched to their corresponding analytes, an individual SIL standard is required for the quantification of each analyte in a multi-analytes LC-MS/MS (Zhou et al., 2017). Several critical factors should be considered for the selection and use of a SIL standard for LC/MS-MS analysis, including stability of the label, optimal mass difference between the analyte and IS, isotopic purity, and molecular sites of the isotopic labels (Nasiri et al., 2021). For example, chemical exchange of deuterium with protons from solvent or matrix components results in the loss of labeled IS, and thus isotope labeling should be positioned on non-exchangeable sites. In addition, if a molecular fragment is detected in MS analysis, the isotope labels should be positioned on the fragment of interest. A mass difference between the analyte and the SIL standard should be also suitable for avoiding the overlap of spectral lines (Jenkins et al., 2015). Isotopic purity is also important. SIL standard should be free of unlabeled species, where unlabeled molecule is undetectable or at a level not to cause interference. In recent years, SIL analogues of target proteins are widely accepted as the optimal IS for accurate quantification of proteins using LC-MS/MS analysis (Faria & Halquist, 2018). Since a SIL protein exhibits the similar physiochemical behavior to the target analyte, the addition of a SIL-protein IS at the beginning of the sample preparation can control the variations in extraction, enzymatic digestion, LC, and MS detection, thereby increasing the accuracy and precision of the quantitative assay. Regulatory guideline also recommends the use of a SIL-protein IS in quantitative LC-MS/MS analysis (Kaza et al., 2019). The multiple reaction monitoring (MRM) technique using a triple quadrupole (Q) mass spectrometer is the most popular for the quantitative analysis of protein drugs in complex biological matrices. In a triple Q mass spectrometer using the MRM mode, a precursor ion of interest is first selected in the first mass analyzer (Q1) based on its accurate mass (Pan et al., 2009). Then, the pre-selected precursor ion is transmitted and fragmented in a collision cell, producing a range of daughter ions. One (or more) of these resulting daughter ions are selected and mass analyzed in a second mass analyzer (Q3). In the MRM mode, monitoring more than one MS-MS transition for each target species allows the detection of multiple components in a single LC-MS/MS run (Cohen Freue & Borchers, 2012). As a result, multiple proteins can also be quantified in a single run, depending on the MS instrument, the numbers of transitions monitored for each peptide, and the number of peptides monitored for each protein (Pan et al., 2009). To establish the optimal MRM condition for high accuracy and specificity, there are some important factors to be considered. Protein quantification is often based on the digestion of proteins of interest and subsequently measuring one or more surrogate peptides. In this case, the selection of the appropriate signature peptide as a surrogate analyte is important (Rauh, 2012). Peptides under electrospray conditions may present various ionized patterns depending on their size and structure. Based on MS responses from ionized peptides, a signature peptide with the highest MS response is selected and the transition-dependent MRM conditions such as source voltages and collision energy should be optimized (Ewles & Goodwin, 2011). The selected signature peptide should have high specificity and be efficiently ionized. Furthermore, it should be a suitable surrogate for the target protein of interest. The preferred length of signature proteins is ∼10–20 amino acid residues (Rauh, 2012). It is recommended to monitor at least three peptides for each target protein to enhance assay specificity and decrease interference from other plasma proteins (Unwin et al., 2005; Rauh, 2012). Although digestion-based methods are successful and widely utilized, it should also be noted that a surrogate peptide may represent only a small percentage of the total protein (van de Merbel, 2019). Consequently, quantification of intact proteins is increasingly being used in LC-MS/MS assay. In addition to MRM, parallel reaction monitoring (PRM) mode has been reported in recent years, which provides high resolution and full scan MS/MS data (Bourmaud et al., 2016; Zhou et al., 2016; Kisiala et al., 2019). It allows for the highly specific extraction of signals for target peptides of interest, thereby restricting the interference from isobaric contaminants (Shi et al., 2012a; Liebler & Zimmerman, 2013). Ionization is a critical step in MS-based protein analysis. Various ionization techniques are available, electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and matrix-assisted laser distortion ionization (MALDI) (Awad et al., 2015; Sedláčková et al., 2022). Among them, ESI has been widely used for protein analysis. It is performed in solution, where (i) the sample is sprayed into the MS, (ii) as the droplets evaporate, electrical charges are transferred to molecules present in the droplet and multiple, charged ions are produced, and (iii) the mass analyzers generate complex ESI spectra (Kebarle & Verkerk, 2009). The flow rate of ESI is an important factor for improving the ionization of analytes and the relatively fast flow rates of conventional ESI (>100 µL/min) can limit the effective ionization of target analytes. To overcome this issue, nano-ESI devices have been developed, operating at very low flow rates (10–100 nL/min) and reducing ionization suppression effects (Schmidt et al., 2003; Tang et al., 2004). Furthermore, advancement in ionization devices using single- or dual-stage ion guides, ion funnels, and ion funnel trap devices improves ion transmission in the atmospheric pressure/vacuum interface (Kelly et al., 2010; Belov et al., 2011; Hossain et al., 2011). A triple quadrupole mass spectrometer provides a wide dynamic range (>105), high sensitivity, and low measurement variation in MRM (Liebler & Zimmerman, 2013). However, it results in a relatively low resolution of precursor m/z measurements, which may be due to interference from nominally isobaric background contaminants in complex mixtures (Liebler & Zimmerman, 2013). In addition to a triple quadrupole mass spectrometer, the quadrupole-time-of-flight (QqTOF) instrument can be used for quantifying proteins. While a mass-resolving quadrupole (Q1) and a collision cell are similar to a triple quadrupole, the third quadrupole (Q3) is replaced by a TOF mass analyzer, improving the sensitivity, accuracy, and mass resolution for both precursor and product ion spectra (Steen et al., 2001). In particular, Q-TOF-based, high-resolution mass spectrometry (HRMS) is a promising approach to improve accuracy and mass resolution (van Dongen & Niessen, 2012). The main advantage of HRMS is its ability to separately detect the responses of molecules having very close molecular masses, thereby providing a more selective detection of a surrogate peptide. Since a Q-TOF-based HRMS system narrows the mass extraction window to a much lower extent than a triple quadrupole, most of the ions of a surrogate peptide can be detected while a major part of the interference from digested plasma proteins is no longer selected for detection (van de Merbel, 2019). It can also measure highly charged intact proteins (Furlong et al., 2012). In recent years, HRMS using Orbitrap mass analyzer is available as another powerful tool for quantitative analysis of proteins and peptides. Orbitrap mass analyzer consists of a spindle-like central electrode and two outer electrodes, trapping of ions in electrostatic fields (Zubarev & Makarov, 2013). With voltage applied between the central and outer electrodes, injected ions oscillate harmonically along the central electrode and the differential image-current is detected by the outer electrodes, Fourier-transformed into the frequency domain, and then converted into a mass spectrum (Zubarev & Makarov, 2013). The resolution is dependent on the number of harmonic oscillations detected. Similarly to Q-TOF, most of Orbitrap analyzers are employed in hybrid (combining a quadrupole analyzer with Orbitrap (Q-Orbitrap)) rather than stand-alone configuration. With continuous technical improvement, Orbitrap-based HRMS becomes more powerful analytical platform, providing high resolution, mass accuracy, and excellent sensitivity in various analytical application. The inclusion of an additional separation step after chromatographic retention or mass selection can also improve the selectivity of MS detection (van den Broek et al., 2013). Various approaches, including high field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS) have been applied for ion mobility differentiation, reducing interference in the LC-MS/MS analysis of proteins (Kanu et al., 2008; Xia et al., 2008; Klaassen et al., 2009). However, FAIMS and DMS have relatively long residence times and may result in broader and lower peaks due to potential loss of analytes (Xia et al., 2008). Complex biological matrices such as plasma and urine cause many difficulties in developing efficient quantitative assays for protein drugs. This review covers various approaches to overcome multiple issues in protein assays, with emphasis on sample preparation and quantitation by LC-MS/MS. Although various analytical methods are available for quantifying protein drugs in biofluids, there is no ideal or universal method that is applicable to a diverse range of therapeutic proteins or to all circumstances. Each method has its own advantages and disadvantages. In general, the choice of method is based on the compatibility of the analytical method with the analyte of interest and on potential interfering substances included in the samples. It is also important to select a method that requires the least manipulation or pretreatment of the samples to reduce the interference from co-existing substances. Additional criteria for the selection of method include assay range, required sample volume, turnaround time, and throughput. In recent years, LC-MS/MS analysis has become the method of choice for the detection, identification, and quantitation of proteins in complex biological matrices. The accuracy, sensitivity, and flexibility of MS instruments facilitate the wide application of LC-MS/MS in the pharmaceutical development of protein drugs. Given that the quality and reproducibility of sample preparation significantly affect MS detection, proper sample preparation is a critical step in LC-MS/MS. Clean samples with limited sample complexity can minimize the suppression of ionization by high-abundance species, improving the selectivity and mass resolution. Furthermore, protein assays tend to move from indirect quantification of a surrogate peptide after protein digestion to direct analysis of the intact protein analyte, promoting the development of materials with improved separation properties for proteins. Therefore, sample preparation, chromatographic separation, and mass detection should be properly integrated into robust workflows for LC-MS/MS analysis. In recent years, instruments have become highly advanced, automated, and equipped with high-end information technology, allowing high-throughput, automated sample analysis, data processing, and storage. User-friendly software is also desirable for robust deconvolution of highly complex mass spectra. Continuous advancement in analytical instruments, devices, and software with other complementary technologies will further improve the bioanalytical performance, complete system integration, and automation, while reducing the workload.

PMC10003148

Nina S. Levy,Veronika Borisov,Orit Lache,Andrew P. Levy

Molecular Insights into IQSEC2 Disease

05-03-2023

IQSEC2,Arf6-GTP,heat shock

Recent insights into IQSEC2 disease are summarized in this review as follows: (1) Exome sequencing of IQSEC2 patient DNA has led to the identification of numerous missense mutations that delineate at least six and possibly seven essential functional domains present in the IQSEC2 gene. (2) Experiments using IQSEC2 transgenic and knockout (KO) mouse models have recapitulated the presence of autistic-like behavior and epileptic seizures in affected animals; however, seizure severity and etiology appear to vary considerably between models. (3) Studies in IQSEC2 KO mice reveal that IQSEC2 is involved in inhibitory as well as stimulatory neurotransmission. The overall picture appears to be that mutated or absent IQSEC2 arrests neuronal development, resulting in immature neuronal networks. Subsequent maturation is aberrant, leading to increased inhibition and reduced neuronal transmission. (4) The levels of Arf6-GTP remain constitutively high in IQSEC2 knockout mice despite the absence of IQSEC2 protein, indicating impaired regulation of the Arf6 guanine nucleotide exchange cycle. (5) A new therapy that has been shown to reduce the seizure burden for the IQSEC2 A350V mutation is heat treatment. Induction of the heat shock response may be responsible for this therapeutic effect.

Molecular Insights into IQSEC2 Disease Recent insights into IQSEC2 disease are summarized in this review as follows: (1) Exome sequencing of IQSEC2 patient DNA has led to the identification of numerous missense mutations that delineate at least six and possibly seven essential functional domains present in the IQSEC2 gene. (2) Experiments using IQSEC2 transgenic and knockout (KO) mouse models have recapitulated the presence of autistic-like behavior and epileptic seizures in affected animals; however, seizure severity and etiology appear to vary considerably between models. (3) Studies in IQSEC2 KO mice reveal that IQSEC2 is involved in inhibitory as well as stimulatory neurotransmission. The overall picture appears to be that mutated or absent IQSEC2 arrests neuronal development, resulting in immature neuronal networks. Subsequent maturation is aberrant, leading to increased inhibition and reduced neuronal transmission. (4) The levels of Arf6-GTP remain constitutively high in IQSEC2 knockout mice despite the absence of IQSEC2 protein, indicating impaired regulation of the Arf6 guanine nucleotide exchange cycle. (5) A new therapy that has been shown to reduce the seizure burden for the IQSEC2 A350V mutation is heat treatment. Induction of the heat shock response may be responsible for this therapeutic effect. IQSEC2 is an X-linked gene that is associated with intellectual disability, autism, and epilepsy [1]. Mutations in IQSEC2 account for approximately 2% of patients with ID and epilepsy referred for exome sequencing [2]. Treatment for these patients is lacking and seizure control is difficult to attain. With the advent of new animal and cellular models for studying the disease, new insights have been gained into the normal function of IQSEC2 and the pathways that may be aberrant in its absence or when its function is altered. In addition, a number of therapeutic strategies have been described. This review will summarize new developments in IQSEC2 research and treatment and discuss promising future directions. IQSEC2 is a member of a subfamily of homologous proteins (IQSEC1, IQSEC2, and IQSEC3) known as guanine nucleotide exchange factors, or GEFs. These GEFs exchange GTP for GDP on another family of proteins known as small GTPases or small G proteins (see Um et al. [3], Petersen et al. [4], and D’Souza and Casanova [5] for review). The IQSEC proteins are GEFs for the six-member Arf family of small G proteins Arf1-6. The Arfs were first identified as a cellular activity required for ADP-ribosylation of Gαs by cholera toxin, a process by which it exerts its toxic effect. Much of the current research on Arfs is not related to ADP-ribosylation. Rather, these small G proteins are best known for participating in membrane trafficking, lipid transformation, and reorganization of the actin cytoskeleton. IQSEC2 is thought to interact most specifically with Arf6 [6], which is the only Arf that regulates the recycling of endosomes and receptors to and from the plasma membrane. The role of IQSEC2 at excitatory synapses has been the focus of numerous studies. The combined work of a number of laboratories supports the following mechanism of action for IQSEC2 [7,8,9,10]: Glutamate release from presynaptic neurons leads to NMDA receptor activation and the influx of calcium ions in postsynaptic neurons. NMDA receptors are also complexed to PSD95 and are therefore in close proximity to IQSEC2. Calcium binds to calmodulin present on the IQ domain of IQSEC2, leading to its dissociation from IQSEC2 and to activation of the GEF catalytic Sec7 domain of IQSEC2. Arf6-GDP undergoes the exchange of GDP for GTP by the Sec7 domain of IQSEC2, thereby leading to the activation of Arf6. Arf6-GTP mediates the activation of downstream effectors such as phospholipase D, phosphatidylinositol-4-phosphate 5-kinases, and Ras-related C3 botulinum toxin substrate 1 (Rac1), leading to changes in membrane trafficking and actin dynamics. Arf6-GTP is inactivated by a GTPase-activating protein (GAP). Myers et al. [9] showed that both active IQSEC2 and JNK activity are required for the downstream removal of AMPA receptors in hippocampal neurons following excitatory stimulation. Ultimately, IQSEC2 is responsible for promoting the growth and development of dendritic spines, axonal elongation, and branching in postsynaptic neurons, all necessary for the proper development of cognition and learning [11]. IQSEC2 is a 1488 amino acid protein containing 6 known functional domains (see Figure 1). These include: (1) an N terminal coiled-coil (CC) domain that mediates protein self-association; (2) an IQ-like domain that binds apo-calmodulin and allosterically influences the Sec7 domain; (3) a Sec 7 domain responsible for GDP–GTP exchange on Arf6; (4) a pleckstrin homology (PH) domain which is thought to be involved in IP3 signaling and localization to the plasma membrane; (5) a proline-rich (PR) domain which is known to bind to the insulin receptor tyrosine kinase substrate of 53 kD (IRsp53), recently shown to control plasma membrane shape [12] and may be involved in dendrite formation; and (6) a PDZ domain which mediates binding to PSD95, an important member of the postsynaptic density responsible for anchoring proteins to the cytoskeleton and mediating signal transduction following excitatory stimulation. Since the discovery of IQSEC2 disease [1], over 120 new mutations have been reported in IQSEC2 patients (see Tables S1 and S2) [13,14,15,16,17]. The majority of cases are null mutations, in which the gene has been deleted or a nonsense codon has been created due to a point mutation or a frameshift mutation. Nonsense mutations generally result in mRNA decay or a truncated protein that is rapidly degraded. However, 37 independent missense mutations have been reported which are concentrated in multiple functional domains present in IQSEC2 (see Figure 1 and Table S1). The majority of missense mutations fall within four functional domains (CC, IQ, Sec7, and PH). Two additional binding domains are certain to be critical (PR and PDZ) as well, but no missense mutations have been reported in these areas as they are quite small (4 and 10 aa respectively). However, their importance may be seen in the case of a missense mutation, R1402T [18], that falls quite close to the PR domain and may affect the binding of IRsp53. One other alteration at aa 1468 and two at aa 1474 create frameshift mutations that terminate after 27, 21, and 133 aa respectively, resulting in the specific abrogation of the PDZ domain. In addition, new documented mutations in IQSEC2 reveal a cluster of four single nucleotide changes just C-terminal to the PH domain, in an area that has not been categorized to date. This may represent a new functional domain that is yet to be characterized. Interestingly, IQSEC1 and IQSEC3 have a second CC domain in this region [3]. Although the homology for the CC domain is not conserved in IQSEC2, this area may contain some common secondary structure of importance in all three family members. Three additional mutations, S257N, R563Q, and D706S, do not fall in any defined domain. These mutations may disrupt intra-protein folding involved in the allosteric effect of the IQ domain on the Sec7 domain. In vitro expression of these mutations might shed light on this possibility. In summary, IQSEC2 appears to contain six or possibly seven functional domains which are absolutely required for normal development and are likely to be involved in multiple protein–protein or protein–membrane interactions. Frank et al. [20] have shown that PSD95 (along with IQSEC2) is found in 1.5 MDa complexes in the mouse forebrain. Most of the work on IQSEC2 has been focused on its physical association with the NMDA receptor. However, the vast majority (97%) of IQSEC2 is not found in complexes with NMDA receptors, indicating that we have only scratched the surface regarding the scope of IQSEC2 interactions [20]. Four mouse models of IQSEC2 disease have been studied. Three are independent knockout (KO) models and one is a transgenic A350V mutation model. The mice used by Mehta et al. [21] were created by introducing a 17 bp deletion into exon 3 of the IQSEC2 gene and the KO mice were maintained on a C57BL6/JJcl and 129+Ter/ScJcl hybrid background. The model used by Sah et al. [22] introduced a single nucleotide deletion and translational frameshift in IQSEC2 exon 7 and the mice were maintained on a mixed C3HeB/FeJ and C57BL/6NJ background. Jackson et al. [23] generated a KO strain which deleted exon 3 and the mice were maintained on a C57BL/6N-Hsd background. All of the KO models resulted in the generation of a premature stop codon with no detectable IQSEC2 protein expression. The A350V transgenic mouse strain [10] was created using CRISPR/Cas9 targeting of the murine wild-type IQSEC2 gene generating an A350V mutation identical to that found in the human index case in which the codon GCT (Ala) at amino acid 350 is mutated to GTT (Val) with an additional AGG to CGT silent mutation (R349). The mutant mice were maintained on a C57Bl/6J background. Mutant A350V protein was found to be expressed in the brain by Western blot analysis (see supplementary Figure S1). All of the models exhibited decreased fertility, hyperactivity, defects in social interactions, and abnormalities in the electrophysiology of isolated neurons (see discussion below). Anxiety was found in two of the KO models [22,23]. Cognitive function was looked at in two models [10,23] and found to be somewhat decreased although this parameter was not studied in depth. Three of the models looked at seizure activity [10,22,23]. The timing and severity of the seizures varied considerably between models. Sah et al. [22] reported that the susceptibility of the KO mice to induced seizures was suppressed and the KO mice were observed to have seizures only on long-term video. However, a post-mortem examination showed evidence of lethal seizures and mortality was 100% in males by approximately 6 months of age. Jackson et al. [23] reported that KO males and heterozygous females had spontaneous seizures (52% and 46%, respectively) beginning on days 29 and 23 after birth, respectively. Mortality was 20% in males and 31% in females. In the A350V model, male mice suffered spontaneous lethal seizures between days 16–20 after birth [24]. Mortality was 43% for males and 20% for females. The variability seen in seizure activity among all of these studies may be due to differences in seizure thresholds of the different genetic strains used or to differences in mutations (KO versus missense). Although IQSEC2 does not escape X chromosome inactivation in mice, the mechanisms governing inactivation can differ between strains, making it difficult to compare results. It may be that finding appropriate drugs to treat IQSEC2-related epilepsy will require personalized systems such as iPSC cells. With regard to therapeutic treatments, Mehta et al. [21] were able to reverse electrophysiological and behavioral deficits by infecting medial prefrontal cortex (mPFC) neurons in IQSEC2 KO mice with an adeno-associated virus (AAV) vector encoding IQSEC2 under the control of the EF1alpha short (EFS) promoter. The social discrimination deficits seen in the A350V mice were rescued with a single dose of PF-4778574, a positive AMPAR modulator [25]. Seizure activity, electrophysiology, and social deficits in the A350V mice were rescued with heat treatment, as will be discussed below [26]. Looking at the clinical data in general, it can be seen that the disease is more severe in males than females [17]. This is logical considering that IQSEC2 is known to escape X inactivation in humans, and therefore female carriers can benefit from one normal IQSEC2 allele. Paradoxically, the levels of IQSEC2 are regulated in females such that overall the levels of IQSEC2 are approximately the same in both sexes [27]. Another report showed that IQSEC2 is expressed at higher levels in males than in females in the brain cortex [28]. The reason for this discrepancy is not clear; however, it seems clear that the level of IQSEC2 is tightly regulated, at least in females. Differences in this regulatory mechanism among individuals may explain why related females heterozygous for the same mutation have differing severity of the disease [17]. Evidence that reduced levels of IQSEC2 are detrimental comes from a study by Madrigal et al. [29], who reported on a family with a splice site mutation in IQSEC2. The percent of aberrant splicing among family members correlated with the severity of the disease, supporting the tenet that disease status is determined by the degree to which IQSEC2 levels are diminished. In vitro studies using inhibitory RNA have shown that a reduction in IQSEC2 leads to abnormalities such as disturbed growth and morphology of developing neurons in cell culture [11] and constitutively activated ARF6-GTP in neuronal cultures [8]. However, the pathogenicity of increased levels of IQSEC2 is less clear. Microduplications in patients with intellectual disability have been found which encompass three disease genes, TSPYL2, KDM5C, and IQSEC2 [27]. These patients’ symptoms may be due to increased IQSEC2, although the contribution of increased IQSEC2 alone is difficult to determine from this study. Myers et al. [9] overexpressed mCherry-tagged IQSEC2 in rat hippocampal slices and showed that the fusion proteins localized to excitatory synapses, similar to endogenous IQSEC2. Brown et al. [7] showed that overexpressing wild-type IQSEC2 in neurons leads to increased neural transmission. Hinze et al. [11] reported that overexpressing wild-type IQSEC2 in IQSEC2 KO neurons altered dendrite and spine morphology compared to wild-type cells. The last two studies suggest that overexpression of IQSEC2 could be harmful; however, there was no quantitation of the levels of IQSEC2 induced in these experiments, making it difficult to know the characteristics of the dose–response curve. Interestingly, as noted above, Mehta et al. [21] used gene therapy to reverse social and electrophysiological deficits in IQSEC2 KO mice. Although quantitation of IQSEC2 expression in treated KO animals was not reported, the authors did investigate the effect of gene therapy in WT animals. These studies showed that overexpression of IQSEC2 in the mPFC of wild-type animals did not affect social behaviors. In summary, it may be that a threshold level of IQSEC2 is required for normal development, below which defects may occur. However, moderately increased levels may be well tolerated. Transgenic mice containing several copies of the IQSEC2 gene under inducible control might shed light on this question, which has important implications for the potential use of AAV vectors for human gene therapy. Although expressed throughout the brain, the highest levels of IQSEC2 have been found in the hippocampus, with expression previously thought to be restricted to the postsynaptic density of excitatory neurons [6]. Prior reports of IQSEC2 electrophysiological function measured excitatory currents in wild-type hippocampal neurons transfected with different IQSEC2 variants, resulting in the overall mechanism of action described above. IQSEC3, another neuron-specific member of the IQSEC family, was reported to be associated with gephyrin [3], a molecule exclusively present in inhibitory neurons. Transfection experiments designed to increase or decrease the expression of IQSEC3 resulted in greater or lesser inhibitory transmission, respectively. This led to the presumption that IQSEC2 is mainly involved in mediating excitatory signaling while IQSEC3 is involved in mediating inhibitory transmission. Reports using the IQSEC2 KO mouse models paint a new picture. Mehta et al. [21] have shown that both excitatory as well as inhibitory synaptic transmissions are impaired in their knockout (KO) model of IQSEC2. Patch clamp recordings were performed on brain slices containing pyramidal neurons in layer 5 of the mPFC in P14–P19 day-old mice. The researchers found that the frequency, but not amplitude, of miniature excitatory (mEPSCs) and inhibitory (mIPSCs) postsynaptic currents were significantly decreased in IQSEC2 KO mice. In addition, it was found that both excitatory (AMPA and NMDA) and inhibitory (GABA) currents were decreased in response to evoked changes in the membrane potential of neurons from IQSEC2 KO mice. The study by Sah et al. [22] also reveals a role for IQSEC2 as an important modulator of inhibitory neurotransmission. This group measured synaptic transmission in dissociated KO hippocampal neurons from P1–P2 day-old mice after 12 days in culture. The authors transfected the cultured neurons with an AAV expressing an enhanced green fluorescent protein driven by a calcium/calmodulin-dependent kinase II promoter (which is preferentially expressed in glutamatergic neurons) to distinguish between excitatory and inhibitory neurons. In contrast to the above study, there was no difference in mEPSC frequency or amplitude in KO glutamatergic neurons compared to wild-type neurons. However, there were significant increases in mEPSC frequency and amplitude in KO GABAergic neurons compared to wild-type neurons. There were no genotype-dependent differences in mIPSCs in glutamatergic or GABAergic neurons. When looking at evoked responses, the researchers similarly found increased EPSCs in the KO GABAergic neurons compared to WT neurons, but no genotype-dependent differences in evoked IPSCs in GABAergic or glutamatergic neurons. In summary, the authors found a specific increase in excitatory synaptic transmission onto inhibitory interneurons. Sah et al. [22] also demonstrated that multiple intrinsic properties of KO interneurons, but not glutamatergic neurons, were altered compared to wild-type, suggesting a neuron-specific role for IQSEC2 in development. The KO mice were shown to have increased numbers of PV-positive cells in the hippocampus. In addition, interneurons from wild-type mice were shown to highly express IQSEC2. This is the first report of IQSEC2 expression in inhibitory cells and further supports the role of IQSEC2 in inhibitory transmission. Using differentiated iPSC cells developed from a child carrying the A350V mutation, Brant et al. [30] showed that immature IQSEC2 mutant dentate gyrus granule neurons were extremely hyperexcitable, exhibiting increased sodium and potassium currents compared to those of CRISPR-Cas9-corrected isogenic controls. Immature IQSEC2 mutant cultured neurons exhibited a marked reduction in the number of inhibitory neurons, which contributed further to hyperexcitability. As the mutant neurons aged, they became hypoexcitable, exhibiting reduced sodium and potassium currents and a reduction in the rate of synaptic and network activity. Jackson et al. [23] also studied the electrophysiological characteristics of neurons from IQSEC2 KO heterozygous females using a microelectrode array. Their results showed that embryonic day 17.5 cultured cortical neurons exhibit hallmarks of immature synaptic networks when compared with their respective wild-type control littermates. These results are similar to those seen in immature A350V differentiated iPSC cells. It is interesting to note that the more mature A350V neurons are more similar to those in the Mehta et al. [21] study, which looked at neurons from older mice (days 14–19). These results point to the additional variable of cellular differentiation that could be a source of discrepancies seen between studies. A novel finding of the studies described above is that loss of IQSEC2 is shown to affect inhibitory neuronal cell transmission, albeit in opposite directions. Mehta et al. [21], who did not differentiate between excitatory and inhibitory cells, found a decrease in inhibitory as well as stimulatory postsynaptic activity in their KO model, while Sah et al. [22] found an increase only in stimulatory activity in GABAergic neurons. The reason(s) for these differences are not clear; however, the conditions used in the two papers vary in a number of ways, including the use of different IQSEC2 KO mouse models, different types of neurons tested, and different culture conditions. Further studies will be needed to fully understand this newly discovered role of IQSEC2 in inhibitory neurotransmission. Shoubridge et al. [1] showed that three mutations in the Sec7 domain of IQSEC2 and one mutation in the IQ region resulted in a decrease in the levels of Arf6-GTP when assayed in a GGA3 pull-down assay of extracts from HEK-293 cells transiently transfected with the mutated genes and Arf6 (see Table 1). Another mutation in the Sec7 domain, A789V, was also shown to result in decreased Arf6-GTP levels [31]. Conversely, in a paper by Rogers et al. [10] the A350V mutant was found to result in increased Arf6-GTP levels. Two other mutations at the same site, A350D and A350T, were also shown to lead to increased Arf6-GTP [32]. Ongoing studies are directed toward understanding how allosteric regulation of the Sec7 domain by the IQ region can explain the unusual effect of the A350 mutants on Arf6-GTP levels in HEK293T cells. More recent studies using the IQSEC2 mouse KO model reported the paradoxical finding that Arf6-GTP levels are increased in KO brains, despite the absence of IQSEC2 protein [23]. Elevated levels of Arf6-GTP were also seen in wild-type neurons by RNAi-mediated depletion of postsynaptic IQSEC2 (see Table 1) [33]. These studies were conducted in conjunction with cortical neuron cultures and synaptoneurosomes from Fragile X mental retardation protein 1 (FMR1) KO mice. IQSEC2 and Fragile X chromosome disease both cause intellectual disability, developmental delay, and autism. The FMR1 protein normally binds to multiple RNAs, including IQSEC2, and causes an increase specifically in large transcripts such as IQSEC2. In its absence, the levels of IQSEC2 are greatly reduced [34]. Cultured neurons from FMR1 KO mice also displayed increased Arf6-GTP levels [33]. It can be seen from Table 1 that neuronal cell environments in which IQSEC2 is low or absent result in high levels of ARF6-GTP. This situation occurs naturally in immature neurons and can be induced by knocking down the expression of IQSEC2 in mature neurons [8]. The mechanism for this phenomenon is not clear; however, the activation of other GEFs or the inhibition of certain GAPs is likely to be involved. It is interesting to note that elevated levels of activated Arf6 have been reported to exist in a number of dysfunctional situations such as cancer cells. Pharmacological inhibition of guanine nucleotide exchange on Arf6 using SencinH3 or NAV2729 has been used successfully to reduce levels of activated Arf6-GTP in cancer cells and could be a potential therapy for IQSEC2 disease [35]. A child carrying the A350V mutation was observed to have few to no seizures for several weeks after experiencing a high fever. In an attempt to recreate the effect of fever, we placed a child with the A350V mutation in a 40 °C Jacuzzi bath twice daily for 15 min. We found that heat treatments significantly reduced seizures and partially normalized the baseline EEG [36]. This therapeutic effect was recapitulated in a transgenic mouse model of the A350V mutation. It was previously shown that approximately 45% of A350V male mice die between days 16 and 20 after birth due to lethal seizures. Mice incubated at 37 °C starting on day 15 after birth for 5 continuous days showed reduced mortality of 2% [26]. In addition, 2-month-old mutant male mice were shown to be defective in making ultrasonic vocalizations when exposed to wild-type female mice. Mutant mice that received heat treatment on days 15–19 were tested for vocalization capability at two months of age and found to perform at the same level as wild-type mice that had undergone heat treatment [26]. As mentioned above, HEK293 cells carrying the A350V mutation show increased Arf6-GTP levels. We found that heat treatment at 40 °C resulted in a significant and rapid 50% reduction in Arf6-GTP with no change in total Arf6. This effect was seen for A350D and A350T mutants as well as wild-type IQSEC2 (abstract). We have shown previously that the increase in Arf6-GTP due to the A350V mutation is associated with a reduction in surface expression of AMPA receptors and abnormal spontaneous synaptic transmission in A350V neurons [10]. We found that heat shock (40 °C for 1 h) of A350V murine hippocampal neurons increased surface AMPAR and spontaneous AMPA-dependent EPSCs compared to that seen in WT hippocampal neurons [32]. The mechanism of action of heat therapy in this model may be the activation of the heat shock response (HSR). Hsp90, a major protein induced by the HSR, is known to influence small GTPases such as Ras which could act to reduce the levels of Arf6-GTP [37]. We were able to reproduce the benefit of heat therapy on seizure protection in the A350V transgenic mouse model using celastrol, a chemical inducer of the heat shock response (HSR) [32]. Celastrol reduced the incidence of lethal seizures from 45% to 19%. By contrast, triptolide, an inhibitor of the HSR, abrogated the protective effect of heat treatment, increasing the incidence of lethal seizures in mice receiving heat treatment from 2% to 42% in mice receiving heat treatment and triptolide [32]. These studies point to modulators of the HSR as potential therapeutic agents. Interestingly, communication with parents of IQSEC2 children via an IQSEC2 Facebook group indicates that the phenomenon of fever benefit is apparent in other children carrying different IQSEC2 mutations. Jacuzzi treatments have also been reported to be beneficial in some of these children (personal communication). These reports indicate that heat therapy and/or the induction of the HSR may be applicable to IQSEC2 disease in general. Further studies in this area are needed to work out the details of this mechanism and whether this therapy may be extended to other IQSEC2 mutations. Recent developments in IQSEC2 research include a new role for IQSEC2 in inhibitory neural transmission, the finding that high Arf6-GTP is correlated with the disease, and that heat therapy can reduce seizures and social deficits in children suffering from a mutation in IQSEC2. These findings allow for the development of new therapies for IQSEC2. As mentioned above, Mehta et al. [21] showed for the first time that injection of an AAV carrying the IQSEC2 gene under the control of the EFS promoter into the brain (mPFC) can restore electrophysiological function as well as social ability in KO IQSEC2 mice. This result is encouraging in light of recent FDA-approved AAV gene therapy protocols [38]. More studies using AAV vectors encoding IQSEC2 are needed to substantiate this mode of treatment. It should be noted that some missense mutations may produce a gain of function proteins, as in the case of A350V, which may need to be knocked down in order for gene therapy to succeed. The testing of small molecules that might benefit IQSEC2 disease has yielded encouraging results [25]. However, continued testing of compounds such as HSR stimulators, GEF inhibitors, and electrophysiological modulators would greatly benefit from a high throughput platform. Several new ideas for IQSEC2 models have emerged for this purpose. These include an IQEC2 KO zebrafish [39] and/or a Xenopus model [40], in which drugs may be tested by dissolving them in the water used to grow the fish and/or tadpoles and tracking them by videography for seizure activity. IQSEC2 is highly conserved in both species and expressed at high levels in the brain. Microelectrode arrays might also be used for screening drugs which might rescue electrophysiological defects seen in KO neurons. Large libraries of FDA-approved small molecules might be tested in this manner. These new directions provide much-needed hope for the future of individuals suffering from IQSEC2 disease.

PMC10003149

Antonella Galeone,Maria Grano,Giacomina Brunetti

Tumor Necrosis Factor Family Members and Myocardial Ischemia-Reperfusion Injury: State of the Art and Therapeutic Implications

27-02-2023

tumor necrosis factor family,myocardial ischemia-reperfusion injury,myocardial infarction

Ischemic heart disease is the principal cause of death worldwide and clinically manifests as myocardial infarction (MI), stable angina, and ischemic cardiomyopathy. Myocardial infarction is defined as an irreversible injury due to severe and prolonged myocardial ischemia inducing myocardial cell death. Revascularization is helpful in reducing loss of contractile myocardium and improving clinical outcome. Reperfusion rescues myocardium from cell death but also induces an additional injury called ischemia-reperfusion injury. Multiple mechanisms are involved in ischemia-reperfusion injury, such as oxidative stress, intracellular calcium overload, apoptosis, necroptosis, pyroptosis, and inflammation. Various members of the tumor necrosis factor family play a key role in myocardial ischemia-reperfusion injury. In this article, the role of TNFα, CD95L/CD95, TRAIL, and the RANK/RANKL/OPG axis in the regulation of myocardial tissue damage is reviewed together with their potential use as a therapeutic target.

Tumor Necrosis Factor Family Members and Myocardial Ischemia-Reperfusion Injury: State of the Art and Therapeutic Implications Ischemic heart disease is the principal cause of death worldwide and clinically manifests as myocardial infarction (MI), stable angina, and ischemic cardiomyopathy. Myocardial infarction is defined as an irreversible injury due to severe and prolonged myocardial ischemia inducing myocardial cell death. Revascularization is helpful in reducing loss of contractile myocardium and improving clinical outcome. Reperfusion rescues myocardium from cell death but also induces an additional injury called ischemia-reperfusion injury. Multiple mechanisms are involved in ischemia-reperfusion injury, such as oxidative stress, intracellular calcium overload, apoptosis, necroptosis, pyroptosis, and inflammation. Various members of the tumor necrosis factor family play a key role in myocardial ischemia-reperfusion injury. In this article, the role of TNFα, CD95L/CD95, TRAIL, and the RANK/RANKL/OPG axis in the regulation of myocardial tissue damage is reviewed together with their potential use as a therapeutic target. Ischemic heart disease is the principal cause of death worldwide and clinically manifests as myocardial infarction (MI), stable angina, and ischemic cardiomyopathy [1]. Myocardial ischemia is usually due to coronary atherosclerosis and occurs when coronary blood flow is reduced because of the occlusion of a coronary artery or a deleterious redistribution of blood flow away from a given vascular territory [2]. Myocardial infarction is defined as an irreversible injury due to severe and prolonged myocardial ischemia inducing myocardial cell death. Type 1 MI is caused by atherothrombotic coronary artery disease and is consequent to the erosion or rupture of an epicardial coronary artery atherosclerotic plaque, followed by thrombosis and occlusion of the coronary artery. Myocardial injury caused by a mismatch between oxygen supply and demand and not by acute atherothrombotic plaque disruption is called type 2 MI [3]. Prompt and effective revascularization may reduce the loss of contractile myocardial muscle mass, decrease the infarct size, and improve clinical outcome [4]. In fact, infarct size is considered one of the major determinants of the prognosis of patients with acute MI [5]. Reperfusion rescues ischemic myocardium from cell death but also induces an additional irreversible injury known as myocardial ischemia-reperfusion (I/R) injury [6]. The pathological mechanisms of myocardial I/R injury that cause irreversible cell death include intracellular calcium overload, oxidative stress, endoplasmic reticulum stress, energy metabolism disorder, apoptosis, pyroptosis, ferroptosis, necroptosis, autophagy and inflammation [7] (Figure 1). The purpose of this review is to update the current knowledge regarding the involvement of tumor necrosis factor (TNF) and TNF super family (TNFSF) members in myocardial ischemia-reperfusion injury and the possible therapeutic implications (Figure 2). Activation of several innate immune molecular pathways have been observed in a spectrum of ischemic cardiac diseases including, but not limited to, infarction, I/R injury, post-injury left ventricular (LV) scaring, and LV dysfunction. Specifically, inflammatory response, mitochondrial damage and calcium overload, as well as cell death and cell survival-associated signaling pathways are involved in the pathophysiology of myocardial I/R injury [8]. During acute myocardial ischemia, ischemic cardiomyocytes switch to anaerobic metabolism to provide ATP, leading to lactate, H+, and nicotinamide adenine dinucleotide (NADH+) accumulation and cytosolic pH decrease. To reestablish the acid-based balance, the plasmalemma Na+/H+ exchanger is activated to extrude H+, and results in intracellular Na+ overload, which, in turn, activates the Na+/Ca2+ exchanger that leads to Na+ extrusion and intracellular Ca2+ overload [9]. The endoplasmic reticulum also reduces Ca2+ reuptake, which exacerbates intracellular Ca2+ overload. The elevation of intracellular calcium levels induces the opening of the mitochondrial permeability transition pore (MPTP) together with the activation of phospholipases and calpain, a Ca2+-dependent cysteine protease [10]. Reperfusion reestablishes blood supply in an ischemic area and provides an influx of oxygen that fuels the production of reactive oxygen species (ROS), which are harmful to the ischemic myocardium. Reperfusion after ischemia can result in injury rather than protection, and this phenomenon is called the oxygen paradox [11]. Calpain-induced xanthine oxidase formation, NADPH oxidase due to neutrophil respiratory burst, and damage to the mitochondrial electron transport chain may all contribute to the increase in ROS levels. The excessive production of ROS decreases membrane fluidity, increases calcium permeability, aggravates intracellular calcium overload and mitochondrial damage by opening the MTPM, and contributes to the release of pro-apoptotic factors, such as cytochrome C. ROS can react with proteins, cause loss of original protein structure and function, as well as damage nucleic acids and chromosomes. ROS also trigger the inflammatory system and cause the expression of cytokines and adhesion molecules that result in leukocyte aggregation, endothelial cell (EC) swelling, and contribute to the no-reflow phenomenon that indicates inadequate myocardial perfusion at the microvascular level even though the proximal coronary artery has been re-opened after a period of ischemia [12]. In response to myocardial ischemia, the inducible nitric oxide synthase (iNOS) is upregulated, leading to enhanced production of NO [13]. High levels of iNOS-derived NO are associated with an increased level of intracellular cGMP, resulting in a decrease in Ca2+ influx which depresses myofilament sensitivity to Ca2+ and, subsequently, attenuates cardiac contractile function [13]. NO also contribute to the formation of peroxynitrite, which subsequently leads to significantly increased oxidative stress and apoptosis, as well as the expression of pro-inflammatory cytokines [13]. Myocardial infarction is the result of cardiomyocyte necrosis, a type of cell death involving mitochondria and sarcolemma rupture, cell swelling, and the release of cellular debris activating inflammation. Cell damage and cell death lead to the release of cellular components such as heat shock proteins, high mobility group box-1, adenosine triphosphate, nuclear and mitochondrial DNA, and RNA into the extracellular space and the circulation. These molecules act as so-called damage (or danger)-associated molecular patterns (DAMPs) and serve as ligands for pattern recognition receptors (PRRs) that, when activated, induce nuclear translocation of various transcription factors as NF-κB and promote pro-inflammatory cytokine expression [14]. The involvement of more regulated forms of cardiomyocyte cell death has been recognized in I/R injury, including apoptosis, necroptosis, and pyroptosis [15,16]. Apoptosis occurs through the intrinsic pathway, following DNA damage, augmented ROS, and intracellular Ca2+ levels, or through the extrinsic pathway, following the activation of sarcolemmal death receptors. The process of apoptosis needs energy, includes the release of cytochrome C from mitochondria, and the activation of caspases, thus leading to DNA fragmentation. Apoptosis does not elicit an inflammatory reaction because the sarcolemma remains intact [17,18]. Opening of the MPTP, with consequential mitochondrial matrix swelling and outer membrane damage, has a major involvement in cardiomyocyte death [19,20]. Cytochrome C release following MPTP activation appears to be the main apoptosis-inducing mechanism [21]. The apoptosis level is also linked to the reperfusion duration. Prolonged periods of myocardial ischemia are linked to an increase in the necrosis rate, whereas, paradoxically, reperfusion leads to the increase in apoptosis. Reperfusion reestablishes glucose and oxygen supply, which is crucial for the survival of viable cells, but also reestablishes the energy required for apoptosis completion and might accelerate the apoptotic process [22,23]. Experimental studies in animals show that apoptosis can be triggered by ischemia and accelerated by reperfusion. Apoptosis is induced following 2 h of coronary occlusion and accelerated after 45 min of ischemia followed by 1 h of reperfusion [24,25]. Other studies in animals report apoptosis in myocardium exposed to a short-term period of ischemia followed by reperfusion, but not in the permanent ischemic area without reperfusion, suggesting that reperfusion initiates apoptosis [26,27]. Necroptosis follows the activation of sarcolemmal TNF receptors or toll-like receptors, which interact with specific serine/threonine-protein kinases and induces the formation of the necrosome. Necroptosis is characterized by the formation of pores in the sarcolemma and the premature loss of plasma membrane integrity, organelle swelling, and leakage of intracellular contents [28,29]. Pyroptosis starts with DAMPs, which lead to the formation of the inflammasome complex that triggers caspase activation, with the consequent formation of gasdermin-dependent pores in the sarcolemma [30,31]. Caspase-3 is known as a marker and key molecule of apoptosis; recent studies have also demonstrated its involvement in pyroptosis. TNFα stimulates caspase-3 to specifically cleave gasdermin E (GSDME), thus leading to the release of the N-terminal PFD of GSDME. The oligomerized N-terminal PFD of GSDME migrates towards the cell membrane to form non-selective pores, thus determining cell pyroptosis [32]. Necroptosis and pyroptosis finally induce the loss of plasma membrane integrity, thus eliciting a pro-inflammatory response with release of interleukins (ILs) and DAMPs. How and to what extent apoptosis, necroptosis, and pyroptosis interact/work in the context of myocardial I/R requires further investigation. Experimental studies in animals have shown that combined inhibition of necroptosis and apoptosis reduces infarct size more evidently than inhibition of either cell death type alone [32,33]. TNFα, a member of the TNF superfamily, is a pro-inflammatory cytokine, initially identified as an inducer of cell death in tumor cells [34]. It is produced primarily by monocytes/macrophages, but B and T lymphocytes, natural killer cells, mast cells, neutrophils, fibroblasts, and osteoclasts can also secrete TNFα. It is initially synthesized as a 26 kDa homotrimer transmembrane protein (mTNF), where it either remains or is cleaved by a membrane-bound metalloproteinase known as TNF-converting enzyme (TACE) to produce the 17 kDa soluble TNF (sTNF) form. Following cleavage, sTNF is released into the blood plasma [35]. Membrane bound and soluble TNF can bind two receptors: TNFR1, which is expressed by all human tissues, and TNFR2, which, in contrast, is expressed primarily by immune cells, ECs, and neurons [36,37]. mTNF-TNFR2 binding generates a more effective response than sTNF [38]. TNFR1 and TNFR2 show different intracellular structures that bind several adaptor proteins [39]. The TNFR1 cytoplasmic tail includes the death domain (DD), thus leading it to engage the TNFR1-associated DD (TRADD) [40]; by comparison, TNFR2 recruits TNFR-associated factor (TRAF) 1 and 2 proteins [41]. The TNFR1 and 2 signaling pathways may trigger a cell survival response, whereas TNFR1 can also induce cell death based on the predominant physiological conditions, which are not completely known [42]. Other studies have led to crucial progress in the clarification of mechanisms regulating the crosstalk between TNFR1 and 2 together with the distinct, but complementary, roles of these two receptors [43,44]. TNFR1 activation can lead to the establishment of four signaling complexes, known as complexes I, IIa, IIb, and IIc, which are involved in different cellular reactions [44,45]. During complex I formation, the activated TNFR1 interacts with TRADD and other components resulting in the activation of mitogen-activated protein kinases (MAPKs) and NF-κB [46,47]. NF-κB dimers are normally present as an inactive form in the cytoplasm of cells because they are linked to members of the inhibitory family of IκB proteins. Following cell stimulation, IκB proteins are quickly phosphorylated, ubiquitinated, and then degraded, thus leading to the exposure of a nuclear localization sequence for the NF-κB proteins (Figure 1). NF-κB dimers thus migrate to the nucleus where they bind to specific sequences, termed κB sites, and, together with other transcription factors, regulate gene transcription. This finally determines the development of pro-survival signaling, where inflammation and immune cell proliferation are induced. Complex I signaling is fundamental for inflammation development, tissue degeneration, cell proliferation, and survival, as well as immune defense against pathogens [45,48]. In contrast to complex I, which is assembled in the cell membrane, complexes IIa, IIb, and IIc are assembled in the cytoplasm [49]. Complex IIa comprises TRADD, TRAF2, RIPK1, cIAP1/2, Fas-associated protein with death domain (FADD), and pro-Caspase-8, [50,51]. Complex IIb also includes RIPK3. The creation of complexes IIa and IIb, also recognized as apoptosome, trigger the activation of caspase-8, thus leading apoptosis. Complex IIc, which is also known as necrosome, triggers the mixed lineage kinase domain-like protein (MLKL) and causes/leads to inflammation and necroptosis [34,52]. TNFR2 engages TRAF2, together with TRAF1, cIAP1, and cIAP2, and this complex determines the downstream activation of NF-κB, AKT, and MAPKs, [49]. TNFR2 engagement is mainly linked to tissue regeneration, cell survival, and proliferation [53]. Furthermore, the activation of this pathway can trigger pro-inflammatory reactions. In general, TNFR1 is fundamental to determining pro-inflammatory and cytotoxic TNFα responses, whereas TNFR2 may be involved in cell proliferation, migration, or activation. TNFα is involved in the pathogenesis of cardiovascular diseases, such as acute myocardial infarction [54], chronic heart failure (HF) [55], atherosclerosis [56], viral myocarditis [57], cardiac allograft rejection [58], and sepsis-induced cardiomyopathy [59]. The heart represents a TNF-producing organ, and both cardiac myocytes and myocardial macrophages produce it [60]. TNFα is not expressed in normal cardiac myocytes, but human cardiac myocytes expose a functional TNFR1 on their membrane and trigger an active response following TNFα binding [61]. Although originally described exclusively as a lipopolysaccharide (LPS)-induced macrophage cytokine, several studies indicate that cardiac myocytes synthetize an important quantity of TNFα following ischemia or LPS exposure. Certainly, ischemia-provoked myocardial TNFα production is significantly higher than sepsis-induced myocardial TNF production, and it may contribute to post-ischemic myocardial alteration by the inhibition of contractility as well as the triggering of myocyte hypertrophy and apoptosis [60]. The expression of TNFR1 and 2 also increases significantly after myocardial infarction [62], and it is positively correlated with infarction size, LV dysfunction, and remodeling [63]. LPS and ischemia-reperfusion activate myocardial p38MAPK and NF-κB with consequent TNFα production. This cytokine negatively affects myocardial function through mechanisms that are NO-dependent or sphingosine-dependent; furthermore, TNFα-TNFR1 interaction may induce cardiac myocyte apoptosis [64]. Experimental studies show that administration of exogenous TNFα reduces cardiac contractility in animals in a dose-dependent manner. TNFα reduces Ca2+ uptake by sarcoplasmic reticulum as well as myofilament Ca2+ sensitivity through the activation of p38MAPK. TNFα also induces cardiac caspase-8 activation, with consequent production of myocardial NO and mitochondrial ROS, thus resulting in ryanodine receptor S-nitrosylation and sarcoplasmic reticulum Ca2+ leak [65]. In vivo studies have demonstrated that TNFα also induces a hypertrophic response in cardiac myocytes by activation of NF-κB and p38MAPK through ROS [66]. In vitro studies have shown that cardiac myocytes undergo apoptosis after stimulation with TNFα, and that cardiac cell death is mediated by TFNR1. TNFR1, and not TNFR2, is mainly and highly expressed by cardiac myocytes in normal human hearts. TNFα stimulation also induces upregulation of TNFR2 that mediates cell repair [67]. Inflammation is recognized as the initial step of myocardial ischemia-reperfusion that leads to increased release of proinflammatory mediators, such as TNFα, IL1β, IL-2, IL-6, and IFN-α. TNFα has pleiotropic effects and can augment the local release of other pro-inflammatory mediators, including IL-1 and IL-6. TNFα shows both beneficial and harmful functions in the myocardium during I/R injury, depending on its concentration, receptor subtype, and exposure duration. Ischemia and anoxia activate cardiomyocytes and myocardial local mononuclear macrophages to synthetize elevated amounts of TNFα, and, simultaneously, TNFR2 expression is also significantly augmented [62]. The TNFα–TNFR1 complex is primarily involved in the inflammatory response and ventricular remodeling after MI, and induces cardiomyocyte apoptosis and cardiotoxicity, whereas the TNFα-TNFR2 complex blunts these events after MI, reduces cardiomyocytes apoptosis, and exerts a protective effect on the heart [63]. After MI in myocardium, TNFα exerts a double function that is time- and dose-dependent. In particular, in the short term, low doses of TNFα could exert a protective role on the myocardium, whereas, in the long term, exposure to elevated TNFα secretion displays lethal activity on cardiomyocytes [68]. TNFα/TNFR1 interaction leads to FADD and TRADD secretion as well as inflammatory mediator release, which determines the progression of ventricular remodeling. TNFα/TNFR1 interaction determines the secretion of RIP1 which could be blocked by TAK1 activation [69]. TNFα /TNFR1 interaction can trigger the NF-κB pathway, stimulate ECs to expose VCAM-1 and ICAM-1, augment neutrophil infiltration into the infarction area, and also determine late ROS generation. TNFα/ TNFR2 interaction also activates NF-κB, but the expression of IL-6 and IL-1 β is inhibited to decrease the injury arising from the inflammatory status. Ischemia/reperfusion injury or no-reflow frequently occurs during reperfusion after MI. This phenomenon is strictly linked with TNFα and clinically manifests with myocardial stunning, arrhythmia, microvascular injury, LV systolic dysfunction, and myocardial necrosis. The physio-pathological mechanisms comprise elevated Ca2+ accumulation in cardiomyocytes, high amounts of ROS production, and oxidoreductase activation. TNFα /TNFR1 interaction leads to NO synthesis, with consequent reduction of myofilament sensitivity to Ca2+ or activation of sphingomyelinase to reduce Ca2+ release. TNFα can also trigger the NF-κB pathway through TNFR1, thus resulting in a vicious cycle involving TNFα and other pro-inflammatory cytokines, which further exacerbate the injury. Experimental studies in animals have demonstrated the existence of sex differences in TNF signaling by TNFR1 after myocardial I/R. TNFR1 signaling resistance in females seems to allow a better postischemic recovery in female WT mice than in male WT mice. Additionally, TNF infusion induces less myocardial depression in female WT mice, despite equivalent TNFR1 expression. TNFR1 ablation positively affected postischemic myocardial function, reduced the activation of p38MAPK, and decreased IL-1β and -6 expression in males but not in females. Moreover, after I/R, WT females produced high levels of the suppressor of cytokine signaling protein 3, which can be partially linked to the TNFR1 signal resistance in the female myocardium [70]. Sex variances also occur in TNF/TNFR2 signaling. In particular, in isolated female and male murine hearts exposed to 20 min ischemia with subsequent 60 min reperfusion, TNFR2 deficiency led to reduced postischemic myocardial retrieval in both sexes, with a greater intensity in females. The negative effects of TNFR2 deficiency are linked to the reduced expression of SOCS3, STAT3, and vascular endothelial growth factor together with the enhanced expression of myocardial IL-1β synthesis in female hearts [71]. CD95 ligand (CD95L also known as FasL, CD178, or TNFSF6), encoded by the FASLG gene, is a type II transmembrane protein displaying a transmembrane domain, a stalk region, a long cytoplasmic domain, a C-terminal region implicated in the CD95 binding, and a TNF homology domain (THD) involved in homotrimerization. The transmembrane CD95L may be cut in the stalk region by different matrix metalloproteases [72], thus resulting in the soluble form of CD95L (sCD95L), a homotrimer [73] whose interaction with CD95 fails to trigger cell death [74,75]. CD95, encoded by the FAS gene, is a tumor necrosis family receptor (TNF-R) member. In the cell membrane, CD95 auto-aggregates as a homotrimer, which is compulsory to increase cell death, and quickly assembles larger signaling platforms in the presence of CD95L [76]. CD95L/CD95 bonding leads to the engagement of FADD, which, consequently, binds pro-caspase-8 in the DISC complex [77]. Outside DISC assembly and activation of the apoptotic signal, FADD and caspase-8 are involved in the organization of different complexes involved in necroptosis or pyroptosis induction. In brief, RIPK1 ubiquitination is a key post-translational modification for the stimulation of NF-κB activation through TNF-R1 [78,79], and its deubiquitination determines cell death. The deubiquitinated RIPK1 recruits TRADD, pro-caspase-8, and FADD, together with the long isoform of FLICE-like inhibitory protein (FLIPL), to activate the apoptotic process [50]. In this complex, the caspase-8-mediated cleavage of RIPK1 obscures the kinase activity. Additionally, c-IAP1 and c-IAP2 degradation inhibits RIPK1 ubiquitination [80] and determines the assembly of another complex in which FADD, together with pro-caspase-8 and FLIPL, interact to activate the apoptotic process. Once caspase-8 has been inactivated in these two complexes, it is possible to have the formation of the necrosome. In detail, RIPK1 recruits and activates RIPK3 to generate the necrosome; MLKL is a constitutive binding partner of RIPK3, and thus it is incorporated in the necrosome. MLKL phosphorylation leads to a conformational change, recruitment into the plasma membrane, and induction of necrosis through membrane permeabilization [81]. Ex vivo studies based on an I/R model of isolated rat and mouse hearts in Langendorff perfusion showed that caspase-dependent apoptosis occurs during postischemic reperfusion. Soluble CD95L is produced de novo and secreted by the postischemic hearts early after reperfusion onset. In primary adult rat myocyte culture, reoxygenation and hypoxia determined a strongly augmented sensitivity to CD95L apoptotic action. Isolated hearts from mice lacking functional CD95 (lpr) display a strong decrease in cellular death following ischemia and reperfusion with respect to wild-type mice [82]. Conversely, CD95 or CD95L deletion failed to decrease the myocardial infarct size in a Langendorff model of I/R injury, suggesting that the CD95 and CD95L apoptotic pathway is not the primary cause of myocardial infarct size and ventricular dysfunction caused by I/R injury [83]. In patients with MI, soluble CD95 was significantly augmented from baseline to 24 h, whereas CD95L reduced over time [63]. However soluble CD95 and CD95L did not show any correlation with infarct size, LV dysfunction, or measures of remodeling [63,84]. TRAIL, belonging to the TNF superfamily (TNFSF10), is a type II transmembrane protein, the active form of which is organized as a homotrimer. TRAIL expression has been demonstrated primarily in immune cells, but also in other tissues, including vascular, valvular, and ECs [85,86,87,88,89,90]. TRAIL determines its effect following binding with its multiple receptors. Five receptors are known for TRAIL (TRAIL-R): the death and the decoy receptors, respectively, DRs and DcRs. TRAIL-R1 (DR4) and TRAIL-R2 (DR5) with agonistic activity belonging to type I transmembrane proteins and show an intracellular death domain (DD) that promotes the apoptotic process (Figure 2). The DcRs with antagonist activity are represented by the soluble osteoprotegerin (OPG) as well as the transmembrane TRAIL-R3 (DcR1) and TRAIL-R4 (DcR2). DcR1 and DcR2 are proteins which do not have a fully developed intracellular DD. When TRAIL engages DR4 or DR5, it triggers a signaling pathway leading to apoptosis through extrinsic or intrinsic pathways. The assembly of the extrinsic pathway is characterized by the binding of DR4 and/or DR5 to the death-inducing signaling complex (DISC), which causes an increase in FADD, which is an intermediate complex involving DD and the inactive pro-caspase 8. Suddenly, the formation of active caspase 8 occurs, which leads to the activation of executive caspases (caspases 3, 6, and 7) with consequent cell apoptosis [91]. In some cells, the executive caspase activation must be additionally increased by the involvement of the internal mitochondrial apoptotic pathway, which is known as the intrinsic apoptotic pathway [88,92]. As for the DcRs for TRAIL, DcR1 is linked to the cell membrane through a glycosylphosphatidylinositol (GPI) linker and does not have a cytoplasmic domain, whereas DcR2 displays a shortened DD. The engagement of DcR2 can activate the NF-κB pathway that determines the transcription of genes promoting cell survival as well as apoptosis resistance (Figure 2) [93]. DcRs do not activate an apoptotic pathway when linked to TRAIL; they compete with DRs for TRAIL binding, thus exerting a protective mechanism against the pro-apoptotic effect of TRAIL [88]. The pro-apoptotic effect of TRAIL is primarily associated to neoplastic cells, or virus infected cells [87,88,92], but is also evident in normal cells [94,95,96]. It has also been shown, however, that TRAIL interaction with DR4 and DR5 can lead to the activation of survival pathways, such as ERK1/2 or PI3-kinase Akt [97]. Interestingly, transmembrane TRAIL stimulates DR4 and DR5 to the same extent, whereas soluble TRAIL mainly stimulates DR4 [98]. Consistently, DR5 is primarily expressed on normal cells, thus explaining their greater resistance to pro-apoptotic TRAIL effects. However, the triggering by TRAIL of the pathways activated by/activating or protected/protecting from apoptosis is linked to the cell type as well as to the balanced expression of death and decoy receptors. Cells resistant to TRAIL pro-apoptotic effects include VSMCs and ECs, although both cell types possess DR4 and DR5 [86,99]. It has been demonstrated in the literature that TRAIL is secreted from the postischemic heart shortly after reperfusion onset [82]. Experimental studies in animals indicate that DR5 is also up-regulated after MI, and that inhibition of TRAIL by blocking DR5 improves cardiac function after MI by preventing cardiac cell death and inflammation [100]. TRAIL can inhibit angiogenesis by determining ECs death but can also promote angiogenesis in vitro. Thus, TRAIL exhibits multiple and opposite effects that make its role in ischemic disease unclear. Experimental studies have shown that TRAIL stimulates angiogenesis following hindlimb ischemia in vivo. The TRAIL pro-angiogenic effect on human microvascular ECs is downstream from FGF2, with the involvement of NOX4 and NO signaling. These results have important therapeutic implications, such that TRAIL may ameliorate the angiogenic response to ischemia and augment perfusion recovery in patients with cardiovascular diseases [101]. The receptor activator of NF-κB ligand (RANKL, TNFSF11) is a transmembrane protein, but a soluble form (soluble RANKL: sRANKL) is also detectable in the blood. This sRANKL derives from the cleavage of membrane-bound RANKL (mRANKL) by a metalloprotease. RANKL is encoded by the TNFSF11 gene on chromosome 13. Trimers of mRANKL or sRANKL bind to RANK trimers following the interaction with specific proteins: TNFR-associated factor (TRAF) proteins. TRAFs are signaling transducers that bind the intracellular domains of various TNFRs. TRAF2 and TRAF6 are the most crucial for RANK signaling. RANK–RANKL signaling by TRAFs activates NF-κBs, mitogen-activated protein kinases (MAPKs), AP1, and interferon-regulatory factors (IRFs) [102]. RANKL is largely expressed on osteoblasts, osteocytes, infiltrating T cells and activated ECs. RANK is a type I transmembrane glycoprotein, and its gene is located on human chromosome 18q22.1. RANK is expressed on the cellular membrane of osteoclast precursors, osteoclasts, dendritic cells, B- and T-cells, chondrocytes, vascular endothelia, mammary gland epithelia, and bone marrow fibroblasts. RANKL exerts an important role in immune responses and osteoclastogenesis. Osteoprotegerin (OPG, TNFRS11B) is a secreted glycoprotein of the TNF receptor superfamily encoded by the TNFRSF11B gene on chromosome 8 (8q24). Circulating measurable OPG exists either as a free 60 kD monomer or a disulfide bond-linked 120 kD homodimer form. The levels of OPG are gender-linked, with women showing greater OPG levels compared with men. Additionally, OPG levels are significantly linked with aging [103]. OPG is the soluble decoy receptor of RANKL and TRAIL. OPG interacts with RANKL through its N-terminal cysteine-rich domains (CRD), thus participating in bone homeostasis regulation. OPG binds TRAIL to regulate its pro-apoptotic activity. The crucial role of the TRAIL/OPG interaction is fundamental to inhibit TRAIL-induced apoptosis in different cell types [104]. OPG is expressed in various tissues, such as the heart, kidney, lung, liver, bone marrow, bone, and immune system, and is produced in vivo by osteocytes, osteoblasts, ECs, vascular smooth muscle cells (VSMCs), placenta, brain, and skeletal muscle [105,106]. OPG is synthetized in basal conditions by ECs following treatment with hormones, inflammatory cytokines, and various circulating molecules. IL-1β and TNFα have been demonstrated to augment OPG levels [107]. While RANKL and RANK are undetectable in healthy human vessels, OPG is expressed in normal arteries in coronary and aortic atherosclerotic plaques, and in the vicinity of VSMCs [103,108]. Various evidence suggests that besides its function in bone remodeling, signaling by the RANKL/RANK/OPG pathway is likewise involved in the pathophysiology of cardiovascular diseases, and it is actually considered one of the key regulators of the progression of calcification of the blood vessel wall [109,110,111,112,113,114,115,116,117,118,119]. Previous studies showed that serum sRANKL levels predict the cardiovascular event risk, including MI [120], and that RANKL may contribute to atherosclerotic plaque destabilization [121]. Additionally, it has been suggested that RANKL determines inflammation of the myocardium during acute cardiac overload [122] and induces impaired remodeling through matrix degradation after acute MI [123]. Studies in vitro showed that RANKL/RANK interaction determines the expression of IL-1α, IL-1β, and TNFα in cultured cardiomyocytes by activating the TRAF6-NF-κB pathway [120]. Experimental studies in mice subjected to 60 min of myocardial ischemia and different reperfusion times up to 72 h showed that RANKL amounts are increased during reperfusion both in systemic circulation and infarcted hearts, and intravenous post-infarction anti-RANKL treatments reduce infarct size and cardiac neutrophil infiltration [124]. In infarcted left ventricles, RANKL expression was significantly augmented by 12 to 72 h of reperfusion with respect to the baseline condition, while OPG protein expression did not change over time during reperfusion. Inside the infarcted hearts, OPG- and RANKL- positive regions were not co-localized, and OPG positivity was associated only to heart vessels. In mouse serum, RANKL levels had already significantly increased 5 min after reperfusion, with a peak observed at 12 h of reperfusion, while OPG serum levels were importantly decreased at 5 min and at 12 h after reperfusion [124]. Experimental studies showed that MI induced RANKL expression mainly in cardiomyocytes and scar-infiltrating cells in mice. In a highly manipulated murine model of myocardial ischemia (that did not include reperfusion), only selective inhibition of RANKL derived from hematopoietic cellular sources, but not selective inhibition of RANKL from mesenchymal cells, improved post-infarct survival and cardiac function. Curiously, a post-ischemic rise in LV gene expression of TNFα was not reduced by RANKL blockade in this study. The study concluded that RANKL produced by cells of hematopoietic origin, but not by cardiomyocytes, contributes to deteriorating cardiac function after MI [125]. Conversely, studies performed in patients with acute MI did not support the increase in RANKL serum levels demonstrated in mice, whereas an early increase in OPG serum levels was found [121,126]. Likewise, serum levels of OPG and T-cells, as well as monocyte gene expression of the NF-κB p50 subunit, significantly increase in patients undergoing coronary artery surgery [127]. Many studies have demonstrated a statistically significant increase in the levels of OPG and TNFα, together with the reduction of TRAIL amounts with the consequent increase in the OPG/TRAIL ratio in the plasma of patients in the acute phase of MI with respect to the controls [128]. An elevated plasma concentration of OPG and the OPG/TRAIL ratio are linked to significantly increased early (30-day) and late (1-year) mortality in patients with both ST and non-ST-segment elevation MI [129,130]. High levels of OPG and the OPG/TRAIL ratio are linked to adverse post-infarction LV remodeling and HF development after MI. In STEMI patients subjected to primary coronary angioplasty, a correlation has been found between the elevated plasma OPG levels on hospital admission and the no-reflow phenomenon frequency together with the appearing of adverse post-infarction LV remodeling [131]. Conversely, experimental studies suggest that OPG could exert a protective and pro-survival effect from oxidative stress in cardiomyocytes. Hydrogen peroxide (H2O2), an ROS, significantly increased the OPG production of adipose stem cells (ASC) and mRNA expression of OPG and DcR1, which attenuates TRAIL-induced apoptosis. In cardiomyocytes exposed to H2O2, treatment with ASC-derived OPG significantly improved cell viability by suppression of caspase 8 activation without affecting DR5 expression [132]. Thus, the function of the RANKL/RANK/OPG pathway in the setting of myocardial I/R injury has not been completely elucidated and requires further investigation. The research on TNFs leads to the identification of potential therapeutic targets (Table 1). The blockade of TNFα with etanercept 10 min prior to I/R injury improved cardiac functions, and reduced infarct size and cardiomyocyte apoptosis in mice [133]. Moreover, a single dose of etanercept injected at the time of MI improved long-term cardiac function and reduced cardiac tissue remodeling in rats [134]. The injection of anti-TNFα antibody 3 h prior to myocardial I/R has also been shown to reduce endothelial dysfunction by reducing the production of endothelial ROS [135]. In another study, a pharmacological TNFα inhibitor (CAS1049741-03-8), inhibiting binding the protein to its receptor, decreased post-infarction inflammatory response but negatively affected cardiac activity due to increased cardiomyocyte apoptosis [136]. Transgenic mice lacking one or the other TNFR leads to the demonstration that the majority of the cardioprotective activity involved TNFR2, while TNFR1 activation triggers pathogenic processes. Consistently, TNFR2 activation blocks the pathogenic TNFR1 downstream pathways. It has been reported that, in the absence of TNFR2, there is evident augmented activity of TNFR1 downstream effector molecules NF-κB [137] and p38MAPK [138] together with an augmented secretion of IL-1β and IL-6 [139]. This could explain the conflicting results obtained between human and animal studies. In fact, a single high dose injection of etanercept did not ameliorate patient outcomes following acute MI [140]. The documented key role of TNFα in cardiovascular events encouraged the testing of its therapeutic value in patients with systolic HF. Randomized, double-blind, placebo-controlled trials were aborted after failing to demonstrate a beneficial effect of etanercept in HF patients with reduced ejection fraction. In fact, the RECOVER (Research into Etanercept: Cytokine Antagonism in Ventricular Dysfunction) and RENAISSANCE (Randomized Etanercept North American Strategy to Study Antagonism of Cytokines) clinical trials were stopped in advance due to lack of beneficial effect [141]. Consistently, the Randomized Etanercept Worldwide Evaluation (RENEWAL) trial, combining the results of RECOVER and RENAISSANCE testing the efficacy and safety of etanercept, demonstrated the absence of helpful effects in terms of mortality and hospitalization [142]. Additionally, in the ATTACH (Anti-Tnf alpha Therapy Against Chronic Heart failure) short-term trial, TNFα antagonism using infliximab did not ameliorate, and high doses increased the risk of HF-related hospitalization or death of patients affected by moderate-to-severe chronic HF [143]. In addition, another study reported that a single high dose etanercept injection did not improve patients’ outcomes following acute MI [140]. Thus, in patients with systolic HF, continuous anti-TNFα treatment did not determine positive effects and can be detrimental and aggravate the disease. Consequently, the use of TNFα inhibitor is not recommended. Thus, in the failing heart, TNFα exerts a cardioprotective effect, but the mechanism should be further investigated. Differently, in patients with autoimmune inflammatory diseases, a long-term anti-TNFα therapy is usually not detrimental, and it can even protect from the risk of increased cardiovascular complications and death. TNFα antagonist use has been linked with a reduced risk of MI and development of acute coronary syndrome, highlighting anti-TNFα therapy as a promising anti-atherosclerotic therapy in rheumatoid arthritis patients (Table 1) [144,145]. It is important to remember that anti-TNFα therapy represents the leading treatment for rheumatic diseases. These patients frequently display a rapid development of diastolic function change. Patients with rheumatoid arthritis and preserved LV activity treated with infliximab displayed a cardiac function improvement [146] together with reduced LV torsion [147]. A large cohort of clinical studies has demonstrated the reduced cardiovascular-related death of rheumatoid arthritis patients treated with adalimumab, infliximab, or etanercept. In an additional multi-center comparative study in patients undergoing long term treatment with adalimumab, etanercept, and infliximab, a decreased risk of cardiovascular-related death was found with respect to patients receiving disease modifying antirheumatic drugs (DMARD). Similar findings have been reported for patients with psoriasis that are at high risk of developing cardiovascular diseases [148,149]. RANKL also contributes to post-MI injury and repair, and thus the anti-RANKL effect was tested in animal models of myocardial ischemia. During ischemia, a “one-shot” injection of neutralizing anti-RANKL IgG reduced MI size and improved cardiac function but did not affect adverse remodeling. These positive effects were associated in vivo with a decrease in cardiac neutrophil infiltration as well as MMP-9 and ROS release. Anti-RANKL IgG injection decreased the rapid increase in neutrophil granule enzymes and cytokines in serum after reperfusion onset [124]. Different studies have reported the involvement of TNFα, RANKL/RANK/OPG axis and TRAIL in MI, thus also stimulating studies on the effect of their neutralization. To date, the neutralization of TNFα in MI patients has not shown a reduction in cardiovascular events, nor an improvement in myocardial function. However, in patients with rheumatic disease, treatment with TNFα inhibitors shows a protective effect against cardiovascular diseases in comparison with other standard treatments. Few studies have been performed on RANKL inhibition, due to the discouraging results obtained in animal models, possibly because RANKL represents an intermediate of the cascade and not the initiator, or maybe because of the pro-survival signaling associated with RANKL. TRAIL seems to be involved in MI, but its signaling pathway is very complex due to the multiple receptors able to bind it; however, trials demonstrating the safety of molecules affecting TRAIL signaling are ongoing for the treatment of cancer and, in the future, could also be used for MI management. Indeed, additional molecular targets belonging to the TNF superfamily, such as tumor necrosis factor-like weak inducer of apoptosis (TWEAK) and CD40L, could give encouraging results. It is also important to remember that other cytokines, such as ILs, are involved in heart disease and myocardial I/R injury, and that the preliminary results of ongoing trials seem to be encouraging.

PMC10003150

Rony Thomas,Sai Qiao,Xi Yang

Th17/Treg Imbalance: Implications in Lung Inflammatory Diseases

02-03-2023

Th17 cells,Treg cells,inflammation

Regulatory T cells (Tregs) and T helper 17 cells (Th17) are two CD4+ T cell subsets with antagonist effects. Th17 cells promote inflammation, whereas Tregs are crucial in maintaining immune homeostasis. Recent studies suggest that Th17 cells and Treg cells are the foremost players in several inflammatory diseases. In this review, we explore the present knowledge on the role of Th17 cells and Treg cells, focusing on lung inflammatory diseases, such as chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), sarcoidosis, asthma, and pulmonary infectious diseases.

Th17/Treg Imbalance: Implications in Lung Inflammatory Diseases Regulatory T cells (Tregs) and T helper 17 cells (Th17) are two CD4+ T cell subsets with antagonist effects. Th17 cells promote inflammation, whereas Tregs are crucial in maintaining immune homeostasis. Recent studies suggest that Th17 cells and Treg cells are the foremost players in several inflammatory diseases. In this review, we explore the present knowledge on the role of Th17 cells and Treg cells, focusing on lung inflammatory diseases, such as chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), sarcoidosis, asthma, and pulmonary infectious diseases. The immune system acts as the guardian of the host and functions to defend against foreign antigens, induce self-tolerance, and promote immunological memory. However, it is not protective or beneficial all the time. The individual’s tissue components may be attacked by the immunological reaction resulting in autoimmune diseases in specific settings. It is certain that a single theory or mechanism cannot explain autoimmune diseases. As proposed by Shoenfeld and Isenberg, autoimmune diseases are caused by various factors, including immunological, genetic, hormonal, and environmental factors [1]. Non-genetic components rather than inherent components play a dominant role in determining disease susceptibility and severity, which has been demonstrated by the discordance of autoimmune diseases in identical twins [2]. Immunological factors play a vital role in the initiation, progression, and regression of autoimmune diseases. In a typical setting, T cells are tolerant to physiological levels of self-antigen. However, this state of tolerance breaks down in some individuals, resulting in autoimmune/inflammatory diseases. One of the critical features of inflammatory diseases is the deregulated Th1/Th17 responses, frequently accompanied by a reduction and/or alteration of regulatory T (Treg) cells. Th17 cells serve as inflammatory cells, which in excess, promote inflammatory diseases. On the other hand, Treg cells show suppressor function, which, when in failure, contributes to the same disease [3]. Initial studies by Infante-Duarte et al. identified CD4+ T cells producing IL-17A as a T helper cell subset distinct from Th1 and Th2 cell subsets [4]. This subset, called Th17 cells, predominantly produces interleukin-17A (IL-17A), IL-17F, IL-21, and IL-22 [5]. IL-17A, originally named CTLA8, was cloned and described by Rouvier et al. [6]. It is a homodimeric glycoprotein with 155 amino acids linked by disulfide bonds. IL-17F, also produced by Th17 cells, shows 55% similarity with IL-17A, and they form IL-17F homodimers, IL-17A homodimers, or IL-17A-IL-17F heterodimers [7]. IL-17 binds to its receptor (IL-17R), a transmembrane protein, highly expressed in rats and mice’s spleen, kidneys, liver, and lungs [8]. Th17 cells require the transcription factor, RORγt, and cytokine IL-6 in combination with transforming growth factor-β (TGF-β) for their differentiation [9]. IL-6 acts as a major factor guiding the differentiation of T cells into Th17 cells or Treg cells [9]. IL-21, together with TGF-β, also functions as an alternative pathway to generate Th17 cells [10]. Once they reach the site of inflammation, IL-17 released by Th17 cells stimulates the expression of pro-inflammatory cytokines like granulocyte-macrophage colony-stimulating factor, Granulocyte-colony stimulating factor, IL-6 and tumor necrosis factor-alpha (TNF-α) [11]. In addition, IL-17 also promotes the secretion of CXC chemokines, which attracts neutrophils in vivo [11]. Moreover, IL-17 stimulates the production of antimicrobial peptides, such as β-defensin and S100 proteins, providing defense against a wide range of microorganisms [12,13]. Furthermore, persistent secretion of IL-17 is involved in many inflammatory diseases [14,15,16,17]. Th17 cells also function as effective B cell helper cells by inducing B cell proliferation and antibody production [18]. As the bias towards pro-inflammatory cytokines and cells induces the development and perpetuation of autoimmunity, immunoregulatory factors are thought to straighten out the laterality. Regulatory T cells are crucial members of the family of immunoregulatory cells that preserve self-tolerance and fine-tune the immune response. Treg cells suppress inflammation by cell-cell contact or releasing cytokines, such as IL-10 or TGF-β, and they require the transcription factor FoxP3 for their differentiation [3,19]. In recent years, research has identified two types of Treg cells called natural Treg cells (nTreg) and inducible Treg cells (iTreg). nTreg cells develop in the thymus, and when entering peripheral tissues, they suppress self-reactive T cells. Studies in both mice and humans found that nTreg cells constitute around 10% of CD4 T cells in the periphery [20]. They express FoxP3 before they are released from the thymus, and the expression of TGF-β helps in their maintenance of inhibitory function after they migrate from the thymus [3,19]. Inducible Treg cells develop from naive T cells in the secondary lymphoid organ upon antigen exposure. Following interaction with TCR, TGF-β induce the FoxP3 expression in CD4+ CD25− cells, thereby, converting them to FoxP3+ CD4+ CD25+ cells [21]. These iTreg cells mediate their inhibitory activities by secretion of IL-10 or TGF-β, which is crucial for inhibiting overexuberant immune response [22] (Figure 1). COPD is a chronic inflammatory lung disease characterized by airway and/or alveolar abnormalities that cause obstructed airflow from the lungs [23]. Studies over the last decade highlighted the relevance of maintaining the balance between Th17 cells and Treg cells to control the inflammatory response in COPD. An increased Th17 response is involved in the progression of Chronic Obstructive Pulmonary Disease (COPD) in both clinical and experimental studies [23]. Th17 cytokine, IL-17A, levels were higher in the sputum of patients with COPD stages 3 and 4 compared to non-smokers and healthy smokers [24]. Reduced numbers of Treg cells were observed in the bronchial epithelium of severe/very severe COPD patients than in those with mild and moderate COPD and healthy smokers [25]. Zheng et al. analyzed the Th17/Treg ratio in lung tissues of no-smoking and no-COPD (CS−COPD−), smoking and no-COPD (CS+COPD−), and COPD patients [26]. Flow cytometric analysis revealed a significantly higher Th17/Treg ratio in the COPD group compared to non-smoking patients [26]. In a mouse model of COPD induced by chronic cigarette smoke (CS) exposure for 4 and 24 weeks, mice chronically exposed to CS showed higher lung Th17 prevalence, increased retinoic acid orphan receptor (ROR)-γt mRNA, and Th17-related cytokines (IL-17A, IL-6, and IL-23) compared to control mice [27]. In contrast, Treg cell prevalence, Forkhead box (Fox)p3 mRNA, and Treg-related cytokine IL-10 were significantly reduced in mice chronically exposed to CS [27]. Similarly, the lungs of mice exposed to CS for 12 and 24 weeks also showed higher Th17 (CD4+IL-17+) cells, RORγt mRNA expression, and IL-6, IL-17, and TGF-β1 levels compared to the control group. In contrast, Treg cells, Foxp3, and IL-10 expression were reduced in the CS-exposed groups. Additionally, the frequencies of Tregs were negatively correlated with Th17 cells (33). Acute respiratory distress syndrome (ARDS) is an important cause of acute pulmonary failure with severe disease and mortality [28]. The most common cause of ARDS is bacterial or viral pneumonia [28]. ARDS is characterized by dysregulated inflammation, increased permeability of microvascular barriers, and uncontrolled activation of coagulation pathways [28]. Activation of several immune cells, including neutrophils, macrophages, and dendritic cells, plays an important role in the development of ARDS [29]. The involvement of CD4+ T cells has been revealed recently for the pathogenesis of ARDS. ARDS patients show a higher frequency of Th17 cells and IL-17 compared to the control group [29]. The Th17/Treg ratio is higher in the peripheral blood of ARDS patients compared with the healthy controls [29]. A higher Th17/Treg ratio is associated with more adverse outcomes in ARDS patients. Mechanistically, recent studies demonstrated that secreted phosphoprotein 1 (SPP1) exacerbated lung inflammation in ARDS by modulating Th17/Treg balance [30]. SPP1 reduces the ubiquitination and degradation of HIF-1α, which, in turn, leads to a higher Th1/Treg ratio. IL-33 production in LPS-induced ARDS is reported to increase the Th17/Treg ratio [31]. IL-33 deficiency inhibits the differentiation of T cells into Th17 cells and restores Th17/Treg balance. Consequently, IL-33 deficiency significantly reduces inflammation in LPS-induced ARDS, whereas recombinant IL-33 treatment exacerbates lung inflammation [31]. Modulation of Th17/Treg balance is relevant to resolve lung inflammation in acute lung injury (ALI), a milder form of ARDS [32]. Alanyl-glutamine (Ala-Gln) was administered to attenuate lung injury in a model of lipopolysaccharide (LPS)-induced ALI. Ala-Gln treatment increased the percentages of Tregs in the BAL fluid, whereas Th17 cells were suppressed, compared to the control group [32]. Similarly, losartan (an antagonist of angiotensin II type 1 receptor) treatment led to the inhibition of Th17 polarization after LPS-induced ALI [33]. These studies point out that the Th17/Treg imbalance is a potential indicator of the disease severity in ARDS patients. Sarcoidosis is an inflammatory disorder characterized by granulomatous inflammation that affects multiple organs, mostly the lungs and mediastinal lymph nodes [34]. Emerging studies suggest the pleiotropic functions of Th17 and Treg cells in the pathogenesis of sarcoidosis. Higher IL-17A cytokine production is observed in the BALF of patients with pulmonary sarcoidosis [34]. Moreover, a higher Th17/Treg ratio was observed in peripheral blood and BAL of patients with active and progressive sarcoidosis [35]. After treatment with corticosteroids, the level of Foxp3 mRNA was elevated in the peripheral blood, and expression of RORγt mRNA was reduced [35]. Moreover, Treg cells of the lungs of sarcoidosis patients exhibit a high level of inducible co-stimulator (ICOS) expression [36]. ICOS expression on Treg enhances the immune suppressive ability of Tregs [36]. In addition, recent studies suggest that the Treg/Th17 ratio can be used as a suitable biomarker for predicting sarcoidosis relapse along with other indicators [37]. The clinical characteristics of relapsed patients were compared with those of stable patients after corticosteroid withdrawal. In the relapsed patients, compared with the stable patients, Tregs cells were increased in parallel with an increase in Th17 cell. Nevertheless, after the retreatment of relapsed patients, Tregs were increased, leading to a higher Treg/Th17 ratio [37]. Tregs are found to accumulate at the sarcoidosis BAL, periphery, and peripheral blood of patients with active disease more than that of healthy controls [38]. Peripheral sarcoidosis Tregs showed an impaired ability to suppress effector CD4+ T cell proliferation [39]. Further studies on sarcoidosis patients with spontaneous clinical resolution showed that Treg cells regained suppressive ability in these patients [39]. Altogether, these studies imply that Th17/Tregs ratio and their functional capacity influence the progression or regression of pulmonary sarcoidosis. Asthma is a chronic inflammatory disease of the airways involving inflammatory cells such as mast cells, eosinophils, neutrophils, macrophages, and T lymphocytes [40]. Typically, asthmatic inflammation is mediated by excessively activated Th2 cells eosinophilia [40], but recent studies showed the involvement of cytokine IL-17A in multiple asthma pathogenesis, including neutrophilic inflammation, steroid insensitivity, activation of epithelial cells, and airway remodeling [41]. A large number of cells positive for IL-17 are reported in the sputum and bronchioalveolar fluids (BALFs) of asthmatic patients [42]. In addition, many reports identified that levels of IL-17A are correlated positively with the severity of asthma [43,44,45]. Inhibition of IL-17 in a model of LPS-induced asthma exacerbation aid in controlling Th2 and Th17 responses and signaling pathways associated with inflammation and remodeling [46]. Several studies highlight the relevance of maintaining Th17/Treg balance in controlling inflammation and the pathophysiology of asthma. In a chronic experimental model of asthma induction by administration of OVA, higher numbers of Treg cells as well as the release of IL-10 was observed with the efficacy of photobiomodulation (PBM) treatment [47]. PBM treatment also reduced recruitment of inflammatory cells, such as macrophages, neutrophils, and lymphocytes in the bronchoalveolar lavage fluid and release of cytokines into the BALFs [47]. Recent studies characterized the role of Treg cell subsets in the pathogenesis of allergic asthma [48]. The proportion of CD25+Foxp3+CD127− Treg cells was reduced in the peripheral blood of allergic asthmatic patients compared to those of healthy subjects [48]. These circulating Treg cells in asthmatic patients expressed reduced CCR6 and IL-17 compared with healthy subjects. However, in a mouse model of allergic asthma induced by house dust mite (HDM), the CCR6+Treg cell number increased in the lung tissue [48]. Under the Th17 environment in the lung, CCR6+Treg cells differentiate into Th17-like cells. This Treg subset is the major pro-inflammatory Treg that promotes inflammation, producing IL-17 instead of immunoregulatory cytokines to exacerbate allergic asthma [48]. In children with allergic rhinitis accompanying bronchial asthma, a reduction in total Tregs was observed, whereas Th17 cells and plasma IL-17 levels were increased [49]. An imbalance of Th17/Treg was also correlated with airway hyperresponsiveness in asthmatic children [50]. In line with this, a combination of inhaled glucocorticoids (ICS) with long-acting β2-agonists (LABA) reduced Th17 cells and decreased the Th17/Treg ratio in house dust mites (HDM) allergic asthmatic children, leading to improvement clinically [51]. Moreover, the expansion of Th17 cells and reduction in regulatory CD4+ T cell subsets was identified as a mechanism by which leptin increases allergic asthma in obesity [52]. These studies using animal models and human studies support the relevance of maintaining Th17/Treg balance in controlling airway inflammation in asthma. In addition to their role in non-infectious inflammatory lung diseases, maintaining Th17 /Treg balance is important for protective immunity against lung infections. Human IL-17A and IL-17F are crucial for protective immunity against mucocutaneous candidiasis [53]. Treg cells prevent the differentiation of naïve T cells into Th17 cells and prevent the clearance of Candida albicans infection [54]. IL-17 is identified as a critical factor required for protective immunity to Pneumocystis infection. Administration of anti-IL-17 neutralizing antibody to wild-type mice infected with P. carinii resulted in severe fungal infection [55]. Similarly, regulatory T cells are recruited to the lung during the course of Pneumocystis infection in mice [56]. Depletion of the Treg population results in increased levels of IL-1β and IL-6, leading to increased lung injury [56]. Th17/Treg balance also acts as a critical factor for controlling lung inflammation during chlamydial infection. IL-17A produced by Th17 cells during chlamydial lung infection has a significant impact on the development of protective type 1 immunity [57,58,59]. Chlamydial lung infection of mice induced IL-17 production in lung and lymph nodes at earlier and later stages of infection [60]. Neutralization of IL-17 in mice resulted in higher body weight loss, bacterial burden, and more severe pathological changes in the lung compared with sham-treated control mice [60]. IL-17 neutralized mice exhibit reduced Th1 responses, increased Th2 responses, and altered DC phenotype. Moreover, the adoptive transfer of DC isolated from IL-17-neutralized mice failed to protect the recipients against challenge infection compared to DC from sham-treated mice [60]. Further examination identified IL-17A producers at early and later stages of chlamydial lung infection. Previous studies in Yang lab have shown that γδ T cells are the major producers of IL-17A at the initial stage of infection and quickly return to the background level at day 4 post-infection. Studies on the γδ T cell subsets further identified that Vγ4+T cells are the major IL-17A producing γδ T cell subset at the early stages of chlamydial lung infection [61]. IL-17A produced by γδ T cells has a promoting role in Th17 responses but no significant influence on T helper 1 response [57]. On the other hand, IL-17A produced by Th17 cells at later stages of chlamydial infection has a significant impact on the development of protective type 1 immunity [57]. These studies collectively suggest that IL-17A-mediated protection against chlamydial lung infection depends mainly on Th17 cells rather than γδ T cells [57]. In contrast to the findings in lung infections, either IL-17 receptor signaling or IL-23-dependent induction of IL-22 and IL-17 is reported to be indispensable for the resolution of genital tract infections [62,63]. On the other hand, higher Treg responses contribute to tissue pathology after chlamydial lung infection [58,59]. Treg cells are observed in the chlamydial infection site of both humans and mice [64,65,66]. Similarly, our recent studies suggested that NK cells provide protective immunity to chlamydial lung infection by maintaining Th17/Treg balance [67,68]. During Chlamydophila pneumoniae (Cpn) lung infection, NK cell depletion increased the number of Treg cells and IL-10-producing CD4+ T cells. The changes in T cell responses were associated with severe disease and bacterial load in the lung. Adoptive transfer of DCs from NK cell-deficient mice induced Treg cells in the recipient mice, which promotes pathological response [67]. In the mice model of Chlamydia muridarum lung infection, NK cell depletion resulted in lower IL-17 cytokine production and Th17 cells [68]. On the other hand, NK cell-depleted mice exhibited increased production of CD4+ CD25+ Foxp3+ T cells resulting in a reduced Th17/Treg ratio [68]. These studies highlight that an imbalance between Treg cells and Th17 cells acts as a major factor determining the severity of lung infection. In some lung infections, a higher Th17/Treg ratio contributes to the severity of the disease. An imbalance in Th17/Treg ratio was also observed in patients with Mycoplasma pneumoniae (MP) infection [69]. Refractory MP pneumonia patients showed a higher Th17/Treg ratio than non-refractory MP pneumonia patients and the control group [69]. It suggests that patients with refractory MP pneumonia have a balance shifted toward the induction of inflammatory responses, while patients with non-refractory MP pneumonia have a balance shifted toward the inhibition of inflammatory responses. It is found that Respiratory syncytial virus (RSV) infection, a major causative agent of pneumonia in infants, increases Th17/Treg ratio, thereby disrupting asthmatic tolerance [70]. Similarly, studies by Qin et al. showed that infection of human bronchial epithelial cells by RSV induces differentiation of lymphocytes into Th17 cells while inhibiting differentiation into Treg cells [71]. In the peripheral blood of infants with RSV bronchiolitis, the percentage of Tregs and the levels of IL-10 and TGF-β were significantly lower compared to those with non-RSV pneumonia and healthy infants [72]. On the other hand, the percentage of Th17 cells and the level of IL-17 were significantly higher in infants with RSV bronchiolitis compared to those with non-RSV pneumonia and healthy infants [72]. Based on the previous studies, it is clear that maintaining Th17/Treg balance by blocking Th17 cell differentiation or inducing Treg activation will effectively treat various inflammatory diseases. To control inflammation in COPD, PBMC from COPD patients was treated with Tiotropium (anticholinergic drug) and Olodaterol (long-acting β2-agonist) [73]. The treatments reduced the percentage of T cells co-expressing acetylcholine (Ach)IL-17A, AChIL-22, and AChRORγt while increasing the Foxp3-expressing T cells in PBMC from COPD patients [73]. In a mice model of lung inflammation and emphysema induced by elastin peptides (EP) intranasally, treatment with erythromycin reduced the Th17 cells while increasing the Treg response [74]. In addition, erythromycin treatment suppressed cigarette smoke extract-exposed dendritic cell-mediated polarization of CD4+ T cells into Th17 cells [75]. The effect of treatment with N-Acetylcysteine (NAC) was tested in COPD patients [76]. Oral administration of NAC significantly reduced the frequencies of Th17 cells in the peripheral blood of the COPD patients group compared to those in the control group [76]. On the contrary, Treg cell frequencies increased in treated COPD patients. Mechanistically, NAC regulated Th17/Treg balance by downregulating HIF1-α, which induced RORγt transcription and Foxp3 protein degradation [76]. Similarly, simvastatin, a clinically used cholesterol-lowering agent, inhibits IL-17 but enhances IL-10 to reverse Th17/Treg imbalance in COPD patients [77]. Blocking IL-17 or cytokines that activate Th17 cells is used as a strategy to alleviate asthmatic inflammation. Anti-IL-17 monoclonal antibodies (mAb) treatment before allergen inhalation strongly reduced bronchial neutrophil infiltration in a mouse model of allergic asthma [78]. Resolvin E1 (RvE1) suppresses IL-23 and IL-6 production to promote the resolution of allergic airway inflammation [79]. IL-23 and IL-6 cytokines, in turn, promote the survival and differentiation of Th17 cells [79]. Dopamine D1-like receptor antagonist attenuates allergic airway inflammation by inhibiting the production of IL-17 and infiltration of Th17 cells in the lung [80]. Similarly, RAPA (inhibitor of mammalian target of rapamycin) treatment inhibits OVA-induced neutrophilic airway inflammation by suppressing Th17 cell differentiation [81]. Administration of rosiglitazone or pioglitazone (peroxisome proliferator-activated receptor agonists) reduced infiltration of inflammatory cells and inhibited IL-17 expression after OVA inhalation [82]. On the other hand, rosiglitazone or pioglitazone administration further enhanced IL-10 cytokine in lung tissues after ovalbumin inhalation [83]. Recent studies demonstrated that Tregitopes (T regulatory epitopes) attenuated airway hyperresponsiveness and inflammation in a murine model of allergic asthma [84]. Tregitopes induce highly suppressive allergen-specific Tregs, which inhibit inflammatory response [84]. Antigen-specific immunotherapy (ASIT) is one of the major methods of in vivo induction of Tregs in allergic asthma. Grass tablet sublingual immunotherapy downregulates the Th2 cytokine response and increases regulatory T-cells [85]. Similarly, dual sublingual immunotherapy enhanced regulatory T cell function with lower DNA methylation of CpG sites within the Foxp3 locus [86]. In a mouse model of allergic asthma, exogenous Semaphorin 3E (Sema3E) treatment reduces Th17 cytokine response leading to diminished collagen deposition, airway hyperresponsiveness, and eosinophilic inflammation [87]. The therapeutic function of Sema3E is also investigated in bacterial infection [59]. Exogenous Sema3E treatment protects mice from chlamydial infection with reduced chlamydial load, lower body weight loss, and pathological changes in the lungs [59]. Sema3E treatment resulted in higher Th1/Th17 response but reduced Treg response in the lungs of chlamydia-infected mice compared to saline-Fc treated mice [59]. The importance of the balance between pro-inflammatory and anti-inflammatory cytokines and cells in maintaining immune homeostasis is widely acknowledged. Th17 cells promote inflammation and pathology, whereas Treg cells maintain self-tolerance. The balance between inflammation and self-tolerance is disrupted, leading to inflammation. Developing therapeutic approaches focusing on Th17/Treg imbalance is likely an efficient way to prevent and/or treat various inflammatory diseases.

PMC10003151

Justin N. Williams,Mavis Irwin,Yong Li,Anuradha Valiya Kambrath,Brett T. Mattingly,Sheel Patel,Mizuho Kittaka,Rebecca N. Collins,Nicholas A. Clough,Emma H. Doud,Amber L. Mosley,Teresita Bellido,Angela Bruzzaniti,Lilian I. Plotkin,Jonathan C. Trinidad,William R. Thompson,Lynda F. Bonewald,Uma Sankar

Osteocyte-Derived CaMKK2 Regulates Osteoclasts and Bone Mass in a Sex-Dependent Manner through Secreted Calpastatin

01-03-2023

extracellular calpastatin,Ca2+/calmodulin (CaM)-dependent protein kinase kinase 2,osteocytes,osteoclasts,bone remodeling

Calcium/calmodulin (CaM)-dependent protein kinase kinase 2 (CaMKK2) regulates bone remodeling through its effects on osteoblasts and osteoclasts. However, its role in osteocytes, the most abundant bone cell type and the master regulator of bone remodeling, remains unknown. Here we report that the conditional deletion of CaMKK2 from osteocytes using Dentine matrix protein 1 (Dmp1)-8kb-Cre mice led to enhanced bone mass only in female mice owing to a suppression of osteoclasts. Conditioned media isolated from female CaMKK2-deficient osteocytes inhibited osteoclast formation and function in in vitro assays, indicating a role for osteocyte-secreted factors. Proteomics analysis revealed significantly higher levels of extracellular calpastatin, a specific inhibitor of calcium-dependent cysteine proteases calpains, in female CaMKK2 null osteocyte conditioned media, compared to media from female control osteocytes. Further, exogenously added non-cell permeable recombinant calpastatin domain I elicited a marked, dose-dependent inhibition of female wild-type osteoclasts and depletion of calpastatin from female CaMKK2-deficient osteocyte conditioned media reversed the inhibition of matrix resorption by osteoclasts. Our findings reveal a novel role for extracellular calpastatin in regulating female osteoclast function and unravel a novel CaMKK2-mediated paracrine mechanism of osteoclast regulation by female osteocytes.

Osteocyte-Derived CaMKK2 Regulates Osteoclasts and Bone Mass in a Sex-Dependent Manner through Secreted Calpastatin Calcium/calmodulin (CaM)-dependent protein kinase kinase 2 (CaMKK2) regulates bone remodeling through its effects on osteoblasts and osteoclasts. However, its role in osteocytes, the most abundant bone cell type and the master regulator of bone remodeling, remains unknown. Here we report that the conditional deletion of CaMKK2 from osteocytes using Dentine matrix protein 1 (Dmp1)-8kb-Cre mice led to enhanced bone mass only in female mice owing to a suppression of osteoclasts. Conditioned media isolated from female CaMKK2-deficient osteocytes inhibited osteoclast formation and function in in vitro assays, indicating a role for osteocyte-secreted factors. Proteomics analysis revealed significantly higher levels of extracellular calpastatin, a specific inhibitor of calcium-dependent cysteine proteases calpains, in female CaMKK2 null osteocyte conditioned media, compared to media from female control osteocytes. Further, exogenously added non-cell permeable recombinant calpastatin domain I elicited a marked, dose-dependent inhibition of female wild-type osteoclasts and depletion of calpastatin from female CaMKK2-deficient osteocyte conditioned media reversed the inhibition of matrix resorption by osteoclasts. Our findings reveal a novel role for extracellular calpastatin in regulating female osteoclast function and unravel a novel CaMKK2-mediated paracrine mechanism of osteoclast regulation by female osteocytes. Bone is a dynamic tissue, uniquely capable of self-renewing through the process of bone remodeling, which involves the sequential and coupled activities of bone-forming osteoblasts (OBs) and bone-resorbing osteoclasts (OCs) [1]. OBs and OCs in turn are regulated by osteocytes, the most abundant bone cells that originate from matrix-entrapped OBs [2,3]. Osteocytes integrate hormonal and mechanical signals to regulate bone homeostasis. As endocrine cells, osteocytes secrete several key factors including sclerostin (Sost), Dickkopf-1 (DKK1), and osteoprotegerin (Opg), which regulate OB and OC functions [4,5,6]. However, the molecular mechanisms by which osteocytes regulate bone remodeling are not fully understood. The Ca2+/calmodulin (CaM)-dependent protein kinase (CaMK) signaling cascade, initiated by transient increases in intracellular Ca2+, involves multifunctional serine/threonine protein kinases CaMKK1 and CaMKK2, and their canonical substrates CaMKI and CaMKIV [7]. CaMKK2 additionally phosphorylates and activates adenosine monophosphate activated protein kinase (AMPK) to coordinate cellular and organismal energy balance [8,9,10,11]. Consequently, inhibition or loss of CaMKK2 in mice protects from diet-induced obesity and insulin resistance [10,11]. CaMKK2 also coordinates inflammatory responses in macrophages and chondrocytes [12,13]. In the skeleton, CaMKK2 plays cell-intrinsic roles in OBs and OCs. Mice lacking CaMKK2 globally (Camkk2-/-) possess more OBs, fewer OCs and increased bone mass compared to wild-type (WT) mice [14]. Blocking CaMKK2 activity using its selective pharmacological inhibitor STO-609 reverses age-associated decline in trabecular and cortical bone mass and strength, prevents ovariectomy-induced bone loss, and enhances bone fracture healing [15,16,17]. Camkk2-/- bone marrow-derived progenitors yield higher numbers of alkaline phosphatase-positive OBs in vitro than WT, in part via activation of cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA), and fewer OCs through the downregulation of cyclic adenosine monophosphate (cAMP) response element binding protein (pCREB)—nuclear factor of activated T cells, cytoplasmic (NFATc1) signaling, indicating cell intrinsic roles for CaMKK2 in OBs and OCs [14]. However, the specific roles of CaMKK2 in osteocytes remain unknown. In this study, we tested the hypothesis that osteocyte-derived CaMKK2 plays an important role in the regulation of bone growth and maintenance using in vivo and in vitro approaches. Our findings reveal a cell-intrinsic role for CaMKK2 in osteocytes in the regulation of OCs in a sex-dependent manner through a novel paracrine mechanism involving secreted calpastatin. We crossbred Camkk2flox/flox mice with transgenic mice expressing Cre driven by a 8-kb dentin matrix protein 1 (Dmp1) promoter to generate heterozygous Dmp1-8kb-Cre::Camkk2flox/WT mice which were then mated to generate male and female Dmp1-8kb-Cre::Camkk2WT/WT (Control) and Dmp1-8kb-Cre::Camkk2flox/flox (Camkk2ΔOCY) mice [11,18,19] (Figure 1A). Camkk2 mRNA levels were 13-fold lower in primary Camkk2ΔOCY osteocytes compared to control osteocytes in both sexes (Figure 1B,C). Deletion of CaMKK2 from osteocytes in female and male Camkk2ΔOCY mice was also confirmed by immunohistochemistry (IHC; Figure 1D,Di,E,Ei). Conditional deletion of CaMKK2 did not affect osteocyte numbers in either sex (Figure 1F,G). Examination of distal femora using micro-computed tomography (µCT) revealed a 2.2-fold increase in bone volume fraction (%BV/TV) in 12-week (w)-old female Camkk2ΔOCY mice compared to age-and sex-matched controls (Figure 1H,Hi). Female Camkk2ΔOCY long bones also possessed significantly higher trabecular number and lower trabecular separation compared to controls mice, whereas no differences were observed in trabecular thickness (Figure 1Hii–Hiv). In contrast, BV/TV (%) and trabecular bone microarchitecture remained similar between 12-week-old male Camkk2ΔOCY and control mice (Figure 1I–Iiv). Cortical bone area, cross-sectional thickness, and polar moment of inertia were similar among cohorts of both sex (Supplementary Figure S1A,B). These data indicate a sex divergent effect on trabecular bone mass by osteocyte-derived CaMKK2. We next evaluated whether deletion of CaMKK2 in osteocytes affected bone remodeling. Examination of Von Kossa–McNeil (VKM) stained femur sections revealed significantly higher numbers of OBs in female Camkk2ΔOCY mice compared to female controls, whereas OB numbers were similar in male Camkk2ΔOCY and control femurs (Figure 2A,Ai,B,Bi). In contrast, osteoid surface and osteoid thickness remained similar between sex-matched cohorts (Figure 2Aii,Aiii,Bii,Biii). Further, dynamic histomorphometry of double-fluorochrome labeled long bone sections revealed no differences in mineralizing surface, mineral apposition rate or bone formation rate between sex-matched Camkk2ΔOCY and control mice (Figure 2C–Ciii,D–Diii). Thus, changes in bone formation were not likely the cause of the female-specific increase in cancellous bone mass in female Camkk2ΔOCY. Static histomorphometry of tartrate-resistant acid phosphatase (TRAP)-stained bone sections revealed a 1.7-fold reduction in OC numbers and OC surface to bone surface in female Camkk2ΔOCY mice compared to controls, whereas no such differences were observed in male mice (Figure 2E–Eii,F–Fii). These histomorphometry data revealed a role for osteocytic CaMKK2 in the regulation of OCs in female mice. We surmised that the differential regulation of OCs by female Camkk2ΔOCY osteocytes occurs through secreted factors. To test this, we isolated primary osteocytes from male and female control and Camkk2ΔOCY long bones and evaluated the ability of the respective conditioned media (CM) to support OB and OC differentiation by primary wildtype (WT) bone marrow (BM)-derived cells (Figure 3A). We observed no differences in the ability of male or female, control or Camkk2ΔOCY osteocyte CM to support OB differentiation by WT BM-derived mesenchymal stem cells (MSCs) in vitro as evidenced by alkaline phosphatase or alizarin red staining intensities (Figure 3B,C). In contrast, WT BM cells exposed to CM from female Camkk2ΔOCY osteocytes yielded 1.7-fold fewer multinuclear TRAP-positive OCs than cells receiving female control CM (Figure 3D,Fi). On the other hand, WT BM cells yielded similar numbers of TRAP-positive multinuclear OCs when treated with male control or Camkk2ΔOCY osteocyte CM (Figure 3D,Gi). Next, to assess the effects of osteocyte CM on OC function, we plated WT BM cells on hydroxyapatite-coated wells in the presence or absence of osteocyte CM and assessed resorption. BM cells that received female Camkk2ΔOCY osteocyte CM formed 3-fold fewer resorption pits and resorbed 3-fold lower hydroxyapatite area than cells exposed to control CM (Figure 3E,Fii,Fiii), whereas no such differences were observed when BM cells were treated with male Camkk2ΔOCY or control CM (Figure 3E,Gii,Giii). It is well documented that osteocytes regulate OC differentiation through the altered expression of receptor activator of nuclear factor κ-B ligand (Rankl) and Opg [20,21]. However, we found no significant differences in Rankl or Opg mRNA levels or their ratio in male and female Camkk2ΔOCY osteocytes compared to controls (Supplementary Figure S2A,B), indicating the presence of another mechanism. To identify OC-inhibitory factors secreted by CaMKK2-deficient female osteocytes, we concentrated serum-free CM harvested from male and female control and Camkk2ΔOCY osteocytes and performed proteomic analysis of the secretome using mass spectrometry (LC-MS/MS) (Figure 4A). The experiments were conducted in triplicate and to initially assess the underlying reproducibility and accuracy of the data, we conducted principal component analysis. This revealed grouping of experimental replicates from the same cohort, and divergence of male and female osteocyte CM samples (Figure 4B), consistent with reproducible proteomic data. Although Camkk2ΔOCY male CM samples displayed more overall variability than other groups within the principal component analysis, they still clustered with each other and apart from the other groups. Mass spectrometry detected a total of 1182 proteins, including 9293 unique peptides, in male and female osteocyte CM. Of these, 236 proteins were upregulated, 108 proteins were downregulated in male and female Camkk2ΔOCY osteocyte CM compared to sex-matched controls, and 117 proteins were significantly altered only in female Camkk2ΔOCY secretome (Figure 4C). Functional annotation analysis confirmed association of the majority of detected proteins with extracellular compartments, including exosomes, vesicles, and extracellular matrix (ECM; Figure 4D), confirming that our CM primarily consisted of secreted and cell surface associated proteins. Reactome pathway analysis identified several pathways associated with degradation of ECM, protein metabolism, and Golgi-associated vesicle biosynthesis and anterograde transport to be significantly altered selectively in female Camkk2ΔOCY osteocyte CM (Table 1). Of the proteins associated with ECM degradation, calpastatin, the specific inhibitor of Ca2+-dependent cysteine proteases called calpains, was of particular interest as its activity is regulated by Ca2+; it possesses CaM-binding domains; and its target calpain has crucial roles in OCs [22,23,24,25]. Though predominantly intracellular, calpastatin and calpains are also secreted molecules [26,27]. Calpastatin was among a group of 62 proteins that were highly enriched in CM from female Camkk2ΔOCY osteocytes, but not detected in CM from female control osteocytes. On the other hand, levels of calpastatin in male Camkk2ΔOCY osteocyte CM were not significantly different from those in male control CM (Figure 4E,Ei,F,Fi). Enzyme-linked immunosorbent assay (ELISA) of CM indicated a 3-fold increase in secreted calpastatin in female Camkk2ΔOCY CM compared to female control CM (Figure 4G). On the other hand, extracellular calpastatin levels in male Camkk2ΔOCY osteocyte CM were only slightly higher than those in control male CM, and the differences were not statistically significant (Figure 4G). Of note, the female control CM possessed the least amount of extracellular calpastatin of all four cohorts. We next examined intracellular levels of calpastatin in these osteocytes and found that both male and female Camkk2ΔOCY osteocytes possessed 3.7–3.9-fold higher intracellular calpastatin compared to sex-matched controls (Figure 4H–Hii). Thus, whereas intracellular calpastatin is elevated in CaMKK2-deficient osteocytes of both sexes, the differential increase in extracellular calpastatin was observed only in CM from CaMKK2-deficient female osteocytes. To understand whether extracellular calpastatin inhibited OC differentiation and function, we treated male and female WT BM cells undergoing RANKL-mediated OC differentiation with varying doses of recombinant human calpastatin domain I, which is non-cell-permeable (NCP) [28,29]. Treatment of female WT BM cells with 0.5, 1.0 and 5.0 µM NCP-calpastatin elicited a 1.7, 1.9 and 3.7-fold decrease in resorption pit number and area resorbed, compared to untreated cells (Supplementary Figure S3A–C). In contrast, only 5.0 µM NCP-calpastatin caused a significant 2-fold reduction in resorption pit number and area resorbed by male WT BM cells undergoing RANKL-mediated OC differentiation, compared to untreated cells (Supplementary Figure S3A,E,F). On the other hand, NCP-calpastatin elicited a dose-dependent reduction in the number of multinuclear OCs produced by male and female WT BM cells (Supplementary Figure S3D,G). Of note, treatment with 5.0 µM NCP-calpastatin resulted in smaller and fewer OCs and resorption pits in cells from either sex. Taken together, our results indicate that, whereas extracellular NCP-calpastatin inhibited OC differentiation in both sexes, it inhibited OC function, only in females. To further investigate the OC-inhibitory role of secreted calpastatin, we incubated female Camkk2ΔOCY osteocyte CM with anti-calpastatin antibody or control IgG and assessed the ability of calpastatin-depleted or IgG-incubated CM to support RANKL-mediated OC differentiation by WT BM cells (Figure 5A–C). Consistent with our previous results (Figure 3D,F), we observed 1.8-fold fewer OCs and a 2.8-fold reduction in the number of resorption sites and area resorbed when WT BM cells were treated with IgG-incubated female Camkk2ΔOCY osteocyte CM (Figure 5C,Ci,D–Dii). Depletion of calpastatin fully reversed the inhibition of OC resorption by female Camkk2ΔOCY CM (Figure 5D–Dii). The main function of calpastatin is calpain inhibition. Secreted calpains cleave ECM components to enable cell spreading, ECM attachment and migration in other cell types [28,29]. Since female Camkk2ΔOCY osteocyte CM inhibits OC differentiation, we surmised that extracellular calpastatin present in the CM blocks migration of osteoclast progenitors towards each other. We performed in vitro monolayer scratch assays to test this and found WT BM cells treated with control CM as well as IgG- or calpastatin-depleted Camkk2ΔOCY CM to display similar rates of migration (Supplementary Figure S4A–C), indicating that extracellular calpastatin does not inhibit cell migration. We next assessed whether calpastatin in the CM affects formation of actin ring-mediated sealing zone that is required for attachment of OCs to bone matrix. WT-BM-derived OCs treated with female control CM, IgG-exposed or calpastatin-depleted Camkk2ΔOCY CM were stained with rhodamine-phalloidin to detect filamentous (F) actin. OC precursors treated with female control osteocyte CM formed multinuclear OCs with large distinct F-actin rings on glass coverslips (Figure 5E). In contrast, OCs treated with IgG-incubated female Camkk2ΔOCY CM were smaller with poorly defined F-actin rings, whereas depletion of calpastatin resulted in larger OCs with more distinct F-actin rings (Figure 5E). Taken together, our data indicate a novel paracrine role for osteocyte-derived CaMKK2 in the regulation of OC differentiation and function through a secreted calpastatin-mediated mechanism. The objective of the current study was to investigate a cell-intrinsic role of CaMKK2 in osteocytes, the master regulators of skeletal homeostasis [6]. Conditional deletion of CaMKK2 from osteocytes elicits a sex-dependent effect on the skeleton. Specifically, we observed enhanced bone mass coupled with fewer OCs in female but not male Camkk2ΔOCY mice. Further, CM isolated from female Camkk2ΔOCY osteocytes suppressed OC formation and function. Calpastatin, a specific inhibitor of Ca2+-activated calpains, was highly enriched in female Camkk2ΔOCY CM, its intracellular levels were significantly elevated in male and female Camkk2ΔOCY osteocytes whereas its extracellular levels were differentially altered only in female Camkk2ΔOCY CM. Levels of extracellular calpastatin were significantly lower in female control osteocyte CM compared to males, and the reason for this suppression is not clear. Immunodepletion of calpastatin attenuated the inhibition of OC function by female Camkk2ΔOCY CM. Moreover, treatment of WT BM-derived myeloid cells with exogenous non-cell permeable calpastatin caused a more pronounced inhibitory effect on OC resorption in female-derived cells than male. Based on these cumulative data, we propose that CaMKK2 is an inhibitor of calpastatin expression in osteocytes and that osteocyte-secreted calpastatin blocks OC function in a sex-specific manner (Figure 5F). Thus, our studies identify a novel sex-specific paracrine role for osteocyte-derived extracellular calpastatin in the regulation of OCs. Calpastatin is the chief inhibitor of Ca2+-dependent cysteine proteases called calpains [22]. Calpains proteolyze several intracellular substrates to critically regulate a multitude of cellular processes such as cell motility, spreading, and adhesion to ECM in multiple cell types including OBs and OCs [24,25,30,31,32,33]. In OCs, cleavage by intracellular calpains of their substrates enriched in actin ring, such as talin, filamin A, and Pyk2, is crucial for OC motility, spreading, sealing zone formation, and bone resorption [32,34]. Though predominantly intracellular, extracellular calpains that cleave ECM components have been reported in several systems including OBs, hypertrophic chondrocytes, healing bone fracture calluses, and synovial fluid from rheumatoid arthritis (RA) and osteoarthritis (OA) patients [35,36,37,38,39,40,41]. Calpastatin is also a secreted molecule found in the synovial fluid of RA and OA patients, plasma of patients with pulmonary arterial hypertension, and exosomes from luminal fluid of ovine uterus [28,42,43]. In this study, we demonstrate for the first time that calpastatin is secreted by osteocytes and that extracellular calpastatin acts to regulate the formation and function of female OCs. Mammalian calpastatin is encoded by a single gene (Cast), but the use of multiple promoters and alternative splicing mechanisms leads to the generation of many calpastatin isoforms that vary in molecular mass from 17.5 kDa to 85 kDa [44,45]. Multiple calpastatin isoforms are often present in the same tissue and even cell type. Calpastatin protein consists of an N-terminal L domain devoid of inhibitory activity and four repetitive inhibitory domains (I–IV) that bind to and inhibit calpain in a Ca2+-dependent manner [44,45]. We observed two intracellular calpastatin isoforms, a predominant 120 kDa species and a minor 80 kDa species in murine osteocytes through immunoblotting, and both isoforms were enhanced in CaMKK2-deficient osteocytes, regardless of biological sex (Figure 4H). Though the size of the osteocyte-secreted calpastatin is unknown, we surmise that it is the 80 kDa isoform since the lacunar–canalicular transport has a molecular cut off limit of 70–80 kDa [46,47]. Further, phosphorylation of calpastatin by Ser/Thr kinases protein kinase A or protein kinase C decreases its efficiency of calpain inhibition [22]. Being a Ser/Thr kinase, CaMKK2 potentially regulates calpastatin levels and/or activity via phosphorylation, and its absence could enhance the levels of both intracellular and extracellular calpastatin in both sexes. Extracellular calpastatin is non-cell permeable [28]. Accordingly, exposure of OCs to female osteocyte CM did not alter intracellular levels of calpastatin, calpain substrate talin or calpain activator PKA (Supplementary Figure S4D). How might osteocyte-secreted calpastatin regulate OCs? The only known function of calpastatin is calpain inhibition, and others have postulated that the regulatory effects of secreted calpastatin mainly involve the inhibition of extracellular calpain [28,48]. Secreted calpains cleave ECM components to facilitate the disengagement of αVβ3 integrins with ECM and enable cell migration [28,29]. However, migration of OC precursors is not influenced by extracellular calpastatin (Supplementary Figure S4A–C). On the other hand, WT BM-derived myeloid progenitors treated with calpastatin-containing female Camkk2ΔOCY osteocyte CM formed fewer functionally deficient OCs that were also smaller with indistinct F-actin rings, consistent with our in vivo data from female Camkk2ΔOCY long bones. Further, depletion of calpastatin from the CM completely reversed the inhibition of OC function by female Camkk2ΔOCY osteocyte CM. Although the mechanism by which extracellular calpastatin regulates OCs is unclear, we hypothesize that osteocyte-secreted calpastatin inhibits OCs either by inhibiting secreted calpain or via an independent mechanism. It is also intriguing why the OC-inhibitory effects of extracellular calpastatin, osteocyte-derived or recombinant, are more pronounced in females. Further, the in vivo phenotype of fewer OCs and enhanced bone mass was also only observed in female Camkk2ΔOCY mice. It is likely that sex-divergent signaling mechanisms downstream of secreted calpastatin in female and male OC precursors are responsible for this dichotomy. On the other hand, our proteomics analyses also identified 116 other proteins to be uniquely altered in the female Camkk2ΔOCY osteocyte secretome. Some of these proteins may also play OC-inhibitory roles, potentially collaborating with secreted calpastatin. In conclusion, we identified a novel cell-intrinsic role for CaMKK2 in osteocytes that results in paracrine effects on OC formation and activity leading to enhanced bone mass only in female mice. This phenotype is in part due to a novel mechanism wherein extracellular calpastatin secreted by osteocytes inhibits bone resorption by female OCs. This novel osteocyte-secreted-calpastatin mechanism could be therapeutically leveraged to treat osteoporosis in women. All animal procedures were performed with prior approval from Indiana University School of Medicine Institutional Animal Care and Use Committee (IACUC). All experiments were performed in compliance with NIH guidelines on the use and care of laboratory and experimental animals. All animals were housed in the Indiana University School of Medicine Laboratory Animal Resource Center (LARC, Indianapolis, IN, USA) under a 12-h light, 12-h dark cycle. Food and water were provided ad libitum. All mice generated in this study were derived of C57BL/6J background. Dentin matrix protein (Dmp1)-8kb-Cre+ mice [18,19] were provided by Dr. Teresita Bellido and Camkk2flox/flox mice have been described previously [11]. We first generated Dmp1-Cre-Camkk2flox+/- by breeding the Dmp1-Cre and Camkk2fl/fl mice. Then we crossed the heterozygous mice to generate Dmp1-Cre::Camkk2+/+ (Control) mice and Dmp1-Cre::Camkk2fl/fl (Camkk2OCY) mice (Figure 1A). Dmp1-Cre+::Camkk2+/+ mice were used to control for potential non-specific effects of Dmp1- regulated Cre recombinase. For all skeletal phenotyping and osteocyte isolation experiments, mice of either sex were used at 12 weeks (w) of age. Bone marrow isolations were performed using 6-week-old wild-type (WT) mice. Long bones were excised at 12 weeks of age and fixed in 4% paraformaldehyde (PFA) for 48 h at 4 °C and transferred to 70% ethanol. Micro-computed tomography (μCT) was performed on femurs at a 5.87 µm image pixel size using a Bruker 1172 μCT system (59 kV, 167 µA, 0.7 rotation step, 0.5 aluminum filter). Reconstructed μCT images (NRecon software, Kontich, Belgium) were analyzed using CT Analyzer software (Skyscan, Kontich, Belgium). The trabecular bone compartment was analyzed within 1 mm proximal of the distal growth plate, while femoral midshaft architecture was measured using cross-sections approximately 3.5 mm proximal to the distal growth plate. Reconstructed 3D models were generated using CTVox software (Skyscan, Kontich, Belgium), from which trabecular bone volume per total volume (BV/TV) (%),trabecular number (Tb.N) (mm−1), trabecular thickness (Tb.Th) (mm), and trabecular separation (Tb.Sp) (mm) as well as cortical bone parameters were calculated using established guidelines [49]. Bone histology was performed by the Indiana Center for Musculoskeletal Health Musculoskeletal Histology Core. Following μCT analysis, dynamic and static histomorphometry were performed on undecalcified femurs embedded in poly-methyl methacrylate (plastic). Longitudinal sections cut at 5 µm thickness were stained with Von Kossa and McNeal’s (VKM) to assess OB numbers and osteoid parameters. Sections were also stained for tartrate-resistant acid phosphatase (TRAP) activity following with hematoxylin counterstain to measure OC parameters. Bone formation and mineralization parameters were measured based on incorporation of dual fluorochrome labels of calcein and alizarin, which mice received via I.P. injection approximately 7 and 2 days prior to euthanasia. Parameters measured included single-label perimeter (sL.Pm), double-label perimeter (dL.Pm), and interlabel width (Ir.L.Wi). From these primary measurements, the following outcome parameters were calculated: mineral apposition rate (MAR = Ir.L.Wi/7 days [µm/day]); mineralizing surface (MS/BS = (0.5 ∗ sL.Pm + dl.Pm)/B.Pm ∗100 [%]); and bone formation rate (BFR/BS = MAR ∗ MS/BS ∗ 365 [µm3/µm2/year]). Static and dynamic measurements and calculations followed the guidelines of the American Society for Bone and Mineral Research Histomorphometry Nomenclature Committee [50]. Long bones were decalcified in 14% EDTA (pH 7.4) and dehydrated before paraffin embedding. Five µm thick serial sections were generated, deparaffinized and incubated with primary antibody against CaMKK2 (rabbit anti-CaMKK2-NT; cat# 033168, US Biological, Salem, MA, USA; 1:100 dilution) and anti-rabbit secondary (Jackson Immunoresearch, West Grove, PA, USA) and counterstained with Gill No. 1 Hematoxylin or Methyl Green (Millipore Sigma, Burlington, MA, USA). Images captured using a Leica DMi8 microscope were processed with Leica LAS-X software (Leica CM1950, Wetzlar, Germany), and quantified by counting immunopositive and total osteocytes within cortical bone from 4 regions of interest per sample using ImageJ (NIH, Bethesda, MD, USA). Osteocyte-enriched fractions derived from mouse long bones were isolated as previously reported by Stern et al. [51]. Cell suspensions from individual mice were cultured in twelve-well plates coated with type-I rat tail collagen (Millipore Sigma) at a seeding density of 1 × 105 cells per well. In α-minimal essential medium supplemented with 2.5% fetal bovine serum (FBS), 2.5% bovine calf serum (BCS) and 1% penicillin and streptomycin (PS) (Thermo Fisher, Hampton, NH, USA). Cells were maintained at 37 °C and 5% CO2 in a humidified incubator. Osteocytes were not disturbed for the first 7 days while they attached to the plate. Media changes were performed every 48 h beginning on day 7, and conditioned media was collected from osteocyte cultures derived from individual mice every 48 h on days 9, 11, 13, and 15 post isolation. Conditioned media (CM) was filtered using a 0.22 µm syringe filter and aliquoted before storing at −20 °C. Serum-free CM was collected for mass spectrometry and immunodepletion assays after a 4 h incubation on day 7 of cultures. Bone marrow cells (BMCs) were isolated from the long bones of 6-week-old WT mice and plated on 0.1% gelatin-coated dishes at a density of 1.5 × 105 cells/cm2 in osteoclast differentiation media (α-Minimum Essential Media (Invitrogen, Thermo Fisher) containing 10% FBS (R&D Systems, Minneapolis, MN, USA), P/S (Invitrogen), 30 ng/mL M-CSF (R&D Systems), and 50 ng/mL RANKL (Peprotech, Rockhill, NJ, USA), which was supplemented with 50% osteocyte conditioned media. BMCs were plated on gelatin-coated wells or glass coverslips to observe OC differentiation and actin-ring formation, respectively, whereas 96-well Corning® Osteo Assay Surface strips (hydroxyapatite-coated, Corning, Thermo Fisher) were used to assess osteoclast resorption. Recombinant human calpastatin domain I (non-cell permeable) was purchased from Miilipore Sigma (catalogue #: 208900), reconstituted in sterile PBS and diluted before adding to OC cultures at 0.1 µM, 0.5 µM, 1.0 µM, and 5.0 µM final concentrations. OC precursor migration was observed by performing a controlled scratch assay after 3 days of differentiation. A sterile 10 µL pipette tip was used to scrape across the middle of each well and cell migration was observed over the course of 24 h. TRAP activity was assessed after 7 days of differentiation using the Acid Phosphatase Kit (Sigma). Actin ring formation was observed after 7 days by staining OCs mounted on glass coverslips with phalloidin-rhodamine (1:50; Thermo Fisher) diluted in PBS containing 1% BSA and mounted on slides using ProLong™ Gold Antifade mounting solution with DAPI (Invitrogen). To measure OC-mediated resorption after 8 days of differentiation, cells were removed from the 96-well Osteo Assay strip surface by incubating with 10% bleach solution for 5 minutes at room temperature, and resorption areas were visualized by Von Kossa staining. Resorbed areas appeared clear whereas the remaining hydroxyapatite-coated areas stained black with Von Kossa stain. The number of multinuclear (>3 nuclei) OCs as well as the number of resorption pits and resorption area were measured using Image J (NIH, USA). Primary osteocyte RNA was isolated using the RNAqueous kit (Invitrogen, Thermo Fisher). Samples were treated with DNAse I for 20 min at 37 °C to remove genomic DNA contamination and DNAse I was inactivated before synthesizing cDNA. RNA concentrations were determined using the BioPhotometer spectrophotometer (Eppendorf, Hauppauge, NY, USA). cDNA was synthesized from 1 μg RNA using a high-capacity reverse-transcriptase kit (Invitrogen, Thermo Fisher). QPCR reactions were performed using iTaq Universal SYBR Green Supermix and the CFX Connect™ Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA, USA). Relative expression to β-Actin was determined via the 2−ΔΔCt method included in the CFX Manager Software (Bio-Rad Laboratories). Primers used in qPCR reactions were purchased from IDT (Integrated DNA Technologies, Coralville, IA) and are as follows: Actin-F (5′GGGAAATCGTGCGTGACATC), Actin-R (5′CCAAGAAGGAAGGCTGGAAAAG), Rankl-F (5′ CATTTGCACACCTCACCATCAAT), Rankl-R (5′GTCTGTAGGTACGCTTCCCG), Opg-F (5′ TCCCGAGGACCACAATGAACAAGT), Opg-R (5′TTAGGTAGGTGCCAGGAGCACATT), Camkk2-F (5′CATGAATGGACGCTGC) and Camkk2-R (5′TGACAACGCCATAGGAGCC). Serum-free osteocyte CM was concentrated 13-fold using centrifugal filter columns (Amicon® Ultra 3K; Millipore Sigma), and protein concentrate was exchanged into ammonium bicarbonate buffer (25 mM). Samples were then dried down and resuspended in 8 M urea with 100 mM ammonium bicarbonate, pH 7.8. Disulfide bonds were reduced by incubation for 45 min at 57 °C with a final concentration of 10 mM Tris (2-carboxyethyl) phosphine hydrochloride (Catalog no C4706, Sigma Aldrich, St. Louis, MO, USA). A final concentration of 20 mM iodoacetamide (Catalog no I6125, Sigma Aldrich) was then added to alkylate these side chains and the reaction was allowed to proceed for one hour in the dark at 21 °C. Samples were diluted to 1 M urea using 100 mM ammonium bicarbonate, pH 7.8. One µg of trypsin (V5113, Promega, Madison, WI, USA) was added, and the samples were digested for 14 h at 37 °C. The following day, samples were desalted using Omix tips (Agilent, Santa Clara, CA, USA). Peptide samples were analyzed by LC-MS on an Orbitrap Fusion Lumos (Thermo Fisher) equipped with an Easy NanoLC1200 HPLC (Thermo Fisher). Peptides were separated on a 75 µm × 15 cm Acclaim PepMap100 separating column (Thermo Scientific) downstream of a 2 cm guard column (Thermo Scientific). Buffer A was 0.1% formic acid in water. Buffer B was 0.1% formic acid in 80% acetonitrile. Peptides were separated on a 120 min gradient with the primary separation from 4% B to 33% B. Precursor ions were measured in the Orbitrap with a resolution of 120,000. Fragment ions were measured in the Orbitrap with a resolution of 15,000. The spray voltage was set at 1.8 kV. Orbitrap MS1 spectra (AGC 4 × 105) were acquired from 400–2000 m/z followed by data-dependent HCD MS/MS (collision energy 30%, isolation window of 2 Da) for a three-second cycle time. Charge state screening was enabled to reject unassigned and singly charged ions. A dynamic exclusion time of 60 s was used to discriminate against previously selected ions. Resulting RAW files were analyzed in Proteome Discover™ 2.4.1.15 (Thermo Fisher Scientific, RRID: SCR_014477) with a Mus musculus UniProt FASTA (both reviewed and unreviewed sequences) plus FBS and common laboratory contaminants. Default minora feature detector settings were used. SEQUEST HT searches were conducted with a maximum number of 2 missed cleavages; precursor mass tolerance of 10 ppm; and a fragment mass tolerance of 0.02 Da. Carbamidomethylation on cysteine (C) residues was included as a static modification. Dynamic modifications used for the search were oxidation of methionines, phosphorylation on S, T, and Y, Met-loss or Met-loss plus acetylation of protein of N-termini. Percolator False Discovery Rate was set to a strict setting of 0.01 and a relaxed setting of 0.05. Quantification methods utilized feature mapper chromatographic alignment tools of maximum shift 10 and min s/n threshold of 5. Precursor ion quantification used precursor intensities of unique and razor peptides without scaling and with normalization based on total peptide amount. Quantitative rollup of the summed abundances was done with the top 3 N unmodified peptides, no imputation with a hypothesis of background-based t-tests. Resulting normalized abundance values for each sample type, abundance ratio and log2 (abundance ratio) values; and respective p-values from Proteome Discover™ were exported to Microsoft Excel, Uniprot accession numbers were uploaded to the online Database for Annotation, Visualization and Integrated Discovery (DAVID) to perform a functional annotation analysis. All processed and raw data are available upon request. Quantification of calpastatin levels in osteocyte CM was performed using the Mouse CAST (Calpastatin) ELISA kit (NBP2-75048; Novus Biologicals, Centennial, CO, USA) according to manufacturer’s directions. Primary osteocytes or WT OCs were harvested and placed into iced tween lysis buffer (25 mM Hepes (pH 7.5), 50 mM NaCl, 25 mM NaH2PO4, 0.5% Tween 20, 10% glycerol, 1 mM dTT, 10 mM β-glycerophosphate, 2 mM EGTA, 2 mM EDTA, 25 mM NaF, 1 mM sodium vanadate, 1 mM PMSF, 1 mg/mL aprotinin, 1 mg/mL leupeptin, 10 mg/mL pefabloc, and 100 nM okadaic acid), sonicated on ice, centrifuged 14,000 rpm for 30 min at 4 °C. Equal amount of protein lysates (7.5 µg/lane) isolated from primary osteocytes or osteoclasts was fractionated under denaturing conditions on SDS-PAGE and transferred onto Immobilon-P membranes (Millipore Sigma). Blocking, primary and secondary antibody incubations were performed in Tris-buffered saline (TBS) containing 5% non-fat dry milk. Washes were performed in TBS with Tween-20 (0.1%, v/v, Millipore Sigma). Membranes were probed with primary antibodies for Cast (Cell Signaling Technology, Danvers, MA, USA; 1:1000), CaMKK2 (BD Biosciences; 1:1000), Talin (C-9) (Santa Cruz Biotechnology, Dallas, TX, USA; SC-365875 1:100), Rabbit p-PKA-C (T197), total PKA-C (D45D3) (both Cell Signaling 1:1000) or b-Actin (MilliporeSigma; 1:3000) followed by horseradish peroxidase-conjugated secondary antibodies (Jackson Immunoresearch; 1:5000). The target proteins were visualized with Clarity Enhanced Chemiluminescence substrate (Bio-Rad) using a ChemiDox MP Image System (Bio-Rad), and band densities quantified using ImageJ. Osteocyte CM used directly for Western blot or media supplementation for osteoclast assays was precleared with Protein G Magnetic Sepharose Xtra Beads (GE Healthcare) and incubated with either rabbit anti-Cast antibody (1:1000, Cell Signaling #4416) or control IgG (1:1000, MilliporeSigma) overnight on a slow rotating mixer at 4 °C. Protein G Magnetic Sepharose Xtra beads were added and slurry allowed to incubate for 1 h with rotation at 4 °C, and centrifuged to separate immunoprecipitate containing beads from supernatant. For media supplementation, the supernatant was passed through a 0.22 µm syringe filter and aliquoted for storage at −20 °C. For immunoblots, beads containing the immunoprecipitates were washed three times with DPBS at room temperature and boiled in 1× protein loading dye prior to loading (30 µg/lane) on SDS-PAGE gel (Novex) for immunoblotting with Rabbit α-Calpastatin antibody (Cell signaling 1:1000). Statistical analyses were performed using the GraphPad Prism software (GraphPad Software, San Diego, CA, USA). Normality assumptions were evaluated using histograms and QQ plots. Data sets that passed normality test were analyzed using unpaired, two-tailed Student’s t-test when comparing Control and Camkk2OCY or ordinary one-way ANOVA followed by Tukey’s post-hoc analysis when comparing >2 groups [52]. When data sets did not pass the normality test, non-parametric tests were used: Mann–Whitney test for 2 sample comparisons or Kruskal–Wallis test followed by Dunn’s post hoc to compare >2 groups). All values are represented as mean ± standard deviation (SD).

PMC10003152

Hyoju Jeon,Chang-Gun Lee,Hyesoo Jeong,Seong-Hoon Yun,Jeonghyun Kim,Laxmi Prasad Uprety,Kang-Il Oh,Shivani Singh,Jisu Yoo,Eunkuk Park,Seon-Yong Jeong

Inhibitory Effects of Loganin on Adipogenesis In Vitro and In Vivo

01-03-2023

loganin,anti-adipogenic effect,ovariectomized mice,high-fat diet mice

Obesity is characterized by the excessive accumulation of mature adipocytes that store surplus energy in the form of lipids. In this study, we investigated the inhibitory effects of loganin on adipogenesis in mouse preadipocyte 3T3-L1 cells and primary cultured adipose-derived stem cells (ADSCs) in vitro and in mice with ovariectomy (OVX)- and high-fat diet (HFD)-induced obesity in vivo. For an in vitro study, loganin was co-incubated during adipogenesis in both 3T3-L1 cells and ADSCs, lipid droplets were evaluated by oil red O staining, and adipogenesis-related factors were assessed by qRT-PCR. For in vivo studies, mouse models of OVX- and HFD-induced obesity were orally administered with loganin, body weight was measured, and hepatic steatosis and development of excessive fat were evaluated by histological analysis. Loganin treatment reduced adipocyte differentiation by accumulating lipid droplets through the downregulation of adipogenesis-related factors, including peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1). Loganin administration prevented weight gain in mouse models of obesity induced by OVX and HFD. Further, loganin inhibited metabolic abnormalities, such as hepatic steatosis and adipocyte enlargement, and increased the serum levels of leptin and insulin in both OVX- and HFD-induced obesity models. These results suggest that loganin is a potential candidate for preventing and treating obesity.

Inhibitory Effects of Loganin on Adipogenesis In Vitro and In Vivo Obesity is characterized by the excessive accumulation of mature adipocytes that store surplus energy in the form of lipids. In this study, we investigated the inhibitory effects of loganin on adipogenesis in mouse preadipocyte 3T3-L1 cells and primary cultured adipose-derived stem cells (ADSCs) in vitro and in mice with ovariectomy (OVX)- and high-fat diet (HFD)-induced obesity in vivo. For an in vitro study, loganin was co-incubated during adipogenesis in both 3T3-L1 cells and ADSCs, lipid droplets were evaluated by oil red O staining, and adipogenesis-related factors were assessed by qRT-PCR. For in vivo studies, mouse models of OVX- and HFD-induced obesity were orally administered with loganin, body weight was measured, and hepatic steatosis and development of excessive fat were evaluated by histological analysis. Loganin treatment reduced adipocyte differentiation by accumulating lipid droplets through the downregulation of adipogenesis-related factors, including peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1). Loganin administration prevented weight gain in mouse models of obesity induced by OVX and HFD. Further, loganin inhibited metabolic abnormalities, such as hepatic steatosis and adipocyte enlargement, and increased the serum levels of leptin and insulin in both OVX- and HFD-induced obesity models. These results suggest that loganin is a potential candidate for preventing and treating obesity. Obesity is a crucial health problem worldwide, and it is caused by hormonal abnormalities, genetic factors, and an imbalance between food intake and energy consumption [1]. Body mass index (BMI), calculated by dividing body weight by the square of height, is the most commonly used diagnostic indicator of obesity [2]. According to the World Health Organization (WHO) guidelines, a BMI of 25–30 and > 30 kg/m2 are considered overweight and obese, respectively [3]. In 2016, 1.9 billion and 650 million adults above 18 years of age were reported to be overweight and obese, respectively [4]. Obesity is characterized by the abnormal deposition of fat in the body, leading to metabolic abnormalities, including fatty liver, elevated plasma insulin/leptin levels, and dyslipidemia [5]. Liver steatosis is caused by an increase in liver fat, which can promote inflammatory signaling pathways that trigger oxidative stress in hepatocytes and produce proinflammatory cytokine. This can lead to the development of non-alcoholic steatohepatitis and macrophage infiltration, which cause liver damage [6,7]. Moreover, excessive fat accumulation alters two main endocrine factors: insulin and leptin [8]. Insulin is a hormone secreted from pancreatic β cells when large amounts of energy are consumed. Insulin regulates energy metabolism by converting glucose into fat. In obese individuals, elevated plasma insulin levels have been observed, in which insulin sensitivity is reduced in insulin-targeted organs such as the liver and adipose tissues, which results in excessive insulin production [9]. Excessive differentiated adipocytes trigger excessive fat accumulation, which leads to an increase in the number or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [10,11]. Adipogenesis is a process in which surplus energy is stored in adipocytes in the form of lipids [12]. Adipogenesis is the process of differentiation of mesenchymal stem cells (MSCs) into adipocytes [13]. MSCs are differentiated by a complex cascade of adipocyte-specific transcription factors, such as peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1) [14,15,16]. These genes are essential adipogenesis-related markers regulating adipocyte differentiation [15,16]. Excessive differentiated adipocytes trigger immoderate fat accumulation, which leads to an increase in the number of adipocytes (hyperplasia) or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [17]. Despite having a relatively short life in plasma, adipocytokines such as leptin and adiponectin play a crucial role in regulating fat accumulation, which influences insulin sensitivity [18]. Overweightness is generally caused by abnormal eating behavior (i.e., calorie-rich food intake, irregular eating habits, and snacking after a meal), insufficient exercise, and inadequate sleep time [19]. Recently, pharmacological therapies, including liraglutide (suppressing appetite) and orlistat (decreasing fat absorption) for managing and preventing obesity, have seen an increase in patients with obesity. However, some medications have serious adverse effects and long-term safety limitations, such as vomiting, nausea, satiety, and oily evacuation [20]. Medicinal herbs have been widely considered as alternative conventional therapeutics in the treatment and prevention of various diseases, owing to their long-term safety and fewer adverse effects [21]. A study has demonstrated that single bioactive components derived from herbal products have beneficial therapeutic effects as natural medicines [22]. In addition, studies have shown that several plants containing the iridoid glycoside bioactive compound loganin alleviated hepatic steatosis in a non-alcoholic fatty liver disease mouse model [23], exhibit antidiabetic activities in obese diabetic rats [24] and inhibit adipocyte differentiation and proliferation in rat preadipocytes [25]. Further, loganin prevents inflammatory responses in mouse 3T3-L1 preadipocyte cells and in Tyloxapol-induced mice [26] resulting in decreased body weight gain via improved glucolipid metabolism [25]. Although several beneficial effects of loganin are known, the specific anti-obesity effects of loganin on adipogenesis remain unclear. Therefore, this study aimed to investigate the inhibitory effects of loganin in 3T3-L1 mouse preadipocytes and adipose-derived stem cells (ADSCs) in vitro and in ovariectomy (OVX) and high-fat diet (HFD)-induced mice in vivo. We first examined whether loganin inhibits adipogenesis in 3T3-L1 mouse preadipocyte cells. Cells were induced to differentiate into adipocytes and were co-incubated with different concentrations of loganin (2, 5, and 10 μM) for 8 d. After the induction of adipocyte differentiation, mRNA expression levels of adipogenic-related markers such as Pparg and Cebpa for adipogenesis, Plin2 for mature adipocytes, and Fasn and Srebp1 for upstream activator of adipogenesis were examined using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and accumulated lipid droplets were visualized using oil Red O staining. Loganin significantly decreased the mRNA expression levels of Pparg, Cebpa, Plin2, Fasn, and Srebp1 in a dose-dependent manner, and treatment with 10 μM loganin showed the greatest inhibitory effect on adipocyte differentiation (Figure 1A). Loganin treatment decreased the number of oil Red O-positive cells (Figure 1B). Further, the cellular viability test showed that loganin did not affect cellular viability in 3T3-L1 cells (Supplementary Figure S1). These results indicate that loganin prevents adipocyte differentiation by reducing expressions of Pparγ, Cebpa, Plin2, Fasn, and Srebp1. We further confirmed the anti-adipogenic effects of loganin on ADSCs isolated from mouse adipose tissues. ADSCs were induced to differentiate into adipocytes and were co-cultured with loganin (2, 5, and 10 μM) for 8 d. Consistent with the results obtained in the preadipocyte cell line, mRNA expression levels of adipogenic-related markers, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 were reduced by loganin treatment (Figure 2A), and the number of oil Red O-positive cells was also decreased (Figure 2B). These results suggest that loganin inhibits adipocyte differentiation by downregulating adipogenic-related markers (Pparγ, Cebpa, Plin2, Fasn, and Srebp1) in both 3T3-L1 mouse preadipocytes and ADSCs. To examine the anti-adipogenic effect of loganin in vivo, we used two different animal models of obesity in mice, i.e., OVX- and HFD-induced obesity. We used the 17β-estradiol (E2; 0.03 μg/kg/d) administration as a positive control for anti-obesity, and strontium chloride (SrCl2; 10 mg/kg/d) administration as a negative control. E2 is a well-known reagent for treating menopausal obesity and SrCl2 is an anti-osteoporotic compound used for treating menopause. As expected, OVX-induced obese mice showed weight gain compared to sham-operated mice because of estrogen deficiency, further hepatic steatosis, and adipose tissue enlargement were observed. Administration of 17β-estradiol (E2), the active form of estrogen, restored OVX-induced estrogen deficiency, resulting in the prevention of weight gain, whereas the negative control group administered with the anti-osteoporotic reagent, strontium chloride (SrCl2), did not show any change in body weight compared to that of OVX-induced obese mice (Figure 3A). However, loganin administration prevented OVX-induced weight gain and reduced hepatic steatosis and adipose tissue enlargement (Figure 3A,B). We further investigated the anti-adipogenic effects of loganin in a mouse model of HFD-induced obesity. Six-week-old mice were fed an HFD, and loganin treatment (2 and 10 mg/kg/d) was orally administered for 12 wk. As expected, HFD increased mouse body weight compared to the normal diet (ND) (Figure 4A), and histological analysis of the HFD-induced animals showed hepatic steatosis and adipocyte enlargement (Figure 4B). However, loganin treatment prevented HFD-induced weight gain and reduced hepatic steatosis and adipocyte expansion (Figure 4A,B). Collectively, these results suggest that loganin administration inhibits OVX- and HFD-induced weight gain, hepatic steatosis, and adipocyte enlargement. Finally, we evaluated the effects of loganin on the plasma levels of leptin and insulin in OVX- and HFD-induced obese mice. OVX- and HFD-induced obese mice showed a significant increase in plasma leptin and insulin levels compared to those in the sham-operated and ND groups. However, loganin administration resulted in decreased plasma leptin and insulin levels in both OVX- and HFD-induced obese mice (Figure 5). These results indicate that loganin ameliorated the OVX- and HFD-induced increase in plasma leptin and insulin levels in mice, resulting in anti-adipogenic effects in mouse models of obesity in vivo. Adipogenesis promotes fat accumulation in mature adipocytes during preadipocyte differentiation, and excessive fat accumulation leads to overweightness and obesity. Regarding excessive adipogenesis initiating obesity, understanding adipocyte differentiation is important to prevent obesity-related diseases [27]. This study examined the inhibitory effects of loganin in a preadipocyte 3T3-L1 mouse cell line and in primary cultured ADSCs in vitro as well as in OVX- and HFD-induced mice in vivo. Preadipocyte 3T3-L1 cells derived from a mouse embryonic fibroblast cell line have been widely used in biological research on adipogenesis [28]. Further, ADSCs are MSCs isolated from white adipose tissue that are most likely to recapitulate adipogenesis during adipose tissue development [29]. Complete differentiation of adipocytes is represented by the formation of lipid droplets, which are visualized using oil Red O staining [30]. In this study, 3T3-L1 preadipocytes and ADSCs induced for adipocyte differentiation and evaluated using oil Red O staining showed that loganin treatment inhibited the accumulation of lipid droplets and decreased the number of oil Red O-positive cells, indicating reduced adipocyte differentiation. Adipocyte differentiation is regulated by various transcription factors, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 [14,15,16]. Pparγ is considered to be a master regulator of adipogenesis and plays a central role in maintaining insulin sensitivity [31]. Cebpa binds to the Pparγ promoter and induces the expression of Pparγ isoform 2, thus enhancing adipogenesis [32]. Plin2, also known as an adipose differentiation-related protein, is a cytoplasmic lipid droplet-binding protein required for storing neutral lipids within lipid droplets in mature adipocytes [33,34]. Further, Fasn stimulates the formation of long-chain fatty acids [35,36], and Srebp1 regulates lipogenesis and fatty acid metabolism in adipocytes [37]. In this study, we examined the mRNA expression of adipogenesis-related genes using qRT-PCR. After the induction of adipocyte differentiation, increased expression of Pparγ, Cebpa, Plin2, Fasn, and Srebp1 was observed. However, loganin treatment inhibited the mRNA expression of adipogenic inducible genes in 3T3-L1 stable cells and primary ADSCs. Collectively, the in vitro results suggest that loganin treatment prevents adipocyte differentiation through the decreased accumulation of lipid droplets and downregulation of adipogenesis-related factors. Mouse models of obesity are widely used to investigate fat development induced by HFD and OVX in mice [38,39]. The HFD contains high amounts of calories from fat and is an appropriate method to trigger excessive fat development in an in vivo obesity model [40,41]. OVX-induced obese mice lack estradiol owing to ovary removal and mimic human menopause with increased susceptibility to gain weight [39]. Based on the in vitro results, we confirmed the attenuating effects of loganin on adipogenesis in HFD- and OVX-induced obese mice. Persistent inappropriate weight gain is strongly associated with metabolic abnormalities, such as hepatic steatosis, adipocyte hypertrophy, and hyperlipidemia [42,43,44]. Liver steatosis and adipocyte enlargement are commonly reported symptoms following excessive fat deposition [45]. A recent study suggested that loganin prevented inflammatory-associated diseases by inhibiting hepatic steatosis [46]. Furthermore, excessively elevated insulin levels inhibit hormone-sensitive lipase, an essential enzyme for lipid digestion [47]. Leptin plays a major role in regulating lipid metabolism through changes in food consumption [48]. In this study, loganin treatment inhibited HFD- and OVX-induced weight gain and fat deposition reduced metabolic abnormalities, such as hepatic steatosis and adipocyte expansion, and increased the plasma levels of insulin and leptin. The results indicated that the protective effects of loganin on metabolic abnormalities induced by HFD and OVX are probably due to anti-obesity effects rather than phytoestrogen activity. Our results thus showed that loganin reduced the total body weight along with adipogenic-associated abnormalities in two mouse models of obesity. Collectively, loganin promoted the reduction of adipocyte differentiation and accumulation of lipid droplets in 3T3-L1 preadipocytes and ADSCs and alleviated obesity-related phenotypes induced by OVX and HFD in vivo. Loganin was purchased from Chengdu Biopurify Phytochemicals Ltd., (Sichuan, China) and was completely dissolved in deionized water. The mouse fibroblast cell line, 3T3-L1, was obtained from the Korean Cell Line Bank (KCLB No. 10092.1). 3T3-L1 cells were maintained in high-glucose Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen, Carlsbad, CA, USA) containing 10% bovine calf serum (BCS; Invitrogen, Carlsbad, CA, USA) and 1% antibiotic-antimycotic (AA; Invitrogen, Carlsbad, CA, USA). For adipogenic induction, cells (1106 cells) were seeded in 6-well plates (SPL Life Sciences, Pocheon, Republic of Korea) and maintained until the cells reached 100% confluent. Then, the cells were replaced with DMEM containing 10% fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA), 1% AA, 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, and 10 μg/mL insulin for 3 days. The medium was then incubated with DMEM containing 10% FBS, 1% AA, and 10 μg/mL insulin for 5 days. Insulin was changed every 2 days, and loganin was replaced every time the media was switched. ADSCs were isolated using the stromal vascular fraction, as previously described [49]. Briefly, 9-week-old mouse epidydimal adipose tissue was digested with collagenase type II for 1 h. The digestive solution was neutralized with low-glucose DMEM containing 10% FBS, followed by filtration using a 100 μm cell strainer (Corning, NY, USA). The cells were then centrifuged at 2500 rpm for 10 min and maintained in low-glucose DMEM containing 10% FBS and 1% AA. For the adipogenic induction of ADSCs, cells were incubated with Mesencult™ Adipogenic Differentiation Medium (STEMCELL Technologies, Vancouver, BC, Canada) for 8 d. The “Control” indicates non-treated cells, and the “Mock” indicates adipogenic induction medium-treated cells. To examine cellular viability tests, 3T3-L1 cells were incubated with loganin in cultured media for 8 d and cellular viability was assessed using D-Plus™ CCK cell viability kit (Dongin Biotech, Seoul, Republic of Korea) in absorbance at 450 nm by iMark™ Microplate Absorbance Reader (Bio-Rad, Hercules, CA, USA). The cells were fixed with 4% paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea) for 15 min and then with 70% isopropanol for 1 min. Thereafter, the cells were incubated with oil Red O (Sigma-Aldrich, St. Louis, MO, USA) for 1 h. Representative images were obtained using a light microscope (Leica Microsystems; Wetzlar, Germany). For quantification of oil Red O-positive cells, cells were destained with 100% isopropanol, and absorbance at 490 nm was measured using a microplate reader (Bio-Rad, Hercules, CA, USA). The values were normalized to the “Mock” sample (1.0) and expressed as relative values for the other samples. Total RNA was isolated using the QIAzol Lysis Reagent (QIAGEN, Hilden, Germany), according to the manufacturer’s instructions. RNA was reverse-transcribed using the RevertAid™ H Minus First Strand cDNA synthesis kit (Fermentas, Hanover, NH, USA) under the following conditions: 2 U of Dnase Ⅰ for 30 min at 37 °C, 50 mM EDTA for 10 min at 65 °C, 1:1 ratio of Random Hexamer and Oilgo (dT) 18 primers for 5 min at 65 °C and 10 mM of dNTP mix, 20 U of RNase Inhibitor, and 200 U of RevertAid H Minus Reverse Transcriptase for 5 min at 25 °C, 1 h at 42 °C and 5 min at 70 °C. qRT-PCR was performed using the SYBR Green I qPCR kit (Takara, Shiga, Japan). The gene-specific primers used in this study were as follows: forward 5′-GCG GGA ACG CAA CAA CAT C-3′ and reverse 5′-GTC ACT GGT CAA CTC CAG CAC-3′ for mouse Cebpa, forward 5′-AAG ATG TAC CCG TCC GTG TC-3′ and reverse 5′-TGA AGG CAG GCT CGA GTA AC-3′ for mouse Srebp1, forward 5′-GGA AGA CCA CTC GCA TTC CTT-3′ and reverse 5′-GTA ATC AGC AAC CAT TGG GTC-3′ for mouse Pparg, forward 5′-GAC CTT GTG TCC TCC GCT TAT-3′ and reverse 5′-CAA CCG CAA TTT GTG GCT C-3′ for mouse Plin2, forward 5′-GGA GGT GGT GAT AGC CGG TAT-3′ and reverse 5′-TGG GTA ATC CAT AGA GCC CAG-3′ for mouse Fasn, and forward 5′-AGC TGA AGC AAA GGA AGA GTC GGA-3′ and reverse 5′-ACT TGG TTG CTT TGG CGG GAT TAG-3′ for mouse Arbp. Relative mRNA expression levels were normalized to those of mouse Arbp (ribosomal protein large P0, also known as Rplp0) expression, and fold change was determined using the 2−ΔΔCt method. The values presented in this study were expressed using “Mock” as a standard (1.0), while other values were expressed as relative values. All animal experiments performed in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of Ajou University School of Medicine (2022-0064). Mice were maintained under specific-pathogen-free conditions at the Animal Care Center at Ajou University School of Medicine and provided with standard food pellets (Feedlab Co., Ltd., Hanam, Republic of Korea) and distilled water ad libitum. The OVX- or HFD-induced obese mice were used as previously described [50,51]. For OVX-induced obese mice, sham-operated (n = 5) and OVX-induced ddY mice (n = 25) were purchased from Shizuoka Laboratory Center Inc. (Hamamatsu, Japan). OVX-induced obese mice were divided into five groups: OVX only, OVX plus β-estradiol (E2; 0.03 μg/kg/day, Sigma-Aldrich), OVX plus strontium chloride (SrCl2; 10 mg/kg/day, Sigma-Aldrich), OVX plus loganin (2 mg/kg/day), and OVX plus loganin (10 mg/kg/day). For HFD-induced obese mice, 4-week-old mice were divided into four groups (n = 5 per group): ND, HFD, HFD plus loganin (2 mg/kg/day), and HFD plus loganin (10 mg/kg/day). The total body weights of the mice were measured using a Micro Weighing Scale (CAS Corporation, Yangju, Republic of Korea) after 4, 8, and 12 weeks of the experiment. E2, SrCl2, and loganin were administered through oral gavage. At the end of the experiment, mice were euthanized using CO2, and tissue samples, including liver and fat, were fixed in 4% paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea). Formalin-fixed tissue samples were dehydrated and embedded in paraffin. The paraffin blocks were sectioned using a rotary microtome (3 μm; Leica Microsystems, Wetzler, Germany). The tissue slides were stained with hematoxylin and eosin (H&E; SSN Solutions, London, UK). Briefly, the sectioned slides were deparaffinized using xylene and rehydrated using sequentially treated ethanol (100%, 95%, and 70%). Slides were stained with Harris hematoxylin solution and differentiated using 1% acid alcohol. Bluing was performed using 0.2% ammonia water and counterstained with eosin Y solution. The slides were then dehydrated using sequentially treated ethanol (70%, 95%, and 100%), cleared with xylene, and mounted using mounting medium (Leica Microsystems, Wetzler, Germany). Slide scanning was performed using an Axioscan Z1 slide scanner (Carl Zeiss). At the end of the experiment, blood samples were obtained from mice using cardiac puncture, collected in EDTA tubes, and stored at −80 °C until use. Plasma leptin and insulin levels were determined using a customized MILLIPLEX® Mouse Adipokine Magnetic Bead Panel (MADKMAG-71K; Millipore, Billerica, MA, USA) and a MAGPIX® multiplex analyzer (Luminex, Austin, TX, USA). Data in bar graphs are expressed as mean ± standard error of the mean (SEM) using GraphPad Prism 9.2.0 software (GraphPad Software, San Diego, CA, USA). Statistical significance was determined using one-way analysis of variance (ANOVA), followed by Tukey’s honest post hoc test using the professional Statistical Package software (SPSS 25.0 for Windows, SPSS Inc., Chicago, IL, USA). This study revealed the inhibitory effects of loganin on adipogenesis in 3T3-L1 preadipocytes, ADSCs, and on OVX- and HFD-induced obesity models in mice. Loganin treatment decreased adipocyte differentiation and lipid droplet accumulation by reducing the mRNA expression of adipogenesis-related factors. In OVX- and HFD-induced obese mice, loganin attenuated the representative obesity phenotypes, including hepatic steatosis, adipocyte hypertrophy, and increased plasma levels of leptin and insulin. These findings indicate the strong potential of loganin as a therapeutic agent for treating and preventing obesity.

PMC10003153

Christoph Watermann,Malin Tordis Meyer,Steffen Wagner,Claus Wittekindt,Jens Peter Klussmann,Sueleyman Erguen,Eveline Baumgart-Vogt,Srikanth Karnati

Peroxisomes Are Highly Abundant and Heterogeneous in Human Parotid Glands

01-03-2023

peroxisomes,parotid gland,human,catalase,differential expression,PSP,mRNA,immunofluorescence

The parotid gland is one of the major salivary glands producing a serous secretion, and it plays an essential role in the digestive and immune systems. Knowledge of peroxisomes in the human parotid gland is minimal; furthermore, the peroxisomal compartment and its enzyme composition in the different cell types of the human parotid gland have never been subjected to a detailed investigation. Therefore, we performed a comprehensive analysis of peroxisomes in the human parotid gland’s striated duct and acinar cells. We combined biochemical techniques with various light and electron microscopy techniques to determine the localization of parotid secretory proteins and different peroxisomal marker proteins in parotid gland tissue. Moreover, we analyzed the mRNA of numerous gene encoding proteins localized in peroxisomes using real-time quantitative PCR. The results confirm the presence of peroxisomes in all striated duct and acinar cells of the human parotid gland. Immunofluorescence analyses for various peroxisomal proteins showed a higher abundance and more intense staining in striated duct cells compared to acinar cells. Moreover, human parotid glands comprise high quantities of catalase and other antioxidative enzymes in discrete subcellular regions, suggesting their role in protection against oxidative stress. This study provides the first thorough description of parotid peroxisomes in different parotid cell types of healthy human tissue.

Peroxisomes Are Highly Abundant and Heterogeneous in Human Parotid Glands The parotid gland is one of the major salivary glands producing a serous secretion, and it plays an essential role in the digestive and immune systems. Knowledge of peroxisomes in the human parotid gland is minimal; furthermore, the peroxisomal compartment and its enzyme composition in the different cell types of the human parotid gland have never been subjected to a detailed investigation. Therefore, we performed a comprehensive analysis of peroxisomes in the human parotid gland’s striated duct and acinar cells. We combined biochemical techniques with various light and electron microscopy techniques to determine the localization of parotid secretory proteins and different peroxisomal marker proteins in parotid gland tissue. Moreover, we analyzed the mRNA of numerous gene encoding proteins localized in peroxisomes using real-time quantitative PCR. The results confirm the presence of peroxisomes in all striated duct and acinar cells of the human parotid gland. Immunofluorescence analyses for various peroxisomal proteins showed a higher abundance and more intense staining in striated duct cells compared to acinar cells. Moreover, human parotid glands comprise high quantities of catalase and other antioxidative enzymes in discrete subcellular regions, suggesting their role in protection against oxidative stress. This study provides the first thorough description of parotid peroxisomes in different parotid cell types of healthy human tissue. Saliva plays an essential role in mastication, speech, protection, deglutition, digestion, excretion, and tissue repair. Salivary glands are exocrine glands that produce and secrete saliva using a system of ducts and acini. Humans have about 800–1000 minor salivary glands and three major paired salivary glands: parotid glands, sublingual glands, and submandibular glands. Of these, the parotid can be described as the largest, bordered anteriorly and medially by the masseter, superiorly by the zygomatic arch, and posteriorly by the sternocleidomastoid. This gland produces a serous fluid that helps with swallowing, chewing, digestion, and phonation [1]. The produced serous secretion comprises rich amylase, sialomucins, sulfomucins, ions, and water along with glycoconjugates that bind to calcium and are responsible for antimicrobial and enzymatic activities in saliva [2]. As the parotid gland has high intrinsic RNase activity, it is particularly challenging to extract intact RNA. We compared different methods to extract intact RNA from murine and human parotid gland tissue without losing the RNA quality [3]. All eukaryotic cells except erythrocytes and spermatozoa include the single membrane-bound organelle called a peroxisome [4]. The shape, size, quantity, and protein content of peroxisomes differ depending on the organism or cell type being studied [5]. The production of cholesterol and plasmalogens, as well as lipid metabolism, are closely related to peroxisomal functions [4]. Furthermore, peroxisomes play a crucial role in the processes of cellular signaling in inflammatory pathologies [5]. Most information on peroxisomes derives from lung, kidney, or liver research. As shown earlier by our workgroup, healthy and malignant tissue of the human parotid salivary gland express peroxisomal proteins differently. The fact that biosynthesis was upregulated while important antioxidant enzymes were downregulated showed that peroxisomes play a pro-tumorigenic role in parotid gland cancers [6]. However, to the best of our knowledge, minimal information is available on the biology of peroxisomes in the different cell types of human parotid glands. The first series of experiments and research on peroxisomes in the human parotid gland were provided by Riva et al. in the late 90s. The authors exploited the power of electron microscopy using the DAB method and showed the cytochemical localization of catalase [7,8]. Subsequently, peroxisomes in rat parotid glands were defined by utilizing an improved DAB method by Graham and Karnovsky [9,10]. The authors that used this improved method observed the sporadic existence of peroxisomes in intercalated duct cells and acinar cells; however, they concluded that the peroxisomes were more frequent in the striated duct cells [9]. Based on these studies, they presented the detailed ultrastructure of excretory ducts in the parotid glands of rats and defined the occurrence of peroxisomes in epithelial cells [11]. Meanwhile, the existence of peroxisomes in the murine parotid gland was confirmed by employing Karnovsky’s DAB method for determining catalase distribution [12]. Tandler and Walter later used a novel method to confirm the existence of peroxisomes in the parotid glands of free-tailed bats [13,14,15]. However, there is still a considerable amount of work to be done in targeting the localization and characterization of peroxisomal proteins. Therefore, this study aimed to characterize and localize peroxisomal proteins and enzymes in the acinar and striated ducts cells of human parotid glands by employing electron- and light-based microscopic techniques combined with molecular analyses. Peroxisomes are numerous, and their protein content is highly abundant in the human parotid glands; however, there were significant cell-specific differences observed in their numerical abundance and enzyme content in the acinar and striated duct cells. Parotid tissue was identified with parotid specific protein (PSP) staining. Since the human parotid gland was surgically removed, we ascertained the origin of the isolated tissue with regular morphology before labeling it with antibodies against proteins that are located inside peroxisomes. The human parotid gland tissue showed the typical anatomical structure of lobes and lobuli with intralobular adipose tissue (Figure 1A–C) and exhibited a gland structure of pure serous acini (Figure 1B). The duct system consists of intercalated ducts, striated ducts, excretory ducts, and main excretory ducts (Figure 1C). As already described in the literature, PSP binds to the membrane of secretory granules and is therefore suitable for detecting parotid tissue. The parotid tissue, which was used for further experiments, reacted clearly positive to PSP staining (Figure 1A–C) [16]. Images of the tissue at a higher magnification show serous secretory cells and striated duct cells with several large and plentiful secretory granules (Figure 1B,C). We subsequently utilized post-embedding immunocytochemistry and the ultra-small gold technique at electron microscopic levels to examine the subcellular localization of PSP. Figure 1D–F demonstrates that gold particles are selectively detected in the secretory granules, indicating that the PSP antibody is highly specific. Organelles of other cells, including mitochondria, were negative. The results of the Psp mRNA expression analysis supported the morphological findings. When compared to Gapdh in Figure 1G, the Psp mRNA expression in the human parotid gland was substantially higher. Western blot analysis for PSP yielded a specific band at 28 kDa, as seen in Figure 1H. These results suggest that PSP is an exclusive parotid-specific marker protein and is highly abundant in secretory granules. We determined the peroxisomal compartment’s distribution pattern in the human parotid gland using peroxisome-specific antibodies. Interestingly, the peroxisomes in the human parotid gland are highly abundant (Figure 2A–F). Immunofluorescence analyses for PEX13p and PEX14p showed a punctate pattern that is typical of peroxisome staining. However, clear visible differences were observed between the acinar cells (Figure 2B,E) and striated duct cells (Figure 2C,F). Acinar cells displayed smaller amounts of stained peroxisomal proteins, as shown by labeling with PEX13p and PEX14p, compared to the striated duct cells (Figure 2B,C,E,F). Both proteins were strongly labeled with peroxisomes in the striated ducts (Figure 2C–F). In light of this, PEX13p and PEX14p Western blot analysis supported the morphological findings, indicating the abundance of both proteins in the human parotid gland (Figure 2I). Further, qRT-PCR analysis for most mRNAs coding for peroxisomal biogenesis proteins (Pex3, Pex5, Pex7, Pex12, Pex13, Pex16, Pex19) and peroxisomal proliferation proteins (Pex11α, Pex11β) revealed significantly higher expression levels compared to Gapdh (all p < 0.0128) in human parotid glands. In contrast, Pex6, Pex10, and Pex14 showed lower expression levels than Gapdh (Figure 2G,H). We also investigated the peroxisomal β-oxidation enzymes in the human parotid gland. In particular, peroxisomal thiolase (ACAA1), which is involved in the last reaction of peroxisomal β-oxidation, demonstrated a typical peroxisomal staining similar to the peroxisomal biogenesis proteins (Figure 3A–C). Striated duct cells showed more intense labeling of peroxisomal proteins than acinar cells (Figure 3A–C). The qRT-PCR analysis of mRNAs for lipid transporters of the distinct ATP binding cassette subfamily D (Abcd1 and Abcd3) also showed significantly higher expression levels in the human parotid gland in comparison to Gapdh (Figure 3D). Furthermore, the human parotid gland showed significantly higher expression of all β-oxidation enzymes (Acox1, Acox2, Mfp1, Mfp2, and Acaa1) except for Acyl-CoA oxidase 3 (Acox3), which was not expressed at a significantly higher level compared to Gapdh (Figure 3E). Of all the peroxisomal β-oxidation enzymes tested, the mRNA encoding for the protein Mfp2 showed the highest expression in comparison to Gapdh (Figure 3E). Western blot examination confirmed the IF and qRT-PCR findings by demonstrating the presence of peroxisomal thiolase (ACAA1) in the human parotid gland (Figure 3F). Glycerone-phosphate O-acyl transferase (Gnpat) and alkylglycerone phosphate synthase (Agps) had significantly higher levels of expression in human parotid glands than Gapdh, according to qRT-PCR data (Figure 4A). Furthermore, compared to GAPDH, the AGPS Western blot analysis showed a considerably increased quantity of this plasmalogen-producing enzyme (Figure 4C). All cholesterol synthesizing enzymes were expressed at high levels in the parotid gland (Figure 4B). The enzyme HMG-CoA reductase (Hmgcr), which is localized in both compartments (peroxisomes and endoplasmic reticulum), has considerably higher levels of mRNA expression in the human parotid gland than Gapdh does [16,17]. In addition, the expression of farnesyl diphosphate synthase (Fsps), phosphomevalonate kinase (Pmvk), and mevalonate 5-disphosphate decarboxylase (Mvd), which are also found in peroxisomes, were also expressed noticeably higher in contrast to Gapdh (Figure 4B). It was also shown that the human parotid gland has elevated levels of 3-hydroxy-3-methylglutaryl-CoA synthase (Hmgcs) and iso-pentenyl diphosphate isomerase (Idi). Human parotid gland expression of the mRNA encoding the ER enzyme squalene synthase (Sqs) was similarly found to be substantially higher than that of Gapdh. Peroxisomal catalase staining revealed the typical punctate distribution with numerous large peroxisomes in acinar and striated duct cells of the human parotid gland (Figure 5A–C). We used a modified protocol based on the alkaline DAB method, which allowed us to detect the peroxisomes in the acinar and striated duct cells of the human parotid gland (Figure 5D–I) [18]. The ultrastructure of acinus cells showed a well-developed rough endoplasmic reticulum (rER), mitochondria, and nuclei with euchromatin. The mitochondria were in physical closeness to the nucleus and rER (Figure 5D–H). Peroxisomes were often closely associated with mitochondria and rER (Figure 5E,F,H). We investigated the localization of the catalase protein using post-embedding immunocytochemistry with ultra-small nanogold in addition to the localization of catalase activity at the electron microscopic level. Ultra-small nanogold particles were only found in the peroxisomal matrix of human acinar and striated duct cells, as illustrated in Figure 5I. The nuclei, mitochondria, and other cell organelles were not labeled. Negative controls using the PAG or ultra-nano gold technique on LR white sections revealed relatively few randomly arranged nanogold particles. The peroxisomes had a round shape and showed the typical single membrane-bound border with a distribution pattern next to mitochondria and the nucleus (Figure 5E,F,H,I). The parotid glands also contain antioxidative enzymes from various subcellular compartments in addition to catalase to defend against oxidative damage. In comparison to Gapdh, the human parotid gland revealed a significantly increased expression of mRNAs encoding for peroxisomal antioxidative enzymes, such as peroxiredoxin 1 (Prdx1), glutathione peroxidase (Gpx), and superoxide dismutase 1 (14). The Western blot analysis for CAT and SOD1 revealed the abundance of these peroxisomal antioxidative enzymes in the human parotid gland (Figure 5K). The mitochondrial superoxide dismutase 2 (SOD2) was detected via immunofluorescence staining and showed a typical localization pattern of the mitochondria in the acinar and striated duct cells (Figure 6A–C). We found clear and robust differences in the number, shape, and morphology of mitochondria between the acini and the striated ducts of human parotid glands. The SOD2 staining showed that the mitochondria were less numerous and displayed a round pattern in the acini compared to the more numerous and elongated form in striated duct cells (Figure 6A–C and Figure 7A–D). Most SOD2-labeled mitochondria were detected in the basal portion of the striated duct epithelial cells and significantly less at the lateral sides and apical portion of the cells (not shown). Strong SOD2 labeling, on the other hand, revealed elongated and tubular mitochondria with extensive network formation throughout the striated duct cells of the parotid gland (not shown). SOD2 is a crucial superoxide radical scavenger that transforms superoxide radicals into less harmful H2O2 in the mitochondrial matrix (Figure 6C). Interestingly, the qRT-PCR analysis of mRNAs encoding for Sod2 and Trx2 showed a significantly higher expression than Gapdh (Figure 6D). The distribution of different thioredoxin isoenzymes suggests that human parotid gland cells also appear to contain a specialized set of antioxidant enzymes in addition to Sod2. Trx2 was more highly expressed in comparison to Trx1 and glutathione reductase (Gr) in the human parotid gland (Figure 6D). Western blot analysis of antioxidative enzymes showed the abundance of SOD2 and GR in agreement with the qRT-PCR analyses (Figure 6E). We chose to investigate the subcellular localization of the SOD2 protein by post-embedding immunocytochemistry of LR white ultrathin cryosections using ultra-small gold-labeled Fab fragments and silver intensification as a secondary detection method in order to achieve the highest sensitivity labeling for SOD2. Our results showed that the ultra-small gold particles used to visualize SOD2 were explicitly and exclusively confined to mitochondria in human acinar and striated duct cells (Figure 7A–D). In immunostainings using SOD2 antigen-specific antibodies, we did not find any gold particles in any other cell compartments. It is well known that several peroxisomal proteins involved in lipid metabolism and oxidative stress and the genes encoding for them are regulated by the peroxisome proliferator-activated receptors (PPARs). There are three family members of the PPARs: Pparα, Pparβ, and Pparγ. Pparα was expressed significantly higher in the human parotid gland, whereas Pparγ was expressed significantly lower compared to Gapdh. Furthermore, the expression level of Pparβ did not show any significant differences compared to Gapdh (Figure 8). The parotid gland is an organ that has an important role in the immune and digestive systems. Salivary glands secrete the necessary proteins that initiate the digestion process and provide tissue lubrication in the oral cavity, and they play a vital role in fighting infections and oxidative stress [19,20,21,22]. A plethora of work has been conducted on the cell biology of the parotid gland and the proteome of saliva [23,24,25]. Recent studies have shown that oxidative stress accompanies parotid gland tumors, suggesting that it plays an important part in the pathogenesis of parotid gland tumors [21]. Peroxisomes harbor a set of antioxidative enzymes, and they are a vital player in the degradation of nitrogen and reactive oxygen species [5]. However, to the best of our knowledge, no significant work is available yet that explains the potential role of peroxisomes and their distribution in different cell types of healthy human parotid glands. Therefore, we explored the role of antioxidative enzymes, peroxisomes, and metabolizing enzymes in the different subcellular sections by using light-, electron-, and immunofluorescence microscopy. The results confirmed the presence of peroxisomes in all cell types of the human parotid gland. It was also shown that there is a substantial difference in the abundance of peroxisomal proteins in acinar cells compared to striated duct cells. Human parotid glands contain high quantities of catalase and other antioxidative enzymes in distinct subcellular sections as well as mRNAs encoding for multifunctional protein 2 and Acyl-CoA oxidase 1. We utilized PSP to categorize the isolated tissue and detected this protein in the parotid gland by using post-embedding immunocytochemistry. The patterns of PSP staining and the respective protein expressions are equivalent to the data provided by Bingle et al., which confirms that parotid tissue was isolated [26]. Moreover, the authors have shown that PSP is an excellent marker to distinguish parotid tissue from surrounding tissue due to its different expression patterns in various tissues and glands [26]. Despite this, the exact role and abundance of PSP is still unknown [26]. Electron microscopy was initially used to identify peroxisomes utilizing the cytochemical localization of catalase activity in the parotid glands of humans, mice, and rats [7,8,9,11,12]. These works confirmed the higher number of peroxisomes in the excretory and striated ducts of parotid glands. Few peroxisomes were found in the cells of intercalated and acinar ducts. Grant et al. showed immunofluorescence staining of PEX14p in human submandibular glands [27]. The location of peroxisomal enzymes and the gene expression-based profile of the proteins involved in peroxisomal biogenesis were not specifically covered in the literature. The best peroxisomal generator protein, PEX14p, is evenly distributed throughout the parotid gland [4,28,29]. In addition to PEX14p, the human parotid gland has many metabolic and peroxisomal biogenesis proteins, as well as antioxidative enzymes. This confirms the importance of peroxisomes in lipid metabolism and their role in the reduction of oxidative stress. The mRNAs encoding the PEX11α, -β, and -γ proteins that are involved in the peroxisomal proliferation are also present in the human parotid gland [30,31,32]. The peroxisome count and the respective morphological structure rely on metabolic need and its cell-specific functions [33,34]. Degradation of bioactive lipids is assisted by peroxisomal β-oxidation. Eicosanoids, for instance, play a role in the production of polyunsaturated fatty acids and the process of inflammation [35]. The prevalence of peroxisomal thiolase in striated duct and acinar cells must be discussed. The rate-limiting enzymes of pathway 1 of the peroxisomal β-oxidation are peroxisomal enzymes, such as acyl-CoA oxidase 1–3 (ACOX). This helps to regulate the substrate flux by using the β-oxidation chain [36]. The human parotid gland has strongly expressed mRNAs for the distinct peroxisomal β-oxidation pathway 1 (Mfp1) and peroxisomal β-oxidation pathway 2 (Mfp2). The metabolism of straight-chain substrates is the primary focus of the MFP1 enzyme, but MFP2 regulates a sizable portion of the substrates for peroxisomal β-oxidation [37]. It is also worth mentioning that the abundance of such enzymes can guard the epithelium against proinflammatory eicosanoids. The high involvement of ABCD3 in the human parotid gland shows that the transporter facilitates an ingress of the branch-like long-chain unsaturated and saturated substrate into the peroxisomes [38]. However, the precise function of peroxisomal β-oxidation in the lipid-transport and homeostasis has not yet been investigated. Peroxisomal β-oxidation can provide the acetyl-CoA units to generate lipids such as plasmalogens or cholesterol precursors [39]. The lipid synthesizing enzymes present in the peroxisomes might play a vital role in the parotid gland. For example, AGPS, which is abundant in the parotid gland, is involved in the synthesis of ether lipids. Ether lipids are known to trap the reactive oxygen species (ROS) (Karnati and Baumgart-Vogt, 2008); therefore, peroxisomes in the parotid gland might help against oxidative damage. Plasmalogens, the largest class of ether lipids, promote the formation of biologically active lipids for cellular signaling [40]. Remarkably, the abundance of lysoplasmalogens is directly linked with the electrophysiological instabilities in myocytes that repress Na+–K+-ATPase in the renal cells [41]. The striated duct cells contain Na+–K+-ATPase in the basolateral and lateral part of the epithelial cells; however, the function of plasmalogens in striated duct cells is so far unidentified. Cholesterol is also a crucial lipid and a mandatory element of bile acids, steroid hormones, and oxysterols [42]. Like other peripheral tissues, the parotid gland uses cholesterol for cellular growth, as was found in rats [43] and mice [44]. It is worth noting that the peroxisomal enzymes can condense acetyl-CoA, which is derived from long-chain fatty acid oxidation, into farnesyl diphosphate (FPP). The reactions of FPP and mevalonate are exclusively peroxisomal except for the reaction of HMG-CoA reductase [45]. The mRNAs of all proteins involved in the synthesis of cholesterol are found to be abundant in the parotid glands of humans, which can affect cholesterol metabolism. In fact, diabetes mellitus and parotid cholesterol metabolism are linked, as evidenced by the discovery of asymptomatic parotid gland enlargement in diabetic rats [46]. More research is needed to determine how low insulin levels specifically affect parotid cholesterol metabolism. High concentrations of antioxidative enzymes can be found in several subcellular compartments of the human parotid gland. Saliva is comprised of antioxidants with special characteristics to protect against oxidative stress [22]. Previous observations have also highlighted that hyposalivation produces oxidative stress by harming the salivary gland’s structure [47,48]. In this respect, it is essential to highlight that the parotid gland possesses peroxisomal enzymes and several other antioxidative catalysts that detoxify H2O2 produced by peroxisomal oxidases [28]. The striated duct cells within the human parotid gland possess an excessive amount of mitochondrial SOD2, an essential scavenging catalyst that transforms superoxide radicles created by the mitochondrial respiratory chain into less toxic H2O2. Several studies have already shown that ROS derived from mitochondrial production grows with age whereas the body’s antioxidative potential decreases [49]. Therefore, the accumulation of ROS becomes harmful for phospholipids and the cell membrane, which is the primary cause of cellular dysfunction [50]. It is worth mentioning that the human parotid gland possesses antioxidant enzymes that are cleared from the thioredoxin isoenzyme distribution. Intriguingly, mRNAs encoding TRX1, certain PEX genes, and cytoplasmic GR were expressed significantly less in parotid gland tissue. It seems that decreasing the antioxidative potential of saliva can increase the vulnerability of the salivary gland to oxidative destruction and maximize the oxidative stress that is related to oral maladies (dental caries, burning mouth syndrome, and oral inflammatory infections like gingivitis, periodontitis, oral mucosa ulceration, and candidiasis) [51]. PPARs play vital roles in glucose metabolism, lipid metabolism, aging, stress, and producing transcription factors [52,53,54]. PPARα is highly expressed within the parotid gland of humans, which may explain the peroxisomal compartment induction. It has already been shown that PPARγ also regulates genes for PEX11, a large number of peroxisomal β-oxidation enzymes, and ABCD transporters by attaching to the PPARs’ responsive regions (PPRE) [34,54,55]. Most of the research on the PPARs’ role in parotid tumors has just recently been published. PPARγ upgrades Sjögren’s syndrome, the over-expressive regulation of cytokines within the peripheral blood or salivary gland, in non-obese diabetic mice [56]. PPARα and PPARγ could inhibit IL-1β-made NO growth in cultured cells of the lacrimal gland acini, proposing that PPARs might be a beneficial therapy target for avoiding NO-mediated gland destruction. Despite this, the PPARα and PPARγ effects on the development of salivary gland dysfunction are not apparent. The human parotid tissue was removed during surgical operations on benign parotid gland tumors following the standard operating procedures. Pathologists examined the samples at the Institute for Pathology of the Justus Liebig University Giessen, Germany. Informed patient consent was obtained from all individual participants included in this study. We collected tissue samples during surgery performed on the parotid gland. The obtained tissue was divided. One part was fixed with 4% PFA in PIPES buffer with 2% saccharose and 0.05% glutaraldehyde at pH 7.4 for electron microscopy, another part was snap-frozen in liquid nitrogen for Western blotting, and the last part of the parotid tissue was either immersed in RNA later, with subsequent freezing, or immersed in 4% PFA in PBS at pH 7.4 and kept at 4 °C for paraffin embedding. The ethical review committee of the Justus–Liebig University Giessen approved removing and examining the human tissue (AZ 95/15, 25 June 2015). All procedures performed in studies involving human participants followed the ethical standards of the institutional and national research committee and the 1964 Helsinki declaration and its later amendments or comparable ethical standards. It was previously documented in detail how the tissues were sectioned, paraffin embedded, and then used for antigen retrieval and immunofluorescence [4,28,29]. To read more about the primary and secondary antibodies used to incubate the sections with antibodies against peroxisomal, mitochondrial, and other proteins, see Table 1. In immunofluorescence preparations of paraffin slices of different tissues, all antibodies against peroxisomal proteins had already undergone testing for their specificities (lung [28], brain [57], and testes [58]). The sections were mounted in Mowiol 4.88 with N-propyl gallate in a 3:1 ratio after being counterstained with TOTO-3 iodide to detect nuclear morphology. Parallel negative controls incubated without primary antibodies. Using a Leica TCS SP5 confocal laser scanning microscope with a 63× objective and the “Airy 1” setting, the immunofluorescence preparations were analyzed. Fresh human tissue was placed into a 4% PFA fixative solution in a 0.1 M sodium cacodylate buffer with 2% sucrose at 4 °C. The embedding was performed with Epon or LR White following the manufacturer’s instructions and placed in a vacuum exsiccator to set. Afterward, the tissue was cut into sections using a thin razor blade. The cytochemical localization of catalase activity with the alkaline DAB-method in human parotid glands was performed as previously described [28]. Briefly, the human parotid gland slices were incubated with an alkaline DAB medium [18] containing 0.2% 3,3′-diaminobenzidine (DAB, Sigma, Steinheim, German), 0.15 % H2O2, and 0.01 M Teorell-Stenhagen buffer at pH 10.5. For the best catalase reaction, the reaction was conducted for two hours at 45 °C in a shaking water bath. The sections were then rinsed three times in 0.1 M cacodylate buffer with a pH of 7.4. The osmicated sections were dehydrated in a succession of increasing concentrations of ethanol solutions before being embedded in epoxy resin 812 (Agar, Essex, England). The trimming of the blocks was done with a diamond trimmer (Reichert TM 60, Austria) and the sectioning with a Leica Ultracut E Ultramicrotome (Leica, Nussloch, Germany). The ultrathin slides were collected on nickel grids covered with formvar, and contrasting was done using lead citrate for 45 s and uranyl acetate for two minutes. A transmission electron microscope, model LEO 906, was used for the study (LEO Electron Microscopy, Oberkochen, Germany). According to Newman et al. [59], another portion of the previously fixed wet parotid sections was directly dehydrated after being exsiccated in 4% PFA-fixative and implanted in medium grade LR White resin (LR White Resin, Berkshire, England). As previously mentioned, slides were collected on formvar-coated nickel grids after ultrathin sectioning (80 nm) was completed. Blocking was performed with 1% bovine serum albumin (BSA) dissolved in a tris-buffered saline solution (TBS) at pH 7.4 for 30 min to prevent unspecific binding. The sections were treated with a rabbit anti-mouse catalase antibody (1:4000 in 0.1% BSA in TBS; a gift from Denis Crane, Table 2) overnight in a wet chamber. The following day, the sections underwent washing with drops of 0.1% BSA in TBS twelve times. The washed grids were incubated with a protein A-gold complex (PAG, gold particle size 15 nm) diluted with 0.1% BSA in TBS (1:75) [60]. The next step was distilled water washing, then air drying. Uranyl acetate was used for the contrasting for two minutes, followed by lead citrate for 45 s. Other ultrathin sections were used as the negative control, which were also treated with non-specific rabbit IgG and placed on grids. In contrast to the other sections, the negative control was followed by the protein A-gold complex alone without a primary antibody. Subsequently, a LEO 906 transmission electron microscope was used for the examination (LEO Electron Microscopy, Oberkochen, Germany). Snap-frozen human parotid glands were cut into small pieces, and the tissue was homogenized in a buffer containing 0.25 M sucrose and 5 mM MOPS (pH 7.4), 1 mM EDTA, 0.1% ethanol, 0.2 mM DTT, 1 mM aminocaproic acid, and 100 µL cocktail of protease inhibitors (#39102, Serva, Germany). The tissue and homogenization buffer were used over an ice bath and treated with a single stroke of a Potter-Elvehjem homogenizer (B. Braun Biotech International, Melsungen, Germany) for 60 s at 1000 rpm. Centrifugation was done at 2500× g for 20 min at 4 °C to sediment connective tissue, nuclei, and giant mitochondria. The protein concentration was measured with the BCA Protein Assay Kit (Pierce, Thermo Fisher Scientific, Langenselbold, Germany) according to the manufacturer’s instructions using an Infinite M200 PRO NanoQuant plate reader (Tecan Group, Maennedorf, Switzerland) for measurement. The total proteins of the human parotid glands (40 µg) were separated on 10% resolving gels using the sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The SDS-PAGE was done using a Mini Protean Tetra electrophoresis module assembly and a Power Pac Basic (BioRad, Dreieich, Germany). Semi-dry blotting was used to transfer the proteins for 50 min at 10 V while utilizing a Trans-Blot Semi-Dry (BioRad, Dreieich, Germany) and a Protran nitrocellulose membrane (Whatman, Dassel, Germany). The membrane was blocked with 5% fat-free milk powder (Applichem, Darmstadt, Germany) in TBS plus 0.5% Tween 20 (Applichem, Darmstadt, Germany) (TBST) for 1 hr at RT. The primary antibodies were diluted in the blocking solution (exact dilution, see Table 1) and incubated overnight at 4 °C. After the incubation, washing of the membrane was performed with TBST (5 min) and TBS (2 × 5 min), and the secondary antibody (for dilution, see Table 1) was put on for 1 hr in RT diluted in 0.5% BSA in TBST. After the washing step, the detection of the immunoreactive bands was done using the Immun-Star WesternC Chemiluminescent Kit (BioRad, Dreieich, Germany) and the ChemiDoc XRS system (BioRad, Dreieich, Germany) for visualization. ImageLab Version 3.0 (BioRad, Dreieich, Germany) was used for image processing and analysis. The membranes were stripped with a 25 mM glycine and 10% SDS solution followed by a 100 mM sodium hydroxide and 10% SDS solution (15 min each) with subsequent reprobing. For RNA isolation, the fresh human tissue was immersed in RNAlater and snap-frozen in liquid nitrogen. The tissue samples were stored at −80 °C before further use. For homogenization of the tissue, a TissueLyser LT (Qiagen, Hilden, Germany) was used. Different methods for RNA isolation were already tested to achieve the best possible RNA quality [3]. Following the manufacturer’s instructions, the subsequent RNA isolation was carried out using the RNeasy Mini Kit (Qiagen, Hilden, Germany). The Agilent 2100 Bioanalyzer system and the Agilent RNA 6000 Nano Kit were used to confirm the RNA quality and concentration (Agilent Technologies, Santa Clara, CA, USA). The High-Capacity RNA-to-cDNA Kit (Applied Biosystems, Weiterstadt, Germany) was used for reverse transcription according to the manufacturer’s instructions together with a C1000 Thermal Cycler PCR system (BioRad, Dreieich, Germany). The Primer Quest Tool (http://eu.idtdna.com/Primerquest/Home/Index accessed on 20 May 2020) was used to design the primers. Eurofins MWG Operon received the order for the primers. Table 2 contains a list of all the primers used. The StepOnePlus Real-Time PCR System (Life Technologies, Darmstadt, Germany) and SYBR Select Master Mix Kit (Life Technologies, Darmstadt, Germany) were used to perform qPCR in accordance with the manufacturer’s instructions. The PCR was conducted using a primer concentration of 5 pmol/L. Program used: 45 cycles of denaturation at 95 °C for 15 s, annealing at 60 °C for 60 s, and extension at 7 °C for 1 min. For the statistical analysis of the different mRNA expression levels, normalized values were used compared to a stable housekeeping reference gene. A Kolmogorov-Smirnov test was used for the normal distribution of the samples. The values are expressed as means ± SEM using the total RNA from human (n = 3) parotid gland samples. The difference in expression between the housekeeping gene and the target genes was evaluated using a Student’s t-test for unpaired samples. All statistical tests were calculated using the GraphPad Prism software version 6.01. Our study’s findings showed that the staining of structures containing peroxisomal proteins is more intense in striated duct cells than in acinar cells, which may indicate that more of the corresponding proteins are present in striated duct cells. However, there is no evidence that the composition of peroxisomal proteins differs between the two cell types. The human parotid gland exhibits a high number of peroxisomes and has distinct subcellular compartments with comparatively high concentrations of catalase and other antioxidative enzymes. This study strongly supports the idea that peroxisomal lipid metabolism also plays a crucial role in the parotid gland. Unraveling the precise metabolic and functional role of peroxisomes in the parotid gland should assist in understanding the cause of parotid tumors and guide the development of therapies.

PMC10003154

Aleksandra Jezela-Stanek,Joanna Chorostowska-Wynimko

SERPINA1 and More? A Putative Genetic Contributor to Pulmonary Dysfunction in Alpha-1 Antitrypsin Deficiency

21-02-2023

AATD,mRNA,methylation,SNP,micro-RNA,SERPINA1 gene

Alpha-1 antitrypsin deficiency (AATD) is a common inherited disorder associated with an increased risk of pulmonary disease. Its clinical presentation, including the nature and severity of organ involvement, is highly variable and unpredictable and is not as strongly linked to genotype and environmental exposure (e.g., smoking history) as might be expected. Significant differences were observed within matched populations of severe AATD patients regarding risk of complications, age at onset, and disease course, including the dynamics of lung function decline. Genetic factors are among the putative modifiers contributing to the clinical variability in AATD, yet their role remains elusive. Here, we review and summarise our current understanding of epigenetic and genetic modifiers of pulmonary dysfunction in subjects with AATD.

SERPINA1 and More? A Putative Genetic Contributor to Pulmonary Dysfunction in Alpha-1 Antitrypsin Deficiency Alpha-1 antitrypsin deficiency (AATD) is a common inherited disorder associated with an increased risk of pulmonary disease. Its clinical presentation, including the nature and severity of organ involvement, is highly variable and unpredictable and is not as strongly linked to genotype and environmental exposure (e.g., smoking history) as might be expected. Significant differences were observed within matched populations of severe AATD patients regarding risk of complications, age at onset, and disease course, including the dynamics of lung function decline. Genetic factors are among the putative modifiers contributing to the clinical variability in AATD, yet their role remains elusive. Here, we review and summarise our current understanding of epigenetic and genetic modifiers of pulmonary dysfunction in subjects with AATD. No protein fits a simple gene–product relationship; the progression from DNA sequence to polypeptide generation is complex, with several vital processes such as posttranslational modifications involved. However, protein functionality also depends on many other factors, pathways, and/or modifiers, which influence the complexity of the clinical course of many inherited diseases. Alpha-1 antitrypsin deficiency (AATD) is an excellent example of such interplay with the highly polymorphic SERPINA1 gene product, which, similar to other serpins, is prone to conformational shifts and therefore significant changes in its functionality [1,2]. AATD (ORPHA 60, MIM #613490) is one of the most common inherited rare diseases in Caucasians, with a prevalence of 1–5/10,000 [3]. Its clinical presentation varies according to the affected organ and severity. Typically, AATD manifests in adults with respiratory disorders, most often early-onset emphysema and/or bronchiectasis, or as a liver pathology of persistent jaundice or cirrhosis in all age groups, newborns, children, and adults. Panniculitis and vasculitis, which have also been linked to AATD, are significantly less prevalent. The natural history of organ-specific pathologies related to AATD is highly unpredictable, with few identified risk factors, such as smoking or occupational exposure to lung or alcohol abuse or viral hepatitis. This is also true for the prognosis and rate of disease progression, as exemplified by a decline in lung function or an increase in liver enzymes. While significant progress has been made in understanding the mechanisms underlying AATD, there is more to be learned [4]. A protease–antiprotease imbalance is hypothesised to be the primary cause of lung destruction; therefore, emphysema does not fully explain the wide variety of clinical phenotypes in AATD. There is increasing evidence suggesting that, in addition to SERPINA1 alterations, other genetic factors and modifiers play an important role [5]. In the era of genomic medicine, widespread use of molecular diagnostics, and high-throughput technologies, the identification of such factors is of primary clinical interest. This review discusses our current understanding of genetic modifiers and prognostic markers contributing to the different respiratory phenotypes of AATD. AAT coding gene SERPINA1 (* 107400; SERPIN PEPTIDASE INHIBITOR, CLADE A, MEMBER 1) was previously known as a protease inhibitor (PI). Its genomic length is 10.2 kb with a 1434-bp coding region [6]. The gene has 4 introns: exon 1, the 5-prime portion of exon 2, and the 3-prime portion of exon 5, which are noncoding regions. The first intron, 5.3 kb long, contains a 143-amino acid open reading frame (which does not appear to be an actual protein coding region), an Alu family sequence, and a pseudo transcription initiation region. Hepatocytes are the major source of AAT, but the gene is also expressed in mononuclear phagocytes and neutrophils [7]. Numerous genetic factors have known or possible direct effects on the clinical appearance of AATD, including single nucleotide polymorphisms (SNPs), DNA methylation, altered microRNA (miRNA) expression, and SERPINA1 mRNA isoforms (Table 1). Other inherited variants may indirectly and independently of AATD affect individual susceptibility to progressive airway obstruction, as shown by the rate of decline in lung density or function. This is the case with IREB2, which encodes iron-responsive element-binding protein 2 [8], a group-specific component that is the major vitamin D-binding protein [9], as well as a variable number of tandem repeats within the interleukin-1 receptor antagonist gene or the tumour necrosis factor (TNF)-α 308 G/A variant in the Asian population [10], which have been shown to advance the development of chronic obstructive pulmonary disease (COPD). A SNP is the most common type of genetic variation. By definition, a specific variant is identified as a SNP if it is observed in ≥1% of the population and the affected gene has more than one allele. As presented in Table 1, clinically significant SNPs identified in AATD include variations in NOS3, GSTP1, TNF-α, IL10, CHRNA3, IREB2, mEH, and immune-related genes. Endothelial nitric oxide synthase (NOS3) oxidatively deaminates L-arginine to L-citrulline, releasing nitric oxide. In turn, NOS3 regulates vascular and airway tone in the lungs and influences various aspects of airway homeostasis [11]. Six polymorphic sites within the NOS3 gene (924A/G, 788C/T, 691C/T, 774C/T, 894G/T, and 1998C/G) in 345 AATD patients (PI*Z homozygotes or compound heterozygotes of PI*Z with other deficiency alleles) and 93 control individuals were analysed. A detailed clinical and smoking history in AATD individuals have been described elsewhere [12,13]. A higher incidence of the 774T and 894T alleles was observed in more severely affected individuals compared with less severe cases (0.417 vs. 0.289 and 0.427 vs. 0.344, respectively), suggesting a link between NOS3 allelic variants and the pathogenesis and/or severity of the disease. Novoradovsky et al. analysed smoking status in 55 patients with a predicted forced expiratory volume in 1 s [FEV1] that was < 35% of the predicted normal value [FEV1%pred] and in matched controls [11]. They observed a trend toward significance in the smokers plus ex-smokers in the frequency of 774T and 894T alleles. Specifically, in smokers and ex-smokers, the 774T allele frequencies were 0.460 and 0.275 (p = 0.072), whereas those of the 894T allele were 0.480 and 0.300 (p = 0.083), respectively. In non-smokers, the 774T allele frequencies were 0.365 and 0.278 (p = 0.371), and the 894T allele frequencies were 0.385 and 0.328 (p = 0.527) in patients and controls, respectively. Given that almost all affected individuals and controls were ex-smokers or non-smokers, investigating the effect of current smoking has not been possible. Glutathione S-transferase P1 is involved in the detoxification of electrophilic substances present in tobacco smoke. Therefore, it has been suggested to play a role in the pathogenesis of smoking-related respiratory disorders [14]. The GSTP1 105Val polymorphism, which results in reduced enzyme activity in vitro, has been of particular interest. Rodriguez et al. [14] evaluated the frequency of Ile105Val polymorphisms in the general population compared with patients with AATD or smoking-related COPD. A total of 99 patients with COPD (current or ex-smokers), 69 patients with AATD with a wide range of lung function impairments, and 198 healthy volunteers were included in the analyses. The GSTP1 105Val frequency was significantly increased in the AATD group (vs. healthy controls: odds ratio [OR] 2.09, 95% confidence interval [CI] 1.17–3.72; vs. COPD group: OR 2.41, 95% CI 1.27–4.59) but was comparable between COPD patients and healthy controls. This result was not observed in COPD patients with normal AAT levels; lung function was not significantly different according to the GSTP1 genotype. Interestingly, lung function (FEV1%pred) was significantly impaired in AATD carriers of GSTP1 105Val. This phenomenon was not observed in PI*MM COPD patients or healthy controls. Tumor necrosis factor (TNF) is a multifunctional proinflammatory cytokine secreted predominantly by monocytes/macrophages that has effects on lipid metabolism, coagulation, insulin resistance, and endothelial function [15]. The rs361525 variant (G-238A) of TNF-α was linked to a higher incidence of chronic bronchitis in AATD in 424 unrelated PI*ZZ subjects with a known history of chronic bronchitis, lung function impairment as assessed by the FEV1%pred, and emphysema and bronchiectasis confirmed by high-resolution CT scanning [16]. Higher levels of the pro-inflammatory cytokine TNF-α have been repeatedly demonstrated in sputum, bronchial biopsy, and peripheral blood samples in both stable and exacerbated COPD patients [17,18,19]. This specific genotype was found to be associated with higher TNF-α expression in lung secretions. It increased downstream signalling in vivo and bioactivity in vitro, suggesting a link to the COPD disease phenotype and progression [20]. Thus, Wood et al. [16] linked TNFα variants to AATD clinical phenotypes. These phenotypes were determined based on full clinical assessments, including smoke exposure, the presence of chronic bronchitis, lung function testing, and high-resolution chest CT scanning. A significant difference in the rs361525 genotype (p = 0.01) and allele (p = 0.01) frequency was observed between subjects with and those without chronic bronchitis, independent of the presence of other clinical phenotypes. No correlation with the TNF-α plasma level was observed. DeMeo et al. [21] conducted family-based association analyses in a group of 378 PI*ZZ individuals from 167 families. They hypothesised that genetic determinants of obstructive lung disease might be modifiers of airflow obstruction in individuals with severe AATD. A panel of 10 genes (IL10, TNF, GSTP1, NOS1, NOS3, SERPINA3, SERPINE2, SFTPB, TGFB1, and EPHX1) previously linked to asthma and/or COPD was analysed. Genetic analysis was performed in all 428 AATD subjects (including genotypes from 50 parents), while spirometry was performed in 378 affected PI*ZZ individuals, which allowed the determination of genetic transmission within families. The qualitative phenotype of COPD was defined using post-bronchodilator spirometry values (FEV1 and the ratio of FEV1/forced vital capacity [FVC]), and a qualitative phenotype of moderate-to-severe COPD was defined for individuals with a predicted FEV1 < 50%pred. Consistent findings for both quantitative and qualitative airflow obstruction phenotypes were noted for IL10 SNPs only. Further assessments with a sliding window haplotype analysis using the 11 SNPs in IL10, as well as 8, 4, 3, and 2 adjacent SNP sliding windows, revealed an association of the −1082 A/G promoter polymorphism with lower lung function but an association of the mutant G (minor) allele with higher lung function. The 1082 rs1800896 SNP has been associated with a functional effect on the IL-10 protein level: the A wild-type allele is associated with a lower IL-10 level, and the G mutant allele with a higher IL-10 level. Prior reports of genome-wide association studies (GWAS) of COPD showed significant associations between COPD susceptibility and SNPs in the 15q region [22], as well as associations with the presence and severity of emphysema [23]. The association between specific SNPs in the chromosome 15q region encompassing CHRNA3 and IREB2 was studied in 378 PI*ZZ individuals in the AAT Genetic Modifiers Study and a replication cohort of 458 subjects from the UK AATD national registry [24]. The authors hypothesised that SNPs in this chromosomal region might be modifiers of intermediate phenotypes of COPD in subjects with severe AATD. Importantly, for COPD phenotyping, both lung function and lung morphology assessed by CT scanning were used to overcome some of the heterogeneity inherent in pulmonary function classifications based solely on spirometric measurements. In contrast to the UK AATD national registry, the AAT Genetic Modifiers Study has shown that SNPs in the genes IREB2, LOC123688, and CHRNA3 are associated with specific lung function phenotypes in AATD PI*ZZ subjects. Specifically, rs2568494 in IREB2, rs8034191 in LOC123688, and rs1051730 in CHRNA3 were associated with pre-bronchodilator FEV1%pred (p < 0.05). Two of these SNPs (rs2568494 and rs1051730) were linked to post-bronchodilator FEV1 %pred (postFEV1%pred) and the preFEV1/FVC ratio; rs1051730 was also linked to the post-bronchodilator FEV1/FVC ratio. There was no association between any of the genotyped SNPs and pack–years of smoking. There is some evidence that the modifier effects of IREB2 and CHRNA3 may be more prominent in males (rs2568494, rs8034191, and rs1051730 for post-bronchodilator FEV1/FVC), which may support the existence of sex-specific features of COPD susceptibility and severity observed in PI*ZZ patients [25]. The phenotypic manifestation of AATD may be influenced by incomplete penetrance and/or variable expression of genes other than pathogenic SERPINA1 alleles. Rigobello et al. performed whole-exome sequencing (WES) in a group of siblings (n = 9) from four different families with extreme phenotypes of the disease. The family members were concordant for genotype but discordant for clinical presentation, i.e., at least one individual was suffering from emphysema, while the other was not affected, and identified variants were compared across unrelated families [26]. By restricting the analyses to AATD siblings with extreme phenotypes, researchers limited the effect of heterogeneity to allow more reliable identification of factors contributing to the development of emphysema. In contrast to other WES studies, no exclusion of common variants was performed as per the justified assumption that frequent alleles may modify the effects of some rare alleles. As a result, 41,877 functionally annotated variants were identified, including 20,748 (49.5%) synonymous and 21,129 (50.5%) non-synonymous variants. There were 15 variants of 14 genes in the recessive model (57% immune-related) and 23 variants of 21 genes in the dominant model (29% immune-related) in the affected but not non-affected AATD individuals. All variants were identified by pathway analysis as functionally important in innate and adaptive immunity and were primarily involved in the activation of the complement cascade, antigen presentation, and immune response regulation, e.g., the rs3747517 variant of IFIH1 and variants of AKNA and MIB2. Of note, in the group of non-affected individuals, other genetic variants with a known immune suppressor function in innate and adaptive immunity, including HLA-C, HLA-DQB1, and HLA-DRB1 variants, were detected. Other gene variants involved in regulating immune homeostasis and maintaining self-tolerance were identified as predisposing to or protecting from emphysema in siblings with AATD. In affected individuals, these were mainly genes with immune-activating functions; in non-affected individuals, immune-suppressing gene variants involving antigen processing, MHC-I presentation, and TCR and PD-1 signalling were present. Interestingly, some of the genes identified in symptomatic patients, including PPT2, DNTTIP2, IQCG, and PRDM16, had also been reported earlier in GWAS or transcriptomic analyses in patients with COPD [27], highlighting their potential significance for COPD predisposition. The dynein regulatory complex protein 9, encoded by the IQCG gene, is active only in the respiratory system [28], where it is incorporated in the nexin–dynein regulatory complex, a key regulator of ciliary/flagellar motility that maintains the alignment and integrity of the distal axoneme and regulates microtubule sliding in motile axonemes. Consequently, the direct causative roles of gene variants identified in COPD pathogenesis remain unclear. By precise phenotypic matching, Rigobello et al. provided objective evidence of SNPs distributed solely in affected or non-affected siblings with AATD; the distribution differed substantially between the two groups. Symptomatic patients harboured, for example, the rs3747517 variant of the interferon-induced helicase C domain-containing protein 1 (IFIH1) gene, which encodes a cytoplasmic viral RNA receptor that activates the type I interferon signalling adaptor molecule via the mitochondrial antiviral signalling protein. Rice et al. [29] showed that gain-of-function variants in IFIH1 are linked to several human disease phenotypes associated with upregulated type I interferon signalling. DNA methylation, an epigenetic mechanism that involves the transfer of a methyl group to the C5 position of cytosine to form 5-methylcytosine, affects gene expression. Epigenetic regulation has been hypothesised to contribute to COPD development, as the development of this disease cannot be fully explained exclusively by inherited factors, i.e., DNA. Qiu et al. were the first to conduct a comprehensive assessment of DNA methylation to analyse its role as a regulator of gene transcription in the context of lung function impairment and COPD [30]. Analyses were performed independently in two cohorts, both with/without COPD (or unclassified COPD status): 369 subjects from the Boston Early-Onset COPD Study (with/without a history of cigarette smoking) and 1085 patients from the International COPD Genetics Network with a history of cigarette smoking. This array-based methylation analysis encompassed 27,578 CpG sites in 14,475 consensus coding sequences and identified two CpG sites (cg02181506 and cg24621042) in the SERPINA1 gene as the highest-ranking methylation marks associated with COPD. Results were similar in both cohorts and were independent of COPD severity and cigarette exposure. Possible associations of DNA methylation with lung function parameters were also investigated. A total of 4798 and 4899 CpG sites were significantly associated with the FEV1/FVC ratio and FEV1, respectively. Interestingly, no participant was a carrier of biallelic variants in SERPINA1. Thus, SERPINA1 hypomethylation was proposed as an essential risk factor for COPD and bronchial obstruction. Sundar et al. analysed DNA methylation in parenchymal lung tissue [31] and sought to determine whether the genome-wide lung DNA methylation profile of smokers (27.14 ± 5.96 pack-years for 7/8 individuals) and patients with COPD (28.8 ± 4.32 pack-years for 7/8 patients) differed significantly compared with non-smokers. Information on AATD status was not provided in this study. Based on previous data showing that SERPINA1 is significantly hypomethylated in smokers and patients with COPD, SERPINA1 (cg02181506 site) was selected for gene-specific CpG assessment. Contrary to the results of Qiu et al. [30], SERPINA1 hypomethylation in smokers and patients with COPD did not show significant changes. A correlation in the SERPINA1 methylation status (as methylation percentages) among non-smoker groups was noted, while no significant hypomethylation of the SERPINA1 CpG site in smokers and COPD groups compared with non-smokers was evident. Beckmeyer-Borowko et al. [32] evaluated SERPINA1 methylation as a possible determinant of lung function and its decline over the life course in a tobacco smoke-exposed population. The objective was to analyse the associations of a comprehensive set of methylation sites in the SERPINA1 gene cluster with lung function parameters and 10- to 15-year lung function decline. The analysed CpGs within the SERPINA gene cluster were from 12 genes: PPP4R4, SERPINA10, SERPINA6, SERPINA1, SERPINA11, SERPINA9, SERPINA12, SERPINA4, SERPINA5, SERPINA3, SERPINA13, and GSC. Overall, 1076 adult ever-smokers from three population-based European cohorts (SAPALDIA, ECRHS, and NFBC) and 259 tobacco smoke-exposed children from the ALSPAC cohort were analysed. None of the methylation sites in the SERPINA1 gene showed any association with lung function after multiple testing corrections both in multivariate cross-sectional and longitudinal regression analyses. On the other hand, methylation at cg08257009, located 32 kb downstream from SERPINA1, was significantly linked to the FEV1/FVC ratio in adults but not children. Interestingly, relative hypermethylation, but not hypomethylation, at the SERPINA1 loci cg02181506 and cg24621042, as shown by Qiu et al. [30], was associated with a lower concentration of serum ATT in the SAPALDIA cohort. Recently, Rotondo et al. [33] showed evidence of the significance of SERPINA1 methylation for COPD risk in acute coronary syndrome (ACS) patients. The methylation analysis was carried out in 115 ACS patients, including 30 COPD+ and 85 COPD- according to lung function, based on spirometry. Mean age ± standard deviation [SD] was 65 ± 9 years, the inclusion criteria comprised smokers or former smokers (≥10 pack/years) and a clinical diagnosis of ACS, while the exclusion criteria included a previous diagnosis of COPD and/or asthma, known pulmonary diseases other than COPD, ongoing pneumonia, ongoing heart failure, documented or suspicion of malignant disease, life expectancy < 1 year, and recent thoracic trauma. SERPINA1 was hypermethylated in 24/30 (80%) COPD+ and 48/85 (56.5%) COPD- (p < 0.05). The authors concluded that hypermethylation of SERPINA1 may represent a potential biomarker for predicting COPD development in acute coronary syndrome patients. Endoplasmic reticulum (ER) stress, resulting from disturbances in ER homeostasis, leads to the activation of several signalling pathways, including the unfolded protein response (UPR). This process was also described in AATD as the ‘AAT Z variant’ [34,35], which represents a substitution of glutamic acid with lysine at position 342 of the mature protein (Glu342Lys), which is misfolded and undergoes intracellular polymerisation in the ER, activating the UPR. Disturbances in miRNA expression were shown to be involved in this process by direct regulation of UPR components or effectors [36]. Hassan et al. assessed miR-199a-5p as a potential clinically relevant biomarker of AATD symptomology [37]. The researchers investigated ex vivo miRNA expression and function in monocytes from asymptomatic PI*MM non-smokers (n = 8) and PI*ZZ (n = 11) individuals and patients with COPD (7 PI*MM and 11 PI*ZZ) to identify miRNA(s) regulating the UPR. miR-199a-5p was the most upregulated miRNA in asymptomatic PI*ZZ individuals compared with asymptomatic PI*MM individuals, and the UPR markers GRP78, p50, and p65 were overexpressed in monocytes from asymptomatic but not symptomatic ZZ individuals. Moreover, in MM monocytes, in vitro pharmacological induction of ER stress led to increased miR-199a-5p expression, followed by increased DNA methylation at CpG sites upstream of miR-199a-5p and, thereby, silencing of miR-199a-5p. Putative targets of miR-199a-5p enriched in the ER protein folding pathway that modulate the expression of UPR components were further defined using bioinformatic tools. miR-199a-5p was found to modulate the expression of UPR components directly. That study was the first to present evidence of higher expression of key UPR components in monocytes from symptomatic ZZ individuals compared with asymptomatic individuals and of lower miR-199a-5p expression in MM and ZZ monocytes from COPD patients compared with asymptomatic MM or ZZ individuals. Although these results have helped further our understanding of the UPR in ER stress-related diseases such as COPD in AATD, their clinical significance requires further investigation. Considering that members of the miR-320 family have potential specific binding sites in the 3′ untranslated region (UTR) of the SERPINA1 gene, Matamala et al. showed increased miR-320c expression in 98 individuals with pulmonary disease irrespectively of the AAT serum level [38]. Likewise, they demonstrated that miR-320c expression was elevated in vitro in HL60 cells exposed to an inflammatory milieu as well as in response to the pro-inflammatory factor lipopolysaccharide. These results suggest a significant role for miR-320c in AATD as an indicator of inflammatory processes in pulmonary diseases; its potential biomarker significance remains to be determined. Esquinas et al. investigated differences in mRNA and miRNA expression and their possible association with the severity of COPD in PI*ZZ AATD [39]. Gene expression profiling of peripheral blood mononuclear cells from six mild and six severe PI*ZZ COPD patients revealed 205 differentially expressed genes as well as 28 differentially expressed miRNAs. Specifically, hsa-miR-335-5p was downregulated, while 12 target genes involved in cytokine, MAPK/mk2, and JNK signalling, as well as angiogenesis, were upregulated in severe compared with mild patients. Altogether, these results suggest the role of miRNAs in COPD progression and provide evidence of molecular pathways affecting immune cell activity. The SERPINA1 gene harbours over 100 polymorphisms, as summarised in the Human Gene Mutation Database [40]. While not all are pathogenic, their potential biological significance has not been verified. The SERPINA1 gene is also worthy of attention due to the complexity of its transcripts, which encompass 11 mRNA isoforms with two transcription start sites, six splicing donors, and three acceptor sites. The different transcripts are generated by alternative splicing in the 5′-UTR [41]. Since the efficiency of the transcript-specific translation may play an important role in tissue-specific AAT expression, the role of the distinct 5′-UTR in a posttranslational regulatory program, resulting in differences in mRNA expression, was assessed by Corley et al. [41]. They proposed that noncoding SERPINA1 fragments control this program via the interplay between alternative splicing and translation efficiency mediated by upstream open reading frames (uORFs) and RNA structure. uORFs are located within the 5′ leader mRNA sequence and are considered inhibitors of downstream translation initiation of protein-coding sequences. From a practical point of view, the proposed model offers a stimulating contribution to our knowledge of tissue-specific AAT expression, which may provide novel insight into potential therapeutic interventions to increase lung-specific AAT concentrations in affected individuals. The therapeutic strategy may, for example, involve antisense oligonucleotides targeting Kozak sequences (CRCCaugG) near the start codon, which influence the rate of translation initiation [42] around uORFs in SERPINA1 transcripts. Recently, the first (preliminary) data on the changes in lncRNA expression during augmentation therapy in AATD patients have been published [43]. In peripheral blood monocytes (PBMs) isolated from n = 5 ZZ individuals pre- and post (day 2)-AAT augmentation therapy, lncRNA microarray profiling was performed. In total, 17.761 lncRNAs were detectable across all samples, which allowed for the identification of 7509 lncRNAs with differential expression post-augmentation therapy: 3084—increased and 4425—decreased (fold change ≥ 2). Since the results refer to the treatment (supporting the manifold effects of AAT augmentation therapy) and have no obvious relation to the AATD pulmonary manifestations, they are not listed in the Table 1. Clinical experience has shown that the AATD phenotype is only partially attributed to the genotype, i.e., pathogenic variants of SERPINA1, and this disparity is not fully explained by smoking or environmental exposure. Moreover, there is high variability in lung disease presentation and course in AATD individuals. As in any inherited condition, incomplete penetrance and variable expressivity should be considered. Nonetheless, it is likely that genes other than SERPINA1 and genetic polymorphisms contribute to the penetrance and expressivity of AATD. Research is ongoing to identify genetic modifiers and reliable prognostic biomarkers in AATD to facilitate the identification and targeted care of high-risk individuals. Currently described genetic factors, which may contribute to the pulmonary phenotype of AATD, can be categorised as follows: SNPs, changes in DNA methylation, altered miRNA expression, and RNA structure-mediated posttranscriptional modifications (Table 1). Despite significant research efforts, no definitive candidate marker or mechanism involved in the respiratory phenotypic presentation of AATD has been identified. As presented in this review, these analyses have several limitations, such as the size of the cohorts and/or poor matching of the patient groups [36,41]. Many exciting observations will require independent validation in larger cohorts and/or verification within the clinical context. For example, the gene expression profiles reported by Esquinas et al. [39] and Rigobello et al. [26] involved 12 COPD PI*ZZ patients (comparable in age, sex, exacerbations, comorbidities, and use of augmentation therapy) and the clinical data from four families. While small study groups are an accepted norm in rare disease research, prospective clinical data collected from international registries, such as the European EARCO registry for AATD, might provide a more reliable source for analyses. In addition, the sizes of the study groups need to be interpreted in the context of the study design. Rigobello et al. applied a case–control study design by comparing closely related AATD probands with contrasting clinical phenotypes. Consequently, certain genetic variants (SNPs) were found exclusively in patients with AATD-related respiratory disease and not in their non-affected siblings with AATD. Data should also be considered in light of their actual, and not just statistical, significance. A statistical cut-off of p ≤ 0.05 is considered the gold standard and directly affects protocol design as well as the expected size of the study groups. Clinical significance, or the minimum clinically important difference, which allocates the specific needs of rare disease research without breaching clearly stated assumptions and precise research methodology, is becoming more accepted. The ultimate verification of both data and conclusions comes from their repeatability in independent, but clinically comparable, cohorts [16]. Wood et al. demonstrated a statistically significant difference in the frequency of TNF-α rs361525 between PI*ZZ individuals with and those without chronic bronchitis (genotype, p = 0.01; and allele, p = 0.01). However, they were unable to verify this observation in a different cohort [4]. DeMeo et al. confirmed this association between TNF and bronchial obstruction in AATD patients; however, there was no overlap in the clinically significant TNF SNPs, preventing any meaningful conclusions [21]. Considering the immunoregulatory role of the AAT protein, independent of its antineutrophil elastase activity and its interaction with the neutrophil-binding TNF-α receptor [45], the potential role of TNF in AATD is worthy of further investigation. There are other interesting observations in need of verification, such as the increased expression of components of the MAPK signalling pathway, specifically EREG, EGR3, and TRIB1, which are important for regulating the inflammatory response [39,46] and modifying the AATD clinical phenotype. There are also contradictory studies on the potential modifying role of certain polymorphisms. DeMeo et al. [21] explored GSTP1 and NOS3 polymorphisms in a family-based study and were unable to confirm the association between the GSTP1 105Val polymorphism and COPD in AATD, proposed by Rodriguez et al. [14], or the increased frequencies of the NOS3 774T and 894T alleles in AATD individuals with severe lung disease, suggested by Novoradovsky et al. [11]. The interaction between genetic, epigenetic, and environmental factors and their effect on AATD clinical presentation is convoluted at present. Whether the DNA methylation changes observed in certain AATD phenotypes are of primary or secondary origin, i.e., result from environmental factors, smoking, or inflammatory stimuli, is an ongoing debate [30]. To fully address this issue, tissue-specific, whole-genome, age-dependent research on methylation markers and their effects on specific physiological mechanisms is warranted. In a blood-based methylome study, Beckmeyer-Borowko et al. did not observe significant associations between SERPINA1 gene methylation changes and lung function parameters after multiple testing corrections [32]. Similarly, a more extensive epigenome-wide association study on smoking showed no relevant link between SERPINA1 epigenetic signatures and smoking [47]. While some researchers believe that the effects of smoking on SERPINA1 methylation do not warrant further investigation, the potential bias introduced by environmental factors, including smoking, continues to be an issue in AATD research. Methodological issues also add to the complexity. A potential link between decreased miR-335-5p expression and AATD-related emphysema was independently proposed by Ezzie et al. [48] and Van Pottelberge et al. [49]; however, differences in clinical characteristics and the biological compartments evaluated rendered analysis difficult. Comparing lung samples from COPD and non-COPD smokers [48] and sputum samples from COPD smokers, non-COPD smokers, and never-smokers [49] did not enable reliable interpretation of observed miRNA up- or downregulation. Moreover, as with DNA methylation, the question of a primary or secondary causative link to disease severity, co-morbidities, medications, and external factors, such as smoking, remains unanswered. Finally, in addition to environmental stimuli, the potential effects of genetic factors other than SERPINA1 cannot be ignored. Although their role in clinical phenotype variability in AATD has not been confirmed, numerous candidate modifiers have been suggested, mostly among immune-related pathways [26,39]. Likewise, most, if not all, research studies and clinical guidelines are focused on the phenotypic presentations of the PI*Z and PI*S alleles. There is a shortage of clinical data on the phenotypic manifestation of rare SERPINA1 variants. Efforts should be made to collect data on the clinical significance of many largely unknown variants.

PMC10003159

Longkun Wang,Chunqian Zhao,Lu Lu,Honglei Jiang,Fengshan Wang,Xinke Zhang

Transcytosable Peptide-Paclitaxel Prodrug Nanoparticle for Targeted Treatment of Triple-Negative Breast Cancer

28-02-2023

paclitaxel,peptide-drug conjugate,TAT peptide,A7R peptide,targeted delivery,anticancer therapy,transcytosis

Triple-negative breast cancer (TNBC) is an extremely aggressive subtype associated with a poor prognosis. At present, the treatment for TNBC mainly relies on surgery and traditional chemotherapy. As a key component in the standard treatment of TNBC, paclitaxel (PTX) effectively inhibits the growth and proliferation of tumor cells. However, the application of PTX in clinical treatment is limited due to its inherent hydrophobicity, weak penetrability, nonspecific accumulation, and side effects. To counter these problems, we constructed a novel PTX conjugate based on the peptide-drug conjugates (PDCs) strategy. In this PTX conjugate, a novel fused peptide TAR consisting of a tumor-targeting peptide, A7R, and a cell-penetrating peptide, TAT, is used to modify PTX. After modification, this conjugate is named PTX-SM-TAR, which is expected to improve the specificity and penetrability of PTX at the tumor site. Depending on hydrophilic TAR peptide and hydrophobic PTX, PTX-SM-TAR can self-assemble into nanoparticles and improve the water solubility of PTX. In terms of linkage, the acid- and esterase-sensitive ester bond was used as the linking bond, with which PTX-SM-TAR NPs could remain stable in the physiological environment, whereas PTX-SM-TAR NPs could be broken and PTX be released at the tumor site. A cell uptake assay showed that PTX-SM-TAR NPs were receptor-targeting and could mediate endocytosis by binding to NRP-1. The vascular barrier, transcellular migration, and tumor spheroids experiments showed that PTX-SM-TAR NPs exhibit great transvascular transport and tumor penetration ability. In vivo experiments, PTX-SM-TAR NPs showed higher antitumor effects than PTX. As a result, PTX-SM-TAR NPs may overcome the shortcomings of PTX and present a new transcytosable and targeted delivery system for PTX in TNBC treatment.

Transcytosable Peptide-Paclitaxel Prodrug Nanoparticle for Targeted Treatment of Triple-Negative Breast Cancer Triple-negative breast cancer (TNBC) is an extremely aggressive subtype associated with a poor prognosis. At present, the treatment for TNBC mainly relies on surgery and traditional chemotherapy. As a key component in the standard treatment of TNBC, paclitaxel (PTX) effectively inhibits the growth and proliferation of tumor cells. However, the application of PTX in clinical treatment is limited due to its inherent hydrophobicity, weak penetrability, nonspecific accumulation, and side effects. To counter these problems, we constructed a novel PTX conjugate based on the peptide-drug conjugates (PDCs) strategy. In this PTX conjugate, a novel fused peptide TAR consisting of a tumor-targeting peptide, A7R, and a cell-penetrating peptide, TAT, is used to modify PTX. After modification, this conjugate is named PTX-SM-TAR, which is expected to improve the specificity and penetrability of PTX at the tumor site. Depending on hydrophilic TAR peptide and hydrophobic PTX, PTX-SM-TAR can self-assemble into nanoparticles and improve the water solubility of PTX. In terms of linkage, the acid- and esterase-sensitive ester bond was used as the linking bond, with which PTX-SM-TAR NPs could remain stable in the physiological environment, whereas PTX-SM-TAR NPs could be broken and PTX be released at the tumor site. A cell uptake assay showed that PTX-SM-TAR NPs were receptor-targeting and could mediate endocytosis by binding to NRP-1. The vascular barrier, transcellular migration, and tumor spheroids experiments showed that PTX-SM-TAR NPs exhibit great transvascular transport and tumor penetration ability. In vivo experiments, PTX-SM-TAR NPs showed higher antitumor effects than PTX. As a result, PTX-SM-TAR NPs may overcome the shortcomings of PTX and present a new transcytosable and targeted delivery system for PTX in TNBC treatment. Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks the expression of estrogen and progesterone receptor (ER/PR), as well as human epidermal growth factor receptor (HER-2), accounting for about 20% of the total diagnosed breast cancers in the world [1,2]. TNBC is mainly prevalent in young women and has the characteristics of high invasion, high heterogeneity, and poor prognosis. The high heterogeneity and lack of specific receptors of TNBC limit the choice of clinical treatments. Nowadays, surgery combined with chemotherapy drugs is still the standard treatment for TNBC [3,4,5]. With the in-depth understanding of TNBC molecular subtyping, an increasing number of targeted drugs have entered research and development [6,7,8,9]. Up to now, four targeted drugs have been approved by the FDA for the treatment of TNBC, including two PARP1 inhibitors (olaparib and talazoparib), one programmed cell death 1 ligand (PD-L1) inhibitor (atezolizumab), and one antibody-drug conjugate (ADC) (sacituzumab-govitecan) [10]. Nevertheless, these drugs cannot meet the demand of all TNBC patients, and new targeting strategies need to be continuously developed to improve the clinical cure rate of TNBC [11]. Paclitaxel (PTX) is a common antitumor agent that mainly acts on cytoplasmic microtubules. PTX binds covalently to the β-subunit of a tubulin protein to interfere with the dynamic balance of microtubules and inhibit microtubule depolymerization, which would arrest cell division in the G2/M phase and form multinucleated cells, ultimately leading to cell death [12,13]. On account of its potent tumor inhibitory effect, paclitaxel has been used for a long time in the clinical treatment of various cancers. As a key component in the standard treatment of TNBC, PTX is an indispensable and important drug in the clinical treatment of TNBC [14]. However, due to its inherent hydrophobic property, weak penetrability, and nonspecific accumulation, the clinical application of PTX is limited to a certain extent [15]. To address these issues, many PTX formulations have been studied. So far, three PTX formulations have been approved by the FDA, including Taxol®, Abraxane®, and Xyotax® [16,17,18]. Nevertheless, they only provide an appropriate solubilization system rather than an ideal active targeted drug delivery system, with a slight attenuation in systemic toxicity caused by PTX. To obtain better clinical applications of PTX, a variety of strategies have been explored continuously [19,20,21]. Peptide-drug conjugates (PDCs) are a kind of new drug delivery strategy derived from antibody-drug conjugates (ADCs), which are formed by coupling flexible peptides with small molecule drugs through cleavage or non-cleavage linkers [22,23,24]. The multifunctional peptides endow the conjugates with some excellent properties, including water solubility, targeting, sensitization, and penetrability [25,26,27,28]. In contrast to other drug delivery systems, PDCs have the advantages of small molecular weight, easy synthesis, low immunogenicity, and a flexible structure [29]. Consequently, PDCs gradually play an important role in tumor therapy. Peptides commonly used in PDCs are divided into two categories, tumor-targeting peptides (TTPs) and cell-penetrating peptides (CPPs) [30,31]. CPPs are widely used in drug delivery systems and can cross the cell membrane through energy-dependent or non-energy-dependent ways to enhance the cellular uptake of drugs [32]. TAT (RKKRRQRRR), as one of the most common CPPs, has the feature of efficient and non-invasive transmembrane transport [33,34]. Nevertheless, due to the lack of tumor specificity, TAT-induced systemic distribution may lead to reduced drug effects and enhanced side effects. To solve the problem, coupling CPPs with TTPs may be an effective method [35,36,37,38]. Solid tumor tissues not only contain tumor cells but also diffuse a large number of newly formed blood vessels. Angiogenesis, the growth of new blood vessels from existing vascular systems, plays a crucial role in cell nutrition supply and metabolic waste excretion. Therefore, angiogenesis is an essential event in tumor progression and is considered an attractive target for cancer therapy [39,40]. Neuropilin 1 (NRP-1) is an important receptor in tumor angiogenesis that regulates this process by binding to ligand VEGF-A and activating downstream signaling pathways [41,42]. NRP-1 is highly expressed in tumor vascular endothelial cells and some tumor cells [43,44]. Additionally, it has been confirmed that NRP-1 expression in TNBC is up-regulated compared to other breast cancer subtypes, and NRP-1 can be used as a potential target for TNBC treatment [45,46,47]. Hence, NRP-1 mediated targeted therapy may be a potential strategy for precise TNBC therapy by simultaneously targeting tumor cells and vascular endothelial cells. An A7R (ATWLPPR) peptide selected by phage screening technology can target NRP-1 and is widely used in tumor-targeted therapy [48]. In the previous study, we designed a novel bifunctional fusion peptide, including A7R and TAT, named TAR peptide. TAR peptide can also target NRP-1 for cargo delivery and effectively penetrate the tumor barrier, which has been used for DNA delivery for the treatment of glioma [49]. In this study, TAR peptide was used to deliver PTX into breast tumors more efficiently. TAR peptide was coupled with PTX using an acid- and esterase-sensitive ester bond and formed a novel prodrug conjugate PTX-SM-TAR. The main difference between tumor cells and normal cells lies in their morphological structure and the mode of growth and metabolism. Tumor cells grow and metabolize more vigorously, thus creating a microenvironment rich in lactic acid and various proteases. Therefore, the conjugate PTX-SM-TAR can remain stable in the normal physiological environment, whereas the ester bond can be degraded quickly and PTX can be released from PTX-SM-TAR at the tumor site with low pH and high esterase activity. In addition, the conjugate PTX-SM-TAR synthesized by hydrophilic TAR peptide and hydrophobic PTX is amphiphilicity and has the characteristics of self-assembly in an aqueous solution to form a core-shell nano-micelle. In antitumor therapy, nanomedicines mainly rely on the enhanced permeability and retention effect (EPR) to target the tumor tissue passively. However, the EPR effect is hindered by increased tumor interstitial fluid pressure, high viscous extracellular matrix, and tumor heterogeneity, which leads to the limitation of drug extravasation in blood vessels and insufficient penetration into the tumor entity to maximize the efficacy of nanomedicines [50]. Transcytosis is a broad transcellular transport process in which substances are transferred from one side of a cell to the other. Unlike passive diffusion, transcytosis is an active transport process that can deliver drugs through multiple pathways [51]. In recent years, transcytosable nanomedicine has become a new interest in promoting the penetration of nanomedicines in tumors [52,53]. The transcytosis design of these nanomedicines could depend on different forms, including receptor-mediated transcytosis, adsorption-mediated transcytosis, and fluid-mediated transcytosis [51]. Based on the receptor-binding and positive charge properties of TAR peptides, we hypothesized that in addition to the EPR effect, the PTX-SM-TAR nanosystem can also be rapidly internalized by endothelial cells or tumor cells through receptor and adsorption-mediated transcytosis, improving extravasation efficiency in tumor vessels and enhancing permeability in tumor tissues. In this study, we focus on developing a novel prodrug conjugate using the PDCs strategy and evaluating its efficacy in the treatment of TNBC. The prodrug conjugate PTX-SM-TAR was designed and synthesized by linking hydrophobic PTX to the hydrophilic TAR peptide using an ester bond. The PTX-SM-TAR possessed the following advantages: (1) With amphiphilic properties, it can self-assemble into nano-complexes, which improves the water solubility of PTX. (2) With an acid- and esterase-sensitive linker, the conjugate can quickly release PTX under certain circumstances. (3) TAR peptide gives the conjugate excellent tumor targeting, transvascular transport, and penetration properties, which could deliver more PTX to arrive at the TNBC tumor site and take active effects. In summary, the conjugate PTX-SM-TAR might be a potential targeted therapy for TNBC. The binding affinity of the TAR peptide to NRP-1 was measured with an SRP assay. As shown in Figure S1, TAR showed a strong binding ability to NRP-1 with a KD value of 3.397 × 10−8 M. TAR peptide labeled with fluorescein Cy5.5-MAL was used to analyze the tumor-targeting delivery ability of a TAR peptide in vivo. After an intravenous injection of Cy5.5-MAL-TAR and free Cy5.5-MAL via the tail vein, the entire body and ex vivo fluorescence images were recorded using an in vivo imaging system. In tumor tissues, strong fluorescence was detected in the Cy5.5-MAL-TAR group while only modest or no fluorescence was detected in the Cy5.5-MAL group (Figure 1a,b). After 8 h of injection, the mice were sacrificed, and the main tissues (heart, liver, spleen, lung, kidney, and tumor) were collected for in vitro fluorescence detection (Figure 1c). The fluorescence intensity of the two groups was equivalent in the spleen and kidney. The fluorescence of Cy5.5-MAL-TAR was significantly weakened in the heart, liver, and lung tissues, especially in lung tissues, which is 40% of free Cy5.5-MAL. However, Cy5.5-MAL-TAR exhibited stronger fluorescence at the tumor site, 1.64 times that of free Cy5.5-MAL (Figure 1d). The slice analysis of tumor tissues showed that Cy5.5-MAL-TAR was widely dispersed in tumor tissues covering all micro-vessels and tumor cells that over-expressing NRP-1 while free Cy5.5-MAL only diverged in a spot-like manner and had no correlation with the expression level of NRP-1 (Figure 1e,f). The synthetic route of PTX-SM-TAR was shown in Figure 2a, which was carried out in three steps. With SA-MAL as the connecting arm, PTX-SA was firstly formed by esterification at the 2′-OH position of PTX, and then PTX-SA-MAL was synthesized by amide reaction. Finally, the equivalent amount of PTX-SA-MAL and the TAR peptide were coupled together through a thioether bond. These products were characterized by 1H-NMR and Q-TOF HRMS spectrum after purification (Supplementary Figures S2 and S3). As shown in Figure 2b, the characteristic peak of the secondary amine of tryptophan in the TAR peptide sequence at 10.834 ppm and that of the secondary amine in the PTX structure at 9.239 ppm. The ratio of the two peak areas (1:1) was consistent with the structural characteristics of PTX-SM-TAR. In the Q-TOF HRMS spectrum, the peak signal of 1671.3668 ([M+2H]2+) and 1114.5837 ([M+3H]3+) were consistent with the calculated molecular weight (3340.8680), suggesting that PTX-SM-TAR has been successfully synthesized (Figure 2c). The purity of PTX-SM-TAR was determined to be 95% by analytical HPLC (Figure 2d). The PTX-SM-TAR conjugate is a typical amphiphilic molecule composed of a hydrophobic PTX and a hydrophilic TAR peptide. Based on the molecular properties, PTX-SM-TAR conjugate can self-assemble into nanoparticles in an aqueous environment. The CAC of PTX-SM-TAR NPs was determined by the conductivity method to be 3.95 × 10−6 mol/L (Figure 3a). TEM and DLS were performed to characterize the morphology, particle size, size distribution, and zeta potential of PTX-SM-TAR NPs. DLS results showed that the PTX-SM-TAR conjugate could form uniform nanocomposites (PDI = 0.21 ± 0.03) with a particle size around 94.70 ± 1.87 nm (Figure 3b) and zeta potential around 14.53 ± 0.31 mV (Figure 3c). TEM results displayed that PTX-SM-TAR conjugate can form spherical nanoparticles in an aqueous solution (Figure 3d). In order to evaluate the sensitivity of PTX-SM-TAR NPs to acid and esterase, the in vitro release of free PTX was investigated in a PBS buffer containing 1% Tween 80. Here, PBS at pH 7.4 mimics the normal physiological environment while PBS at pH 6.8 with esterase mimics the microenvironment around the tumor. As shown in Figure 3e, in the absence of esterase, the amount of PTX released from PTX-SM-TAR NPs in PBS at pH 7.4 was 35.52 ± 1.53% and pH 6.8 was 39.55 ± 2.59% after 48 h incubation. In the presence of esterase, the release rate of PTX in PBS at pH 7.4 was 52.77 ± 3.84% and pH 6.8 was 57.02 ± 0.51% after 48 h incubation. In order to verify the targeting properties of PTX-SM-TAR NPs to NRP-1 in vitro, PTX-SM-TAR/C6 NPs were prepared by loading coumarin-6. PTX-SM-TAR/C6 NPs were co-cultured in 4T1-mCherry-Luc cells with high or low expression of NRP-1, followed by observing and quantifying cell uptake through LSCM and flow cytometry. The NRP-1 siRNA was used for establishing the 4T1-mCherry-Luc cell lines with NRP-1 down-regulated expression. A Western blot assay was used to determine the expression of the NRP-1 receptor. As depicted in Figure 4a, the expression of NRP-1 in the NRP-1 siRNA group was significantly lower than that in the control group, indicating that NRP-1 siRNA inhibited NRP-1 expression in 4T1-mCherry-Luc cell lines. As presented in Figure 4b,c, green fluorescence was visualized in the cytoplasm of cells after being cultured, and the fluorescence became stronger over time. At the same time point, the untreated cells with high expression of NRP-1 had more PTX-SM-TAR/C6 NPs uptake (Figure 4d). In order to further verify the targeting effect of PTX-SM-TAR NPs realized by the specific binding of TAR and NRP-1 receptor, an extra TAR peptide was added into cell culture to block the receptors. At the same time point, the uptake of PTX-SM-TAR/C6 NPs by wild 4T1-mCherry-Luc (NRP-1 higher expression) cells co-cultured with TAR peptide was significantly reduced compared with that without TAR peptide (Figure 4e). However, there was no significant difference in PTX-SM-TAR/C6 NPs uptake by NRP-1 low expressed cells with or without TAR peptide (Figure 4f). Moreover, the decrease in PTX-SM-TAR/C6 NPs uptake induced by TAR competition also occurred in the HUVEC cells with high NRP-1 expression (Supplementary Figure S4). In order to evaluate the penetration of PTX-SM-TAR NPs in tumor vessels, we measured the vascular barrier penetration efficiency of PTX-SM-TAR/C6 NPs in vitro. After the vascular barrier was successfully constructed in vitro (Figure 5a), PTX-SM-TAR/C6 NPs and coumarin-6 were added for incubation. The results of fluorescence determination were shown in Figure 5b,c. PTX-SM-TAR/C6 NPs showed a high penetration rate in the vascular barrier, which was significantly higher than that of the coumarin-6 group, showing a significant difference. The transcellular migration experiment in 4T1-mCherry-Luc cells was conducted to evaluate the transcytosis of PTX-SM-TAR NPs. As shown in Figure 6, the coverslips (1)–(3) of the PTX-SM-TAR/C6 NPs group showed obvious fluorescence, indicating that PTX-SM-TAR/C6 NPs can be taken up by the cells in the coverslip (1) and can be transported to other coverslip cells. The coumarin-6 group also underwent efflux transport after uptake, but the intracellular fluorescence intensity was significantly weaker than that of the PTX-SM-TAR/C6 NPs group. A 3D tumor spheroid is a general model for evaluating permeability in vitro, which can simulate solid tumor tissue in vivo [54,55]. To evaluate the tumor penetrability of TAR peptide-mediated PTX-SM-TAR NPs, we used 4T1-mCherry-Luc cells to construct a multicellular spheroid (MCS) model, which was observed by CLSM after incubation. In this experiment, the tumor spheroids were incubated with PTX-SM-TAR/C6 NPs and coumarin-6, respectively, for 2 or 4 h and then scanned at an interval of 10 μm. As presented in Figure 7a,b, the fluorescence of the PTX-SM-TAR/C6 NPs treated group was distributed in most areas of MCS after incubation for 2 h while the fluorescence of the coumarin-6 treated group was mainly distributed in the outer edge of MCS. Over time, the fluorescence distribution of both groups developed more extensively. After incubation for 4 h, both groups could observe distinctive fluorescence in the internal region of the tumor spheroids (Figure 7c,d). Among them, the PTX-SM-TAR/C6 NPs treated group could observe obvious green fluorescence under different scanning layers while the fluorescence of the coumarin-6 treated group gradually disappeared after the Z-axis exceeded 60 μm. To investigate the effects of PTX-SM-TAR NPs on microtubules in 4T1-mCherry-Luc cells, microtubules were observed by LSCM using an anti-tubulin antibody (Figure 8a) and the cytotoxicity effect of PTX-SM-TAR NPs against normal cells EA.hy926 (Figure S5). The microtubules in the control group were evenly distributed while the microtubules in the PTX and PTX-SM-TAR NPs treated groups aggregated and showed high green fluorescence. In addition, toxicological results against EA.hy926 cells showed that the linker SM had no toxicity to normal cells, and the PTX had slight toxicity to normal cells in the low-concentration. However, with the increase of drug concentration, the toxicity of PTX to normal cells also increased, and the conjugate PTX-SM-TAR showed the same trend as the PTX. CCK-8 method was used to detect the anti-proliferation effect of PTX-SM-TAR NPs against 4T1-mCherry-Luc cells (Figure 8b). From 0.0001 nM to 10,000 nM, the inhibition rate of TAR, PTX, TAR plus PTX, and PTX-SM-TAR NPs on 4T1-mCherry-Luc cells increased gradually. At all concentrations, the cell proliferation inhibition rate of the PTX-SM-TAR NPs group was higher than that of the PTX group with statistical differences, which may be caused by an increased cell uptake of PTX-SM-TAR NPs mediated by TAR peptide. To assess the migration inhibitory effect of PTX-SM-TAR NPs on 4T1-mCherry-Luc cells, the wound healing assay was conducted. At 24 h, the migration rate was 36.89 ± 2.09% in the control group, 32.23 ± 3.81% and 32.53 ± 1.43% in 10 nM PTX-SM-TAR NPs and PTX groups, and 20.10 ± 3.15% and 18.96 ± 2.76% in 100 nM PTX-SM-TAR NPs and PTX groups (Figure 8c,d). The migration rate of 4T1-mCherry-Luc cells treated with PTX-SM-TAR NPs was equivalent to that of PTX. The mice TNBC 4T1-mCherry-Luc model was constructed by subcutaneous inoculation to study the anti-tumor effect of PTX-SM-TAR NPs in vivo. 4T1-mCherry-Luc cells reacted with D-luciferin potassium salt to produce bioluminescence, which was determined by an IVIS spectrum imaging system. The intensity of the fluorescence signal is related to tumor size, hence tumor growth in mice can be monitored in real-time. As shown in Figure 9a, the tumor growth rate of the PTX-SM-TAR NPs group was lower than that of the NS, TAR, and PTX groups. At the end of the experiment, the tumor tissue was weighed, and the results were consistent with the trend of fluorescence intensity (Figure 9b). The tumor inhibition rate was 43.24% in the PTX-SM-TAR NPs, 28.47% in the PTX, and 7.81% in the TAR. The tumor inhibitory effect of the PTX-SM-TAR NPs group was stronger than that of the PTX group, and the difference was significant. In addition, the TUNEL and H&E staining results of tumor tissues showed that the TNBC treated with PTX and PTX-SM-TAR NPs had obvious apoptosis and serious tissue damage (Figure 10). On the contrary, NS group tumor cells were arranged closely and orderly, and no visible apoptosis or necrosis was observed. The changes in mice weight during treatment were measured to evaluate the toxic and side effects of PTX-SM-TAR NPs (Figure 9c). The body weight of mice in TAR, PTX, and PTX-SM-TAR NPs groups remained stable during the experiment while the body weight of mice in the NS group began to decrease gradually after 8 days of administration. The TAR peptide combines the advantages of A7R and TAT peptide, which not only specifically target NRP-1 on cells, but also can efficiently transport across the cell membrane. In order to verify whether the TAR peptide carrier can successfully and effectively transport drugs to the tumor site, the fluorescence distribution of Cy5.5-MAL-TAR in vivo was monitored by an IVIS spectrum imaging system. In vivo imaging data showed that Cy5.5-MAL-TAR remarkably increased the content of Cy5.5-MAL and prolonged its retention time in the tumor site. It was observed with staining that Cy5.5-MAL-TAR was widely dispersed in tumor tissues, covering all micro-vessels and tumor cells, while free Cy5.5-MAL only diverged in a spot-like manner, indicating that TAR acted as a carrier and delivered a large amount of Cy5.5-MAL into tumor tissues. In addition, the TAR vector targets more Cy5.5-MAL to the tumor site, thereby reducing the distribution of Cy5.5-MAL in normal tissues, which may facilitate the reduction of systemic toxicity in the future delivery of drugs. Because of its excellent delivery performance, the TAR peptide is used to modify PTX to improve its deficiency. Through structural analysis, it was found that the lysine and arginine in the TAR peptide played an important role in cell penetration. In addition, arginine at the C-terminal was the guarantee for the realization of targeting. When a TAR peptide was used for the structural modification of PTX, it needed to be ensured that the active sites of TAR peptide were not covered. Therefore, a cysteine was added to the N-terminal of TAR to form a thioether bond, which is common in ADCs design, to finally synthesize the intelligent PDC. In the structure of PTX, the C2′-OH is not only the active site of PTX, but also the commonly used modification site, which can be temporarily shielded to synthesize inactive prodrugs. Therefore, SA-MAL was used as the connecting arm to connect TAR with PTX through a three-step reaction, forming the acid- and esterase-sensitive prodrug PTX-SM-TAR. PTX-SM-TAR is an amphiphilic molecule with self-assembly properties and can be soluble in an aqueous solution. We hypothesize that the Π-Π interaction between PTX molecules and the hydrogen bonding between TAR molecules may lead to the formation of a hydrophilic peptide shell, and the hydrophobic PTX was wrapped in the core to form water-soluble micelles. An act verified by TEM and DLS experiments, when the concentration was higher than 3.95 × 10−6 mol/L, PTX-SM-TAR could self-assemble to form uniform and dispersed spherical nanoparticles with particles size of 94.70 ± 1.87 nm. The above data showed that PTX-SM-TAR molecules could increase the water solubility of PTX through self-assembly into nanoparticles. To verify the targeting properties of PTX-SM-TAR NPs, in vitro cellular uptake was performed in 4T1-mCherry-Luc cells with high and low expression of NRP-1. After being co-cultured with PTX-SM-TAR/C6 NPs solution, untreated 4T1-mCherry-Luc cells showed stronger fluorescence than NRP-1 siRNA treated 4T1-mCherry-Luc cells. Assuming that this phenomenon is caused by receptor-mediated endocytosis, we further conducted the competitive experiment. After TAR incubation, the uptake of fluorescent substances in normal 4T1-mCherry-Luc cells was significantly decreased with TAR competition while that in NRP-1 siRNA treated cells was not significantly changed. TAR indeed has the ability to block the entry of PTX-SM-TAR/C6 NPs into cells with high NRP-1 expression, indicating that PTX-SM-TAR/C6 NPs have the same mechanism as TAR for cell entry. Therefore, it can be inferred that PTX-SM-TAR has the targeting ability to NRP-1 and enter into cells through receptor-mediated endocytosis, which is helpful for PTX to target new blood vessels and tumor sites where NRP-1 is highly expressed. Tumor therapeutic drugs should not only actively target the tumor but also effectively penetrate the tumor tissue after reaching the tumor site. In this study, we first measured the permeability of PTX-SM-TAR NPs in the vascular barrier. The results showed that PTX-SM-TAR NPs could successfully cross the vascular barrier, which facilitates drug penetration from blood vessels into the tumor solid site to increase drug concentration at the tumor site. Then, the transcellular migration experiment showed that PTX-SM-TAR NPs can be transported between cells, which facilitates drug delivery from tumor edge cells to interior cells. In addition, we utilized the 4T1-mCherry-Luc cells tumor spheroid to simulate the penetration of PTX-SM-TAR NPs in vivo. Compared with free coumarin-6, coumarin-6 encapsulated in PTX-SM-TAR NPs could penetrate deeper into the tumor spheroid, and the depth was increased over time. TAR peptide enhanced the penetration of PTX, which contributed to its effects on cells within the tumor parenchyma. TAR reacted with the active site 2′-OH of PTX to form the prodrug PTX-SM-TAR NPs. Prodrugs are generally inactive during normal circulation in vivo and take effect in abnormal tumor microenvironments by stimulating the release of free active drugs. The ester bond is considered to be an acid- and enzyme-sensitive bond. When the pH decreases or the content of esterase increases, the unstable ester bond will be disconnected. In the release experiment, PTX can be released slowly under different conditions without burst release. When the conditions of low pH and high esterase were satisfied at the same time (tumor simulation environment), the release of PTX reached the maximum. The results demonstrated that the release of PTX in PTX-SM-TAR NPs prodrug was controlled and sustained. In vitro microtubule experiment, compared with the control group, 4T1-mCherry-Luc cells treated with PTX and PTX-SM-TAR NPs showed a dynamic imbalance of microtubules in the cytoplasm, which was consistent with the mechanism of PTX stabilizing microtubule polymerization. In vitro cell anti-proliferation experiments showed that the growth of 4T1-mCherry-Luc cells in each group was inhibited in a dose-dependent manner. Among them, the conjugate PTX-SM-TAR NPs exhibited stronger cytotoxicity against 4T1-mCherry-Luc cells than free PTX. These results indicated that PTX modified by TAR peptide did not affect its biological activity, and 4T1-mCherry-Luc cells took up more PTX-SM-TAR mediated by TAR, resulting in increased intracellular content of PTX. In vitro cytotoxicity assay against normal cells EA.hy926 showed that the linker SM is low toxicity, but PTX and PTX-SM-TAR NPs were not completely safe and non-toxic to normal cells. It is inferred that the toxicity of PTX-SM-TAR to normal cells is mainly attributed to PTX, and the linker we used is safe. In vivo, the PTX-SM-TAR NPs mainly tend to tumors and accumulate less in other normal tissues, thereby reducing the damage to normal tissue cells. Moreover, PTX-SM-TAR NPs and PTX also can effectively inhibit the migration of 4T1-mCherry-Luc cells. The antitumor effect of PTX-SM-TAR NPs in vivo was evaluated by 4T1-mCherry-Luc animal models. The distribution of PTX-SM-TAR NPs in the tumor leads to distinct apoptosis and tissue damage. PTX-SM-TAR NPs can effectively inhibit the growth of TNBC tumors, which is superior to free PTX. In summary, TAR peptide-mediated PTX-SM-TAR NPs can actively target and penetrate into tumor tissue in vivo, and effectively inhibit tumor growth. The paclitaxel was purchased from Wuxi Taxus Pharmaceutical Co., Ltd. (Jiangsu, China). Succinic anhydride (SA), 4-dimethyl aminopyridine (DMAP), 1-hydroxy-benzotriazole (HoBt), and 2-(1H-Benzotriazole-1-yl)-1,1,3,3-tetramethyluronium hexafluorophosphate (HBTU) were purchased from Macklin (Shanghai, China). N,N-Diisopropylethylamine (DIPEA) was purchased from Aladdin (Shanghai, China). N-(2-Aminoethyl) maleimide trifluoroacetate salt (MAL) was purchased from J&K Chemical Ltd. (Beijing, China). TAR peptide (CRKKRRQRRRATWLPPR) was synthesized from China Peptide Co., Ltd. (Shanghai, China). Esterase and coumarin-6 were purchased from Shanghai yuanye Bio-Technology Co., Ltd. (Shanghai, China) Rabbit anti-NRP-1 antibody was purchased from Abcam (Cambridge, UK). Rabbit anti-β-actin antibody and secondary antibody (anti-rabbit) were purchased from ProteinTech (Beijing, China). 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was obtained from BioFroxx (Einhausen, Germany). Cy5.5 maleimide (non-sulfonated, Cy5.5-MAL) was obtained from APExBIO (Houston, TX, USA). Tubulin-tracker green and DAPI were obtained from Beyotime (Shanghai, China). Regular agarose G-10 was purchased from Biowest (Spain). F-12K medium, heparin and endothelial cell growth supplement (ECGS) were obtained from MacGene (Beijing, China). 1640 medium was obtained from Meilunbio (Dalian, China). Human umbilical vein endothelial cells (HUVEC) were obtained from ATCC (Manassas, VA, USA), and 4T1-mCherry-Luc cells (TNBC cells) were obtained from Caliper Life Sciences (Boston, MA, USA). HUVEC cells were cultured in F12K medium containing 10% fetal calf serum (FBS), 1% ECGs, and 1% heparin. 4T1-mCherry-Luc cells were cultured in 1640 medium containing 10% FBS. Both of them were incubated at 37 °C with 5% CO2. Healthy female BALB/c mice (18–20 g) were purchased from Shandong University Laboratory Animal Center. Mice were housed in a pathogen-free environment under conditions of 25 ± 2 °C, 50 ± 5% relative humidity, and 12-h light/dark cycles. They were provided with food and water ad libitum. All animal experiment protocols were approved by the Ethics Committee of School of Pharmaceutical Sciences, Shandong University (22017) and implemented according to the regulations of the Shandong Council on Animal Care. To establish the mice TNBC model, 1.0 × 106 4T1-mCherry-Luc cells were subcutaneously injected into the left forelimb armpit of mice. D-fluorescein potassium salt solution was injected into mice through the abdominal and reacted with 4T1-mCherry-Luc cells to produce bioluminescence. Then, the fluorescence signals were observed and counted by an IVIS Spectrum imaging system (IVIS Kinetic). The surface plasmon resonance (SPR) detection technique was used to determine the binding affinity of TAR peptide to NRP-1 by Biacore T200 instrument (GE). First, the purified NRP-1 protein was immobilized on the CM5 chip. Then, using HBS-EP as a running buffer, a gradient-diluted TAR peptide solution was configured to flow through the surface of the chip for binding and dissociation. Finally, the data were analyzed using the Biacore T200 evaluation software 2.0.1. Cy5.5-MAL-TAR was synthesized by covalently linking the near-infrared dye Cy5.5-MAL with TAR peptide. The in vivo distribution experiment was carried out to determine the in vivo delivery capacity of TAR peptide to drugs. The 4T1-mCherry-Luc tumor-bearing BALB/c mice were treated with Cy5.5-MAL-TAR and Cy5.5-MAL (4 mg/kg) via tail vein injection (n = 3). Three mice in each group, a total of six mice were used. At 2, 4, 8, 12, and 24 h after treatment, mice of each group were taken to capture the fluorescent imaging of bio-distribution. At 8 h after administration, mice were sacrificed, and their major organs were extracted for future in vitro imaging. PTX (427.5 mg, 0.5 mmol), SA (32.5 mg, 0.3 mmol), and DMAP (5 mg, 0.03 mmol) were dissolved in 10 mL dichloromethane. The reaction solution was stirred for 6 h at room temperature in dark, and real-time monitoring was carried out with thin-layer chromatography (TLC). After the reaction, saturated NaHCO3 and saturated NaCl solutions were used for extraction, then the products were purified by silica gel column (methanol/dichloromethane). Finally, PTX-SA was obtained by rotary evaporation (80% yield) and analyzed by 1H-NMR (AVANCE III 600) and Q-TOF HRMS (Bruker, Maxis II). 1H-NMR (DMSO-d6, 600 MHz): δppm 0.991 (s, 3H), 1.021 (s, 3H), 1.470–1.511 (m, 4H), 1.607–1.649 (m, 1H), 1.753 (s, 3H), 1.773–1.814 (m, 1H), 2.108 (s, 3H), 2.240 (s, 3H), 2.295–2.346 (m, 1H), 2.612–2.633 (m, 2H), 3.429–3.449 (m, 2H), 3.569–3.587 (m, 1H), 3.984–4.021 (m, 2H), 4.085–4.126 (m, 1H), 4.899–4.949 (m, 2H), 5.341–5.356 (d, 1H), 5.401–5.413 (d, 1H), 5.513–5.542 (t, 1H), 6.292 (s, 1H), 7.174–7.203 (m, 1H), 7.429–7.467 (m, 4H), 7.488–7.512 (m, 2H), 7.555–7.580 (m, 1H), 7.655–7.680 (m, 2H), 7.727–7.453 (m, 1H), 7.839–7.853 (m, 2H), 7.971–7.985 (m, 2H), 9.241–9.255 (d, 1H), 12.257 (s, 1H). The calculated molecular weight for C51H55NO17 is 953.3470. [M+Na]+ HRMS m/z: 976.3346 (Supplementary Material, Figure S2). PTX-SA (40 mg, 0.042 mmol) was dissolved in 2 mL N,N-Dimethylformamide (DMF), then MAL (11.2 mg, 0.044 mmol), HoBt (6.24 mg, 0.046 mmol), HBTU (17.48 mg, 0.046 mmol), and DIPEA (27.72 mg, 0.168 mmol) were added to the solution and stirred at room temperature overnight. DMF was first removed with rotary evaporation, and then the products were redissolved with dichloromethane (DCM) and extracted three times with saturated NaCl solution. Finally, PTX-SA-MAL was purified with column chromatography (85% yield) and characterized by 1H-NMR and Q-TOF HRMS. 1H-NMR (DMSO-d6, 600 MHz): δppm 0.997 (s, 3H), 1.025 (s, 3H), 1.484–1.510 (m, 4H), 1.601–1.655 (m, 1H), 1.766 (s, 3H), 1.777–1.818 (m, 1H), 2.101 (s, 3H), 2.233 (s, 3H), 2.254–2.344 (m, 3H), 2.556–2.617 (m, 2H), 3.086–3.195 (m, 2H), 3.392–3.441 (m, 2H), 3.569–3.581 (d, 1H), 3.989–4.0442 (m, 2H), 4.081–4.123 (m, 1H), 4.905–4.917 (d, 2H), 5.330–5.345 (d, 1H), 5.408–5.420 (d, 1H), 5.517–5.546 (t, 1H), 6.289 (s, 1H), 6.988 (s, 2H), 7.174–7.212 (m, 1H), 7.431–7.463 (m, 4H), 7.483–7.508 (t, 2H), 7.549–7.573 (t, 1H), 7.651–7.676 (t, 2H), 7.724–7.749 (t, 1H), 7.846–7.859 (d, 2H), 7.976–8.005 (m, 3H), 9.202–9.216 (d, 1H). The calculated molecular weight for C57H61N3O18 is 1075.3950. [M+H]+ HRMS m/z: 1076.4059, [M+NH4]+ HRMS m/z: 1093.4322 (Supplementary Materials Figure S3). TAR peptide (90 mg, 0.040 mmol) was dissolved in 2 mL PBS solution at pH 7.4, and PTX-SA-MAL (60 mg, 0.05 mmol) was dissolved in 3 mL methanol. The PTX-SA-MAL solution was slowly dropped into the TAR peptide solution. The reaction mixtures were stirred at room temperature in dark for 2 h, monitored with analytical HPLC (Agilent 1200 Infinity II). The final product PTX-SM-TAR (SM is the abbreviation of SA-MAL) was purified with semi-preparative HPLC (H&E), and its structure was verified by 1H-NMR and Q-TOF HRMS (75% yield, 10–100% acetonitrile containing 0.1% trifluoroacetic acid). The calculated molecular weight for C153H231N45O38S is 3340.8680. [M+2H]2+ HRMS m/z: 1671.3668. [M+3H]3+ HRMS m/z: 1114.5837 (Figure 2). A series of PTX-SM-TAR solutions were prepared using sterile water, following the concentration range from 2.34 × 10−8 mol/L to 1.90 × 10−4 mol/L. Subsequently, CAC was determined by the digital conductivity meter (DDS-11A) at 25 °C. The morphology of PTX-SM-TAR NPs was characterized by transmission electron microscopy (TEM, JEM-1200EX). The particle size distribution and zeta potential of PTX-SM-TAR NPs were measured by dynamic light scattering (DLS, BIC-Brookhaven, New York, NY, USA). The acid and esterase sensitivity of PTX-SM-TAR NPs was ascertained by in vitro release experiment, and PBS solution containing 1% Tween 80 was used as the release medium. There are four different release conditions, pH 7.4, pH 6.8, pH 7.4 plus 100 U/L esterase, and pH 6.8 plus 100 U/L esterase were set to simulate the physiological environment. An amount of 1 mL PTX-SM-TAR NPs solution with a concentration of 1.2 mg/mL was prepared and packed into a dialysis bag (MWCO = 1000 Da). These bags were placed in a container containing 100 mL release medium and incubated in a shaker (ZQZY-85CN) at 37 °C, 100 r/min. At the specific time point, 1 mL medium was removed from the container, and then 1 mL fresh medium was added. The content of PTX in all samples was measured by analytical HPLC (10–100% acetonitrile over 0–15 min). 4T1-mCherry-Luc cells with high and low expression of NRP-1 were used to detect the targeting of PTX-SM-TAR to NRP-1. NRP-1 siRNA was used to construct 4T1-mCherry-Luc cells with NRP-1 down-regulated expression. NRP1-Mus-1755 siRNA was designed and synthesized by GenePharma (Suzhou, China). The transfection of siRNA was performed using the Invitrogen lipofectamine RNA iMAX transfection reagent in accordance with the manufacturer’s instructions. An amount of 5 × 105 4T1-mCherry-Luc cells were planted into the 6-well plate and cultured overnight. Then, siRNA (25 pmol) was mixed with transfection reagent at room temperature for 5 min and then added to the plate for 6 h. Cells were lysed in a mixture of the protease inhibitor, phosphatase inhibitor, and RIPA lysate for 30 min, and the total proteins were extracted after centrifugation. The concentration of extracted proteins was determined by the BCA kit. The total proteins extracted from cells were separated by SDS-PAGE and transferred to a PVDF membrane. The membrane was blocked in 5% skim milk powder solution for 2 h and then was incubated with primary antibody at 4 °C overnight and with secondary antibody at room temperature for 1 h. Finally, proteins were colored using enhanced chemiluminescence (ECL) and imaged on a chemiluminescence gel imaging analysis system (ChemiDoc XRS+). Coumarin-6-loaded PTX-SM-TAR NPs were prepared and applied to explore cell uptake. An amount of 6.5 × 104 NRP-1 siRNA treated and untreated 4T1-mCherry-Luc cells were seeded in a glass-bottom cell culture dish and cultured overnight. After cell adherence, 100 ng/mL coumarin-6 equivalent PTX-SM-TAR/C6 NPs solution was added to each group, and 30 μM TAR peptide was extra added to co-incubation in the competition inhibition groups. After incubation for 0.5 and 1 h, the cells were washed with PBS, fixed with 4% paraformaldehyde for 30 min, and then stained with DAPI dye for 5 min. The laser scanning confocal microscope (LSCM, Dragonfly 200) was used for photographing. For flow cytometry analysis, cells were planted in 6-well plates with a density of 3 × 105 cells per well. After incubation overnight, PTX-SM-TAR/C6 NPs solution with or without 30 μM TAR peptide was added and incubated for 0.5 and 1 h. After washing the cells with PBS, 500 μL trypsin was added to each well for 1 min, and then, the cells were collected and centrifuged at 1000 r/min for 5 min. The supernatant was discarded and cells were resuspended with 300–500 μL PBS. The intracellular fluorescence was quantified by a flow cytometer (Accuri C6 Plus). The tightly connected EA.hy926 cell layer was used to simulate the tumor vascular barrier in vivo. EA.hy926 cells were seeded at a density of 1 × 106 per well in a 0.44 μm Transwell upper chamber for one week. When the transmembrane resistance TEER reaches 200 Ω detected by the resistance detector, it was considered that the in vitro vascular barrier was successfully constructed. An amount of 250 ng/mL coumarin-6 equivalent PTX-SM-TAR/C6 NPs solution was added to the Transwell upper chamber, and PBS solution was added to the lower chamber. At 2, 4, 8, and 12 h, the lower chamber solution was taken for fluorescence determination. The fluorescence intensity of the initial addition of coumarin-6 was 100%, and the relative percentage of the fluorescence intensity of the lower chamber was calculated as the penetration rate of the vascular barrier. After incubation for 12 h, the Transwell chambers were washed with PBS, fixed with 4% paraformaldehyde for 30 min, and observed by LSCM. An amount of 5 × 104 4T1-mCherry-Luc cells were seeded in coverslips (1)–(3) and cultured overnight. After cell adherence, 100 ng/mL coumarin-6 equivalent PTX-SM-TAR/C6 NPs solution was added to the coverslip (1) for 4h at first. Then, the cells on the coverslip (1) were washed with PBS three times and co-incubated with cells on the coverslip (2) in fresh medium for 4h. As mentioned above, cells on the coverslip (2) and coverslip (3) were co-incubated for 4h. Finally, the cells were washed with PBS, fixed with 4% paraformaldehyde for 30 min, and then stained with DAPI dye for 5 min before being imaged with LSCM. After adding 150–200 μL of 2% agarose solution to each well, the 48-well plate was placed on the ultra-clean bench under UV irradiation for 30 min before solidification. The 4T1-mCherry-Luc cells were planted into the plate at the density of 4 × 104 cells per well and cultured in the incubator for one week. After the cells aggregated into spherical shapes, tumor spheroids were transferred to confocal dishes and incubated with PTX-SM-TAR/C6 NPs and coumarin-6 solution for 2 and 4 h. The tumor spheroids were washed with PBS, fixed with 4% paraformaldehyde for 30 min, and observed with LSCM. 4T1-mCherry-Luc cells were cultured overnight in 6-well plates and treated with PTX and PTX-SM-TAR NPs (31.25 nM), respectively, for 24 h. After that, the cells were washed with PBS and fixed with 4% paraformaldehyde for 20 min. Subsequently, 2% BSA was used for blocking, and 0.1% Triton X-100 was used for permeation. Finally, Tubulin-tracker green staining solution was used for 45 min, and LSCM was used for photography observation. The anti-proliferative activity of PTX-SM-TAR NPs on 4T1-mCherry-Luc cells was evaluated by CCK-8 methods. Briefly, the 4T1-mCherry-Luc cells in the logarithmic phase were digested and spread into the 96-well plate at the density of 8 × 103 cells per well. Cells were cultured overnight and then incubated with 200 μL different concentrations of drugs. After incubation for 48 h, the drug-containing medium was discarded and 100 μL fresh basic medium was added per well, followed by 10 μL CCK8 for 1–4 h. The cell viability was measured at 450 nm by a microplate reader (BIO-RAD, Hercules, CA, USA). The effect of PTX-SM-TAR NPs and PTX on 4T1-mCherry-Luc cell migration was evaluated with wound-healing assay. 4T1-mCherry-Luc cells were seeded in 6-well plates at a density of 3 × 105 cells per well. After overnight culture, the cells were wounded linearly by a 200 µL pipette tip. Then, cells were incubated in the medium containing PTX-SM-TAR NPs and PTX (100 nM). Images of 0 and 24 h were captured by an inverted microscope. Four days after tumor cell implantation, mice were randomly divided into four groups (n = 7). Seven mice in each group, a total of twenty-eight mice were used. Then, saline, TAR peptide (10.6 mg/kg), PTX (4 mg/kg), and PTX-SM-TAR NPs (15.6 mg/kg) were injected through the tail vein every two days. Tumor size and body weight were measured every 4 d. After 16 d of treatment, mice were sacrificed and tumors were removed, weighed, and further analyzed. Mice tumor tissues were fixed in 4% paraformaldehyde, decolored and embedded in paraffin, and sliced about 3–5 microns in thickness. Tumor paraffin sections were stained with H&E and TUNEL, respectively, and scanned by a digital slice scanning microscope (VS120). Statistical analyses were performed with GraphPad Prism 8.0. The Student’s t-test or one-way ANOVA was conducted to identify the differences between groups. A value of p < 0.05 was considered statistically significant. In this study, we designed and synthesized a transcytosable tumor-targeting prodrug delivery system based on the concept of “PDCs”, which covalently bonded a bifunctional TAR peptide and chemotherapy drug PTX. The final product PTX-SM-TAR could self-assemble into nanoparticles with a shell-core structure driven by hydrophilic TAR peptide and hydrophobic PTX, and it greatly improved the water solubility of PTX. In addition, with the mediation of the TAR peptide, PTX could be specifically delivered to the tumor site. The transvascular transport, intracellular delivery, and tumor penetration of PTX were increased as well, which leads to the highly effective extravasation on vascular, transcytosis between tumor cells, and infiltration in tumors. Afterward, due to the sensitivity of the ester bond, the prodrug PTX-SM-TAR can release free PTX in the abnormal tumor microenvironment for action, expecting to reduce systemic toxicity. Finally, combined with the above advantages, PTX-SM-TAR NPs could effectively inhibit the growth of TNBC tumors and had a stronger effect in promoting apoptosis and inhibiting tumor growth than PTX. In conclusion, PTX-SM-TAR NPs may present a new strategy for a targeted therapy for TNBC.

PMC10003176

Felix Yang,Andy Sivils,Victoria Cegielski,Som Singh,Xiang-Ping Chu

Transient Receptor Potential (TRP) Channels in Pain, Neuropsychiatric Disorders, and Epilepsy

01-03-2023

transient receptor potential channels,TRP,TRPM,TRPV,TRPC,pain,depression,bipolar,epilepsy,seizure

Pharmacomodulation of membrane channels is an essential topic in the study of physiological conditions and disease status. Transient receptor potential (TRP) channels are one such family of nonselective cation channels that have an important influence. In mammals, TRP channels consist of seven subfamilies with a total of twenty-eight members. Evidence shows that TRP channels mediate cation transduction in neuronal signaling, but the full implication and potential therapeutic applications of this are not entirely clear. In this review, we aim to highlight several TRP channels which have been shown to mediate pain sensation, neuropsychiatric disorders, and epilepsy. Recent findings suggest that TRPM (melastatin), TRPV (vanilloid), and TRPC (canonical) are of particular relevance to these phenomena. The research reviewed in this paper validates these TRP channels as potential targets of future clinical treatment and offers patients hope for more effective care.

Transient Receptor Potential (TRP) Channels in Pain, Neuropsychiatric Disorders, and Epilepsy Pharmacomodulation of membrane channels is an essential topic in the study of physiological conditions and disease status. Transient receptor potential (TRP) channels are one such family of nonselective cation channels that have an important influence. In mammals, TRP channels consist of seven subfamilies with a total of twenty-eight members. Evidence shows that TRP channels mediate cation transduction in neuronal signaling, but the full implication and potential therapeutic applications of this are not entirely clear. In this review, we aim to highlight several TRP channels which have been shown to mediate pain sensation, neuropsychiatric disorders, and epilepsy. Recent findings suggest that TRPM (melastatin), TRPV (vanilloid), and TRPC (canonical) are of particular relevance to these phenomena. The research reviewed in this paper validates these TRP channels as potential targets of future clinical treatment and offers patients hope for more effective care. The last century of scientific development, especially in neurological sciences, has emphasized describing ion channels that play various roles in pathology. Accurate descriptions can open avenues for potential treatments, alongside enabling a deeper understanding of diseases themselves. Transient receptor potential (TRP) channels are one set of those discovered that have a wealth of potential. They are a collection of proteins that mainly function as nonselective cation channels [1]. First observed in a mutant strain of Drosophila, contemporary science has delineated 28 different TRP channels across multiple species [2,3]. Looking at genetic differences, the TRP superfamily can be separated into seven different subfamilies: TRPC (canonical); TRPV (vanilloid); TRPM (melastatin); TRPP (polycystin); TRPML (mucolipin); TRPA (ankyrin); and TRPN (NOMPC-like) [4]. Each TRP family channel consists of six transmembrane helical domains (TM1-TM6), N- and C-terminal regions in the cytosol, and a loop between the TM5 and TM6 domains, forming the important channel pore (Figure 1) [5]. Each TRP is being investigated as a possible treatment target for cerebrovascular disease, pain, psychological and neurological illnesses, diabetes, and even cancer [1,6,7,8,9,10]. In this paper, emphasis is placed on TRPM, TRPC, and TRPV, concerning their roles in pain, psychiatric diseases, and epilepsy (Table 1). Melastatin homology regions (MHRs) distinguish TRPMs from the TRP superfamily, in addition to the fact that TRPMs have the most amino acids in their systolic domain. The TPRM family can be further subdivided into TRPM1-TRPM8, where sequence homology produces related pairs as follows: TRPM1 and TRPM; TRPM2 and TRPM8; TRPM4 and TRPM5; and the last pair, TRPM6 and TRPM7 [5]. All of the TRPMs permit different ions to pass through the channel pore with some sharing similar permeability and others varying. (For an in-depth look at ion permeability, see the cited review [11]). Each of the TRPMs has a conserved Ca2+-binding site, but recent data suggest that only TRPM2 and TRPM8 require it for gating [11,12,13]. TRPM4 and TRPM5 are uniquely the only TRPM channels impermeable to divalent ions such as Ca2+, even though these are Ca2+-activated channels [14]. Noted mutations in genes encoding TRPMs create channelopathies that influence cancer, neuropathic pain, inflammation, hypertension, diabetes, and hypomineralization [11]. TRPC channels were given their name—TRP canonical—due to the fact they most resembled Drosophila TRP channels that were found to be responsible for light sensing [15]. There are seven members of this subfamily, TRPC1-7, which can also be further subdivided into four groups based on their sequence homology: TRPC1, TRPC2, TRPC3/6/7, and TRPC 4/5 [16]. Other studies have noted that TRPC2 is found to be a pseudogene in humans and have thus organized the subfamilies into TRPC1/4/5 and TRPC3/6/7 [17]. Mammalian TRPC channels are activated downstream from receptors that signal using phospholipase C (PLC) but are expressed in numerous tissue types with various functions that differ from similar Drosophila proteins [18]. Due to the relationship between the Ca2+ filling store and PLC, these channels sometimes become activated in response to changing Ca2+ levels and are permeable to cations, namely Na+ and Ca2+ influx [18]. Research has shown that these channels play important roles in cardiovascular and renal health, as well as being potential targets for epilepsy treatment [19,20,21,22]. TRPV1 was the first mammalian TRP channel to have its structure delineated and to be cloned [23,24]. Of this subfamily, TRPV1-4 functions as the thermal sensing channels, which are temperature-activated, while TRPV5-6 functions are not activated by temperature and instead take the more conventional TRP route of being calcium-sensitive [25]. TRPV1, 2, and 4 have been shown to influence cerebral ischemic injury where these channels demonstrate a neuroprotective effect via Ca2+ influx and other signaling pathways, such as JNK and p38 MAPK [26]. Further research observed TRPV1 channel activation inhibiting neutrophil infiltration and reducing free radical generation in ischemia–reperfusion injury [27]. Together, these membrane subtypes pose significant opportunities for future research and biomedical innovation. Table 1 has shown the TRPM in pain, psychiatric and epileptic disorders. The basic mechanism of pain can be broken down into transduction, transmission, and modulation with the introduction of a noxious stimulus [64]. Furthermore, calcium ions play an important role in generating action potentials in order for nociceptive signals to be sent out through neurons [64]. Ion channels, such as voltage-gated calcium channels (VGCCs), have been well established as integral mediators of pain [65]. The role of calcium in nociception is highlighted in our review of TRP channels as several studies have portrayed this family of receptors as an important modulating target for analgesia in acute and chronic pain [66,67]. Although it has been speculated that TRPM ion channels have both pain-exacerbating and pain-alleviating mechanisms, the majority of studies using both agonism and antagonism of TRPM subtypes support their pro-inflammatory and pain-inducing functions [28,29]. TRPM2 channels are one such family of proteins that have interactions with reactive oxidative species (ROS) [30] and is involved in pathological pain [31]. The current understanding of the receptor is that it acts as a sensor for both ROS and adenosine diphosphate ribose (ADPR) in calcium gating [31]. Its expression in mice is mostly seen in primary afferent sensory neurons, including both A and C fiber neurons [31]. TRPM2 knock-out (KO) mice in a study conducted by Haraguchi et al. demonstrated reduced nocifensive response in inflammatory, neuropathic, mechanical, and thermal pain, without the loss of baseline sensitivity to mechanical and thermal sensation [32]. Primarily expressed in somatosensory dorsal root ganglion (DRG) neurons, thermogenic TRPM3 plays an integral role in heat nociception. TRPM3 knockout mice displayed a decreased response to noxious heat stimuli [26,68]. Blockage of the receptor by hesperetin, isosakuranetin, and primidone decreased intracellular transport of calcium ions, and similar to TRPM3 knockout mice, rodents treated with flavanones and primadone displayed decreased pain behaviors in response to noxious heat stimuli [33]. The development of the antagonists and modulators of TRPM channels is already underway, especially for TRPM8. TRPM8 was first characterized as a receptor for cold sensory afferents, which are activated by certain natural molecules known to produce this sensation, such as menthol, icilin, and eucalyptol [34]. The goal of cold sensation in the context of this receptor’s activation is the promotion of analgesia. However, TRPM8 is also believed to be involved in pain amplification due to cold hypersensitivity. While more research must be conducted to identify a definitive role in thermal-associated pain, knockout mice of this gene lacked cold hypersensitivity [69]. Other implications of pain for TRPM8 include migraines and bladder pain [70,71,72]. It is likely that TRPM8 is expressed for cold-afferent functions, and the modulation of the receptor shows potential for thermoreceptive pain analgesia. Unfortunately, most psychiatric illnesses are without complete descriptions of their etiology. One new theory contends that the oxidative state of cells and subsequent downstream calcium changes may have an influence [73]. While it is highly contested whether the antioxidant system is upregulated or downregulated in psychiatric disorders, many studies demonstrate changes in superoxide dismutases (SODs), catalase (CAT), and glutathione peroxidases (GPXs) that correlate with mental health issues [73,74]. A meta-analysis of double-blind, randomized, placebo-controlled trials evaluating the effects of N-acetyl cysteine (NAC) found that treatment significantly improved depressive symptoms in heavy smokers, those with trichotillomania, and those with bipolar or depressive disorders [73,75]. One double-blind, randomized, placebo-controlled, clinical trial of its efficacy as an adjunctive treatment for patients with schizophrenia on antipsychotic medications showed that patients taking NAC presented improvements on the Positive and Negative Syndrome Scale (PANSS) compared to the placebo group [76]. The same trial demonstrated significantly improved cognitive functions [76]. However, how exactly do TRPM channels relate to the psychiatric significance of redox reactions at the cellular level? The TRPM2 channel is among a group of highly sensitive proteins that are influenced by redox status [73]. When they are activated, they induce Ca2+ entry and transfer redox activity into intracellular Ca2+ signaling [73]. Specific details have been more thoroughly reviewed elsewhere [77]. With only this information, one can see the theoretic bridge between redox reactions, intracellular calcium, and psychiatric illness that TRPM channels provide. Two studies have demonstrated the need for TRPM2 in order to have NMDAR-dependent long-term depression in the hippocampus [78,79]. Another investigation demonstrated the key role that TRPM2 channels play in the H2O2-dependent modulation of substantia nigra pars reticulata GABAergic neurons [35]. Fine mapping linkage analysis showed that TRPM2 on chromosome 21q is associated with bipolar disorder [36]. One of the identified single nucleotide polymorphisms (SNPs) leads to a deletion of TRPM2, and subsequent studies demonstrated that TRPM2 KO mice exhibit bipolar-disorder-related behaviors [37]. What is even more intriguing is that one of the essential targets of lithium is GSK-3, which experiences increased phosphorylation whenever TRPM2 is disrupted [37,79]. Other findings expand the likely effects of TRPM2 channels to include major depressive disorders, as well as other behavioral phenotypes that are related to oxidative stress [38]. Beyond TRPM2, recent research highlights TRPM3 as a potential player in the development of mood and anxiety disorders, with specific mention of post-partum mood disorders [80]. Similar efforts revealed that TRPM3 expression was changed in a mouse model of bipolar disorder, furthering the aforementioned evidence [81]. Epilepsy is a chronic neurological disorder caused by abnormal electrical excitability in the brain. Calcium ion (Ca2+) accumulation has been hypothesized to play a critical role in the etiology of this disease [82]. Though not fully understood, the activation of tissue transglutaminase (tTG) by calcium accumulation is thought to trigger glutamate-induced neurotoxicity that yields seizure activity [83]. This hypothesis is like that of neuronal injury in brain ischemia and trauma, where the amount of calcium influx correlates with the degree of damage [84]. Loss-of-function K+ channels and gain-of-function Na+ channels have also been identified as contributors to neuron excitability and causes of epilepsy. TRP channels are nonselective transmembrane cation proteins that allow cations such as Ca2+ to pass through their pores [39,85,86]. Because ionic disbalance plays a central role in the etiology of epilepsy, these nonselective TRP channels serve as areas of interest within the field. Three TRPM channels that have shown direct effects in epilepsy include TRPM2, TRPM3, and TRPM7. TRPM2 is co-expressed and has direct physical interactions with the EF-hand motif-containing protein, EFHC1. Typically, EFHC1 enhances the susceptibility of TRPM2 to neuronal apoptosis through ROS and H2O2. In juvenile myoclonic epilepsy (JME), however, there is a mutation in EFHC1. Given the direct relationship between EFHC1 and TRPM2, it is suggested that TRPM2 plays a protective role against cell death that contributes to the phenotypic presentation of JME [40]. Developmental and epileptic encephalopathies (DEEs) are groups of conditions characterized by epilepsy with comorbid developmental delay. Gain-of-function mutations that cause overactivity in the TRPM3 channel are associated with DEEs [41]. Like most other TPR channels, TRPM3 is a nonselective cation channel that is permeable to calcium [42]. Primidone, a clinically approved antiepileptic, is a TRPM3 antagonist whose antiepileptic effects could be in part due to its inhibition of TRPM3 [41]. Therefore, the development of TRPM3 inhibitors serves as a focus for future epileptic therapeutics. Within the brain, TRPM7 is activated and expressed during epilepsy, perpetuating a positive feedback loop and contributing to the production of ROS. This is confirmed by the fact that TRPM7 ablation prevents a cation current under circumstances of oxygen–glucose deprivation, and therefore prevents ROS-mediated cell death [43]. A recent study published in the International Journal of Molecular Sciences demonstrated that TRPM7 inhibition reduced the seizure-induced expression of TRPM7 channels [87]. This resulted in decreased intracellular zinc accumulation, ROS production, and postictal apoptotic neuronal death [87]. Other TRPM channels have demonstrated regulatory roles that could translate to the pathogenesis of epilepsy if found within epileptic regions of the brain. GTL-2 is a TRPM that influences local ion composition in non-neuronal tissues. Its function in the epidermis has been compared to the modulatory role of glial cells, as GTL-2 channels contribute to ionic buffering and glutamate uptake that regulate neurotransmitter release [88]. If found in neuronal tissues, GTL-2 could play a role in the ionic modulation of Ca2+ that yields glutamate release during seizures. In the mouse retina model, TRPM1 localized to the dendrites of ON-bipolar cells and modulated depolarization in response to light-induced glutamate release [89]. Similar to GTL-2, if TRPM1 contributes to depolarization and glutamate release in brain regions impacted during epileptic episodes, its inhibition could hold a significant role in regulating seizures. Table 1 also has shown the TRPV in pain, psychiatric and epileptic disorders. Among the TRP channels, ones belonging to the TRPV family appear to have the strongest backing from the literature, supporting their roles in modulating pain sensation. TRPV1 is expressed in a variety of tissues, including sensory ganglia and small sensory neural fibers [90]. More than a decade ago, early rodent models using TRPV1 antagonism highlighted the receptor’s role in thermosensation and pain perception, similar to that of TRPM [44]. This idea was further tested in human trials, where TRPV1 antagonist SB-705498 produced significant results in increasing the heat pain threshold in treated skin [45]. More recently, one study reported inhibition of pain behavior in osteoarthritis (OA) mice after intra-articular administration of JNJ-17203212, a TRPV1 antagonist [46]. This was measured by evaluating the attenuation of weight-bearing asymmetry after antagonism of the receptor [46]. The same study also found that there was an increased expression of this receptor in human OA, rheumatoid arthritis (RA), and postmortem (PM) synovium via immunohistochemistry [46]. Based on this evidence, modulation of TRPV1 may prove to be beneficial in attenuating inflammatory joint pain, especially because TRPV1 has been seen to respond to oral paracetamol antinociception in human patients [91]. In addition to joint pain, TRPV1 expression in microglia in anterior cingulate cortices, GABAergic spinal interneurons, as well as other sensory ganglia, plays roles in numerous pain mechanisms of neuroinflammation, allodynia, and mechanical hyperalgesia [92,93,94]. Interestingly, cannabidiol (CBD) is another molecule that has been tested to modulate TRPV1 to observe its role in analgesic pathways. Cannabis-based products have become easily accessible and clinical trials in humans have supported their usage in self-medicated pain relief [29,95]. In a Parkinson’s disease mouse model, CBD increased anandamide binding to TRPV1 receptors and produced analgesic effects [96]. CBD’s exertion of pain alleviation may be dose-dependent as one group found that concentrations of 10 and 50 μmol/L CBD were required for decreased calcium shuttling in TRPV1 channels [47]. The TRPV4 receptor is expressed in a variety of tissues, including immune cells, sensory neurons, glial cells, the spinal cord, cortical pyramidal neurons, the thalamus, and cerebellum basal nuclei [97]. Similar to TRPV1, TRPV4 is thermosensitive and can be activated by heat, as well as by mechanical forces [97]. One of the most important roles of TRPV4 found in studies is the alleviation of neuropathic pain via its inhibition. A major source of chronic pain commonly seen in patients is chronic back pain. In several studies, TRPV4 antagonism was seen to reduce cartilage degradation after mechanical compression, reduce IL-1β-mediated NO release, and decrease neuropathic pain in chronic compression of DRG pain models in rats [98,99,100]. One pre-clinical candidate thought to inhibit TRPV4, named GSK3527497, was described to be a potential TRPV4 antagonist that can be used for therapeutic pain management [101]. More recently, GSK3527497 generated favorable results and was found to be well tolerated in Phase I clinical trials in both healthy volunteers and heart failure patients after 14 days of dosing [57]. While more studies utilizing human subjects are needed, these findings suggest antagonists of TRPV4 could be a new type of pharmacotherapy in the future. As mentioned in the section discussing TRPMs, TRP channels are suggested to play a role in the etiology of psychiatric illnesses. In the TRPV family, TRPV1 has amassed the most evidence, indicating its relevance in the realm of mental health [48]. For example, TRPV1 KO mice have shown less anxiety-related behavior, freezing, and contextual fear in different methodological designs [49]. These findings were paralleled by an impairment in hippocampus-dependent learning, consisting of a deficit in long-term potentiation, not unlike the TRPM2 findings [49]. Further investigations have examined the role of these physiological manipulations in the etiologies of mental disorders. One study looked at the antidepressant effects of TRPV1 agonists and found that the administration of capsaicin and olvanil provided significant protective effects against induced depression in mice [50]. Another experiment focusing on the ventral hippocampus in rats found that TRPV1 channels have an important role in regulating anxiety [51]. This was shown via the antagonism of the TRPV1 channels via capsazepine and was redemonstrated by Kasckow et al. [50]. Outside of the hippocampus, similar findings have been observed in the periaqueductal grey where, again, antagonism of TRPV1 led to anxiolytic-like effects [52]. Another set of mental health issues, namely substance use disorders, are also found to correlate with TRPV1 activity. Multiple studies demonstrate that continued methamphetamine exposure leads to increases in TRPV1 expression, specifically in the frontal cortex [102]. Another investigation found that the deletion of TRPV1 channels led to an altered behavioral response to ethanol administration in mice [103]. Together, these findings demonstrate that TRPV1 is a significant target for future research regarding the treatment of psychiatric diseases. TRPV1 is one of the most well-characterized and documented transient-receptor potential-vanilloid channels in the TRPV family. Like other TRP channels, it yields nonselective Ca2+ permeability. TRPV1 was initially found to be highly expressed in the DRG, the sensory neurons. This paved the way for the discovery of the significant role of TRPV1 in inflammatory hyperalgesia [24]. Subsequent research demonstrated that TRPV1 is also located in various nuclei locations within the human brain, including the cortex, hypothalamus, and hippocampus [53]. Glutamate excitation through Ca2+ activation, especially in the calcium-sensitive hippocampus, has long been an important etiologic consideration for epilepsy [39]. The function of TRPV1 in hippocampal excitation thereby highlights a new focus in the field. Capsaicin is a TRPV1 agonist that can be used to elicit the effects of the channel. In the mouse model, capsaicin demonstrated pro-convulsant activity that was only blocked by pretreatment with capsazepine (CPZ), an antagonist of TRPV1 [104]. Further, systemic or hippocampal administration of a TRPV1 antagonist reduced the susceptibility of mice to pentylenetetrazol (PTZ)-induced seizures [54]. The activation of TRPV1 by capsaicin caused apoptosis in the hippocampi and DRG of rats, indicating that this channel is important for regulating epileptic episodes. Conversely, TRPV1 blockers such as CPZ demonstrated a protective role against neuronal apoptosis and epilepsy in the same rat model [105]. Cannabidiol (CBD) is argued to be an antagonist and agonist of TRPV1 and TRPV2, respectively [47,106]. In either case, CBD administration decreased in vitro epileptiform activity and in vivo seizure activity in rats [107]. In a descriptive study of humans, increased expression of TPRV1 mRNA/proteins was found in patients with mesial temporal lobe epilepsy compared to the control [55]. These findings provide evidence of the role of TRPV1 functions in perpetuating seizures among animals and likely humans. Future work concentrating on TRPV1 inhibitors as antiepileptic therapeutics remains a promising area to be researched. Table 1 has shown the TRPC in pain, psychiatric and epileptic disorders. All TRPC channels reveal calcium permeability, which is an important part of pain transduction and sensitization of nociceptors as previously mentioned. Based on this cellular mechanism, it is worthwhile to continue the investigation of the TRPC channels’ role. While new research surrounding TRPC3 leans more toward its role in non-histaminergic itch, it is likely that TRPC3 signals both itch and pain, given that it is expressed heterogeneously in both nociceptors and pruriceptors [108]. In situ hybridization in one study found that TRPC3 was exclusively expressed in small-to-medium-diameter sensory neurons in rat DRG [109,110]. Disruption of endogenous TRPC3 in these ganglia resulted in decreased expression of store-operated calcium entry (SOCE), UTP, or protease-activated receptor 2 (PAR2) agonist-evoked calcium transduction [109]. TRPC3′s contribution to calcium-induced nociceptor sensitization and its relationship with co-expression with other proinflammatory receptors support its importance in future pain therapies. The strongest support for the future of TRPC-related non-opioid analgesia comes from research surrounding TRPC5. Recently, the function of this receptor in pain perception was observed in murine models of osteoarthritis where TRPC5 KO mice had significantly exacerbated pain-like behaviors compared to that of the wild type (WT) [111]. Along with behavioral results, findings were also found at the microscopic level where TRPC5 KO mice had increased mast cell markers and extracellular matrix remodeling, synonymous with synovial inflammation [111]. One group shared similar findings with TRPC5 gene-deleted mice and saw increased weight-bearing asymmetry, inflammatory cytokines, and secondary hyperalgesia in human inflammatory arthritis synovia after chronic treatment of a TRPC5 antagonist (ML204) [56]. While some osteoarthritis models suggest TRPC5 inhibition leads to more inflammation and pain, other researchers saw reversed touch pain in mice models of sickle cell disease, migraine, chemotherapy-related pain, and surgical pain after TRPC5 inhibition [58]. TRPC5 appears to have great translation potential as well, due to its high expression in donor human DRG tissues [58]. Of all the TRP channels, TRPC channels have become the biggest target for potential treatments [48]. For one, TRPC5 is thought to be responsible for transferring conditioned fear responses to the amygdala, as they are expressed in the thalamus, amygdala, and cortical areas related to fear responses [48,112]. TRPC4 was identified by the same group of researchers to be essential for behavioral responses to anxiety-inducing stimuli, seeing as KO mice demonstrated an anxiolytic behavioral phenotype [112]. Because TRPCs are expressed in B lymphocytes, one study found that expression on those cells was changed in those with bipolar disorder, suggesting a functional change in the channel in the disease state [113]. Interestingly, treatment for 7 days with lithium reduced the TRPC3 protein in those same cells in bipolar patients [114]. Looking more at the impact on neuronal populations implicated in the reward system and other goal-oriented behavior, one study found that TRPC1 deletion led to a loss in striatal cells, in addition to proteomic alterations [115]. A further physiological mystery of the TRPC channels in the brain was found in an investigation of IL-10 KO mice. These mice had reduced TRPC5 expression in the medial prefrontal cortex and amygdala [59]. These mice then demonstrated enhanced depressive and anxiety-like behavior, potentially relating the immune system to the TRPC channels already implicated in depression and anxiety [59]. Some researchers have taken these TRPC findings far enough to develop treatments with novel agents. In fact, acute treatment with a novel TRPC4/5 inhibitor was found to produce antidepressant and anxiolytic effects in mice [116]. Furthermore, they posit that these effects are mediated through downstream signaling involving BDNF [116]. Another study with a different but equally novel TRPC4/5 inhibitor was able to generate similar findings [60]. The compound reduces CCK-4-invoked neuronal activity in amygdala slices, the brain region known to produce fear responses [60]. Together, these findings suggest once more that TRP channels are implicated in psychiatric illness and physiology, specifically the TRPC channels mentioned above. Among the TRPC families, TRPC3 is the most reviewed within the setting of epilepsy. While all TRP channels regulate cations in some regard, TRPC3 uniquely mediates low Mg2+ and Ca2+ depolarization contributing to epilepsy. In addition, higher expression of TRPC3 makes the immature cortex more excitable and thus decreases the threshold for epileptic susceptibility [117]. In animal models of pilocarpine-induced status epilepticus, TRPC3 has been studied using different pharmacologic agents. The main outcomes from targeting this channel with Pyr3, a TRPC3 inhibitor, included decreases in TRPC3 channel expression and reductions in the root mean square of power/theta activity of seizures [118]. In hyperthermia-induced febrile seizure rats, elevated mRNA and protein levels were detected in neuronal cells within the hippocampus. Accordingly, when the Pyr3 inhibitor was administered in this model, seizure severity, neuroinflammation, and neuronal cell death decreased [119]. While Pyr3 is a selective and potent TRPC3 inhibitor, its metabolic instability and toxicity limit its full benefit. A modified pyrazole compound, JW-65, was recently studied for its effects on TRPC3. Systemic administration of JW-65 prior to pilocarpine induction showcased a delay in seizure initiation. JW-65 administration after pilocarpine-induced seizures initiated anti-seizure activity, confirmed by electroencephalographic monitoring with video. Seizure susceptibility decreased in a dose-dependent manner in accordance with JW-65 administration [61]. These findings suggest that JW-65 is a novel therapeutic of interest in seizure attenuation. In conjunction, the results of these TRPC3 studies demonstrate that TRPC3 is important in promoting electrical excitability within various seizure models. Inhibition of this channel proves significant to reducing seizure activity. Thus, TRPC3 channel inhibitors serve as an area of interest in the field of anticonvulsant therapeutics. TRPC1 and TRPC6 are two other TRPC channels of epileptogenic interest [62]. Among humans with focal cortical dysplasia (FCD), increased mRNA and protein expressions of TRPC1 were found in cortical tissue. Such findings of overexpression in cell-specific patterns suggest that TRPC1 may play a role in creating conditions permissive for FCD. Notably, TRPC1 also showed colocalization with GFAP in reactive astrocytes, indicating that the channel may aid in astrocyte modulation of epilepsy [63]. TRPC6 holds unique consideration in epilepsy, as it was shown to be downregulated under chronic epileptic conditions in the rat model. Furthermore, ablation of TRPC6 by protein-specific silencing RNA causes increased susceptibility to pilocarpine-induced seizures. This may be because TRPC6 is involved with signaling the expression of proteins important to mitochondrial function [120]. A deeper understanding of TRPC6 in neuroprotective signaling pathways will be beneficial for understanding the impact of this channel, especially in the setting of epilepsy. TRP channel subfamily involved in pain, psychiatric, and epileptic disorders have been shown in Table 1. TRP channels are a group of multifunctional membrane proteins that serve important functions in neurological physiology and pathology. They significantly influence oxidative species sensing, afferent nociceptive signaling, bipolar disease, depression, anxiety, and seizure disorder [35,39,66,67,78,121,122]. In addition, TRP channels play important roles in cardiovascular and renal health [19,20]. Most TRPs highlighted in this review are subjects of pharmacological development and intense study, especially to mitigate the progression of these pathological conditions. The aim of this review was to examine TRPM, TRPV, and TRPC channels and gain perspective and understanding of their growing impact on pain sensation, psychiatric diseases, and epilepsy. Regarding pain, TRP channels represent an area of focus that is of high interest to researchers and pharmaceutical companies to develop non-opioid interventions for chronic pain. Currently, medical management of chronic pain remains dominated mainly by opioid analgesics, but the downsides of addiction and tolerance make it an unsatisfactory long-term treatment option for pain [123,124]. Thus, advancements in modulating TRP channels and nociceptive signaling from the peripheral nervous system are a more favorable route. TRPM8 is implicated in cold hypersensitivity and is theorized to alleviate inflammatory or neuropathic pain, but there is still controversy regarding the effects of TRPM8 agonism and antagonism on pain perception [34,69,125]. Inhibition of TRPV1 and TRPV4 is related to several pain-alleviating findings, especially neuropathic pain and mechanical hyperalgesia seen in inflammatory joint disease [46,91,92,93,94]. TRPV1 is also believed to serve a first-line defense role in noxious heat stimuli via capsaicin [126]. A growing field of pharmacological therapeutics that target TRPV1 includes CBD, which decreases Ca2+ transduction in DRG after stimulation with capsaicin [29,47,95]. In the setting of chronic neuropathic pain, non-opioid antagonism of TRPV4 shows promising data to be a major analgesic target [57]. While TRPC3 shares similar characteristics to the previously mentioned properties of TRPs, TRPC5′s physiological role likely leans more toward reducing inflammation and pain [56,108,111]. Although several psychiatric diseases do not have completely clear mechanisms of pathology, a wealth of research support TRP channel expression and function in the setting of neuropsychiatric diseases. In fine-mapping linkage of bipolar subjects, TRPM on chromosome 21q is seen to be associated with bipolar disease behaviors [36,37]. While lithium is traditionally used for bipolar symptoms, TRPM2 is a candidate for several new compounds developed within the last 5 years. Namely, ADPR analog TRPM2 antagonists may prove beneficial in the future for a spectrum of neuropsychiatric diseases, including bipolar disease [127]. There is literature supporting TRPV1′s antagonism benefiting anxiety, and its agonism promoting protection against depression, anxiety, and substance use disorder [49,51,102,103,128,129]. Antagonism of TRPV1 is a possible route for the reduction in anxiety and fear responses with future translational research [49,129]. Continuing the mechanisms of anxiety, TRPC4 and TRPC5 are heavily implicated in the transmission of conditioned fear responses to the amygdala, and gene disruption in mice demonstrated anxiolytic effects [48,112]. Two antagonists of TRPC4/5, M084 and HC-070, have already been developed, and researchers found that the administration of these two agents induced anxiolytic and anti-depressant effects in mice [60,116]. Together, these findings highlight TRPC’s important role in the physiology of anxiety and depression. Cation transduction, including that of calcium ions, is believed to play a massive role in the pathology of epilepsy and seizures, possibly due to the glutamate-induced neurotoxicity from tissue transglutaminase activation [82,83,130]. Because ion imbalances serve a central role in the etiology of epilepsy, TRP channels are a major area of interest in understanding and treating epilepsy [82,85,86]. TRPM2 may be a channel protein of interest in juvenile myoclonic epilepsy as EFHC1, the candidate gene for this disease, potentiates TRPM2 in ROS-mediated neuronal death [40]. Primidone, along with diclofenac and maprotiline, have all been demonstrated to be efficient blockers of TRPM3 with IC50 at 0.6–6 μM [131]. Other TRPM channels that have the potential to be therapeutic targets in epilepsy include TRPM7, where inhibition reduced the seizure-induced expression of TRPM7 channels and reduced ROS-related neuronal death [43]. Agonism of TRPV1, which is expressed in the brain, hypothalamus, and hippocampus, with capsaicin and pentylenetetrazol (PTZ) demonstrated pro-convulsant activity that was only blocked with TRPV1 antagonism [54,104,126,132]. Microscopically, researchers saw apoptotic mechanisms in hippocampal and DRG cells of rats after capsaicin TRPV1 agonism, which strengthens its relationship with seizure etiology [105]. The administration of CBD also decreased in vitro and in vivo seizure activity in rat [107]. Its direct effects on TRPV1 and TRPV2 is not certain as it more strongly modulates cannabinoid receptors. Expression of several TRPC channels is consistently seen to have an impact on chronic epileptic conditions, and TRPC3 uniquely mediates low Mg2+ and Ca2+ depolarization, contributing to epilepsy [61,62,63,117,118,120]. There is abundant information and research highlighting TRP channels and their roles in pathological processes involving cation transduction through cellular membranes. Clinical trials regarding TRP modulation are already undergoing and have generated promising results. Future investigations into pharmacological interventions of TRP channels will propagate further developments in patient treatments, especially in the setting of pain, neuropsychiatric diseases, and epilepsy.

PMC10003181

Muhammad Usama Younas,Guanda Wang,Haibo Du,Yi Zhang,Irshad Ahmad,Nimra Rajput,Mingyou Li,Zhiming Feng,Keming Hu,Nasr Ullah Khan,Wenya Xie,Muhammad Qasim,Zongxiang Chen,Shimin Zuo

Approaches to Reduce Rice Blast Disease Using Knowledge from Host Resistance and Pathogen Pathogenicity

05-03-2023

Oryza sativa,blast disease,resistance gene,quantitative trait locus,avirulence gene

Rice is one of the staple foods for the majority of the global population that depends directly or indirectly on it. The yield of this important crop is constantly challenged by various biotic stresses. Rice blast, caused by Magnaporthe oryzae (M. oryzae), is a devastating rice disease causing severe yield losses annually and threatening rice production globally. The development of a resistant variety is one of the most effective and economical approaches to control rice blast. Researchers in the past few decades have witnessed the characterization of several qualitative resistance (R) and quantitative resistance (qR) genes to blast disease as well as several avirulence (Avr) genes from the pathogen. These provide great help for either breeders to develop a resistant variety or pathologists to monitor the dynamics of pathogenic isolates, and ultimately to control the disease. Here, we summarize the current status of the isolation of R, qR and Avr genes in the rice–M. oryzae interaction system, and review the progresses and problems of these genes utilized in practice for reducing rice blast disease. Research perspectives towards better managing blast disease by developing a broad-spectrum and durable blast resistance variety and new fungicides are also discussed.

Approaches to Reduce Rice Blast Disease Using Knowledge from Host Resistance and Pathogen Pathogenicity Rice is one of the staple foods for the majority of the global population that depends directly or indirectly on it. The yield of this important crop is constantly challenged by various biotic stresses. Rice blast, caused by Magnaporthe oryzae (M. oryzae), is a devastating rice disease causing severe yield losses annually and threatening rice production globally. The development of a resistant variety is one of the most effective and economical approaches to control rice blast. Researchers in the past few decades have witnessed the characterization of several qualitative resistance (R) and quantitative resistance (qR) genes to blast disease as well as several avirulence (Avr) genes from the pathogen. These provide great help for either breeders to develop a resistant variety or pathologists to monitor the dynamics of pathogenic isolates, and ultimately to control the disease. Here, we summarize the current status of the isolation of R, qR and Avr genes in the rice–M. oryzae interaction system, and review the progresses and problems of these genes utilized in practice for reducing rice blast disease. Research perspectives towards better managing blast disease by developing a broad-spectrum and durable blast resistance variety and new fungicides are also discussed. Rice (Oryza sativa) is pivotal to human life, especially in Asia where millions of people depend either directly or indirectly on rice consumption for calorie uptake. Being a major cereal crop and critical to global food security, the United Nations Organization (UNO) has declared 2004 as the International Year of Rice [1]. The growth, development and yield of rice is constantly challenged by various biotic and abiotic stresses. Abiotic stresses include drought, salinity and nutrient deficiency while biotic stresses challenge rice production in the form of insect attack and viral, bacterial and fungal diseases. Among these biotic stresses, a fungal disease called rice blast poses a great threat to rice yield, which is caused by Magnaporthe oryzae (M. oryzae); it accounts for yield losses up to 10–30% annually, and complete loss (100%) in the years of pandemics [2,3,4]. Currently, rice blast disease is prevalent in more than 85 countries [5]. Several factors such as high humidity (>80%), cloudy and wet weather, low temperature (15–25%) and excessive application of fertilizers may increase the incidence of rice blast [6,7]. M. oryzae may infect aerial parts of the rice plant at any development stage, which causes seedling blast, leaf blast, node blast, grain blast and neck blast, based on the appearance of lesions on different rice parts [8]. The pathogen spreads in rice biotrophically during early infection and then switches to the necrotrophic phase in 4 to 5 days, which is considered a hemibiotrophic pathogen. In the biotrophic stage, the blast fungus produces a unique cell called an appressorium, which is a prerequisite for its infection [9]. Chemicals, fungicides especially, are the easiest and most general method to control rice blast. The most successful and effective fungicides for the control of rice blast in Japan are copper fungicides [10]. However, it soon became apparent that copper fungicides are phytotoxic and adversely affect both human health and soil microbiota. Then, a mixture of phenylemercuric acetate (PMA) and copper fungicides proved effective agents compared to copper alone to manage rice blast with less toxicity to both human health and the rice plant. With the extensive application of one kind of fungicide, the emergence of resistance to the fungicide in M. oryzae was reported. As a result, the application of different fungicides or a combination thereof in rotation has been widely recommended in practice to manage rice blast. Currently, lots of different kinds of fungicides have been developed to be used solely or in combination to curb rice blast disease [11]. However, despite widespread applications in plant pathogen control and plant protection, fungicides pose a great threat to human health and the environment. Fungicides have been shown to drastically decline beneficial microorganisms and the fungal community in soil [12,13]. Some of the microbes are key to soil texture transformation, nitrogen fixation, nutrient use efficiency, decomposition of organic matter, soil structure and fertility [12,13,14,15,16]. It is well known that developing resistant varieties with resistance genes is the most effective and economical strategy to control the disease. There has been a focus in the past few decades to identify such resistance genes that can combat M. oryzae strains and transfer them through breeding into susceptible cultivars; thus, such resistant cultivars can be used as safer alternatives to toxic fungicides. Such classical breeding approaches are complemented by the combination of classical breeding and genetic engineering to develop broad-spectrum resistance cultivars [17]. With the rapid development of molecular biology and genetics, both qualitative resistance (R) and quantitative resistance (qR) genes to rice blast have been extensively identified from rice natural varieties as well as wild rice. Despite a few R genes showing broad-spectrum resistance to multiple strains/isolates, most of them presented a typical “gene-for-gene” resistance to some strains/isolates. Corresponding to some R genes, a few avirulence (Avr) genes have been isolated from different strains/isolates. When the host R protein recognizes the pathogen Avr protein, resistance is activated, while the sequence variation of either one will lead to host susceptibility. Therefore, knowledge about Avr genes and their interaction mechanism with the corresponding R genes could be used to guide disease management. With respect to rice breeding, broad-spectrum resistance is highly preferred in agriculture practice. Therefore, how to develop a broad-spectrum and durable resistance variety is particularly important for rice production, as well as a need to comprehensively understand both R genes from the rice host and Avr genes from M. oryzae. In this review, we summarize the current status of isolated R and qR genes from rice and Avr genes from M. oryzae, and the progresses of these genes that have been utilized in rice breeding and disease management. The rice genome has a repertoire of resistance genes, some of which confer race-specific resistance and others which confer broad-spectrum resistance. To date, more than 100 R genes have been identified and mapped to different chromosomes of the rice genome and, among them, up to 38 R genes scattered on all rice chromosomes have been cloned (Table 1). Among 12 chromosomes, chromosome 11 carries the highest number (28) of R genes, while chromosomes 3, 7 and 10 possess a single R gene. The majority of the identified R genes are located in clusters, generally in three major clusters on chromosomes 6, 11 and 12. For instance, the cluster on chromosome 6 contains at least 7 R genes, Piz-t, Pi9, Pigm, Pi2, Pi40, Piz and Pi54, which all encode proteins with the nucleotide-binding domain (NB-domain) and leucine-rich repeats (LRR) domain. Wide variations on either coding regions or copy numbers of NBS-LRR genes in this cluster were reported. The Pigm donor variety ‘‘Gumei4′’ contains the highest number (13) of NBS-LRR genes compared with the donors of other R genes in this cluster. The presence of 18 aa changes in the LRR domain of Piz-t and not only specifies the resistance induction but also renders Piz-t distinct from Pi2 [18]. Although the majority of R genes encode NBS-LRR proteins, some are exceptions such as Pi-d2, pi21 and Ptr. The pi21, cloned from rice cultivar ‘Owarihatamochi’, encodes a protein rich in proline amino acids [19]; Pi-d2, isolated from ‘Digu’, encodes the aB-lectin receptor kinase [20]; Ptr on chromosome 12 from M2354 encodes an ARM repeat domain protein [21]. Pi21, Pi5, Pi63 and Pb1 are pathogen-inducible expressions, while almost all the remaining R genes are constitutively expressed no matter the existence or not of M. oryzae [22]. Most of the cloned R genes confer resistance to rice blast pathogen at the seedling stage, while others such as Pi68, Pi25, Pb1 and Pi64 show resistance at the seedling as well as the adult stage [23,24,25,26]. Although most of these R genes show race-specific resistance, some R genes, such as Piz-t, Pi9, Pigm, Pi2 and Pi54, located at chromosome 11, were reported to confer broad-spectrum resistance, especially for Pi9, Piz-t and Pigm [18,27]. With respect to a resistance mechanism, plants have evolved a complex system to recognize and respond to pathogen attack with the help of specialized receptors known as pattern-recognition receptors (PRRs). Such a primary line defense to halt pathogens is termed pattern-triggered immunity (PTI) [28,29]. PTI not only acts to curtail pathogen invasion but also to maintain normal microbiota inside the plant leaf which is beneficial for plant health [28,29,30,31]. However, in order to infect successfully, pathogens may further secrete various types of virulence-causing molecules, also commonly known as effectors, and deliver them inside the plant cell or apoplast in order to bypass PTI. To resist the infection, plants have evolved a series of special class intracellular receptors to recognize effectors and trigger a second line of immunity, commonly known as effector-triggered immunity (ETI), to limit the spread of the pathogen. In general, these intracellular receptors are very conserved with the typical domain of NBS-LRR, also called NBS-LRR receptors (NLRs), which have been widely identified in plants against various pathogens [32]. This ‘zig-zag’ model under the mechanism of PTI–ETI interplay was proposed by Dangl in 2006, who suggested it was a two-layer defense system to respond to different types of pathogens. However, how PTI and ETI interplay contributes to qualitative or quantitative resistance in plants has remained a hot topic of debate in the scientific community in the past decade [33]. Extensive research on this paradigm concluded that the activation of two distinct classes of receptors, PRRs and NLRs, during PTI and ETI leads to cascades of early signaling that ultimately defeat the pathogen [33,34,35]. The signaling cascades are manifested in different outputs, such as ROS, calcium flux, hormone signaling, transcription reprogramming and mitogen-activated protein kinase (MAPK) cascade [36,37,38]. These outputs pinpoint the intersectional points of PTI–ETI interplay to ensure robust immunity against a plethora of pathogens. The majority of the cloned R genes for rice blast encoding NBS-LRRs proteins follow a similar mechanism of action as ETI, represented by the hypersensitive response (HR) with the phenomena of ROS burst and programmed cell death (PCD). The host elicitor proteins are recognized directly or indirectly by host NLR proteins in cytoplasm. Upon recognition, a cascade of downstream signaling pathways is directed that ultimately combats the pathogen elicitors. One of the classical examples of blast R genes is Pigm, which is a multi-allelic locus and encodes clusters of NBS-LRRs including cognate pairs of receptors such as PigmS and PigmR. The former is a weak attenuator of pathogen pathogenicity via homodimerization while the latter confers broad-spectrum resistance to multiple races of rice blast. Moreover, both of these pair sustains a balance between yield and resistance against blast [39]. Additional aspects of the mechanistic study of Pigm unraveled an additional partner of Pigm known as PIBP1 (PigmR-Interacting and Blast Resistance Protein 1), which encodes an RNA recognition motif (RRM)-containing protein. PIBP1 is found to interact only with NLR proteins of rice blast resistance genes conferring broad-spectrum resistance [40]. PIBP1 is a transcriptional factor that directly activates other transcription factors such as OsPAL1 and OsWAK14 that ultimately lead to ETI-based broad-spectrum resistance [27]. In fact, almost all R genes-mediated immunity may produce a typical ETI response, but the signals linking R genes and ETI, represented by the phenomena of ROS burst and PCD, remain largely unknown. Different studies have demonstrated that rice resistance to M. oryzae is complex and often involves the interaction of various qR and R genes in a synergistic approach [41]. Contrary to the R gene, qR genes, such as Pi21, bsr-d1 and bsr-k1, generally deploy a different type of resistance mechanism against rice blast. One such classic example is Pi21, which encodes a protein rich in proline amino acids and carries a protein–protein interacting domain and metal-binding domain. The presence of the heavy metal domain suggests that Pi21’s inherent capability of metal transport might be associated with broad-spectrum resistance. A 1705 bp long polymorphic region in the ORFs of resistant and susceptible alleles of Pi21 was identified, and the resistant allele had undergone two key mutations (21 and 48 bp) in the proline-rich region. These two mutations in the key polymorphic region of resistance rice lines hinder the access of this target region being targeted by the product of pi21 negative regulators, thus contributing to the broad-spectrum resistance of Pi21 against rice blast [42]. Another example is bsr-d1, which was identified from a well-known rice cultivar ‘Digu’ with broad and durable blast resistance [43]. The bsr-d1 encodes a C2H2 transcription factor (TF), and one critical SNP variation in its promoter region leads to an upstream TF MYBS1 that is more strongly binding to the promoter of bsr-d1 in response to the M. oryzae infection and then suppresses its transcription. Since BSR-D1 protein is one of the directly positive regulators of peroxidase encoding genes, functioning in decreased H2O2, the low level of BSR-D1 in bsr-d1 plant results in it accumulating more H2O2 and ultimately limiting the spread of M. oryzae. H2O2 plays a great part in plant immune response and MABS1 is a commonly inducible gene by M. oryzae, which accounts for the broad-spectrum resistance of bsr-d1 to blast. At the moment, more than 26 Avr genes have been mapped in the M. oryzae genome and 14 of them have already been cloned (Table 2). With the exception of ACE1 and AVR-Pita, most of these Avr genes code for secretory proteins with less than 200 amino acids [72]. ACE1 is a non-secretory protein of secondary metabolite origin that exists as a hybrid of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). The NRPS part containing the β-ketoacyl synthase domain has been shown to elicit avirulence. Fifteen of the 24 Avr genes mapped so far have been located near the chromosomal ends, while five Avr genes are interspersed by transposons on either one or both sides of the Avr genes. The existence of transposons on either side of the Avr genes supports the hypothesis that Avr genes might have experienced a gain or loss of function during pathogen evolution. Besides, nine cloned genes have presence/absence polymorphism in the rice-infecting population. The predominant Avr gene AVR-Pia is known to have been acquired by different isolates or at least translocated between chromosomes 5 to 7 in different isolates of M. oryzae. With respect to R-Avr interactions, several interaction modes were observed based on the advances of seven R-Avr pairs. Two of these pairs, Pii/AVR-Pii and Piz-t/AvrPiz-t, interact indirectly and recognize each other. The remaining five pairs interact directly in three different ways. The first way is a classical gene-for-gene model, one Avr protein of the pathogen is directly recognized by a corresponding R protein, for instance, Pi54/AVR-Pi54 and Pi-ta/AVR-Pita [72]. One of the earliest studied R–Avr interactions is the Pi-ta/AVR-Pita pair in M. oryzae that laid the foundation for plant–pathogen interaction and their interplay in the onset of disease or development of resistance [73]. AVR-Pita, a telomere like the Avr gene, encodes a secreted protein with a distinct Zn-metalloprotease domain. The mature form of Avr-Pita is protease containing 176 aa at the C-terminus [74]. Avr-Pita belongs to a special class of the AVR-Pita gene family with three distinct genes, i.e., AVR-Pita1, AVR-Pita2 and AVR-Pita3. The former two are functional genes triggering Pita-mediated resistance while the latter one is a pseudogene without Avr function [75]. The corresponding Pita gene of the pair is a classical NLR (928 aa) receptor localized in the cytoplasm and expressed constitutively [65]. The leucine-rich domain (LRD) of the Pita protein directly interacts with the AVR-Pita176 protein and induces downstream signaling cascades. Functional validation through site-directed mutagenesis has shown that the AVR-Pita lose avirulence function by substituting two amino acids, i.e., avr-pita176E177D and avr-pita176M178W. Similarly, a mutant of the Pita gene with a single amino acid substitution (LRDA918S) diminishes the AVR-Pita176 -Pita LRD physical interaction, suggesting the practical outcomes of R–Avr pair interplay in the development of immunity against M. oryzae [76]. Besides the interaction between Pita–AVR-Pita, Han et al. (2021) recently found that Avr-Pita was able to interact with a cytochrome C oxidase (COX) assembly protein, OsCOX11, in mitochondria to reduce ROS accumulation for suppressing rice innate immunity [73]. The second way is that one Avr protein is sensed, interacts with two R protein homologs, and triggers an immune response upon recognition [56,65,77,78]. Pia locus comprises two NLRs proteins called RGA4 and RGA5, oriented face to face in opposite directions. Both proteins interact with a single Avr protein AVR-Pia with an N-terminal secretory protein [79]. Isolates of the M. oryzae avirulent to the Pia gene in rice contain 1-3 copies of AVR-Pia, depending on the specific isolate [80]. RGA5 alternative splicing produces two isoforms, RGA5-A and RGA5-B, of which only RGA5-A mediates Pia resistance. The constitutive expression of RGA4 causes cell death, which is then prevented by RGA5 in planta in the absence of infection, according to in vitro experiments. The NB domain of RGA4 is mandatory for cell death induction [80,81,82]. The physical interaction of AVR-Pia with the C-terminal non-LRR domain of RGA5 relieves the inhibition status and stimulates RGA4-mediated cell death. The third interaction works as a decoy model in which resistance mediated by the R-Avr pair is determined by an additional decoy protein interacting with the R-Avr pair. The best example is the Pii/Avr-pii pair interacting with two additional rice proteins, OsExo70-F2 and OsExo70-F3. The simultaneous knockdown of OsExo70-F2 and OsExo70-F3 completely diminished Pii immune receptor-dependent resistance against Avr-pii. The interaction of OsExo70-F3 with pathogens AVR-Pii is mandatory to induce Pii-triggered immunity, suggesting a role for OsExo70 as a decoy or helper in Pii/AVR-Pii interactions [59,83,84]. The fourth type of R–Avr interaction is the indirect interaction between Piz-t and AvrPiz-t. This interaction may represent a classic example where a single AvrPiz-t interacts with different rice proteins to suppress immunity. However, the broad-spectrum R protein recognizes these proteins to restore or enhance immune response [85]. The product of AvrPiz-t is a secretory similar to other common Avr genes, which is composed of Cys62- Cys75 disulfide-bonded six-strand β-sheets [25]. The structure of AvrPiz-t and a similar gene, ToXB, have been determined by Nuclear Magnetic Resonance. A single point mutation in any of the cysteine residues diminishes the avirulence of AvrPiz-t [86]. Using yeast two-hybrid analysis, several AvrPiz-t interacting proteins (APIPs) in rice were identified, and AvrPiz-t was found to directly interact with APIP4 (encoding a bowman-birk trypsin inhibitor protein), APIP5 (encoding a bZIP transcription factor), APIP6 (encoding a RING E3 ubiquitin ligase), APIP10 (encoding a RING-type E3 ligase) and OsAKT1 (encoding a plasma-membrane-localized K+ channel protein) to disturb the rice PTI response [25]. For instance, APIP4 exhibits trypsin inhibitor activity and is required for rice innate immunity, while, upon infection, the M. oryzae effector AvrPiz-t interacted with APIP4 and suppressed APIP4 trypsin inhibitor activity. Interestingly, Piz-t can interact with APIP4 and enhance its accumulation and activity, which leads to resistance against virulence strains [44]. AvrPiz-t may target APIP10 for degradation, but, in return, APIP10 may ubiquitinate AvrPiz-t, causing its degradation [87]. This results in the silencing of APIP10 in the non-Piz-t background, which compromises the basal defense against M. oryzae, while silencing it in the Piz-t background causes cell death and enhances resistance. Most recently, APIP10 was found to directly interact with two rice transcription factors, VASCULAR PLANT ONE-ZINC FINGER 1 (OsVOZ1) and OsVOZ2, which is required for defense response. Notably, both OsVOZ1 and OsVOZ2 were found to interact with Piz-t and stabilize its transcription and accumulation, indicating the two proteins positively contribute to Pi-zt-mediated immunity [66]. During the necrotrophic stage of M. oryzae in rice, APIP5 negatively regulated necrosis or cell death, while Avrpi-zt could interact with APIP5 and suppress its transcriptional activity and protein accumulation. At the same time, Pi-zt interacts with APIP5, which may stabilize each other for either preventing necrosis mediated by APIP5 or enhancing immunity mediated by Piz-t [85]. Most recently, APIP5 directly interacts with OsWAK5 and CYP72A1, which play roles in ROS production and defense compound accumulation, respectively [44]. These studies also suggest that being a broad-spectrum R gene, the type of resistance or immune response depends not only on the type of APIPs but also the genetic background of rice in which Piz-t exists. For instance, PTI is suppressed by AVrPiz-t in Piz-t-lacking Nipponbare rice while stabilizing Piz-t in the Piz-t background when infected by M. oryzae [87]. Nowadays, marker-assisted selection (MAS) has been widely and successfully used to develop rice varieties with blast R genes [95,96]. The list of R genes and their corresponding molecular markers have been applied by different researchers to develop rice blast-resistant varieties (Table 3). By MAS, Feng et al. (2022) developed a new cultivar ‘Yangnonggeng 3091’ with the introgression of Pigm [97]. The new variety shows excellent blast resistance, tested by 184 isolates collected from rice growing regions in the lower region of the Yangtze River, as well as good performance on both grain yield and quality. However, due to the fact that large-scale deployment of the same R genes in rice cultivars brings uniformity, this ultimately causes the corresponding M. oryzae strain to undergo mutations. Such mutations lead to the emergence of a new virulent resistance-breaking strain, often resulting in pandemics owing to the high specificity of the blast resistance genes [98]. Therefore, although race-specific resistance is robust and effective against a particular pathotype, it is not durable. Regarding these concerns, besides utilizing broad-spectrum R genes, it is important to identify the distribution frequency of these known R genes in varieties in a particular area and then design varieties by pyramiding appropriate R genes. The application of combinations of different genes and pyramiding them in a single rice cultivar for developing broad-spectrum durable resistance is the most desired strategy. Several rice blast-resistant lines have been created using a pyramiding strategy with the three R genes Pi2, Pi46 and Pita [96]. Using careful phenotyping followed by tagging with molecular markers, groups of researchers have characterized diverse rice germplasm for the distribution of different rice blast R genes in cultivated rice varieties. Xiao et al. (2018) have characterized rice varieties in the Heilongjiang Province of China and found that the distribution frequencies (DFs) of Pi-ta, Pi5 and Pib are higher than those of other genes, reaching 31.37%, 29.41% and 18.62%, followed by Pi2, Pi-d2 and Pi-d3 with DFs of 9.80%, 1.96% and 1.96%, respectively [99]. In another study, Li et al. (2019) identified the existence of Pi54, Pi5, Pi-ta, Pib and Pikm but not Pi9 in the core rice germplasm in Ningxia Province, China [100]. In a contemporary study performed in Guizhou Province, China, Ma et al. (2018) identified relatively high DFs of Pi5 and Pi54 in local varieties, at 32.35% and 30.86%, respectively; while the DFs of Pi9 and Pi2 were relatively lower, at 2.56% and 2.47%, respectively [101]. Wang et al. (2022) genotyped 195 rice varieties in Jiangsu province using diagnostic markers of 14 known R genes and found that most varieties in Jiangsu province carried two to five known R genes, and none of them contained Pigm [66]. The distribution frequencies of Pib, Pita and Pikh were relatively high and all exceeded 45% in the varieties tested; the remaining 10 genes were under 30%. Notably, after combining with the phenotype of panicle blast resistance, they further found that only three (Pita, Pia and Pi3/5/i) of these gene loci showed a significant contribution to panicle blast resistance and observed significantly positive interaction effects on resistance between Pita and either of the other two gene loci. This indicates that Pita and Pia or Pi3/5/I are appropriate gene combinations for developing resistant varieties against blast disease, at least in Jiangsu province. Using near-isogenic lines (NILs), several previous studies have also identified that complex interactions exist among different R genes [78,99]. This demonstrates that identifying appropriate R genes for pyramiding is important for breeding programs in a certain region. However, very little effort has been carried out in this important field so far. Quantitative resistance or partial resistance permits the development of lesions but halts lesion expansion and spore formation, thereby slowing down the infection and conferring sustained or prolonged resistance. Such resistance is durable and broad-spectrum due to low selection pressure on causative pathogens, which is less likely to mutate its population and minimizes the chances of an emergence of new resistance-breaking strains [39]. Therefore, current breeding programs are aimed to develop elite rice germplasm by deploying durable partial resistance to manage rice blast disease. To date, over 350 QTLs have been identified in different rice germplasm and several of these large-effect QTLs have been deployed to curb rice blast disease. Recent studies on the genetic analysis of partial blast resistance have been documented, mainly targeting QTLs such as Pb1, pi21, Pi34, Pi35 and Pi39 with the help of molecular markers tightly linked to these QTLs [19,24]. MAS has greatly facilitated rice breeders to characterize and select rice lines possessing rice blast QTLs of interest in the past decade. The deployment of a single partial resistance might not have been proved to effectively control rice blast, instead stacking multiple QTLs in a single rice line has contributed to durable and broad-spectrum resistance. However, details related to pyramid-suitable QTLs have been rarely documented. In one such study, Fukuoka et al. (2012) documented the pyramiding of three major rice blast QTLs, i.e., qBR4-2a, qBR4-2b and qBR4-2c, and significantly reduced the blast lesion area [102]. In total, compared with the cloned R genes, the small number of qR genes isolated so far is the critical problem that limits the breeding utilization of qR genes or resistance QTLs in practice. Based on the gene-for-gene concept, the distribution frequency of Avr genes in pathogen population and the corresponding R genes in rice varieties can be employed to indirectly predict the epidemic severity of rice blast in a specific region as well as guide breeders to select appropriate R genes in breeding programs. For instance, Selisana et al. (2017) investigated the resistance spectrum of Avr genes in different strains of M. oryzae and showed how such a resistance spectrum was used to estimate the resistance efficiency of various rice cultivars [103]. The resistance frequency of cognate R genes in different rice lines perfectly matched the frequency of Avr genes. By applying genetic and molecular marker analysis, they identified additional R genes, most likely alleles of Pi19 in rice cultivars. This study demonstrated that early diagnosis based on Avr genes can precisely predict the specificity and effectiveness of resistance conferred by different R genes in various rice cultivars, which in turn is crucial for predicting and managing rice blast epidemics (Table 4). Using the specific and diagnostic markers for each of the 10 Avr genes, one can predict the distribution of strains/isolates containing specific avirulence genes in a population [103]. Despite the cloned Avr genes and diagnostic markers developed for their identification, there are challenges to utilizing the given information on avirulence genes in practice. Possible reasons are as follows. First, the number of characterized avirulence genes is too few to fully represent the characteristics of the pathogen population. So far, only 14 Avr genes have been cloned and well characterized, contrary to diverse populations of M. oryzae strains (Table 2). In order to ensure the best utilization of Avr genes in practice, there is a pressing need to clone and characterize as many Avr genes as possible. Second, there are too many isolates or strains in field condition which need a large-scale collection of isolates [104], resulting in inconvenience and needing a highly efficient and low-cost genotyping method. Different strains of M. oryzae are routinely screened by different genotyping methods such as RAPD, SSR, SNP and FFLP. Third, high sequence variations in Avr genes may affect the value of the result in practice [105]. The high sequence variations are due to extensive gain or loss of genes via point mutation, transposition and translocation [106]. Such extensive evolutionary changes in the M. oryzae genome sometimes inactivate existing Avr genes while giving rise to new virulent isolates, thus complicating the practical significance of Avr genes in breeding programs. Fourth, due to the fact that the combination of some R genes could further broaden the resistance spectrum; however, the mechanism remains unclear, which means that the gene-for-gene relationship alone may not be enough to manage blast disease, including the utilization of appropriate R genes. The key challenge to controlling rice blast is the constantly changing population of rice blast fungus and the emergence of new virulent strains. Thus, the best management strategy to detect constantly evolving Avr genes of rice blast fungus is to have an efficient surveillance system at hand. Thus, an effective surveillance system is necessitated to monitor emerging novel virulent strains of M. oryzae. The advent of Next Generation Sequencing (NGS) and molecular breeding tools means that rice breeders are now able to design more robust methods of rice blast surveillance and control. For example, Mutiga et al. (2021) in Africa recently proposed a robust pathogenomic-based rice blast surveillance system known as the Mobile and Real-Time Plant Disease (MARPLE) system [107]. In this system, infected rice leaf tissue is collected to identify the characteristics, genomic signatures and genetic shift in the pathogen population in the field. In the next step, DNA is isolated from infected leaves followed by enrichment of the DNA with putative avirulence genes via multiplex PCR prior to targeted genome sequencing by oxford nanopore sequencer. The sequencing data are subsequently analyzed to predict avirulence gene evolution and acquired fungicide resistance. Based on the analyzed data, rice breeders make precise and timely decisions to breed and deploy virulent-specific rice cultivars to curb rice blast disease. Due to the fact that it is impossible to stop the evolution of blast fungus and host rice, it is important to unceasingly mine new R genes. Although pyramiding R genes is undoubtedly a good approach to developing a broad-spectrum resistance variety, complex interactions do exist among known R genes. The effective deployment and utilization of an effective combination of different R genes in breeding against rice blast has been found to be challenging owing to the abundance of R genes in rice and their complex interaction mechanisms [108]. Therefore, it is of critical importance to find those R gene combinations with a positive interaction for increasing the resistance spectrum and to elucidate their molecular mechanism. Some studies have shown that the interaction between R genes during pyramiding is linked with the number of R genes being pyramided. Thus, combining more R genes in the same cultivar reflects higher resistance against M. oryzae and vice versa [100,106]. However, in more practical cases, increasing the number of R genes slows down the level of resistance of the cultivar owing to the linkage drag associated with multiple pyramided genes [93,99]. Thus, developing key positive interactions among R genes during pyramiding is attributed to understanding the interaction mechanism, screening different R combinations and finally deploying the right combination pattern of R genes in single rice cultivar. Xiao et al. (2016) have successfully pyramided Pi-ta and Pi46 and broadened the resistance spectrum of the pyramided line as compared to monogenic lines [109]. Similarly, the perfect combination and interaction of Pik/Piz pairs in the rice variety ‘Jefferson’ have proved broad-spectrum resistance since 1997 [110,111]. It is suggested that more novel R genes should be mined, and their interaction mechanism should be investigated deeply for developing novel types of broad-spectrum resistance. Due to the importance of qR genes in developing durable resistance variety, deeply mining qR genes is particularly important. Genome-wise association studies (GWAS) should be a promising strategy to widely identify qR genes or susceptible genes. This process is performed in three steps to identify more qR genes via GWAS. In the first step, different rice cultivars containing different Pi genes are subjected to artificial inoculation with different strains of M. oryzae that are prevalent in a specific cultivation area. This, in turn, helps to characterize different prevalent isolates of M. oryzae. In the second step, multiplex and robust genotyping methods are used to characterize both the resistant cultivars and their corresponding pathogens simultaneously. Most importantly, the abundant SNP markers available via a robust and multiplex genotyping system further assist in GWAS to identify novel genomic regions either associated with single R genes of race-specific resistance or qR genes conferring broad-spectrum resistance against M. oryzae isolates. The third phase is to combine the results of the above mentioned steps for gene mining via multiple crosses to develop a variety that confers broad-spectrum rice blast resistance [107]. In the assessment phase, the newly developed rice cultivars containing novel qR genes are evaluated for multiple years and at multiple locations to validate their durability and broad-spectrum resistance against different isolates of M. oryzae. The application of molecular technologies such as MAS, genomic selection and genome editing is hoped to not only assist but also speed up breeding programs aimed at developing rice blast-resistant rice cultivars. Conventional breeding techniques are not only costly and labor intensive, but also need a long time to develop rice blast-resistant varieties. On the contrary, genomic selection assisted by molecular markers shortens the time required for cultivar development by selecting blast-resistant lines in earlier generations. Moreover, genomic selection followed by MAS potentiates the precise pyramiding of several candidate R genes into a single cultivar for developing durable and broad-spectrum rice blast resistance. Progress made in rice genomics and development has enabled rice breeders to clone more and more rice blast R and M. oryzae Avr genes. The successful cloning of Pi2, Pi9 and Pigm opened new avenues to identify functional SNPs closely associated with resistant genotypes. Such functional SNPs can be used to develop robust Kompetitive Allele-Specific PCR (KASP) markers in abundance for marker-assisted rice blast resistance breeding programs [107]. In a similar study, Wang et al. (2019) sequenced and assembled a high-quality genome of ‘Tetep’, a broad-spectrum rice blast-resistant germplasm which is also the donor of the Pi5 gene [112]. A total of 455 NLRs genes were predicted in the genome assembly ‘Tetep’ [112]. Molecular markers designed from these predicted NLRs have not only enabled rice breeders to select resistant rice cultivars, but have also assisted in introducing these NLRs to new breeding varieties for durable rice blast resistance. To grasp the practical potential of genomic selection and MAS, Feng et al. (2022) evaluated 162 accessions from the USA for their resistance to six rice blast isolates and found that genomic selection and MAS can be effectively used for rice blast resistance [97]. Xiao et al. (2019) utilized the potential of MAS to pyramid Pi2, Pi46 and Pita and developed broad-spectrum rice blast-resistant lines [96]. Furthermore, Xiao et al. (2019) successfully introgressed broad-spectrum resistance gene Pi2 into the genetic background of an elite Chinese rice cultivar ‘Feng39S’ through SNP array-based marker-assisted backcrossing coupled with genomic-based background selection, and the newly developed rice line ‘Feng39S’ with durable resistance was suggested to replace the original parent in developing the popular hybrid rice variety ‘Fengliangyou4’ [96]. Genome Editing Technologies (GETs) have emerged as key players in gene functional research. Among TEGs, CRISPR/Cas9 has been widely adapted by scientists as robust, technically less demanding and precise gene-editing tools. This technology is becoming the prime choice of gene editing tools by rice breeders. The function of several rice blast resistance genes has been validated recently. For example, Wang et al. (2016) selectively mutated the OsERF922 gene in rice with CRISPR/Cas9 and found that the mutated line conferred higher resistance to M. oryzae than the wild type [85]. Similarly, the targeted mutation of the rice blast durable resistant Ptr gene via CRISPR/Cas9 rendered the gene susceptible, thus successfully validating gene function [21]. Most recently, in aid of CRISPR/Cas9, two studies reported the generation of rice lines with broad-spectrum resistance to blast variety by editing two genes, Pi21 and Bsr-d1, and found that simultaneously editing the two genes had much stronger resistance than editing one of them [29]. These findings prove that simultaneous editing of numerous S genes is an effective method for creating novel rice cultivars with broad-spectrum resistance. In the near future, CRISPR/Cas9-mediated gene editing technology will be undoubtedly widely used to develop sustainable and durable resistance rice cultivars against blast disease. The available sequence genome of M. oryzae has led to the successful isolation of 14 Avr genes (Table 2). However, compared to the isolation of 38 R genes, the progress of the isolation of Avr genes from M. oryzae strains remains slower. One of the reasons is that the rice blast Avr-gene family is highly diversified, and the pathogen is capable of rapidly undergoing evolutionary changes in the form of retrotransposons, deletions, translocations and point mutations. Such drastic evolutionary changes might lead to a loss of avirulence [113]. Some classical Avr genes, such as Avr-Pia, Avr-Pii and Avr-Pik, were found completely absent in assembled rice blast fungal genomes [84]. This shows that presence/absence polymorphism is a driving evolutionary force of Avr genes. Such presence/absence polymorphism hampers the cloning of Avr genes as shown by failed amplifications of six Avr genes from different strains by different primer combinations [114]. Multiplex methods should be devised to accelerate the cloning of Avr genes from diverse strains of M. oryzae as well as to determine its sequence variance in the M. oryzae population. In addition, the interplay of R-Avr pairs is important for an efficient surveillance system and for deploying broad-spectrum resistance. Some of these interacting models have been shown to confer broad-spectrum resistance against rice blast [115]. However, the interaction of R-Avr and R-R gene pairs has been investigated in detail in the past few decades, and the detailed interaction mechanisms between most isolated R and Avr genes remain to be elucidated. In addition, attention should also be focused on investigating the interaction among different Avr genes in M. oryzae strains. In cereal powdery mildew, it has been shown that the interaction of Avr with the suppressor of the Avr gene could lead to the mechanism of recognition specificity [115,116,117]. This implies that complex interactions might exist not only in R-Avr pairs and R-R genes but also in Avr-Avr genes, which together affect the host phenotype, being either resistant or susceptible. Therefore, the isolation of more Avr genes and elucidating their interactions with both R genes and themselves are quite important for better managing rice blast. The extensive application of a wide array of modern fungicides not only dramatically reduced damage caused by M. oryzae strains but also greatly enhanced the quality and yield potential of global rice production. The frequent deployment of the same fungicide may lead to the emergence of novel pathogenic strains that further necessitate the discovery of novel compounds to curb rice blast resistance-breaking strains. Appressorium formation is required for the successful infection of M. oryzae, and melanin plays an important role in appressorium growth and penetration via the cuticle layer of the rice plant [116,117]. Thus, melanin biosynthesis inhibitors (MBIs) have been used to suppress appressorium growth and penetration via the cuticle layer. Broadly, two groups of MBIs fungicides, i.e., scytalone dehydratase (MBI-D) and poly-hydroxynaphthalene reductase (MBI-R), proved fatal against appressorium growth inside rice plants. The latter group, comprising mainly phthalide, pyroquilon and tricyclazole, witnessed no resistant pathogen emergence despite 30 years of longer duration widespread application. Few resistant mutants have been identified in laboratories in China without the emergence or isolation of any resistant strain in the field [118]. Most recently, He et al. (2020) found that M. oryzae utilizes a special class of enzymes called septin GTPases for the appressorium-mediated development of infection [119]. However, septin GTPases require very long-chain fatty acids (VLCFAs) for membrane-based septin assembly for infection progression. The chemical fungicides developed by the group contain inhibitors of septin biosynthesis, thereby affecting septin assembly and appressoria-based host membrane penetration. The advantage of the septin inhibitor-based novel class of fungicides is that these compounds do not only control rice blast but also confer broad-spectrum resistance against fungal pathogens of plants and animals without affecting the target host [119]. The development of a resistant variety is one of the most economical and efficient approaches to control rice blast, which requires an understanding of the mechanism of both rice resistance and pathogen pathogenicity. This review summarized the advances in the isolation of R and qR genes from the rice host and Avr genes from M. oryzae and that the interactions between the rice host and pathogen depend on R-Avr gene pairs. In addition, the problems of using these advances to manage the disease were discussed. Based on these advances and potential problems, five research focuses for the future were suggested, which are crucial for developing a broad-spectrum resistance variety.

PMC10003184

Kunwar Somesh Vikramdeo,Amod Sharma,Shashi Anand,Sarabjeet Kour Sudan,Seema Singh,Ajay Pratap Singh,Santanu Dasgupta

Mitochondrial Alterations in Prostate Cancer: Roles in Pathobiology and Racial Disparities

24-02-2023

prostate cancer,mitochondria,racial disparity,biomarkers,pathobiology

Prostate cancer (PCa) affects millions of men worldwide and is a major cause of cancer-related mortality. Race-associated PCa health disparities are also common and are of both social and clinical concern. Most PCa is diagnosed early due to PSA-based screening, but it fails to discern between indolent and aggressive PCa. Androgen or androgen receptor-targeted therapies are standard care of treatment for locally advanced and metastatic disease, but therapy resistance is common. Mitochondria, the powerhouse of cells, are unique subcellular organelles that have their own genome. A large majority of mitochondrial proteins are, however, nuclear-encoded and imported after cytoplasmic translation. Mitochondrial alterations are common in cancer, including PCa, leading to their altered functions. Aberrant mitochondrial function affects nuclear gene expression in retrograde signaling and promotes tumor-supportive stromal remodeling. In this article, we discuss mitochondrial alterations that have been reported in PCa and review the literature related to their roles in PCa pathobiology, therapy resistance, and racial disparities. We also discuss the translational potential of mitochondrial alterations as prognostic biomarkers and as effective targets for PCa therapy.

Mitochondrial Alterations in Prostate Cancer: Roles in Pathobiology and Racial Disparities Prostate cancer (PCa) affects millions of men worldwide and is a major cause of cancer-related mortality. Race-associated PCa health disparities are also common and are of both social and clinical concern. Most PCa is diagnosed early due to PSA-based screening, but it fails to discern between indolent and aggressive PCa. Androgen or androgen receptor-targeted therapies are standard care of treatment for locally advanced and metastatic disease, but therapy resistance is common. Mitochondria, the powerhouse of cells, are unique subcellular organelles that have their own genome. A large majority of mitochondrial proteins are, however, nuclear-encoded and imported after cytoplasmic translation. Mitochondrial alterations are common in cancer, including PCa, leading to their altered functions. Aberrant mitochondrial function affects nuclear gene expression in retrograde signaling and promotes tumor-supportive stromal remodeling. In this article, we discuss mitochondrial alterations that have been reported in PCa and review the literature related to their roles in PCa pathobiology, therapy resistance, and racial disparities. We also discuss the translational potential of mitochondrial alterations as prognostic biomarkers and as effective targets for PCa therapy. Prostate cancer (PCa) is the second most diagnosed cancer in men in the United States, with an expected 268,490 new diagnoses in 2022. It is also the fifth leading cause of cancer-related mortality, with an estimated 34,500 deaths this year [1]. Significant disparities in PCa incidence and health outcomes are reported among various racial and ethnic populations. African American (AA) men bear the highest burden of PCa. They are 1.7 times more likely to be diagnosed with PCa and more than twice more likely to die because of it than Caucasian American (CA) men [2,3]. The underlying causes of such large disparities are not well understood but could involve a variety of factors, including access to quality healthcare, lifestyle, social exposures, and ancestry-related predispositions [4,5]. PCa is a highly heterogeneous disease. Most patients are diagnosed early, especially in developed countries, due to prostate-specific antigen (PSA)-based screening. However, PSA fails to discern between indolent and aggressive PCa and remains a concern for overdiagnosis. Moreover, most positive PSA tests are found to be false positives, thus making it an unreliable biomarker for the prediction of PCa [6], thus warranting a need for the development of newer, specific, and reliable biomarkers. Androgen deprivation therapy (ADT) or castration therapy (CT) is the primary treatment option for patients with locally advanced or metastatic PCa; however, therapeutic failure is inevitable in most patients. Castration-resistant (CR) PCa is highly aggressive and difficult to manage. The use of androgen receptor (AR) targeting agents such as abiraterone and enzalutamide is effective, but therapy resistance develops sooner or later, culminating in patient death [7,8]. Thus, we desperately need newer sets of biomarkers and therapeutic targets to curb PCa-associated mortalities. Mitochondrial alterations in cancer and their relevance as a biomarker have been re-explored in recent years [9,10,11,12]. Mitochondrial DNA is potentially a better biomarker as its genome is well characterized, and its high copy number allows its alteration to be assessed easily from even a limited amount of samples [13]. Mitochondria, the ‘powerhouse’ of the cell, play a crucial role in cellular metabolism and energy production via oxidative phosphorylation (OXPHOS) [14]. Mitochondria also communicate with the nucleus to convey the information needed to adapt to the metabolic demands of the cell, as well as with the cell’s surroundings leading to stromal remodeling [15]. Here we review the mitochondrial alterations reported in PCa and discuss their roles in pathobiology and racial disparities. We also discuss potential strategies to target dysfunctional mitochondria, as well as their utility as prognostic biomarkers. Mitochondria contain their own circular genome (16.5 kb) in multiple copies located in the mitochondrial matrix. It consists of genes coding for 13 mitochondrial proteins (subunits of respiratory complexes), 2 ribosomal rRNAs (12s and 16s rRNAs), and 22 transfer RNAs (tRNAs), along with a noncoding region termed as D-loop (Figure 1). The mitochondrial genome lacks protective histones and a robust DNA repair machinery, which makes it particularly susceptible to DNA damage. This vulnerability, coupled with the presence of numerous copies of mitochondria, often causes heteroplasmy, a state where a proportion of mitochondria in the cells have alterations in their mitochondrial genome. Phenotypic changes in the cell often take place when the level of heteroplasmy crosses a threshold and leads to altered mitochondrial function and signaling changes within the cell. A comprehensive tissue analysis of somatic mtDNA alterations in 1675 cancer cases, including 80 cases of PCa, displayed a significant proportion of somatic mtDNA mutations, predominantly single-nucleotide variations, followed by insertions and deletions. Further, this study suggested that functionally detrimental mtDNA mutations are more likely to be heteroplasmic [16]. Below we discuss the various types of aberrations that can potentially alter mitochondrial function. There have been reports that suggest DNA damage usually corresponds with increased mitochondrial content. However, the information in the literature about the variation in mtDNA content in PCa has been quite ambiguous. A high mitochondrial content has been associated with the poor prognosis and aggressiveness of PCa [17,18] and has also been reported to correlate with early-stage PCa patients [19]. In contrast, there have also been studies that link low mtDNA content in the peripheral blood leukocytes to the increased risk of developing an aggressive form of PCa [20,21] and poor prognosis. In a study on PNT1A cells, prostate epithelial cells, which were depleted of mtDNA content by treating them with ethidium bromide, displayed enhanced cell survival and migration through the activation of the PI3K-Akt pathway [22], which seems to corroborate in vitro studies that report that PCa cells with a low mtDNA content show an increase in cell growth and survival. High-grade PCa tumors have been reported to display a higher mitochondrial copy number compared to low-grade PCa tumors [23]. However, a study by Kalsbeek et al. in PCa tissues suggests that the depletion of the mtDNA copy number in PCa tissues is not uniform and rather displays the heterogeneous nature of PCa. They also reported that a high mtDNA content in normal adjacent prostate tissue may be associated with poor prognosis [24]. PCa cell lines with low mtDNA display androgen independence and thus promote therapy resistance [25]. Mutations in the mitochondrial genome are associated with the initiation and progression of a variety of cancers. The association between alterations in the mitochondrial genome and PCa has been known for quite some time now. Mitochondrial point mutations and mtDNA instability are known to occur at a high frequency in PCa [26]. In fact, in a study performed with 64 tumor samples from 55 PCa patients, the mitochondrial genome displayed a 55-fold higher mutation rate compared to the nuclear genome [27]. In another study involving the next-generation sequencing of 115 PCa tumor samples, 74 unique PCa-specific somatic mtDNA mutations were identified. Most of these mutations were single-nucleotide variants (SNVs) and correlated with disease relapse [24]. A study identified a high frequency of 309 C-T mutations in the D-loop of mtDNA of PCa patients [28]. Another study carried out on 384 tumors from PCa patients reported HV1, a part of the D-loop, as the most frequently mutated region. They also identified 157 SNVs in the protein-coding regions and observed that MT-ND5 was the most frequently mutated respiratory complex subunit, followed by MT-ND1 and MT-CO1 [29]. Earlier studies have associated the mutation of the respiratory complex to be predominant in PCa patients. Mutations in MT-ND2 and MT-ND4 have been linked to early-stage PCa [30,31]. Mutations in other respiratory complexes, such as MT-CYTB (A14769G) and MT-ATP6 (C8932), have also been reported to be associated with PCa and promote the growth of PCa cells [32]. Further, T8993G mutations in the MT-ATP6 gene have been shown to promote PCa cell growth and invasion in the bone stromal environment by the modulation of FGF-1 and FAK expression in mice [33]. In addition to the alteration of the mitochondrial genome, changes in nuclear-encoded mitochondrial genes have also been linked to PCa. Several studies have reported mutations in TCA-cycle enzymes such as fumarate hydratase and isocitrate dehydrogenase in PCa [34,35,36]. One study reported two IDH1 mutations, i.e., R132C and R132H, to be prevalent in PCa, although these did not correlate with either the stage or grade of PCa [37]. A subsequent study further seemed to confirm the occurrence of these two R132C mutations of IDH1 in PCa [38]. Most of the mutations in the mtDNA reside in the respiratory complexes and as such have the potential to effect significant changes in mitochondrial functions and metabolism. There has been increasingly accumulating evidence in the literature underlining the important role of OXPHOS in the progression and development of several types of cancers. As such, there is scant evidence in the literature about changes in metabolism and their significance in the development of PCa. Drug-resistant PCa cells have been shown to primarily depend upon OXPHOS rather than glycolysis [33]. In addition, drug-resistant PCa shows an increased flux of primary fuel sources such as glucose, glutamine, and lactate through OXPHOS [39]. The expression of mitochondrial respiratory complexes has been linked to early-onset PCa. Some earlier studies have reported the reduced expression of MT-RNR1, MT-CO2, and MT-ATP6 in PCa tumor samples [40,41]. In a study carried out by Verma et al. in the transgenic adenocarcinoma of a mouse prostate (TRAMP) model, they showed the reduced expression of nuclear-encoded mitochondrial genes such as COX10, COX15, and COX17, along with MT-ND4, MT-CO1, MT-CO2, and MT-CO3 [42]. Another study reported the reduced expression of NDUFS4, SDHA, UQCR2, MT-CO1, and ATP5F1A in tumor samples from 94 PCa patients who had undergone radical prostatectomy after tumor diagnosis. The most depleted subunit reported in this study was ATP synthase F1 subunit alpha (ATP5F1A) [43]. Although earlier studies have reported alterations in Complex I in PCa, increasing evidence suggests a pivotal role of Complex II in the promotion of PCa tumorigenesis. The cBioPortal database analysis shows several alterations in SDHA and SDHB genes in PCa patient samples [44,45]. Recent reports show that PCa cells preferentially utilize succinate oxidation for their metabolic needs [46,47]. A recent study by Schopf et al. suggests a link between mtDNA mutations and shifts in metabolism in the context of the substrate used for energy production in PCa. They report that benign and normal prostate tissues display a higher dependency on glutamate- and malate-driven OXPHOS, while malignant tissues primarily depend upon the oxidation of succinate for their energy [23]. The most frequent mutation of protein-coding genes was the T10551C mutation in the MT-ND4L gene. This study also provides evidence that mutations in respiratory complexes display an optimal shift in the metabolism at heteroplasmy levels of around 30–60%. Further, it suggests that while alterations in Complex IV can adversely affect the total OXPHOS capacity of the cells, alterations in Complex I can be sufficiently compensated. A reduction in the expression of NADH–ubiquinone oxidoreductase subunit B8 (NDUFB8), an accessory subunit of Complex I, is reported to be critical for Complex 1 assembly and function [48]. A high-throughput analysis of formalin-fixed PCa tissue samples revealed that malignant tissue displayed a reduced expression of NDUFB8 and MT-CO1. These tissues also revealed a high mitochondrial mass, which may suggest a potential compensatory measure by the cell to cope with respiratory complex dysfunction [49]. Altogether, these mitochondrial variations lead to many diseases, including cancer (Figure 2). ROS has been widely known to aid in the neoplastic transformation and aberrant growth and proliferation of cells [50]. Changes in the ROS levels of the cells trigger the activation of a variety of signaling pathways that contribute to cell survival under oxidative stress conditions [51]. These processes are reported to be responsible for the initiation and progression of many cancers, including PCa [52]. Several studies over the last few years have established a crucial role of oxidative stress in the development of PCa [36,53,54]. Tumor cells inevitably create a hypoxic environment as a consequence of their rapid and unchecked proliferation. To counteract the consequences of a low oxygen environment, cancer cells stabilize and activate hypoxia-inducible factor (HIF-1) [55]. However, it has been shown that this also results in an increase in ROS generation, with the predominant source being mitochondria. When PCa cells are exposed to a hypoxic environment, the modulation of ROS levels along with metabolism promotes its survival and growth [56]. High ROS levels can further sustain the expression of HIF-1 by inhibiting prolyl hydroxylases, which usually degrade HIF1. ROS can also promote the formation of new blood vessels by increasing the expression of VEGF [57]. Mitochondrial glycerophosphate dehydrogenase (mGPDH) increases ROS generation in PCa cells and sustains elevated glycolysis [58]. Cancer cells keep a delicate balance of ROS to maintain its growth-promoting potential while at the same time avoiding its cytotoxic effects. To achieve this, they often rely on altering the expression of antioxidant genes. Erythroid 2p45 (NF-E2)-related factor 2 (Nrf2), a master regulator of the antioxidant-response system, carries out its function by binding to the antioxidant-response element (ARE) present in various antioxidant genes [59]. The loss of Nrf2 expression has been shown to occur in PCa, and further studies in a knockout mice model show that it results in a reduction in GST levels, enhances ROS, and correlates positively with PCa development [60]. The restoration of Nrf2 levels has been reported to cause a reduction in the anchorage-independent growth of PCa cells [61]. However, some studies have reported that high Nrf2 levels are beneficial in countering the proteotoxic stress in PCa cells and may be involved in enhancing its aggressiveness [62]. Furthermore, Nrf2 can also promote chemoresistance by the maintenance of cancer stem cells [63]. Peroxisome proliferator-activated receptor gamma coactivator 1 (PGC1) is a family of transcriptional coactivators that are important for the regulation of mitochondrial biogenesis. Recent studies have shown that PGC1 is downregulated in PCa patients, which increases the migration and invasion of PCa cells [64]. Further, PGC1α expression negatively correlates with the Gleason score [65]. Its expression decreases as the disease progresses towards the metastatic state. The restoration of PGC1α expression inhibits growth and metastasis in PCa cell lines [65]. AR can promote the expression and activity of IDH1, a key enzyme of the TCA cycle, and thus reprogram the metabolism of PCa cells [66]. AR also possess a mitochondrial localization signal (MLS) and is shown to be localized inside mitochondria in both PCa tissues and cell lines [67]. AR signaling also causes the increased production of TCA-cycle enzymes and intermediates such as citrate synthase, acetyl-CoA, and oxaloacetic acid and leads to castration resistance [68]. AR also upregulates DRp-1, a protein integral to mitochondrial fission, which then helps in the formation of the VDAC-MPC2 complex, which facilitates enhanced pyruvate transport into mitochondria and increases OXPHOS [69]. One of the most important heat-shock proteins in mitochondria is Hsp60, which is crucial for maintaining protein homeostasis in mitochondria. HSP-60 along with HSP-27 has been suggested as a potential biomarker for PCa recurrence [70]. A high expression of HSP-60 has been associated with poorly differentiated PCa and reduced survival. HSP-60 interacts with caseinolytic protease P (ClpP), a mitochondrial protease responsible for degrading unfolded or misfolded proteins in mitochondria and promoting cell survival. This interaction has been shown to promote the growth of PCa cells [71]. The literature suggests that PCa progression is fraught with an increase in ROS that promotes its aggressiveness. During the transformation and later stages of PCa development, PCa cells increase their mitochondrial respiration along with a high glycolytic rate to meet their energy requirement. As a result of enhanced mitochondrial respiration, ROS levels rise, inducing the signaling pathways associated with PCa growth and survival [72,73,74]. Further, advanced stages of PCa are marked by the elevation of the TCA cycle and increasing levels of citrate, which are utilized by the cancer cells for biomolecule synthesis to support their growth [68]. The epithelial-to-mesenchymal transition (EMT) provides cancer cells with an enhanced migratory and invasive capacity, facilitating tumor dissemination and metastasis. Transcription factors involved in EMT also orchestrate intricate metabolic reprogramming that fulfills the increased energy requirement created by a high motility and growth rate [75]. Reports have shown that oncogenic mutations in mitochondrial metabolic enzymes, succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase induce EMT in cancer cells [76,77,78]. Mutations in isocitrate dehydrogenase isoforms IDH1/2 were found in several cancers, including PCa [79]. The mutant isocitrate dehydrogenase enzyme can produce 2-hydroxyglutarate from α-ketoglutarate, which has been shown to act as a potent oncometabolite inducing EMT in several cancers [80,81,82]. The accumulation of oncometabolites because of mutations in mitochondrial enzymes causes epigenetic changes by affecting chromatin structure and function and influencing the signaling pathways involved in EMT [83,84]. In some reports, the downregulation of mitochondrial proteins involved in OXPHOS has also been shown to correlate with increased EMT and aggressive disease features [85,86]. Androgen deprivation therapy (ADT) is a first-line therapy against PCa. However, in the majority of cases, the patients develop resistance and stop responding to ADT, a phenomenon called castration resistance. The development of castration resistance is marked by the switching of glycolytic metabolism to OXPHOS [33]. mtDNA mutations are known to alter the response of PCa cells to chemotherapeutic agents. A mutation in MT-CO2 (m.6124CT>C) was reported to impair the sensitivity of PCa cells to statin treatment [87]. Changes in the expression of mitochondrial genes also correlate with PCa growth, survival, and resistance. Mitochondrial fission factor (MFF) and dynamin-related protein-1 (Drp1) are also reported to be amplified in castration-resistant PCa and lead to poor patient survival [88]. MFF is also shown to be implicated in the maintenance of PCa stem cells, which further reiterates its importance in the promotion of castration resistance [89]. In a recent study, it was observed that PCa cells secrete mtDNA, which in turn causes the production of C3a, an anaphylatoxin, which then promotes resistance to docetaxel and tumor progression [90]. Ceramides are produced in the ER and transferred to mitochondria via mitochondria-associated membranes (MAMs) and play an important role in programmed cell death (apoptosis), cell cycle, and differentiation [91]. Ceramides are reported to be crucial in the development of resistance to AR inhibitors such as enzalutamide in PCa [92]. Apart from their function as the powerhouse of the cell, mitochondria also play an important role in the cell death pathway such as apoptosis. Mitochondria are crucial for the activation of apoptosis via the intrinsic pathway in response to excessive oxidative stress and DNA damage [93]. Since cancer cells are known to generate excess ROS, they must strive to inhibit the mitochondrial apoptosis apparatus. Bcl-x is a member of the Bcl-2 family of proteins and acts as an anti-apoptotic protein by inhibiting the release of cytochrome c. A higher expression of Bcl-x is associated with high-grade PCa tumors along with both lymph node and distant metastasis [94,95]. Sirtuin 4 (SIRT4) is a mitochondrial matrix protein and has been shown to halt cell proliferation by inhibiting glutamine metabolism in response to DNA damage [96]. A recent study has shown that SIRT4 is degraded via ubiquitination, promoted by the action of p21-activated kinase 6 (PAK6) [97]. Interestingly, the expression of PAK6 is known to be elevated in PCa [98,99], suggesting its important role in the promotion of the cell survival of PCa cells. Trefoil factor 3 (TFF3), a secretory product of mucin-producing cells, is overexpressed in PCa, and promotes cell survival by inhibiting mitochondria-dependent apoptosis [100,101]. The high growth rate of cancer cells creates a higher requirement for energy metabolism and cellular building blocks. Cancer cells use various strategies to obtain and utilize nutrients for their survival, growth, and metastasis. PCa development and progression are impacted by rewiring of the mitochondrial metabolism and mitochondrial adaptation. mtDNA mutations in PCa resulted in OXPHOS remodeling and increased succinate oxidation [23]. Cancer cells are known to modulate mitochondrial function in the surrounding stromal cells for the supply of high-energy metabolites. PCa cells alter the mitochondrial metabolism in stromal cancer-associated fibroblast (CAF) cells and create a nanotube to transfer mitochondria from CAF cells to cancer cells [39]. Cancer cells use mitochondrial metabolites and signaling pathways to remodulate their stromal composition and metabolism, which provides a positive microenvironment for tumor growth. Damage-associated molecular patterns (DAMPs) are a large number of chemically unrelated molecules that are retained in normal living cells and during cell death or stress and are released, causing a strong induction of sterile inflammation [102]. Immune cells possess specific DAMP receptors that allow them to sense and react to damage [103]. Research has shown DAMPs could play a crucial role in cancer development and in the host response to cancer therapy. The release of DAMPs from dying cancer could activate the protective function of immune cells, triggering the immunogenic death of the cancer cells. On the other hand, DAMPs could induce chronic inflammation in the tumor microenvironment (TME) and may cause the development and promotion of cancer [104,105]. Typically, DAMPs include extracellular DNA, high-mobility group box-1 (HMGB-1) [106], heat-shock proteins [107], ATP [108], and S100 proteins [108]. S100 proteins act as Ca2+ sensors inside the cells; however, they are secreted extracellularly under stress conditions, can influence a variety of biological processes, and have been reported to be dysregulated in PCa cells [109,110,111]. Mitochondrial DAMPs include mtDNA, ATP released from damaged mitochondrial, N-formyl peptides, succinate, cardiolipin, and cytochrome c [112]. Elevated levels of circulating mtDNA have been found in various cancer types, including PCa [113,114,115,116,117]. mtDNA can be recognized by pattern recognition receptors such as TLR9, type I interferon response, and cytosolic inflammasomes of the innate immune system, and this interaction initiates a proinflammatory response [112]. The activation of TLR9 signaling has been shown to promote the growth of PCa cells and correlate with poor prognosis [118,119]. The HMGB1-TLR4/RAGE axis promotes chemoresistance to docetaxel in prostate tumor cells [106]. DAMP-induced inflammation plays a crucial role in recruiting immune cells in the TME and creating a cancer-promoting immunological niche. Taken together, the decreased mitophagy and increased rupture of mitochondria may enable the release of mitochondrial DNA (or mitochondrial proteins) that serve as DAMPs and promote ROS production, which may act as DAMP modifiers to promote cancer. The accumulation of metabolites due to debilitated anabolic and catabolic processes is a characteristic of mitochondrial alteration. mtDNA mutations and defects in nuclear-encoded mitochondrial enzymes can result in a deregulated mitochondrial metabolism. The accumulated mitochondrial metabolites could serve as cancer-promoting factors by providing growth advantages. These metabolites are referred to as oncometabolites. The mitochondrial metabolites that are well established as oncometabolites are succinate, 2-hydroxyglutarate, and fumarate. A high amount of these metabolites is produced as a result of oncogenic mutations in succinate dehydrogenase, isocitrate dehydrogenase (IDH), and fumarate hydratase enzymes [120]. Mitochondria also exert a robust impact on chromatin structure via the overproduction of oncometabolite 2-hydroxyglutarate, which induces DNA hypermethylation and causes wide-ranging epigenetic changes to support cancer progression [58,121]. The production of oncometabolite 2-hydroxyglutarate is linked with alterations in the gene expression of TCA-cycle enzymes and is known to inhibit the enzymatic activity of ATP synthase and cytochrome-c oxidase [122]. Alterations in IDH lead to the accumulation of its metabolic byproduct, 2-hydroxyglutarate, and have been reported to promote cell invasion in PCa with a negative or low expression of AR [114]. These findings show that isocitrate dehydrogenase mutations in cancer cells result in the accumulation of 2-hydroxyglutarate, which contributes to the energy metabolism changes contributing to the cancer progression. A decrease in TCA-cycle enzyme fumarate hydrates resulted in an increase in transcription factors Nrf1 and Nrf2 [123]. The transcriptional or mutagenic activation of Nrf2 can contribute to tumorigenesis by managing the high ROS produced in PCa cells [62]. In conclusion, the abundance of oncometabolites created by mutation activation or the oncogene-induced activation of mitochondrial metabolic enzymes can lead to mitochondria dysfunction, ROS production, epigenetic modification, increased EMT, and cancer progression. Early studies exploring the connections between PCa and mitochondria identified mutations in MT-CO1 as a risk factor for PCa development. In addition, mitochondrial alterations also show a distinct association with different ethnic groups in the context of PCa [124]. The AA population tends to harbor polymorphism in CO1 lineages and therefore carries a risk for the development of PCa [32]. However, mutations in MT-CO1 have also been found to correlate with PCa in CA men [125]. Although both somatic and germline mutations in MT-CO-1 depict a predisposition for PCa, the latter poses a considerably higher risk. In a study by Petros et al., mitochondrial cytochrome oxidase subunit I (COMI) germline mutation was reported as an important risk factor for PCadevelopment in African American patients. In the same cohort study, some patients also contained a germline ATP6 mutation [32]. PC cell lines harboring mutations in a T8993G mutation in MT-ATP6 show enhanced growth and proliferation. A study showed enhanced mitochondrial biogenesis and OXPHOS in AA tumors compared to those from European American (EA) patients [126]. AA tumors also had a higher number of mitochondria than their EA counterparts. Overall changes in mtDNA content have also been observed in AA PCa patients. AA tumors also had a higher number of mitochondria than their EA counterparts. A study conducted on AA patients with PCa reported an enhanced mtDNA in the leukocytes, which correlated with an aggressive form of the disease and poor prognosis [127]. Interestingly, normal prostate tissues of AA men also display low mtDNA content compared to CA men, which suggests a potential predisposition towards PCa development [13]. G10398A mutation in MT-ND3 has been linked with an increased risk for PCa [25]. Furthermore, the cells with this type of mutation displayed an enhanced Complex I activity. Although mutations in MT-ND-3 and MT-ATP6 show a racial disparity between AA and CA populations, they do not show any association with the development of PCa in Mexican–Mestizo men, suggesting that factors specific to AA population may be involved in the increased PCa risk in AA men [128]. In a very recent study, researchers identified a significant racial disparity in the expression of pi class glutathione S transferase (GSTP1), a cellular detoxifying enzyme [129]. This enzyme is highly expressed in basal epithelial cells, while it is epigenetically silenced via hypermethylation in many PCa cases and is considered to be an early event in PCa carcinogenesis. However, this may suggest a possibility of the presence of a distinct molecular subtype of PCa and thus requires further investigations. High expression of GSTP-1 in breast cancer has been reported to result in chemoresistance [129,130,131] and thus high expression of GSTP1 in Black men with PCa may predict a poor response to chemotherapy. An earlier study identified that PCa tumors from AA men show a high expression of zinc transporters hZIP1 and hZIP2 compared to white men, while it is low in normal prostate [132]. The reduction in zinc levels as a result of a lack of zinc transporters relieves the inhibition of mitochondrial aconitase. This modulates the metabolism of PCa cells towards enhanced citrate oxidation, which fuels their growth [133]. Mitochondria also produce small mitochondrial peptides (MDPs) such as small humanin-like peptide-2 (SHLP2), mitochondrial open reading frames (ORF) of the 12S rRNA type-c (MOTS-c), and humanin through small ORFs [134], which are required for normal mitochondrial function. The overall reduction in the levels of these MDPs is shown to increase the risk for PCa development [135]. While CA patients show reduced plasma levels in MDPs, AA patients had an even lower concentration of these, which suggests that AA men are more susceptible to a high risk of PCa [136]. Mitochondrial gene alterations and their association with racial disparity in PCa are depicted in (Table 1). mtDNA is maternally inherited and does not undergo recombination like nuclear DNA. This often results in the accumulation of characteristic mtDNA SNVs within a population, which show variations in their metabolic profiles accordingly. These subpopulations are termed haplogroups and can be a factor in displaying a predisposition towards the development of various pathologies, including PCa [141,143]. mtDNA haplogroup U and its signature A12308G point mutation in tRNALeu2 are associated with a higher incidence of PCa. Thus, people with haplotype U are at a higher risk predisposed, and this haplotype could serve as a prognostic marker for predicting predisposition towards the development of PCa [144]. Furthermore, the analysis of mtDNA content could itself serve as a prognostic marker, as its alteration has been reported by several groups to be associated with various cancers, including PCa [20,21,145,146,147]. High levels of cytochrome c levels in serum from various cancers, including PCa, have been reported and correlated with an advanced and aggressive form of the disease and suggest its significance as a prognostic marker [125]. Although mutations in respiratory complex genes have been reported in a wide variety of cancers, no particular mutation type has been shown to predict the risk for the development of the disease. However, several studies have reported frequent mutations in MT-ND5, MT-ND4, MT-CO2, ATP6, and D-loop in PCa patients [29,148,149,150]. The categorization of mutations in these regions in patients may be an effective way to predict the risk for PCa development. Unlike normal cells, the reprogramming of metabolism is a key cellular process in cancer cells that is responsible for energy production and the synthesis of new molecules to sustain their potential for indefinite growth and proliferation. Emerging evidence suggests that tumor cells show a dependency on mitochondrial metabolism for their various oncogenic properties, such as proliferation, stemness, and chemoresistance [151,152]. Within the same TME, considering tumor heterogeneity, some cells could have a higher glycolytic rate, and others might have a higher mitochondrial respiration. Castration-resistant PCa cells are known for their dependence on OXPHOS for their energy requirements, and as such, respiratory complex inhibitors show excellent potential for the treatment of PCa. Targeting OXPHOS in PCa has been reported to block autophagy and render them sensitive to chemotherapeutic drugs [73,122]. In a normal prostate cell, the metabolic pathways are uniquely regulated to maintain the secretion of prostatic fluid, a primary function of the prostate gland. AR signaling favors the accumulation of zinc in prostate acinar cells, which inactivates the m-aconitase enzyme of the TCA cycle and leads to the synthesis of a large amount of citrate, which is the main component of prostatic fluid and is required for the healthy function of the prostate gland [153,154]. In prostate adenocarcinoma, zinc accumulation is inhibited due to downregulated zinc transporters; therefore, citrate undergoes oxidation through the TCA cycle and produces anabolic substrates required to promote the growth and proliferation of cancer cells [153,155]. The tumor-suppressive role of zinc transporters was confirmed, and it was shown that the overexpression of zinc transporters in PCa cells inhibited NF-κB activity, thereby reducing their tumorigenic potential [156]. Overall, it seems that citrate oxidation is necessary but not sufficient to transform prostate epithelial cells into prostate adenocarcinoma. For a malignant transformation of PCa, the interaction of cancer cells with other cells in the TME is also essential to provide metabolic substrates (e.g., lactate) to cancer cells, which can be used in anabolic pathways as energy support [157,158]. Further, lactate secreted from CAF cells has been shown to regulate the expression of several genes involved in lipid metabolism, which leads to the accumulation of lipid droplets and affects epigenetic modifications in PCa cells [159]. Indeed, the metabolic phenotype of PCa is primarily lipogenic, unlike other solid tumors, and greatly dependent on OXPHOS [160,161,162]. Aberrant AR signaling has been central to regulating metabolic transformation and anabolic processes to fuel the proliferation and growth of PCa cells [163,164]. More specifically, the AR regulates the expression of several genes involved in key regulatory steps of glucose metabolism, fatty acid synthesis, nucleotides, amino acid metabolism, and polyamine biosynthesis [68]. Therefore, the AR antagonism strategy has been highly efficient, as it can also affect the associated metabolic network; however, in the case of androgen-resistant PCa, androgen-independent AR activation takes place to bypass the AR requirement and become a more aggressive AR-indifferent carcinoma [165]. More recently, it has been shown that the inhibition of AR induces distinct metabolic reprogramming rather than suppressing these metabolic alterations [68,166]. Understanding these distinct metabolic features and their connection with AR signaling could lead to the identification of various metabolic vulnerabilities that can be exploited to devise new anti-PCa therapies. Mitochondria undergo continuous fusion and fission to maintain mitochondrial health and function to meet various cellular demands. In many cancers, the aberrant expression of genes regulating mitochondrial dynamics machinery has been reported, and dysregulated fusion–fission has been linked with cancer progression, chemoresistance, and metastasis [167,168]. Androgen signaling enhances DRP1 expression to promote mitochondrial metabolism, including oxidative phosphorylation and lipogenesis. Targeting DRP1 induced a metabolic stress response and autophagy and reduced the AR-mediated growth of PCa [69]. Recently, Civenni et al. have shown that the silencing of BRD4, a chromatin reader protein, inhibits mitochondrial fission and blocks the self-renewal of PCa stem cells, which leads to the loss of tumorigenic capability [89]. Moreover, a mitochondrial Rho GTPase 2 (MIRO2) involved in mitochondrial localization and dynamics has been found to be overexpressed in metastatic PCa compared to localized tumors. The inhibition of MIRO2 markedly suppressed colony formation and tumor growth in vivo and can be exploited as a therapeutic target [169]. The improved mitochondrial dynamics in PCa cells could promote mitochondrial trafficking and increase tumor cell migration and invasion [170]. Mitofusin-1 (MFN1) and mitofusin-2 (MFN2) were reported to be upregulated in PCa patients, as well in PCa cell lines, while MFN2 was also detected in the circulating exosomes of patients with benign and progressive PCa [30]. This observation provides a potential use for MFN2 as both a prognostic and a therapeutic marker. These findings present a strong rationale to target mitochondrial dynamics as a therapeutic treatment to combat cancer progression. The transport of proteins, metabolites, solutes, ions, and other soluble factors across the outer and inner membranes is crucial for mitochondrial integrity and proper function. Both the outer and inner mitochondrial membranes encompass specialized translocases or transporters for this vital process. The outer membrane encompasses translocases of outer membrane (TOM or TOM40) complexes and TOM/SAM complexes and the voltage-dependent anion channel (VDAC), whereas translocases of inner membrane (TIM) 23 and TIM22 complexes and mitochondrial carrier family (MCF) or solute carrier family (SLC) proteins are present at the inner mitochondrial membrane [171,172]. The expression of these transporters is essential for mitochondrial metabolism and might be implicated in the growth and proliferation of cancer cells. The role of outer membrane transporters is critical, as these proteins provide the entry point for the translocation of several proteins, and the dysregulation of TOM complexes has been linked to cancer progression. An analysis of multigene signatures identified TOM40 to be altered in PCa patients [173]. Its expression is also upregulated in androgen-independent PCa cell lines and leads to an increase in growth and survival [69,174]. The VDAC is also an important target for cancer therapy due to its role in the transport of glycolytic proteins, protection against apoptosis, and calcium homeostasis [175]. Downregulating the expression of the VDAC in PCa cell lines causes a reduction in their proliferation and tumor growth [176]. The VDAC is also reported to form a complex with mitochondrial fission factor (MFF) in PCa and is important for the maintenance of mitochondrial integrity and function. Hence, this complex can be exploited as a therapeutic option in PCa [88]. PCa cells fuel their OXPHOS via the increased absorption of succinate via the plasma membrane Na+-dependent dicarboxylic acid transporter NaDC3 (SLC13A3 gene). Since this protein is not produced in normal prostate cells, targeting NaDC3 could be a specific and effective target for PCa treatment [177]. Another type of solute carrier family, SLC25 transporters, is the largest family of solute carriers and is involved in the transport of amino acids, cofactors, nucleotides, inorganic ions, protons, fatty acids, and various metabolites associated with the TCA cycle and glycolysis pathways [178]. A bioinformatics analysis of mitochondrial genes using public datasets suggested the differential mRNA expression of SLC25 family members in PCa cell lines [179]. Although these observations require further in-depth studies, SLC25 family members have been implicated in other cancers [180,181] and could turn out to be a potentially effective therapeutic avenue for PCa (Figure 3). PCa has a complex pathobiology and is influenced by a variety of factors, such as genetic and epigenetic alterations, environmental factors, and is responsible for the development of the disease. Mitochondria is a very important organelle central to fulfilling the metabolic and energetic demands of the cells, and cancer cells often benefit from their various alterations at every step of tumor development. Since PCa is characterized by heterogeneity in metabolic preferences, the identification and establishment of key mitochondrial alterations associated with PCa could provide us with an excellent noninvasive diagnostic and prognostic strategy for the assessment of normal prostate health and not just tumor malignancy. In addition, the SNVs and mutations of mtDNA may provide us with information about the racial disparity of PCa and could be helpful in devising a precision medicine approach for its treatment. This review summarizes how the various mitochondrial alterations contribute to PCa racial disparity and should direct future studies towards the development of targeted therapeutic strategies that could help in diminishing the racial disparity in clinical outcomes.

PMC10003185

Yu Mori,Kazuko Ueno,Daisuke Chiba,Ko Hashimoto,Yosuke Kawai,Kazuyoshi Baba,Hidetatsu Tanaka,Takashi Aki,Masanori Ogasawara,Naoto Shibasaki,Katsushi Tokunaga,Toshimi Aizawa,Masao Nagasaki

Genome-Wide Association Study and Transcriptome of Japanese Patients with Developmental Dysplasia of the Hip Demonstrates an Association with the Ferroptosis Signaling Pathway

06-03-2023

cartilage,developmental dysplasia of the hip,ferroptosis signaling pathway,genome-wide association study,Japonica array,psychiatric disorders,UK Biobank

This study examined the association between developmental dysplasia of the hip (DDH) and disease-associated loci in a Japanese cohort. A genome-wide association study (GWAS) of 238 Japanese patients with DDH and 2044 healthy individuals was performed. As a replicate, GWAS was also conducted on the UK Biobank data with 3315 cases and matched 74,038 controls. Gene set enrichment analyses (GSEAs) of both the genetics and transcriptome of DDH were performed. Transcriptome analysis of cartilage specimens from DDH-associated osteoarthritis and femoral neck fractures was performed as a control. Most of the lead variants were very low-frequency ones in the UK, and variants in the Japanese GWAS could not be replicated with the UK GWAS. We assigned DDH-related candidate variants to 42 and 81 genes from the Japanese and UK GWASs, respectively, using functional mapping and annotation. GSEA of gene ontology, disease ontology, and canonical pathways identified the most enriched pathway to be the ferroptosis signaling pathway, both in the Japanese gene set as well as the Japanese and UK merged set. Transcriptome GSEA also identified significant downregulation of genes in the ferroptosis signaling pathway. Thus, the ferroptosis signaling pathway may be associated with the pathogenic mechanism of DDH.

Genome-Wide Association Study and Transcriptome of Japanese Patients with Developmental Dysplasia of the Hip Demonstrates an Association with the Ferroptosis Signaling Pathway This study examined the association between developmental dysplasia of the hip (DDH) and disease-associated loci in a Japanese cohort. A genome-wide association study (GWAS) of 238 Japanese patients with DDH and 2044 healthy individuals was performed. As a replicate, GWAS was also conducted on the UK Biobank data with 3315 cases and matched 74,038 controls. Gene set enrichment analyses (GSEAs) of both the genetics and transcriptome of DDH were performed. Transcriptome analysis of cartilage specimens from DDH-associated osteoarthritis and femoral neck fractures was performed as a control. Most of the lead variants were very low-frequency ones in the UK, and variants in the Japanese GWAS could not be replicated with the UK GWAS. We assigned DDH-related candidate variants to 42 and 81 genes from the Japanese and UK GWASs, respectively, using functional mapping and annotation. GSEA of gene ontology, disease ontology, and canonical pathways identified the most enriched pathway to be the ferroptosis signaling pathway, both in the Japanese gene set as well as the Japanese and UK merged set. Transcriptome GSEA also identified significant downregulation of genes in the ferroptosis signaling pathway. Thus, the ferroptosis signaling pathway may be associated with the pathogenic mechanism of DDH. Osteoarthritis (OA) of the hip causes pain and disability in elderly individuals. Developmental dysplasia of the hip (DDH) is one of the most important causes of OA [1,2,3,4]. The mean incidence of DDH varies widely according to ethnic background, with rates of 0.06, 76.1, and 3.6 per 1000 live births in Black African, Native American, and British populations, respectively [5]. However, epidemiological studies of radiographic imaging of DDH in the Japanese population show that the rate of radiological DDH (center–edge angle less than 25° [6]), including asymptomatic DDH, is 16% and 19% [7], and 5.1% and 11.6% in men and women, respectively [8]. In particular, the incidence of DDH has been reported to be higher in the Japanese population than in other ethnic groups. DDH is a complex disorder with known associations with the female sex, first birth, breech birth, and family history [9]. There is no causative therapy for DDH, and hip replacement is performed when the joint destruction progresses. The reported benefits of hip arthroplasty in easing pain and improving function are widespread [10,11]. However, there is a need for revision surgery due to loosening, and although efforts have been made to prevent stress shielding with low-modulus titanium alloys [12], there is room for improvement. DDH is heritable; however, its genetic association has not yet been fully elucidated. There have been reports of genetic polymorphisms in the OA-related genes growth differential factor 5 (GDF5) [13,14], calmodulin 1 (CALM1) [15,16], and asporin [17]. In contrast, there have been several reports on DDH-related genes. Several linkage scans and candidate gene studies have suggested the possibility of related genetic variants, including GDF5 [9,18,19,20]; however, to date, only a few studies have identified a genome-wide significant locus [21,22,23]. The C-X3-C motif chemokine receptor 1 (CX3CR1) gene has also been associated with DDH, and abnormal hip morphology has been reported in mice deficient in this gene [24,25,26]. A genome-wide association study (GWAS) in the Han Chinese population suggested an association between mutations in the ubiquinol–cytochrome C reductase complex assembly factor (UQCC)—a gene adjacent to GDF5 [27]. However, no DDH-sensitive gene has been reported in the Japanese population, which experiences a high prevalence of this disease. The GWAS tests millions of gene variants across the genomes of many individuals to identify genotype–phenotype associations. Since the first GWAS for age-related macular degeneration was published in 2005, a number of reports have been published [28,29]. The Tohoku Medical Megabank Organization constructed a reference panel containing over 20 million single nucleotide polymorphisms (SNPs) from the whole-genome sequence data of 1070 Japanese general individuals [30]. A new custom-made genotyping SNP array with approximately 659,253 SNPs, named Japonica array v1, which was optimized to impute the non-observed variants from the genotyping SNPs, especially for Japanese individuals, was applied [31]. The Japonica array v1 has GWAS experience for risk gene exploration in glaucoma [32], osteoporosis among patients with inflammatory bowel disease [33], and primary biliary cholangitis [34] in Japanese patients. Based on this evidence, we considered it reasonable to analyze risk factors for DDH using Japonica array v1, which is the most appropriate GWAS for the Japanese population. The purpose of this study was to examine the association between DDH and disease-associated loci in a Japanese population and to assess the genotype–phenotype relationships between risk variants and clinical features of the disease. The characteristics of 238 Japanese patients with DDH are shown in Table 1. Of the 238 patients, 206 (86.5%) were female. The mean age at the time of genomic DNA collection was 60.0 ± 15.0 years, and 94 patients (39.4%) had a family history of DDH. A history of orthotic or casting treatment for DDH during childhood was detected in 110 cases (46.2%), and surgical treatment for DDH was performed in 161 cases (67.6%). Seventy-two (30.0%) patients underwent hip replacement surgery. Transcriptome analysis of chondrocytes was performed in 12 cases of DDH-related OA and 8 cases of femoral neck fracture; 11 out of the 12 patients with DDH-related OA were female, and the mean age at the time of surgery was 64 ± 7 years. Seven of the eight patients with femoral neck fractures (control) were women, and the mean age at the time of surgery was 80 ± 7 years. Qualitative real-time polymerase chain reaction (RT-PCR) was performed in 14 cases of DDH-related OA and 14 cases of femoral neck fracture; 13 of the 14 patients with DDH-related OA were female, and the mean age at the time of surgery was 69 ± 5 years. In addition, 11 of the 14 patients with femoral neck fractures (control) were women, and the mean age at the surgery was 80 ± 13 years. After quality control (QC; Table 2) of the genotyping results of 238 DDH samples and 2044 samples from the general population in Japan, the whole-genome genotype imputation process was applied using the phased reference panel of Phase 1 version 3 of the 1000 G containing 1092 individuals [35]. For the imputed genotyping results, a GWAS was conducted (referred to as the “Japanese GWAS”). Four directly genotyped SNPs in different locations reached the genome-wide significance level (p < 5 × 108): rs11802858 (chr1:4682515:T:C; 1.98 × 10−11); rs2554380 (chr15:84315884:C:T; 1.04 × 10−16); rs79657649 (chr17:505105:T:C; 1.19 × 10−18); and rs17699467 (chr17:11359275:A:G; 9.82 × 10−11) (Table 2a, Figure 1a). The genotyping concordance rates of all four direct genotyping SNPs were high (>0.98) between the genotyping results of the SNP array and the whole-genome sequence data for the shared 190-sample set (Table S1). Notably, there were no SNPs with high linkage disequilibrium (LD) (r2 > 0.2) with rs79657649 around this SNP. rs2554380 is positioned in the promoter region of ADAMTSL3 and is related to many phenotypes in a phenome-wide association study (PheWAS), such as standing height and impedance of the leg (Table S1). rs79657649 is located in the coding region of VPS53, and the minor allele of this SNP causes a missense mutation (Asn > Ser). rs17699467 is present in the intronic region of SHISA6. After genotype imputation, no additional variants reached the significance level of the former four regions, while three additional loci reached the genome-wide significance level (p-value < 5.0 × 10−8; Table 2); the three lead variants in each locus were rs11802858 (chr1:4682515:T:C; 1.98 × 10−11) in the upstream (around 32 kb) from the transcription start site (TSS) of AJAP1, rs149003127 (chr2:79236134:G:T; 1.82 × 10−8) in the upstream (around 16 kb) from the TSS site of REG3G, rs55669018 (chr11:132871263:T:A; 4.09 × 10−8) in the intronic region of OPCML, and rs77485026 (chr16:8846734:T:C; 1.34 × 10−8) in the intronic region of ABAT (Figure 1a). To conduct the replication study as an independent cohort study, part of the participants in the UK Biobank with White British genetics were used. In this study, 3315 samples assigned to at least one category (M161, M162, and M163 in ICD10) were selected as DDH patients, and 74,038 healthy individuals were selected as controls. The minor allele frequencies (MAFs) of rs79657649 and rs11802858 were lower than 0.01 in the UK population (0.001618/6 [MAF/allele count] and 0.000809/3, respectively, in TwinsUK [36]) and could not be included as replication targets. For the remaining two SNPs, the genotyping information of rs2554380 and rs17699467 (0.22411/831 and 0.141046/523 in TwinsUK, respectively) was reported in the imputed genotyping result in the UK Biobank and the nominal p-values were 0.63 and 0.098, respectively. For rs17699467, in a PheWAS of the Finnish population, a phenotype “disease of the musculoskeletal system and connective tissue” reached the phenome-wide significance level in the data freeze 5 (https://r5.finngen.fi/ (accessed on 1 August 2022.); Bonferroni p-value threshold = 1.78 × 10−5 [0.05/2803]; p = 9.4 × 10−6; Figure S1). The MAFs of rs149003127 and rs77485026, which reached the genome-wide significance level in the Japanese GWAS after imputation, were lower than 0.01 in the UK population and could not be included as replication targets. Another SNP, rs55669018, which also reached the genome-wide significance level in the Japanese GWAS after imputation, had a nominal p-value of 0.81 and could not be replicated in the UK dataset. For the downstream analysis, a GWAS was conducted (UK GWAS) on the UK dataset with case and control, and one locus reached the genome-wide significance level (p = 3.84 × 10−8) (Table 2b and Figure 1b). In previous DDH studies [9,18,19,20,21,22,23,24,25,26,27], a very limited number of shared genetic variants was detected among different studies. In our study, most of the discovered candidate variants could not be directly replicated because of the different allele frequencies or LD between the Japanese and White British populations. Thus, we attempted to interpret the DDH disease-related factors from the categories of variant-related genes. For gene-based enrichment analysis, we extracted suggestive SNPs (p-value < 1 × 10−5) for downstream analysis. Using functional mapping and annotation (FUMA), 42 and 96 genes were assigned to the Japanese GWAS and UK GWAS, respectively (Tables S2 and S3). There were no shared genes between the two cohort studies. Using each gene set, we performed three functional enrichment analyses using FUMA2FUNC, ingenuity pathway analysis (IPA), and ToppGene (https://toppgene.cchmc.org/enrichment.jsp (accessed on 1 August 2022) [37]). For both cohorts, no significant pathway enrichment (adj. p < 0.05) was observed in the FUMA2FUNC analysis. In the IPA, no significant category was enriched in the UK gene set; however, one significantly enriched category was found in the Japanese gene set (Table 3a). Pathway gene sets were considered significantly enriched when the Benjamini–Hochberg (BH) false discovery rate (FDR) was <0.1, and there were at least three overlapping genes between the gene set and the study gene list. The enriched category was the ferroptosis signaling pathway (p-value = 0.0015; BH FDR 0.065), with three DDH-related genes: cathepsin B (CTSB; chr8:11,698,033-11,727,596), farnesyl-diphosphate farnesyltransferase 1 (FDFT1; chr8:11,651,082-11,698,818), and GTP cyclohydrolase-1 (GCH1; chr14:55,306,723-55,371,542). Ferroptosis is a type of programmed cell death, which was predicted to be related to OA in a previous study [38]. In the ToppGene disease analysis, no category was significantly enriched in the Japanese gene set. Pathway gene sets were considered enriched when the Bonferroni p-value was < 0.01, and there were at least three overlapping genes between the gene sets. However, two categories were significantly enriched in the UK GWAS (Table 3b). The top hit was OA, including four DDH GWAS-related genes on different chromosomes: ITIH1 (chr3:52,809,615-52,828,078), ASTN2 (chr9:119,183,391-120,179,335), LTBP3 (chr11:65,304,030-65,327,699), and IL11 (chr19:55,873,750-55,883,831). The second most common hit was bipolar disorder. An epidemiological study was conducted on 74,393 patients with psychiatric disorders to assess the association between psychiatric disorders and OA. The study reported that affective psychoses, neurotic illnesses, personality disorders, and other mental disorders are risk factors for OA [39]. Thus, there might be genetic risk factors, such as ITIH1, between the top-hit OA and the second-hit mental disorder. To interpret the shared DDH disease factors among the two studies with different genetic backgrounds, the 42 and 81 Japanese and UK GWAS genes were merged into 123 genes and re-analyzed using the same tools, FUMA2FUNC, IPA, and ToppGene. In the FUMA2FUNC analysis, there were two significant categories (the condition is the same as the definition in 2.3), cytoskeleton organization (Gene Ontology [GO]: 0007010) and cell signaling (GO: 0007267) (Table 3c). The GO category cytoskeleton organization contained seven genes from the Japanese GWAS and nine genes from the UK GWAS. Notably, three dynein axonemal heavy chain (DNAH) family members in different chromosomes were enriched in DDH: DNAH1 (chr3:52,348,335-52,436,508); DNAH7 (chr2:196,600,427-196,935,561); and DNAH8 (chr6:38,681,087-39,000,568). DNAH1 was a candidate gene in the UK GWAS, and DNAH7 and DNAH8 were candidate genes in the Japanese GWAS. In the IPA, the ferroptosis signaling pathway was found to be the top p-value pathway by adding a novel gene from the UK GWAS, BRCA1 associated protein 1 (BAP1; chr3:52,433,024-52,446,024) (Table 3d). In ToppGene disease analysis, OA was still the top p-value pathway (Table 3e). However, none of the DDH risk genes in the Japanese population were categorized as OA. In contrast, bipolar disorder, which was significant in the UK GWAS dataset, was also significantly present in the merged set by adding two novel genes from the Japanese GWAS: DNAH8 (chr6:38,681,087-39,000,568) and IMPA1 (chr8:82,567,151-82,600,589). This result further suggests a potential general risk association between mental illness and DDH. In all, 1079 and 822 genes were significantly expressed in DDH-related OA patients (DDH patients) compared to that in the control samples. Related pathways were predicted for each gene set using the IPA. The GP6 signaling pathway was at the top of the former gene set (p = 3.98 × 10−17), and the ferroptosis signaling pathway was at the top of the latter gene set (p = 1.67 × 10−7). As predicted by the Japanese GWAS, the ferroptosis signaling pathway was independently predicted by transcriptome analysis from the Japanese dataset. Seventeen genes have been identified in this pathway. We analyzed the shared genes categorized in this pathway from both the genomic and transcriptomic perspectives (Figure 2). GCH1 is a disease susceptibility gene in the Japanese GWAS and was expressed significantly less in DDH samples than in healthy individuals (Figure 3). This indicates that a lower gene expression level than that in the control group is possibly associated with the disease. The results of qualitative RT-PCR for the expression of GCH1 are shown in Figure 4. GCH1 expression in the DDH-related OA group had significantly decreased compared to the non-OA group. RT-PCR analysis was performed using chondrocyte-derived RNA from different cases from the transcriptome analysis; RT-PCR results were able to reproduce the results of the transcriptome analysis. In the present study, a GWAS of 238 Japanese patients with DDH and 2044 patients from the general population was performed. Several significant SNPs were found, none of which had been previously reported; thus, the authors referred to the UK Biobank data. As there were few significant SNPs, we extracted suggestive SNPs with p < 1e-05. We then assigned genes to those SNPs: 81 genes from the GWAS of the UK Biobank dataset and 42 genes from the GWAS of the Japanese patients using FUMA. No similarities were observed between the two gene sets. Ontology analysis of each gene set using FUMA and IPA revealed no significant pathways in the UK Biobank gene set; however, significant pathways were identified as culminating in the ferroptosis signaling pathway in the gene set of the Japanese patients. This pathway is associated with OA [40,41,42]. It has also been reported that the ferroptosis signaling pathway is present in the chondrocytes of OA patients [43]. However, no studies have demonstrated that OA progresses due to the inhibition of ferroptosis signaling using clinical specimens from patients with OA. The current study is the first to report an association between the ferroptosis signaling pathway and DDH. In a comparative analysis of chondrocyte transcriptomes of patients who underwent arthroplasty for secondary hip OA after DDH and those with femoral fractures without articular cartilage degeneration, the expression of GCH1, CTSB, and FDFT1, which are factors in the ferroptosis signaling pathway, was lower in the hip OA group than in the control group. GCH1 has been reported to be associated with ferroptosis in esophageal and colorectal cancers [44,45]. CTSB and FDFT1 are associated with ferroptosis in pancreatic and kidney cancer, respectively [46,47]. Transcriptome analysis of OA chondrocytes showed that GCH1, a component of this pathway, was significantly downregulated. In a future study, we will identify the genes involved in this pathway using IPA and confirm the expression variation of these genes. The importance of genes involved in the ferroptosis signaling pathway in OA is not clear, but there may be differences between OA and DDH-related genes such as GCH1, CTSB, and FDFT1. As the OA cases analyzed in this study were DDH-related, transcriptome analysis of chondrocytes confirmed that the variation in ferroptosis signaling in these cells was significant. It was also interesting to note that the results of GWAS and chondrocyte transcriptome analysis showed a consistent trend. The GDF5-UQCC1 region is frequently reported as the related region to DDH. In this region, our Japanese GWAS had a consistent feature to previous DDH studies [21,27,48]. In a Chinese population study [48], rs143384 was reported as the significant lead variant. In our Japanese population GWAS, the rs143384 had the p-value 0.0029 with the same direction OR 1.50. In our GDF5-UQCC1 region, the lead p-value SNP was rs34414056 (OR = 2.06, p-value = 0.000554). This SNP is located in the intronic region in GDF5 (Figure S2). For the rs34414056, a Japanese eQTL database ImmuNexUT reported UQCC1, and a European eQTL GTEx V8 database reported both GDF5 and UQCC1. Notably, the GWAS Catalog (date of search: February 2023) registered rs34414056 as a trait susceptibility SNP such as the waist–hip index. Disease ontology analysis of the UK GWAS gene sets of DDH enriched the gene sets of bipolar disorder. This feature was also observed in the merged gene set, including the additional genes IMPA1 and DNAH8 from the Japanese GWAS. Patients with the hip disease exhibit significant pain, anxiety, and depression [49,50]. While we considered the possibility of psychiatric abnormalities secondary to hip pain, it is also possible that OA and DDH might be associated with psychiatric disorders. This study is the first to report the possibility of an association between DDH and psychiatric disorders using a genetic analysis approach. A report described a case of neurodevelopmental disorder resulting from an abnormality in Golgi-associated retrograde protein (GARP), of which VPS53 is a component, and was described to be associated with hip dislocation [51]. Abnormalities in GARP may cause neurodevelopmental disorders and hip dislocations. This case report supports our findings, suggesting a link between DDH and mental and neurological disorders. Although further research is needed to confirm the association between DDH and psychiatric disorders, this study may elucidate the pathogenesis of intractable hip diseases. This study had several limitations. First, the DDH cases used in the analysis were from a single institution and examined patients from a localized area in Japan (the northeastern region of Japan), and the number of cases was small. Future large-scale studies should include cases from other regions in Japan. Second, transcriptome analysis was performed on a small, limited number of cases because cartilage samples were collected from postoperative specimens, and future studies should examine larger numbers of DDH and femoral neck fracture cases and compare them with healthy cartilages. In conclusion, using GWAS, a comparison of results from patients with DDH and those from healthy controls showed that the ferroptosis signaling pathway was associated with the disease, although no unique disease susceptibility genes were identified in Japanese patients with DDH. Transcriptome analysis of chondrocytes showed that the genes involved in the ferroptosis signaling pathway were expressed in these cells, and their expression was downregulated in the DDH-related OA group compared with that in the control group. Studies on the association between ferroptosis signaling and DDH may contribute to the search for disease susceptibility genes for DDH and to the elucidation of novel mechanisms to prevent cartilage damage. The present study included 238 Japanese patients with DDH. All patients were treated at our facility and diagnosed as having DDH using radiographic images, and the history of treatment was confirmed using medical records. The inclusion criteria were hip pain and radiographic findings with a center–edge angle of less than 20°. Control data for 2044 individuals from the general Japanese population in the same region were also obtained. Written informed consent was obtained from all the participants. The study was approved by the Committee on Research Ethics of Tohoku University Graduate School of Medicine (2017-1-296), Tohoku Medical Megabank Organization (2017-0010), Kyoto University (G1208, G1216), and the National Center for Global Health and Medicine (NCGM-A-003267). All methods were performed in accordance with the institutional ethical guidelines and regulations. Human articular cartilage samples were obtained from the femoral heads of 26 patients, collected after total hip arthroplasty for secondary hip OA associated with DDH, and from the femoral neck fracture of 22 patients as controls after hemiarthroplasty. Surgery was performed at the affiliated hospital of Tohoku University Department of Orthopedic Surgery. The study was approved by the Ethics Committee of the Tohoku University School of Medicine, and informed consent was obtained from all participating patients. Genomic DNA was extracted from whole blood using the standard phenol-chloroform extraction–precipitation method with the PAX gene DNA Kit (BD, Franklin Lakes, NJ, USA). Genome-wide SNP genotypes of patients with DDH were determined using the Japonica v1 array (Toshiba, Tokyo, Japan), which is an SNP array specifically designed for the Japanese population. The array contained 659,253 SNPs, including tag SNPs for imputation and SNPs associated with phenotypes from previously reported GWAS and pharmacogenomics studies [52]. Genotype calling was performed using the apt-probeset-genotype program in Affymetrix Power Tools ver. 1.18.2 (Thermo Fisher Scientific Inc., Waltham, MA, USA). Sample QC was conducted according to the manufacturer’s recommendations (dish QC > 0.82 and sample call rate >97%). The clustering of each SNP was evaluated using the Ps classification function in the SNPolisher package (version 1.5.2, Thermo Fisher Scientific Inc.). SNPs that were assigned “recommended” by the Ps classification function were used for downstream analyses. Pre-phasing was conducted using EAGLE v2.3.2, with the default settings. Genotype imputation was conducted using IMPUTE4 v1.0, with a phased reference panel of Phase 1 version 3 of 1000 G containing 1092 individuals. These procedures were conducted using default settings. Cryptic relatives were excluded using PRIMUS with the default settings. Principal component (PC) analysis (PCA) was performed using East Asian samples from the International 1000 Genome Project (104 Japanese in Tokyo, 103 Han Chinese in Beijing, 93 Southern Han Chinese, 91 Chinese Dai in Xishuangbanna, and 99 Kinh in Ho Chi Minh City), in addition to the case and control samples. The PCA identified the outliers to be excluded using the Smirnov–Grubbs test with a Bonferroni-corrected p < 0.05. Association analysis was performed using PLINK version 1.9. The following options were used for PLINK: call rate >97.0%; Hardy–Weinberg equilibrium p > 0.000001; MAF >1%; and logistic regression modeling. An association analysis was also performed with the UK Biobank dataset, with the ethnic group genetically assigned to the category of White British (Data-Field 22006). Categorized as M161, M162, or M163 in ICD-10, the DDH case samples were selected, and samples with any ICD-10 assignment were selected as the healthy controls. The demographics of the samples are presented in Table S4. The GWAS was performed using PLINK version 1.9. The following options were used for PLINK: call rate >97.0%; Hardy–Weinberg equilibrium p > 0.000001; MAF > 1%; and logistic regression modeling with PC1 and PC2 as covariates. Four direct genotyping SNPs reached the genome-wide significance threshold (rs11802858, rs2554380, rs79657649, and rs17699467). For all four SNPs, the clustering status was “Poly high-resolution” and passed the SNP QC. To examine the misclassification of genotypes, for example, hetero as alternative homo and alternative homo as hetero, we checked the genotyping concordance rates between the genotype from the SNP array and the whole-genome sequence from the shared 190 samples. The concordance rates to whole-genome sequencing for all SNPs were consistent (Table 2), and all SNPs (rs11802858, rs2554380, rs79657649, and rs17699467) were included in the GWAS. The GWAS was also conducted on the UK Biobank data (3315 cases and 74,038 controls) using the fastGWA-GLMM [53] method of GCTA [54] with sex and PC1 to PC10 as covariates (call rate >95.0% and MAF > 1%). Genes were assigned to SNPs with p < 1 × 10−5 in the GWAS by FUMA (https://fuma.ctglab.nl/ (accessed on 1 August 2022)) with the default settings. In the Japanese GWAS, 684 variants passed the criteria, and 42 genes were assigned. In the UK GWAS, 1622 variants passed the criteria, and 81 genes were assigned. These gene sets and merged gene sets (123 genes) were used for further GSEAs. RNA extraction was performed as previously described [55,56]. Briefly, cartilage samples were cut into small pieces and suspended in the QIAzol Lysis Reagent (Qiagen, Crawley, UK). The suspension was homogenized on ice using a TissueRuptor (Qiagen, Crawley, UK) to crush the cartilage pieces and then extracted from the supernatant prepared according to the manufacturer’s instructions. RNA expression was quantified as previously described [56]. The total RNA extracted from 12 OA and eight femoral neck fracture cartilages, with RNA integrity numbers greater than 6.5, was subjected to microarray analysis using the 3D-Gene Human Oligo Chip 25k (Toray Industries, Tokyo, Japan). The extracted total RNA was labeled with Cy5 using the Amino Allyl MessageAmp II aRNA Amplification Kit (Applied Biosystems, Foster, CA, USA). The Cy5-labeled aRNA pool was applied to the hybridization buffer and hybridized for 16 h according to the supplier’s protocol. Fluorescence signals were scanned using a 3D-Gene Scanner (Toray Industries, Inc., Tokyo, Japan) and analyzed using the 3D-Gene Extraction software (Toray Industries, Inc.). A normalization method was used to adjust the median of all the detected signal intensities to 25. The mean fold change between the OA and control groups was less than 0.5, or greater than 2, and the round-robin comparison of gene expression between 12 OA and 8 control samples (96 combinations in total) showed that more than 80% (77 out of 96 combinations) of the combinations had significant differences in gene expression [56]. Genes for which significant differences were found in 80% or more of the samples (77 or more out of 96 combinations) were selected for analysis. This analysis aimed to narrow down highly specific genes without affecting mean gene expression. Results with p < 0.05 were considered statistically significant. GSEAs were performed using FUMA [57], pathway analysis in IPA (https://digitalinsights.qiagen.com/ja/qiagen-ipa/ (accessed on 1 August 2022)), and disease analysis using ToppGene (https://toppgene.cchmc.org/enrichment.jsp (accessed on 1 August 2022)), with each of the gene sets derived from the GWAS and mRNA microarray. The default parameters on the indicated website were used for all analyses. Qualitative RT-PCR was performed in 14 cases of DDH-related OA and 14 cases of femoral neck fracture (control), as previously described [58,59]. cDNA was synthesized from total RNA using a cDNA reverse transcription kit (Applied Biosystems, Foster City, CA, USA). Real-time amplification of target genes was performed using Taqman Universal Master Mix II containing uracil-N glycosylase and ready-to-use Taqman Gene Expression Assays (Applied Biosystems) with GTP cyclohydrolase 1 (GCH1, Hs 00609198_m1) and glyceraldehyde triphosphate dehydrogenase (GAPDH, Hs 02786624_g1) as endogenous controls. Relative gene expression data were calculated by the delta-delta-Ct method with PCR-efficiency correction using StepOne software (version 2.2.2; Applied Biosystems).

PMC10003191

Qiao Wang,Mamadou Thiam,Astrid Lissette Barreto Sánchez,Zixuan Wang,Jin Zhang,Qinghe Li,Jie Wen,Guiping Zhao

Gene Co-Expression Network Analysis Reveals the Hub Genes and Key Pathways Associated with Resistance to Salmonella Enteritidis Colonization in Chicken

02-03-2023

chicken,transcript factors,Salmonella,cecal microbiome,SCFAs

Salmonella negatively impacts the poultry industry and threatens animals’ and humans’ health. The gastrointestinal microbiota and its metabolites can modulate the host’s physiology and immune system. Recent research demonstrated the role of commensal bacteria and short-chain fatty acids (SCFAs) in developing resistance to Salmonella infection and colonization. However, the complex interactions among chicken, Salmonella, host–microbiome, and microbial metabolites remain unelucidated. Therefore, this study aimed to explore these complex interactions by identifying the driver and hub genes highly correlated with factors that confer resistance to Salmonella. Differential gene expression (DEGs) and dynamic developmental genes (DDGs) analyses and weighted gene co-expression network analysis (WGCNA) were performed using transcriptome data from the cecum of Salmonella Enteritidis-infected chicken at 7 and 21 days after infection. Furthermore, we identified the driver and hub genes associated with important traits such as the heterophil/lymphocyte (H/L) ratio, body weight post-infection, bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance. Among the multiple genes detected in this study, EXFABP, S100A9/12, CEMIP, FKBP5, MAVS, FAM168B, HESX1, EMC6, and others were found as potential candidate gene and transcript (co-) factors for resistance to Salmonella infection. In addition, we found that the PPAR and oxidative phosphorylation (OXPHOS) metabolic pathways were also involved in the host’s immune response/defense against Salmonella colonization at the earlier and later stage post-infection, respectively. This study provides a valuable resource of transcriptome profiles from chicken cecum at the earlier and later stage post-infection and mechanistic understanding of the complex interactions among chicken, Salmonella, host–microbiome, and associated metabolites.

Gene Co-Expression Network Analysis Reveals the Hub Genes and Key Pathways Associated with Resistance to Salmonella Enteritidis Colonization in Chicken Salmonella negatively impacts the poultry industry and threatens animals’ and humans’ health. The gastrointestinal microbiota and its metabolites can modulate the host’s physiology and immune system. Recent research demonstrated the role of commensal bacteria and short-chain fatty acids (SCFAs) in developing resistance to Salmonella infection and colonization. However, the complex interactions among chicken, Salmonella, host–microbiome, and microbial metabolites remain unelucidated. Therefore, this study aimed to explore these complex interactions by identifying the driver and hub genes highly correlated with factors that confer resistance to Salmonella. Differential gene expression (DEGs) and dynamic developmental genes (DDGs) analyses and weighted gene co-expression network analysis (WGCNA) were performed using transcriptome data from the cecum of Salmonella Enteritidis-infected chicken at 7 and 21 days after infection. Furthermore, we identified the driver and hub genes associated with important traits such as the heterophil/lymphocyte (H/L) ratio, body weight post-infection, bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance. Among the multiple genes detected in this study, EXFABP, S100A9/12, CEMIP, FKBP5, MAVS, FAM168B, HESX1, EMC6, and others were found as potential candidate gene and transcript (co-) factors for resistance to Salmonella infection. In addition, we found that the PPAR and oxidative phosphorylation (OXPHOS) metabolic pathways were also involved in the host’s immune response/defense against Salmonella colonization at the earlier and later stage post-infection, respectively. This study provides a valuable resource of transcriptome profiles from chicken cecum at the earlier and later stage post-infection and mechanistic understanding of the complex interactions among chicken, Salmonella, host–microbiome, and associated metabolites. Salmonella infections threaten the poultry industry and public health. While spontaneous Salmonella spp. infection is unlikely to result in a considerable number of chicken deaths, it will have a significant detrimental impact on poultry production capacity and health. Additionally, it is a zoonotic disease that poses a significant hazard to public health and safety [1,2,3,4,5]. Therefore, it is crucial to understand the mechanisms of the complex interactions among chicken, Salmonella, and host–microbiome to minimize economic losses in poultry production and protect animal and human health [6]. The gut microbiota of chickens is diverse and complex, and it is critical for nutrition, immune system development, and pathogen exclusion. In their study, Kempf and co-authors defined super shedding as a shed of high levels of pathogens resulting from successful infection and colonization persistence in the ceca [7]. They also hypothesized that a high diversity or the presence of specific features of the gut microbiota inhibits pathogens growth [7]. The gut microbiota can protect against harmful bacteria by sticking to the intestinal epithelial walls [8]. These bacteria are capable of producing many compounds involved in the barrier effect such as short-chain fatty acids (SCFAs: acetate, propionate, and butyrate), organic acids (lactic acid), and antibacterial chemicals (bacteriocins), as well as generating non-pathogenic immunological responses that benefit the animal by providing sustenance and protection [8,9,10]. Commensal bacteria provide fundamental benefits to the host by providing nutrients, competitively excluding pathogens or non-native germs, and stimulating and training the immune system [11]. Furthermore, the host’s intestinal microbiota can promote the development of the immune system, which includes the intestinal epithelial cells, mucus layers, intestinal immune cells, and lamina propria [1,11,12]. Previous studies demonstrated that chickens and other avian species with low heterophil/lymphocyte (H/L) ratio are more resistant to environmental stressors than birds with a high H/L ratio [13,14]. Recent studies have suggested that a low H/L ratio provides resistance benefits such as better immune response, performance, adaptability, and longevity [15,16]. Our previous study demonstrated that chickens with low H/L are more resistant, which could be associated with increased cecal relative abundance in Proteobacteria and Bacteroidetes [17], thus suggesting that the commensal Proteobacteria and Bacteroidetes could be involved in this resistance against Salmonella through diverse mechanisms not well understood. To date, no study has been conducted to examine the complex interactions between chicken, Salmonella, and host–microbiome by assessing gene regulation and correlation with the resistance to Salmonella infection. Therefore, with the aim to contribute to developing better understanding of these mechanisms, the current study was initiated to identify the candidate genes and signaling pathways associated with the resistance to Salmonella mediated by the intestinal microbiota and derived metabolites. Through this, we have identified the differentially expressed, developmentally dynamic driver and hub genes associated with the resistance to Salmonella and correlated with factors such as the body weight post-infection, H/L ratio, bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance by combining data from the transcriptome and weighted gene co-expression network analysis (WGCNA) of the cecum from chickens infected with Salmonella Enteritidis 7 and 21 days after infection. This may be valuable for the understanding of the mechanisms of resistance to Salmonella infection. To evaluate the resistance to Salmonella infection mediated by the gut microbiota and derived metabolites between high and low H/L ratio Salmonella Enteritidis (SE)-infected chickens, we measured the H/L ratio (at 7 days old), body weight post-infection (BW), bacterial load, propionate and valerate contents, and the cecal microbiota relative abundance at 7 and 21 days post-infection (dpi). The H/L ratios of chickens with high and low H/L ratio were significantly (p < 0.0001) different at 7 and 21 dpi (Figure 1A). It was noteworthy that chickens with a low H/L ratio showed significantly reduced body weight loss compared to chickens with a high H/L ratio at 21 dpi (Figure 1B). The determination of SE load in the cecum tissues revealed that the chickens with low H/L ratio displayed a lower bacterial load than chickens with a high H/L ratio, with a significant difference (p = 0.0053) observed at 7 dpi (Figure 1C). Regarding propionate and valerate cecal contents, we observed that the chickens with a low H/L ratio were characterized by increased concentration of these microbial metabolites (Figure 1D,E). To assess the cecal microbiome composition of chickens with high and low H/L ratios, 16S rRNA sequencing analysis was performed at 7 and 21 dpi. In this study, the more abundant phyla were Firmicutes (p = 0.030), Bacteroidetes (p = 0.0014), and Proteobacteria (p = 0.0090), with a differential abundance among groups over time points post-infection (Figure 1F). The number of DEGs detected between high and low H/L ratio SE-infected chickens at 7 (H7 and L7), and 21 (H21 and L21) dpi varied from 155 to 855 (Figure 2A). To obtain an insight into the cecum gene transcription among the four groups, we performed the following comparison: H7 vs. L7, H21 vs. L21, H7 vs. H21, and L7 vs. L21. The results showed more DEGs in the comparison between same H/L ratios level (high or low) at 7 and 21 dpi (H7 vs. H21 with 855 DEGs and L7 vs. L21 with 737 DEGs; Figure 2A). However, a low number of DEGs was observed in comparing high and low H/L ratio chickens at 7 or 21 dpi (H7 vs. L7 with 276 DEGs and H21 vs. L21 with 155 DEGs; Figure 2A). The overlapping genes among these four features of comparison are shown in Figure 2B. The top DEGs identified from the different comparisons are shown in Table 1. From these comparisons, four potential genes were identified as involved in the defense against Salmonella infection. Immune-related gene such as FKBP5 (H7 vs. L7) was upregulated in chickens with a low H/L ratio than in chicken with a high H/L ratio at 7 dpi. Compared to chicken with a high H/L ratio, chicken with a low H/L ratio showed upregulation of CEMIP gene expression at 21 dpi (H21 vs. L21). Moreover, we detected that EXFABP and S100A9 genes were significantly and differentially expressed between 7 and 21 dpi in chickens with low H/L ratios (L7 vs. L21). They were upregulated at 7 dpi in comparison to 21 dpi. To identify the biological process regulated by the significant DEGs and their effect on the resistance to Salmonella infection, Gene Ontology (GO) enrichment (Figure 3) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (Figure 4) analyses were performed for each of the four versus. The results showed that the four versus displayed different numbers and categories. Biological processes such as monooxygenase activity and ribosome-related regulation were significantly enriched in H7 vs. L7 (5 GO terms) and H21 vs. L21 (9 GO terms), respectively (Figure 3A,B). It was noteworthy that only the versus comparing the same H/L ratio level between the two-time points post-infection showed immune-related GO (Figure 3C,D). The KEGG pathways analysis of detected DEGs from the four versus is presented in Figure 4. The PPAR signaling pathway and oxidative phosphorylation were significantly enriched in H7 vs. L7 and H21 vs. L21, respectively (Figure 4). Pathways such as cytokine−cytokine receptor interaction and calcium signaling pathway were significantly enriched and both detected between H7 vs. H21 and L7 vs. L21 (Figure 4). The genes such as EXFABP and S100A12 were detected as involved in the GO terms immune response, response to external stimulus, response to other organisms, defense response, and extracellular region, which were enriched in H7 vs. H21 and L7 vs. L21. The detailed GO terms enrichment and KEGG pathways of the four versus are shown in Supplementary Table S2. To explore the gene expression changes during Salmonella infection in the cecum, the genes with significant temporal changes (DDGs) were detected. Between the two times post-infection tested (7 and 21 dpi), 1290 genes were identified as DDGs, including 86 Transcript Factors (TFs) and 79 Transcription Co-Factors (TCFs) (Supplementary Table S3). Based on the DDGs analysis, 877 and 886 genes were identified as significant DDGs in high and low H/L ratio SE-infected chicken groups, respectively. The Venn analysis showed with 842 shared DDGs between high (35 unique DDGs) and low (44 unique DDGs) H/L ratio chickens (Supplementary Figure S1A). The top 20 enriched GO terms for these TFs of DDGs are shown in Supplementary Figure S1. From the GO analysis, genes such as HESX1 and SMAD5 were involved in most biological processes and identified as potential immune-related DDGs. The KEGG analysis for these TFs of DDGs showed four enriched KEGG pathways, including C-type lectin receptor signaling pathway, influenza A, adipocytokine signaling pathway, and TGF-beta signaling pathway (Supplementary Figure S1C). Genes such as IRF1, RAF1, NFATC3, NFKBIB, and JAK2 were involved in these KEGG pathways and identified as key immune DDGs. Detailed GO and KEGG information for the TFs are shown in Supplementary Table S4. Weighted Gene-Co-Expression Network Analysis (WGCNA) was performed using factors of interest such as days post-infection (dpi), H/L ratio, body weight post-infection (BW), bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance (Supplementary Figure S2A). In the present study, cecum transcriptome data were used to construct the expression matrix, and traits data from high and low H/L ratio SE-infected chickens at 7 and 21 dpi were combined and analyzed (including 19 samples). A total of 19,501 genes were obtained to build the weighted gene co-expression network after removing the offending genes. First, we determined the best soft threshold (8) using the scale-free topological model and mean connectivity (Supplementary Figure S2B). Next, the cluster dendrogram of co-expression network modules was generated using hierarchical clustering of genes based on the 1-TOM formula (Supplementary Figure S2C). As a result, 27 co-expression modules were obtained, and the corresponding modules–traits relationships are presented in Figure 5. Ten modules were identified as highly correlated with the factors, including dark-turquoise, magenta, dark-green, black, green, yellow, blue, pink, tan, and brown (Figure 6). It was noteworthy that the yellow module was significantly and negatively correlated with the majority of factors, while the blue module was significantly and positively correlated with the factors (Figure 5). The blue (r = 0.85, p = 5e−06) and brown (r = 0.61, p = 0.005) modules were significantly and positively correlated with dpi, while the yellow module (r = −0.75, p = 2e−04) was significantly and negatively correlated (Figure 5). Based on the results obtained no modules were significantly correlated with H/L ratio. However, the dark-green module was positively correlated with H/L ratio (r = 0.42, p = 0.07; Figure 5). The yellow module (r = −0.77, p = 1e−04) was significantly and negatively correlated with body weight post-infection, while the blue module (r = 0.83, p = 1e−05) was significantly and positively correlated (Figure 5). The dark-turquoise (r = 0.52, p = 0.02) and magenta (r = 0.51, p = 0.02) modules were significantly and positively correlated with bacterial load, while the blue (r = −0.77, p = 1e−04) and the brown (r = −0.57, p = 0.01) modules were significantly and negatively correlated. Concerning the microbial metabolites, the yellow module was significantly and negatively correlated with propionate and valerate (r = −0.64, p = 0.003 and r = −0.65, p = 0.003, respectively), while the blue (r = 0.69, p = 0.001 and r = 0.77, p = 1e−04, respectively), tan (r = 0.55, p = 0.01 and r = 0.48, p = 0.04, respectively), and the brown (r = 0.61, p = 0.006 and r = 0.57, p = 0.01, respectively) modules were significantly and positively correlated (Figure 5). The black (r = −0.49, p = 0.04), blue (r = −0.49, p = 0.03), and pink (r = −0.51, p = 0.02) modules were significantly and negatively correlated with Firmicutes relative abundance (Figure 5). The Bacteroidetes relative abundance was significantly and negatively correlated with the yellow module (r = −0.60, p = 0.007), while significantly and positively correlated with blue module (r = 0.69, p = 0.001; Figure 5). It was remarkable that no modules were significantly and negatively correlated with Proteobacteria relative abundance, whereas the black (r = 0.73, p = 4e−04), green (r = 0.64, p = 0.003), and yellow (r = 0.71, p = 7e−04) modules were significantly and positively correlated with Proteobacteria relative abundance (Figure 5). In addition, the top 10 driver genes of the interesting modules were identified according to the absolute value of gene significance (|GS| > 0.5) and module membership (|MM| > 0.5). As a result, the top 10 driver genes of the interesting module are shown in Table 2. To identify the hub genes involved in the resistance to Salmonella in chickens’ cecum, we selected 4 key modules (blue, brown, green, and yellow) strongly correlated with the factors. The co-expression network with detected hub genes of the key modules selected are shown in Figure 6. The genes such as NDUFAF8, MAVS, TADA2A, and ENSGALG00000052684 identified in the top DEGs and driver genes were identified as hub genes in the blue (Figure 6A), brown (Figure 6B), green (Figure 6C), and yellow module (Figure 6D), respectively. To assess the biological process regulated by the hub genes and their effect on the resistance to Salmonella infection, GO enrichment and KEGG pathways analyses were performed for the genes detected in the blue, brown, green, and yellow modules (Figure 7). The KEGG analysis showed that the oxidative phosphorylation metabolic pathway was significantly enriched by the cluster of genes from the blue module. It was noteworthy that among the four modules selected, the green module showed more enriched GO terms and KEGG pathways related to the immunity than the blue, brown, and yellow modules (Figure 7). Among the top 20 GO terms significantly enriched in the green module, inflammatory response, lymphocyte activation, regulation of immune system, T cell activation, immune response, leukocyte activation, positive regulation of myeloid cell differentiation, and leukocyte-mediated immunity were significantly enriched (Figure 7E); eight KEGG pathways were significantly enriched in this module, cytokine−cytokine receptor interaction, herpes simplex virus 1 infection, cell adhesion molecules, phagosome, lysosome, Toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, and intestinal immune network for IgA production (Figure 7F). The detailed information on GO enrichment and KEEG pathways analyses of the four interesting modules are shown in Supplementary Table S5. To identify the driver genes from the significant module–traits relationship, the genes were screened according to their gene significance (GS), module membership (MM), and p-value (p < 0.01). The top 10 driver genes of the interesting module–traits relationship are presented in Table 2. To detect the genes significantly correlated with some interesting factors, a Venn diagram analysis was performed to identify the genes shared between four factors that have been demonstrated to play a role in the resistance to Salmonella infection (Figure 8). The FAM168B, RAF1, HESX1, USP8, C2CD5, PIGC, ENSGALG00000053041, and ENSGALT00000092369 were found to be top driver genes shared among dpi, body weight post-infection, and propionate and valerate cecal contents (Figure 8A). Concerning the genes shared in the top driver from dpi, bacterial load, and propionate and valerate cecal contents, EMC6, NFU1, ENSGALG00000021686, and ENSGALG00000048205 were identified (Figure 8B). The gut microbiota can modulate the immune system of the host through SCFAs or direct inhibition, and it is in this optic that we identified FAM168B, RAF1, HESX1, PIGC, and ENSGALT00000092369 as the top driver genes shared among body weight post-infection, Bacteroidetes relative abundance, and propionate and valerate cecal contents (Figure 8C). The detailed information of unique and shared genes among multiple combinations of four factors is shown in Supplementary Table S6. To verify the implication of some candidate genes in the process and acquisition of resistance to Salmonella infection in chicken, we quantified the expression of EMC6, FKBP5, NFU1, S100A12, FAM168B, PIGC, HESX1, and USP8 in cecum tissues of non-infected and Salmonella Typhimurium (ST)-infected Dagu chickens using qRT-PCR. Through this, we were able to assess whether the expression level of these genes is associated to the resistance to pathogenic infections such as Salmonella. Figure 9 shows that compared to the control group, the gene expression of FKBP5 and S100A12 increased significantly after Salmonella infection, while the expression of EMC6, FAM168B, and HESX1 decreased significantly. The expression level of NFU1, PIGC, and USP8 decreased under Salmonella infection, without a significant difference between non-infected and ST-infected chickens (Figure 9). Chickens with a low H/L ratio are superior to the chickens with a high H/L ratio in terms of survival, immune response, and resistance to Salmonella infection [13,14,15,18,19]. Our previous experiment demonstrated that the H/L ratio was linked to important features such as intestinal immunity, the inflammatory response, and the cecal microbiota composition in SE-infected chicken. In the present study, we performed a time course (at 7 and 21 dpi) transcriptome profiling of cecum tissues during SE infection to identify genes associated with important immune traits involved in Salmonella resistance directly or mediated by the gut microbiota and its metabolites. Therefore, this study provides valuable genetic resources on the mechanisms of resistance to Salmonella colonization in chickens. Salmonella infections in poultry have been linked to reduced performances, intestinal colonization, inflammation, and deep organ invasion [20]. In the present study, under Salmonella infection, chickens with a low H/L ratio displayed increased body weight (at 21 dpi), propionate (at 21 dpi), valerate (at 21 dpi), and significantly higher Proteobacteria and Bacteroidetes cecal relative abundance at 7 and 21 dpi, respectively. Our previous study discussed these results, where we demonstrated that the H/L ratio modulates the cecal microbiota, and this modulation could be one of the multiple mechanisms of resistance to Salmonella infection [17]. Recent studies reported that chickens with a low H/L ratio were more resistant to Salmonella through increased IL-1β and IFN-γ blood serum concentration and intestinal expression and potentially through a particular cecal microbiota composition and SCFAs cecal content at specific days after infection [16,17,19]. Chickens acquire resistance to Salmonella infection with age due to the development of their gastrointestinal and immune systems [21,22]. The intestinal epithelial cells and mucus layers act as barriers between the host and the microbes, defending the host against undesirable gut microorganisms. Microbial metabolites can also modulate the immune system by affecting host cells’ physiology and gene expression [23,24,25]. The SCFAs possess bacteriostatic properties that inhibit the growth of foodborne pathogens such as Salmonella spp. [26]. The cecum transcriptome profiling performed in this study identified genes such as FBXO32 (H7 vs. L7), FKBP5 (H7 vs. L7), NDUFAF8 and CEMIP (H21 vs. L21), TIMD4 (H7 vs. H21), PER2 (H7 vs. H21), EXFABP (L7 vs. L21), MST1 (L7 vs. L21), and S100A9 (L7 vs. L21) as candidate genes for resistance to Salmonella infection. The role of these genes in chicken is not clearly defined. Therefore, further investigations are needed to explain their function and possible involvement in chicken’s disease resistance. Among the genes detected, FKBP5, CEMIP, EXFABP, and S100A9/12 are promising candidate genes for studying the mechanisms of resistance to Salmonella colonization. Although it is well established that FK506-binding protein 5 (FKBP5), a protein cochaperone, is involved with the inflammatory response, the regulatory mechanisms underlying leukocyte FKBP5 DNA methylation remain unknown [27]. It has been reported that epigenetic FKBP5 overexpression, a stress-induced protein cochaperone, is related to nuclear factor-B (NF-B)-mediated inflammation [28]. This gene has been linked to the control of NF-κB and IL-1. In the current work, we detected that the peroxisome proliferator-activated receptors (PPARs) metabolic pathway was significantly enriched by the cluster of genes differentially expressed between chickens with low and high H/L ratios at 7 dpi. The PPARs control numerous pathways, such as modulation of the immune system and inflammatory response and the sensing of nutrients (fatty acids and their derivatives) [29]. Out of the three PPAR isotypes, PPARα can strongly inhibit inflammation through the repression of nuclear factor kappa B (NF-κB), activation of protein 1 (AP-1), as well as the signal transducer and activator of transcription (STAT) signaling pathways [29], whereas PPARγ is described as a double-edged sword, showing both pro- and anti-inflammatory effects and exerting beneficial as well as harmful effects upon host defenses against pathogenic bacteria [30]. PPARγ possesses anti-inflammatory effects via inhibition of pro-inflammatory molecules such as IL-6, TNF-α, IL-1β, and IL-12 [30]. The host and commensal bacteria can trigger PPARγ. In this context, Kelly and co-authors demonstrated that the commensal Bacteroidetes Thetaiotaomicron blocks the dysfunctional acute inflammatory response to infection by pathogenic Salmonella enterica by inducing binding of PPARγ to NF-κB RelA subunit and their joint nuclear export and cytosolic localization, resulting in the inhibition of the transcription of pro-inflammatory cytokine IL-8 [31]. Moreover, Grabacka and co-authors reported that microbiota products could influence PPARα signaling and, on the other hand, PPARα activation can affect microbiota profile, viability, and diversity [29]. It has been reported that PPARα activity is critical for maintenance of the intestinal barrier and the development of tolerance towards gut microbiota through suppression of Th1/Th17 inflammatory response [32]. PPARα-mediated IL-22 production by innate lymphoid cells has been described to be necessary for maintaining gut commensal microbiota homeostasis, protecting from pathogens, supporting beneficial microbiota, and suppressing unnecessary inflammation [29]. IL-22 is an IL-10 family cytokine, which is indispensable for the production of antimicrobial peptides such as regenerating islet-derived proteins RegIIIβ, RegIIIγ, calprotectin (S100A, S100B), as well as tight junction protein claudin 2; all these proteins are crucial to the host for control and clearance of intestinal pathogens [33,34]. Accordingly, in this study, S100A9 was significantly and differentially expressed between low H/L ratio chicken 7 and 21 dpi (L7 vs. L21). S100A9 was upregulated at 7 dpi in chicken with low H/L ratio (L7), compared to chicken with low H/L ratio at 21 dpi (L21). Moreover, the gene S100A12 was involved in major immune-related GO terms identified across time points post-infection (H7 vs. H21 and L7 vs. L21). It is possible to suggest that the PPAR metabolic pathway and S100A9/12 are involved in the resistance to Salmonella infection in chicken through unknown mechanisms. The oleoylethanolamide (OEA) is an endogenously produced PPARα ligand (Grabacka et al., 2022) [29]. Recently, a study by Paola and co-authors demonstrated that administration of exogenous OEA to mice could increase microbial diversity and shift in colonic microbiota composition towards higher Bacteroidetes and lower Firmicutes abundance 11 days after inoculation [35]. Consistent with our results, we previously found that chickens with a low H/L ratio showed increased Bacteroidetes compared to chickens with high H/L ratio at 21 dpi [17]. We could hypothesize that PPAR pathway enrichment associated with increased expression of S100A9/12 at 7 dpi is involved in the increased Bacteroidetes and resistance to Salmonella infection in chicken. The increased Bacteroidetes abundance was significantly and positively correlated with propionate and valerate cecal concentration [17]. In line with our hypothesis, a study performed on mice with high-fat diet (HFD)-induced diabetes revealed that mice treated with fenofibrate (synthetic PPARα agonist) had increased concentration of SCFAs (acetate, propionate, butyrate) [36]. These authors also reported that fenofibrate improved barrier functions of intestinal mucosa in HFD mice, visible by lower permeability and higher expression of genes encoding for tight junction proteins, zonula occludens 1 (ZO-1), and occluding in the colon [36]. Moreover, they also observed that the percentage of Proteobacteria group was also decreased after administration of the synthetic PPARα agonist, fenofibrate [36]. These reports and our findings suggest that the PPAR metabolic pathway could be involved in the shift of gut microbiota composition and the inhibition of Salmonella growth, respectively through an increase in Bacteroidetes and the antibacterial effect of the calprotectin S100A. The gene S100A12, also known as calgranulin C [37], is a calcium-binding protein of the S100 subfamily of myeloid-related proteins that acts as an alarming signal to induce a pro-inflammatory innate immune response [38]. Yang and co-authors, in their study, reported that S100A12 gene expression was very sensitive to low levels of LPS, indicating that exposure to higher levels of LPS enhances S100A12 expression [39]. Interestingly, Hasegawa et al. reported that a PPAR-γ agonist inhibits S100A12 expression by macrophages [40]. In accordance with our results, we found that PPAR signaling pathway was significantly enriched by the genes differentially expressed between chickens with low and high H/L ratios at 7 dpi. This result suggests that after induction of strong inflammatory response, the overexpression of PPAR was necessary for inhibition of inflammatory reactions. Realegeno et al. [41], in their study, demonstrated that S100A12 is involved in the antimicrobial network against Mycobacterium leprae in human macrophages. An important pathway for macrophage activation in innate immunity is through the recognition of bacterial lipoproteins by Toll-like receptor 2/1 heterodimers (TLR2/1) [42], which stimulates an antimicrobial response [43]. Realegeno et al. reported that S100A12 is sufficient to directly kill Mycobacterium tuberculosis and Mycobacterium leprae and that is also required for TLR2/1L and IFN-γ induced antimicrobial activity against M. leprae in infected macrophages [41]. These observations, following our findings, suggest that S100A12 plays a key role in macrophages’ antimicrobial activity via innate and adaptative immune response. However, to our knowledge, there is a lack of information regarding the role of S100A12-mediated antimicrobial activity against bacterial pathogens such Salmonella in macrophages. Interestingly, Komadath and co-authors, in a Salmonella-infected pig model and gene co-expression network analysis, identified S100A12 among other genes as correlated with Salmonella shedding level and response to bacterial or Salmonella infection [44]. In line with this observation, Realegeno et al., in their study, identified S100A12 in a module that was found to be significantly and positively correlated with TLR2/1L and associated with the Gene Ontology terms such as defense response, killing of cells of other organisms, chemotaxis, cytokine, and inflammatory response [41]. These observations constitute evidence that S100A12 plays a key role in the host defense against pathogenic infection. In this work, we found that the Oxidative phosphorylation (OXPHOS) pathway was significantly enriched in the cluster of genes differentially expressed between high and low H/L ratios chicken at 21 dpi. OXPHOS and mitochondrial reactive oxygen species (mtROS) are involved in multiple immune cell functions [45]. In addition, mitochondria are powerful organelles that can provide immunogenetic molecules, such as mitochondrial DNA (mtDNA), which triggers innate immune system activation [45]. M2 macrophage-mediated tissue repair and release of anti-inflammatory cytokine IL-10 often depends on the energy produced by OXPHOS and fatty acid oxidation [46]. Mitochondria also play a key role in NOD-like receptor family pyrin domain 3 (NLRP3) inflammasome activation [45]. Interestingly, in this study, we detected the gene co-expressed network of mitochondrial antiviral signaling protein (MAVS) as hub gene in the brown module. This module was significantly and positively correlated to propionate and valerate cecal concentration and Bacteroidetes relative abundance, while it was significantly and negatively correlated to Salmonella load. These results suggest that the OXPHOS pathway is involved in the control (inhibition) of Salmonella colonization through mechanisms involving MAVS. Accordingly, Park and co-authors, in their study, reported that MAVS regulates the production of type I IFN associated with NLRP3 [47]. The recruitment of NLRP3 leads to caspase-1-dependent secretion of pro-inflammatory cytokines, such as interleukin-1b (IL-1b) and IL-18 [45]. In line with our hypothesis that the OXPHOS pathway is associated with the inhibition of Salmonella growth through MAVS-mediated NLRP3 inflammasome activation, we reported in our previous study that a low H/L ratio is correlated with increased IL-1β and IFN-γ at 21 dpi [16]. In their study, Li and collaborators reported that OXPHOS and glycolysis metabolic pathways were required for protection against pathogenic microorganisms and that both were crucial for neutrophil homeostasis, migration, and inflammatory cytokine secretion [48]. Wang and McLean reported that M2 macrophages, regulatory T cells (Tregs), and memory T cells rely on OXPHOS and fatty acid oxidation [49]. Here, we provide clear evidence of links between the host, Salmonella, microbiota, and associated metabolites. The OXPHOS metabolic pathway and MAVS could be of interest for future study regarding the host, Salmonella and Bacteroidetes-derived propionate interactions. Based on the correlation degree and the genes involved, four interesting modules were selected to determine the hub genes, namely the blue, brown, green, and yellow modules. In the blue module, genes such as NDUFAF8, CDC27, and GOLGA4 were identified as hub genes, while only MAVS was identified in the brown. In contrast to the blue and brown modules, the green and yellow modules were negatively correlated to most traits. Notably, the green and yellow modules, were positively correlated with Proteobacteria cecal relative abundance. Genes such as TADA2A and IL-1β were identified as hub genes in the green module, while C2CD5 and ENSGALG00000052684 were identified as hub genes in the yellow module. The biological process analysis of these modules revealed that the brown and green modules displayed significantly enriched immune-related GO and KEGG pathways compared to the blue and yellow modules. However, the OXPHOS metabolic pathway was significantly enriched by the cluster of genes from the blue module. Furthermore, it was remarkable that the green module showed important immune-related GO and KEGG pathways, indicating that the genes contained in this module could be potential candidate genes. In addition, the green module was significantly and positively correlated with Proteobacteria relative abundance. These results suggest that Proteobacteria could play a crucial role in acquiring and developing adaptative immunity. The Proteobacteria relative abundance was significantly associated with genes involved in major immune-related biological processes such as leukocyte and T cell activation. Suggesting a potential involvement of this phylum in the activation and maturation of the immune system. Driver genes such as FAM168B, USP8, C2CD5, PIGC, RAF1, EMC6, NFU1, and several others were found shared among major factors involved in the resistance to Salmonella and could be potential candidate genes. In this study, we also detected that the extracellular fatty acid binding protein (EXFABP) was significantly downregulated at 21 dpi compared to 7 dpi in chickens with low H/L ratio. In their study, Hu et al. demonstrated that Salmonella Enteritidis (OTU607) was positively correlated with EXFABP among others genes, indicating that Salmonella Enteritidis infection arouses EXFABP transcription in chicken, which induces the sequestration of siderophore secreted by enteric bacteria and Gram-positive bacilli, such as Escherichia-Shigella and Enterococcus, resulting in a decrease of their abundance [50]. During infection, Salmonella escapes the antibacterial effect of EXFABP-mediated growth inhibition through salmochelin, which is not recognized by EXFABP [50]. Thus, the inflammatory response induced by Salmonella increases EXFABP proteins and could limit the growth of Enterobacteriaceae [50]. The Enterobacteriaceae have a protective role by competing for oxygen and niche with Salmonella [51]. This could be one of the mechanisms of Salmonella for establishing successful infection. It is also possible that EXFABP-mediated inhibition of enteric bacteria could affect Salmonella despite salmochelin’s presence. To our knowledge, there is limited information on the enteric inhibitory growth effect of EXFABP on Salmonella. It was noteworthy that genes such as EXFABP and S100A12 among others identified (Supplementary Table S2 GO and KEGG, L7 vs. L21 and H7 vs. H21) were involved in the enrichment of Gene Ontology (GO) terms: response to external stimuli (GO:0009605), defense response (GO:0006952), and extracellular region (GO:0005576). These results strongly suggest the potential involvement of EXFABP and S100A12 in the host’s immune response and inhibition of Salmonella growth. We further detected the expression of eight selected candidate genes in the cecum tissues of Dagu chickens infected with Salmonella Typhimurium, including EMC6, FKBP5, S100A12, FAM168B, HESX1, NFU1, and PIGC. We found that the expression of most genes changed significantly due to Salmonella infection, which indicates that these genes may participate in the host’s immune response to Salmonella. In this study, we found that FKBP5 and S100A12 were differentially expressed in chickens with high and low H/L ratios and between non-infected and ST-infected chickens. Moreover, at 7 dpi, the expression of FKBP5 and S100A12 were significantly upregulated in chickens with low H/L, which is consistent with their potential protective and immune enhancer functions reported in the literature. In addition, we observed that the expression of cell migration inducing hyaluronan binding protein (CEMIP) was upregulated in chickens with low H/L ratios, compared to chickens with high H/L ratios at 21 dpi. Accordingly, Cazals and collaborators reported that CEMIP, among other genes, was significantly upregulated in both the resistant line N (low carriage) and in low carriers of the susceptible line (line 6) [52]. These results were in line with our findings indicating that chickens with low H/L ratios were more resistant than chickens with high H/L ratios at 21 dpi, and the CEMIP gene could be involved in the acquisition of resistance against Salmonella and maybe other pathogenic infections in other species. A study recently published by Dokoshi et al. reported that CEMIP regulates host defense against Staphylococcus aureus skin infection [53]. They found that CEMIP loss increases inflammation and antimicrobial activity following a skin infection and that CEMIP−/− mice challenged with S. aureus had higher IL-6 and neutrophil infiltration [53]. These results indicate that CEMIP regulates inflammation and antimicrobial activity [53]. To date, the regulatory mechanisms of intestinal inflammation by CEMIP remain unelucidated. This is of further interest to understand the mechanisms of resistance to pathogenic intestinal infections. Taken together, it is possible to suggest that at the earlier stage of infection, an overexpression of genes such as FKBP5 and S100A9/12 could confer enhanced immune response, while an overexpression of a gene such as CEMIP and the enrichment of OXPHOS pathway will exert an anti-inflammatory effect and antimicrobial activity. The strong immune response at the earlier stage of the infection will induce pathogen clearance and at the later stage post-infection, the regulation of the inflammation and enhanced antimicrobial activity will restore the intestinal homeostasis. In the present work, we identified the PPAR and OXPHOS metabolic pathways as involved in the mechanisms of resistance to Salmonella infection in chickens. The hub and driver genes detected in this study could contribute to developing new targets for control of Salmonella. A group of 200 one-day-old Jinxing yellow chicks from our previous study was used in the present work [17]. The birds were housed in sterilized isolation ventilated cages. Throughout the trial, the chicks received ad libitum Specific Pathogen Free (SPF) feed (Beijing Keao Xieli Feed Co., Ltd., Beijing, China) and free access to sterilized water. Before infection, all chicks were tested for Salmonella by culturing cloacal swab samples overnight at 37 °C with agitation in buffered peptone water [54]. No contaminated chicks were discovered, according to the results. At 7 days old, Salmonella Enteritidis 50335 (Institute of Veterinary drugs Control, Beijing, China) was used to challenge the birds with 1 mL of PBS containing 1 × 1010 CFUs of SE /mL. The samples collection was performed at 7 and 21 days post-infection by randomly selecting 30 chickens. Before slaughter, the chicks were individually weighed and blood samples (1.5 mL distributed in one blood vial EDTA tube) were collected from the wings and stored at −20 °C. Next, the two ceca were aseptically sampled (section performed 2 cm from the junction ileocecal). After sectioning the ceca, sterile tweezers were used to squeeze the contents into sterile cryovial tubes for SCFAs and DNA extraction for 16S sequencing analysis. Then, the tissues were washed with PBS and stored in cryovial tubes at −80 °C for later DNA and RNA extraction. The H/L ratios were determined using 10 µL of fresh blood, based on a method described elsewhere [19,55]. In brief, the blood smears were stained using Wright-Giemsa solution (G1020, Solarbio, Beijing, China) according to the manufacturer’s instructions. The concentration of propionate and valerate contents were measured by Gas Chromatography–Mass Spectrometry (GC-MS) using 100 mg of accurately weighted cecal contents [17]. The genomic DNA (gDNA) utilized in the current study was purified using a modified phenol–chloroform method. To quantify total Salmonella load in the cecum tissues, we used a method previously described elsewhere [16]. The cecal microbiota diversity was determined by 16S rRNA gene sequencing analysis [56], according to a method described elsewhere [17]. To extract the RNA from the cecum tissues, 32 cryopreserved samples were used (including 8 low and 8 high H/L ratios chickens from 7 and 21 dpi). Total RNA was isolated using the QIAGEN RNeasy Kit, and genomic DNA was removed using the TIANGEN DNase KIT (Tiagen, Beijing, China). The purity of the RNA was assessed using a kaiao K5500® Spectrophotometer (Kaiao, Beijing, China), while the integrity and concentration of the RNA were determined using the RNA Nano 6000 Assay Kit and the Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). A total of 2 µg of RNA were used as input material to synthesize the transcriptome analysis RNA samples. A total of 22 samples were utilized for transcriptome profiling based on the quality and purity of the isolated RNA. Cecal tissues from 4 to 7 individuals per group were used for transcriptome profiling and detection of genes differentially expressed. To understand the cecum’s gene transcription between high and low H/L ratio SE-infected chickens at the earlier and later stages post-infection, transcriptome data of 22 individuals were used (Supplementary Table S1). After filtering and quality control, more than 40 million clean reads were obtained. From the alignment of clean reads to the chicken reference genome (GRCg6a), a total of 22,701 genes were detected, with an average rate of 92.40% among all cecum samples. The transcriptome data were aligned in paired-end mode to the chicken reference genome (Ensembl GRCg6a) using the HISAT2 Version: 2.2.0 (https://daehwankimlab.github.io/hisat2/, accessed on 26 May 2021) with default settings. The NEBNext® UltraTM RNA Library Prep Kit for Illumina® (E7530L, New England Biolabs, Ipswich, MA, USA) was used to construct the sequencing libraries according to the manufacturer’s instructions, and index codes were applied to assign sequences to each sample. Purification of mRNA from the whole RNA was performed using poly-T oligo-attached magnetic beads. Next, fragmentation was carried out at elevated temperatures in the NEBNext First Strand Synthesis Reaction Buffer utilizing divalent cations (5X). The first strand of cDNA was produced with a random hexamer primer and RNase H, whereas the second strand was created with buffer, dNTPs, DNA polymerase I, and RNase H. Purification of library fragments was accomplished using QiaQuick PCR kits, followed by elution with EB buffer, terminal repair, A-tailing, and adaptor insertion. Finally, the target products were determined, the PCR reactions were performed, and the library was completed. The sequencing data were then subjected to quality control using FastQC (version 0.11.5) [57]. The differentially expressed genes (DEGs) were identified using DESeq2 [58] (Version 18.2.0) in the R programming language. The Wald test was used to determine the p-values, which were then adjusted using the Benjamini–Hochberg (BH) method [59]. The significance was set at a fold change of |log2 fold change| ≥ 1 and padj < 0.05. The normalized gene expression data of all constructed libraries were used to detect the developmental dynamics genes (DDGs). The DDGs were found using the maSigPro package (version 1.46.0) [60,61], which applied a negative binomial model to the expression distribution and adjusted the false discovery rate using the Benjamini and Hochberg approach. The “Backward” approach was used to pick significant genes with alpha equal to 0.05. The examination of gene expression patterns was conducted following the design of a single series time course. The following settings were used to cluster gene patterns: counts = TRUE, min.obs = 19, and rsq = 0.6. The clusters for data portioning (k) function with k.mclust = TRUE were utilized to obtain the optimal number of clusters. To investigate the function of DEGs between the different H/L groups at 7 and 21 dpi, the ClusterProfiler package version 3.14 [62] and the org.Gg.eg.db package (version 3.14) [63] in R software was used to perform GO and KEGG pathway enrichment analyses. Based on the DEGs obtained from the comparative analysis of low and high H/L ratio groups from each dpi, GO and KEGG enrichment analyses were performed with a p-value of 0.05 stated as a threshold for significant enrichment. A weighted gene co-expression network analysis was performed on all samples’ normalized gene expression data using the WGCNA (version 1.41) package [64] in R software, with some minor modifications. Out of the 22 samples from the transcriptome analysis, 19 were used to perform the weighted gene co-expression network analysis. The Fragments Per Kilobase per Million (FPKM) was utilized as a standardized measurement of transcription abundance to construct a gene expression matrix with a total of 19 samples, including 10 and 9 samples from 7 and 21 dpi, respectively (7 dpi: 4 low H/L ratio and 6 high H/L ratio chickens; 21 dpi: 4 low H/L ratio and 5 high H/L ratio chickens). The WGCNA default function removed the genes with low expression. The topological overlap matrix (TOM) was constructed using the step-by-step network construction method (soft-threshold equal to 8), with a minimum module size of 30 for the module detection. Next, we generated a cluster dendrogram including the module colors and merged it dynamically. The modules’ colors were merged at 0.25. The cluster dendrogram of co-expression network modules was generated using hierarchical clustering of genes based on the 1−TOM matrix. To assess associations of co-expressed gene clusters with dpi, the 7 and 21 dpi groups were assigned nominal values of 1 and 2, respectively; for the gene clusters with H/L group, the low and high H/L ratio chicken groups were assigned nominal values of 0 and 1, respectively [65,66,67]. The association of co-expressed genes with the other traits was also evaluated. High absolute values of gene significance (|GS| > 0.5) and module membership (|MM| > 0.5) with a threshold of p-value < 0.01 were used to identify the driver genes [65,68]. Gene co-expression networks were determined using Cytoscape version 3.6.0 [69] with the edges and nodes provided by the WGCNA “exportNetworkToCytoscape” function. Next, the genes with a high weight based on the intramodular connectivity were identified as hub genes [70,71]. Dagu chickens were orally infected by Salmonella Typhimurium 21484 (ST, China Industrial Microbial Culture Preservation Center, Beijing, China) with 1 mL of PBS containing 1.5 × 1013 CFU of ST/mL at 14 days old. The chicks from the non-infected group were given the same volume of sterile PBS. In this work, the cecum of 6 chickens in the infection group and 6 chickens in the control group were randomly selected to extract RNA to verify the expression of candidate genes. The total RNA of the cecum was extracted by Trizol reagent (Invitrogen). RNA (1000 ng) was reverse transcribed by cDNA synthesis kit (TIANGEN) for quantitative real-time PCR. Primers were designed according to chicken coding region sequences and synthesized by The Beijing Genomics Institute (BGI), listed in Supplementary Table S7. Data were normalized to the expression of the housekeeping gene ACTB. Quantitative real-time PCR was performed in triplicate using the Invitrogen PowerUp™ SYBR® Green Master Mix (ABI) with the following cycle profile: 95 °C for 3 min, 40 cycles of 95 °C for 3 s, and annealing temperature for 34 s in the QuantStuio 7 Flex Real-Time PCR System (Waltham, MA, USA). The results were analyzed by 2−∆∆Ct method [72]. The data were analyzed using GraphPad Prism version 8 (GraphPad Software, San Diego, CA, USA) and R version 4.1. Two-way ANOVA with Sidak’s multiple comparisons analyzed differences between low and high H/L ratio groups at 7 and 21 dpi. Kruskal–Wallis’s sum rank test analyzed the four groups and detected significant differential abundance features at the phylum level. Assessment of DEGs, DDGs, and driver genes shared between different groups was performed using jvenn, an open-source online tool for comparing lists using Venn Diagrams (http://bioinfo.genotoul.fr/jvenn, accessed on 26 May 2021) [73]. The results are expressed as the mean and standard error of the mean (SEM). All significance was declared when p < 0.05.

PMC10003194

Zhiwei Chen,Qi Jiang,Guimei Guo,Qiufang Shen,Jun Yang,Ertao Wang,Guoping Zhang,Ruiju Lu,Chenghong Liu

Rapid Generation of Barley Homozygous Transgenic Lines Based on Microspore Culture: HvPR1 Overexpression as an Example

03-03-2023

Hordeum vulgare L.,microspore culture,transformation,doubled haploids,pathogenesis-related-1 gene

Obtaining homozygous lines from transgenic plants is an important step for phenotypic evaluations, but the selection of homozygous plants is time-consuming and laborious. The process would be significantly shortened if anther or microspore culture could be completed in one generation. In this study, we obtained 24 homozygous doubled haploid (DH) transgenic plants entirely by microspore culture from one T0 transgenic plant overexpressing the gene HvPR1 (pathogenesis-related-1). Nine of the doubled haploids grew to maturity and produced seeds. qRCR (quantitative real-time PCR) validation showed that the HvPR1 gene was expressed differentially even among different DH1 plants (T2) from the same DH0 line (T1). Phenotyping analysis suggested that the overexpression of HvPR1 inhibited nitrogen use efficiency (NUE) only under low nitrogen treatment. The established method of producing homozygous transgenic lines will enable the rapid evaluation of transgenic lines for gene function studies and trait evaluation. As an example, the HvPR1 overexpression of DH lines also could be used for further analysis of NUE-related research in barley.

Rapid Generation of Barley Homozygous Transgenic Lines Based on Microspore Culture: HvPR1 Overexpression as an Example Obtaining homozygous lines from transgenic plants is an important step for phenotypic evaluations, but the selection of homozygous plants is time-consuming and laborious. The process would be significantly shortened if anther or microspore culture could be completed in one generation. In this study, we obtained 24 homozygous doubled haploid (DH) transgenic plants entirely by microspore culture from one T0 transgenic plant overexpressing the gene HvPR1 (pathogenesis-related-1). Nine of the doubled haploids grew to maturity and produced seeds. qRCR (quantitative real-time PCR) validation showed that the HvPR1 gene was expressed differentially even among different DH1 plants (T2) from the same DH0 line (T1). Phenotyping analysis suggested that the overexpression of HvPR1 inhibited nitrogen use efficiency (NUE) only under low nitrogen treatment. The established method of producing homozygous transgenic lines will enable the rapid evaluation of transgenic lines for gene function studies and trait evaluation. As an example, the HvPR1 overexpression of DH lines also could be used for further analysis of NUE-related research in barley. Barley is the fourth largest cereal crop in the world and also one of the most important crops in China. It has been part of the modern agricultural industry technology systems of China since 2007 [1]. Cell engineering breeding based on anther and microspore culture is an important component of the barley breeding system and these techniques have been widely used in barley breeding and scientific research in China. This has been facilitated by improvements in microspore culture techniques, including genotype-independent microspore culture, and the combination of mutagenesis and hybridization with microspore culture to produce new DH lines [2,3,4,5]. Transgenesis is increasingly used in barley gene function analysis and breeding. However, it is time-consuming and laborious to obtain homozygous transgenic plants by traditional means. The production of doubled haploid (DH) plants from the T0 plants could substantially speed up the process, and transgenic DH plants could be selected without further consideration of heterozygosity. Thus, the production of DH plants would greatly improve the efficiency of transgenic-related research or breeding in barley and other crops. The Green Revolution based on the incorporation of dwarfing genes into breeding programs and the use of inorganic chemical fertilization (especially nitrogen fertilizer) has led to huge increases in crop yields [6]. However, this mode of crop production is now facing many problems [7,8] and new strategies for improving crop yield while reducing N inputs are receiving more attention. Previously, we found a special response of the barley pathogenesis-related 1 (HvPR1) gene to low nitrogen stress in the barley cultivar BI-04, based on RNA-seq data (NCBI accession number: PRJNA400519) [9]. In this study, we aimed to combine transgenesis with microspore culture to generate doubled haploid (DH, homozygous) transgenic barley plants overexpressing the HvPR1 gene, and verify its function in low nitrogen stress as well as its effects on nitrogen use efficiency (NUE). The workflow that was established will be beneficial to the study of gene function and breeding in barley, and also provide an example for other crops. The HvPR1 gene was cloned into the modified binary plasmid pCAMBIA1301-FLAG with a hygromycin resistance marker gene (Table 1). The recombinant plasmid was transformed into Agrobacterium tumefaciens and the Agrobacterium tumefaciens with the recombinant plasmid was used for the infection of immature embryos of the barley cultivar Golden Promise for genetic transformation. In total, eighteen T0 plantlets were regenerated and transplanted in an artificial climate room, and eleven of these survived to form seedlings (Figure 1A,B). These seedlings were screened by PCR amplification of the hygromycin resistance marker gene, and eight of them were positive (Figure 1B). A total of 46 DH0 plants (T1) were obtained just from the 10th T0 transgenic plant, and 43 of them survived to form seedlings (Table 2; Figure 1C). Among these surviving seedlings, 24 were shown to be transgenic (Figure 1D), and 9 of these grew to maturity and produced seeds. Therefore, a method was established for the efficient and rapid generation of homozygous transgenic barley plants based on microspore culture (Figure 1E). Considering the relatively small number of transgenic seedlings (T0 plants) and the statistics, PCR detection alone was used for transgenic detection. The transgenic rate was very high, indicating that the transgenic screening system was very effective. PCR and qPCR analysis were used together for the detection of transgenic DH0 lines. From the PCR detection, more than half of the plants were positive. However, fewer plants grew to maturity and produced seeds, indicating that some might not have completed chromosome doubling. This might have been caused by the barley genotype or weak growth due to the transgenesis. Seven transgenic DH0 lines with enough seeds (DH1 generation) were used for the qPCR analysis of the HvPR1 gene at seedling stage, and only two of them had significantly higher gene expression than the wild type (WT) (Figure 2A). This might be related to the microspore culture process and the differences between individual transgenic plants. Thus, the transgenic DH1 lines (T2) of 10–33 and 10–42 were taken for functional analysis of the HvPR1 gene. To verify the function of the HvPR1 gene under low nitrogen stress, the nitrogen use efficiency (NUE) and morphological traits were investigated under normal nitrogen (NN, control) and low nitrogen (LN) treatments at seedling stage (Figure 2). It was found that the NUE of WT and all DH1 lines increased under the low nitrogen treatment compared with the normal nitrogen treatment, but only WT and 10–35 (the negative transgenic DH1 line) were significant (Figure 2B). Comparing to the WT, it was found that the NUE of transgenic DH1 line of 10–42 was significantly lower than that of the WT under NN treatment, but the NUE of both 10–33 and 10–42 was significantly lower than that of WT under LN treatment (Figure 2B). In addition, there were no significant differences in NUE between WT and 10–35 under NN or LN treatment. For other traits, there were significant reductions in plant height (PH) and shoot dry weight (SDW) under the LN treatment compared with NN treatment in WT and all DH1 lines, and there were reductions in root dry weight (RDW) under the LN treatment compared to the NN treatment in WT and all DH1 lines, but this was only significant in 10–35. However, the root length (RL) was different, being significantly increased under LN treatment compared with NN treatment in all DH lines except the WT (Figure 2C–E). Compared with the WT, it was found that the PH of all DH1 lines was significantly reduced under both nitrogen treatments, while there were significant reductions in SDW in the 10–33 and 10–42 lines under NN treatment and significant reductions in SDW only in the 10–33 line under LN treatment. There were significant reductions in RDW only in the 10–35 line, and there were significant increases in RL in the 10–33 and 10–35 lines under NN treatment (Figure 2C–E). These results indicate that the inhibition of plant growth by LN treatment might be mainly reflected in shoots at first. The overexpression of the HvPR1 gene could inhibit plant growth even under the NN treatment, while the inhibition of NUE was mainly reflected under the LN treatment. The homozygosity of transgenes is necessary for phenotyping and trait evaluation. For a long time, scientists have tried to create homozygous transgenes quickly by genetically modifying haploid cells and then doubling them. Transformations based on anthers or microspores are most commonly used in barley [10,11,12,13]. However, the rapid generation of homozygous, transgenic T0 plants by the microspore culture of T0 pollens seemed to be the simpler option. Recently, the rapid generation of homozygous transgenic barley DH plants by anther culture of T0 pollen has also been reported [14]. However, microspore culture is more efficient and advantageous in producing DH plants [15]. Moreover, a microspore culture technology system that is genotype-independent and has a high rate of regeneration of green plants is now established, enabling more than one thousand DH plants to be derived from a single parent plant. This technology has become the main technical approach for barley DH line production used in scientific research and breeding in China [16]. Therefore, it may be more suitable to develop homozygous barley transgenics based on the microspore culture of T0 pollen. The Agrobacterium-mediated transformation of immature embryos of the variety Golden Promise is very successful and widely used [13]. In our study, eight of eleven T0 plants were positive by PCR detection (with a rate of about 73%), showing that the Agrobacterium-mediated transformation was very efficient. However, we only obtained DH plants from T0-6 and T0-10 plants. This was most likely due to the poor state of growth of these transgenic plants. Moreover, many transgenic DH0 lines from the T0-10 plants were sterile (with a rate of 62.5%), as were non-transgenic DH0 lines. The reduced fertility might be due to transformation [10]. Additionally, high rates of haploids were also observed in anther culture [14]. Normally, after transplanting in the nursery, regenerated seedlings are treated with 0.1% colchicine for chromosomal doubling, but this step is currently omitted due to the high rate of spontaneous chromosomal doubling of barley and the high efficiency of our culture system [3,15]. In this case, the artificial chromosomal doubling was necessary to improve the fertility of the regenerated green plants from the microspore culture of T0 pollen. In addition, there were high rates of albino plants in the anther culture [13,14], while this was not a problem in microspore culture. Considering the high efficiency of microspore culture and the difficulty of transformation of microspores, the establishment of a homozygous transgenic system based on the microspore culture of T0 pollen, especially genotype-independent microspore culture for the rapid generation of homozygous transgenic barley plants. Research on the PR1 gene mainly focuses on disease resistance in plants, while recent studies have shown that it may be involved in a variety of abiotic and biotic stresses [17,18]. However, the role of the PR1 gene in low nitrogen tolerance or nitrogen use efficiency in barley has not been reported. In this study, we found that the HvPR1 gene inhibited nitrogen use efficiency under low nitrogen treatment, and overexpression of HvPR1 also affected barley growth even under a normal nitrogen supply. Therefore, the acquisition of homozygous transgenic barley lines will be of great benefit for further research. At the same time, we also found that only two DH1 lines showed significant upregulation of the HvPR1 gene. This suggested the possibility of gene silencing or transgene loss, which had been reported previously [19]. This was not observed in anther culture using normal RT-PCR validation [14]. Leaves of barley cultivar BI-04 were used for RNA extraction. RNA extraction and cDNA synthesis were performed according to Chen et al. [20]. The cDNA was used as the template to clone the full length of HvPR1 cDNA (GenBank: Z21494.1). Its coding region, minus the stop codon, was further sub-cloned into the modified binary plasmid pCAMBIA1301-FLAG using the LR cloning system (Thermo Fisher Scientific, Waltham, MA, USA), according to He et al. [21]. pCAMBIA1301-FLAG also contains a hygromycin resistance marker gene. The primers used for gene cloning and vector construction are listed in Table 1. The recombinant plasmid was transformed into the Agrobacterium tumefaciens strain AGL1 and Agrobacterium tumefaciens with the recombinant plasmid used for the infection of immature embryos of the barley cultivar Golden Promise for genetic transformation according to Shen et al. [22]. The single colony of Agrobacterium AGL1 within the HvPR1 vector was cultured in liquid MG/L medium within Rifampicin and Kanamycin at 28 °C until the OD600 value was around 1.5. Barley spikes of Golden Promise were collected at 15 DAF, when the embryos were approximately 1–2 mm in diameter. Then, the immature seeds were sterilized with 70% ethanol and 10% sodium hypochlorite, respectively. The embryos were isolated from these sterilized seeds, and transferred into CI medium any antibiotics (the scutellum was placed upside). Then, a droplet of the prepared Agrobacterium was inoculated to each scutellum, then transferred to new plates within CI medium for cocultivation (the scutellum was placed downside). Approximately 3 days later, these co-cultured embryos were transferred to new CI medium with the antibiotics Timentin and Hygromycin, as well as copper for callus induction and selection. Yellowish, loosely structured, and distinctly granular calli were selected and transferred to T medium for two weeks. Then, calli with green regions or developing shoots were selected and transferred to modified B1 medium for regeneration. The regenerated barley T0 plants from transformation were transplanted in an artificial climate room, and these seedlings were confirmed by PCR amplification of the hygromycin resistance marker gene. This pair of primers for the hygromycin resistance marker gene is also listed in Table 1. The confirmed transgenic barley plants (T0) were further used as donor plants for microspore culture according to Lu et al. (Table 2) [3]. Spikes of the transgenic barley plants were collected at mid- to late-uninucleate microspore stage and stored in a refrigerator at 4 °C for 2–3 weeks. These spikes were surface-sterilized with 10% NaClO for 10 min and then rinsed with sterilized water. Approximately 300 anthers were separated and placed into 50 mL centrifuge tubes, and then the isolation buffer was added for microspore isolation. Microspore isolation buffer contained 60 g/L mannitol, 1.1 g/L CaCl2, 0.976 g/L MES and 20 mg/L colchicine. The isolated microspores were suspended with the induction medium and adjusted to a density of 5.0 × 105 microspores/mL. The induction media were mainly based on N6 medium with some modifications. A total of 1 mL or 3 mL of this microspore mixture was transferred into a Petri dish with size of 35 mm × 12 mm (smaller Petri dish) or 60 mm × 15 mm (bigger Petri dish) in size, respectively, then the Petri dishes were sealed with parafilm and incubated in darkness at 25 °C for callus induction. After approximately 19 days, the calli were transferred into 100 mL triangle flasks with 50 mL differentiation medium for plant regeneration at 25 °C under fluorescent lights with a 16 h photoperiod. The differentiation medium was 2/3 MS medium supplemented with kinetin at 1.5 mg/L, 6-BA at 0.5 mg/L, and NAA at 0.05 mg/L, with 30 g/L maltose as the carbon source, and solidified with agar at 6 g/L. Approximately two weeks later, the regenerated shoots were then transferred into 100 mL triangle flasks with 50 mL rooting medium at 25 °C under the fluorescent lights with a 16 h photoperiod for approximately one month. The rooting medium was 1/2 MS medium supplemented with MET (4 mg/L) and NAA (0.05 mg/L), with 30 g/L sucrose as the carbon source and solidified with agar at 6 g/L. Then, the regenerated plantlets (or R0 plants) were cultured in the 1/2 Hoagland nutritional liquid for 2–3 weeks in an artificial climate room. The microspore isolation buffer and introductive mediums were sterilized by filter sterilization, while the regeneration and rooting mediums were sterilized by high-temperature autoclaving (0.11 Mpa, 121 °C for 15 min), and all mediums were adjusted to pH 5.8. The seedlings after transplanting in the nursery were cultivated in pots within soil for harvesting seeds in artificial climate room. These plants were different transgenic DH0 lines and were analyzed by the PCR amplification of the hygromycin resistance marker gene as mentioned above. The WT and transgenic DH0 lines that could grow to maturity and produce seeds (DH1) were used for qPCR analysis. RNA extraction, cDNA synthesis, and qPCR procedures were mainly conducted according to Chen et al. [20]. Primers used for the HvPR1 gene and reference genes are listed in Table 1. The primers for the HvPR1 gene were designed by Primer-BLAST using the NCBI website, while primers for reference genes were directly taken from Chen et al. [9]. The two most stable reference genes, as calculated by geNorm, were used for normalization: HvGAPDH (glyceraldehyde-3-phosphate dehydrogenase) and HvTUBB6 (beta tubulin 6). The NRQ (normalized relative quantity) was calculated using this formula (NRQ = ). The transformed Cq′ values (Cq′ = log2 (1/NRQ)) were used for the comparisons, and the significant differences in gene expression between the wild type (WT) and the transgenic DH1 shoots were evaluated by the LSD test at the 0.05 level (p < 0.05). There were three biological replicates for WT and each transgenic DH1 line. Wild-type (WT) barley seeds and the DH1 seeds (10–33, 10–35 and 10–42) were sterilized with 1% NaClO for 30 min, then rinsed with water. After soaking in water for 6 h, seeds were germinated at 25 °C for one week. Seedlings were cultured in an artificial climate chamber, and the growth conditions and nitrogen treatments were mainly conducted according to Chen et al. [23]. NH4NO3 was used as the nitrogen source, and there were two nitrogen treatments: the normal nitrogen (NN) supply with 1.43 mM NH4NO3 (control) and low nitrogen (LN) stress with 0.24 mM NH4NO3. The low nitrogen treatment was started from the 3- to 4-leaf stage of seedling development for two weeks. The plants were then harvested, and plant height (PH) and root length (RL) were measured directly. Then, shoots (above grounds) and roots were separated and collected, respectively. There were ten biological replicates for the WT and DH1 lines, respectively. The separate shoots and roots were incubated at 105 °C for 1 h and dried at 80 °C for 2 days until constant weight; then, they were weighed for shoot dry weight (SDW) and root dry weight (RDW), respectively, using an electronic analytical balance. Every three dried shoots (three biological replicates) formed a new biological replicate, and nine dried shoots formed a total of three new biological replicates. The dried shoots were ground to powder and approximately 0.2 g of the dry powder of each sample was digested (H2SO4-H2O2) for total nitrogen determination using the Kjeldahl method. Based on the different definitions, the NUE was evaluated by the shoot biomass [24,25]. The shoot nitrogen content (SNC) (%, g N/100 g SDW) of each sample could be directly calculated from the total nitrogen detection. The NUE was calculated as follows: NUE (g) = SDW/SNC. This indicated that the higher dry weight and lower nitrogen content would result in higher N use efficiency. In summary, we established a method for the efficient and rapid generation of homozygous transgenic barley plants based on microspore culture. This method requires only one generation to obtain homozygous transgenic plants, and although microspore culture takes some time, far more time is saved because of the additional generations required for traditional methods. The planting scale is also small, which can use space more efficiently and save labor. Meanwhile, we also obtained homozygous HvPR1-overexpressing plants and demonstrated the role of this gene in response to low nitrogen stress in barley.

PMC10003195

Giulia Franzoni,Lorena Mura,Elisabetta Razzuoli,Chiara Grazia De Ciucis,Floriana Fruscione,Filippo Dell’Anno,Susanna Zinellu,Tania Carta,Antonio G. Anfossi,Silvia Dei Giudici,Simon P. Graham,Annalisa Oggiano

Heterogeneity of Phenotypic and Functional Changes to Porcine Monocyte-Derived Macrophages Triggered by Diverse Polarizing Factors In Vitro

28-02-2023

pig,macrophages,polarization,classical activation,IL-4,IL-10,TGF-β,dexamethasone,cytokines,surface markers,Toll-like receptors

Swine are attracting increasing attention as a biomedical model, due to many immunological similarities with humans. However, porcine macrophage polarization has not been extensively analyzed. Therefore, we investigated porcine monocyte-derived macrophages (moMΦ) triggered by either IFN-γ + LPS (classical activation) or by diverse “M2-related” polarizing factors: IL-4, IL-10, TGF-β, and dexamethasone. IFN-γ and LPS polarized moMΦ toward a proinflammatory phenotype, although a significant IL-1Ra response was observed. Exposure to IL-4, IL-10, TGF-β, and dexamethasone gave rise to four distinct phenotypes, all antithetic to IFN-γ and LPS. Some peculiarities were observed: IL-4 and IL-10 both enhanced expression of IL-18, and none of the “M2-related” stimuli induced IL-10 expression. Exposures to TGF-β and dexamethasone were characterized by enhanced levels of TGF-β2, whereas stimulation with dexamethasone, but not TGF-β2, triggered CD163 upregulation and induction of CCL23. Macrophages stimulated with IL-10, TGF-β, or dexamethasone presented decreased abilities to release proinflammatory cytokines in response to TLR2 or TLR3 ligands: IL-10 showed a powerful inhibitory activity for CXCL8 and TNF release, whereas TGF-β provided a strong inhibitory signal for IL-6 production. While our results emphasized porcine macrophage plasticity broadly comparable to human and murine macrophages, they also highlighted some peculiarities in this species.

Heterogeneity of Phenotypic and Functional Changes to Porcine Monocyte-Derived Macrophages Triggered by Diverse Polarizing Factors In Vitro Swine are attracting increasing attention as a biomedical model, due to many immunological similarities with humans. However, porcine macrophage polarization has not been extensively analyzed. Therefore, we investigated porcine monocyte-derived macrophages (moMΦ) triggered by either IFN-γ + LPS (classical activation) or by diverse “M2-related” polarizing factors: IL-4, IL-10, TGF-β, and dexamethasone. IFN-γ and LPS polarized moMΦ toward a proinflammatory phenotype, although a significant IL-1Ra response was observed. Exposure to IL-4, IL-10, TGF-β, and dexamethasone gave rise to four distinct phenotypes, all antithetic to IFN-γ and LPS. Some peculiarities were observed: IL-4 and IL-10 both enhanced expression of IL-18, and none of the “M2-related” stimuli induced IL-10 expression. Exposures to TGF-β and dexamethasone were characterized by enhanced levels of TGF-β2, whereas stimulation with dexamethasone, but not TGF-β2, triggered CD163 upregulation and induction of CCL23. Macrophages stimulated with IL-10, TGF-β, or dexamethasone presented decreased abilities to release proinflammatory cytokines in response to TLR2 or TLR3 ligands: IL-10 showed a powerful inhibitory activity for CXCL8 and TNF release, whereas TGF-β provided a strong inhibitory signal for IL-6 production. While our results emphasized porcine macrophage plasticity broadly comparable to human and murine macrophages, they also highlighted some peculiarities in this species. Macrophages are innate immune cells which were discovered in the late nineteenth century by Metchnikoff and named due to their phagocytic activity (“macro” (big) “phage” (eaters)) [1]. Later, it was observed that macrophages are involved in a wide array of functions, in tissue homeostasis, by clearing senescent cells, cellular debris, and repairing tissues after inflammation [2] and also in immune responses to infective and not infective stressors [3]. Macrophages are characterized by remarkable plasticity, and they can quickly change their function and phenotype in response to external stimuli [4]. The two antithetic extremes of activation states are represented by classically activated (M1) macrophages, characterized by increased microbicidal or tumoricidal capacity, and alternatively activated (M2) macrophages, associated with mechanisms of immunosuppression and wound repair [5]. In humans and mice, M2 macrophages have been generated in vitro by exposure to IL-4 and/or IL-13, whereas classical macrophage activation has been achieved in vitro by exposure to two signals: the first signal is the obligatory cytokine IFN-γ, whereas the second signal is TNF (itself or an TNF inducer). TLR agonists such as LPS can induce endogenous TNF production, and therefore, they are frequently used as the second signal to achieve classical activation [5]. This simplistic view of two potential statuses was subsequently refined with alternative activated macrophages being divided into subsets, such as M2a macrophages (following stimulation with IL-4 or IL-13), M2b macrophages (following exposure to immune complexes in combination with IL-1β or LPS), and M2c macrophages (stimulated with IL-10, TGF-β, or a glucocorticoid) [6]. Considering that exposure to diverse activators can lead to unique phenotypes [4,7], nomenclature based on the activator/s used, for example, M(IL-4), M(IFN-γ), M(IL-10), M(LPS), and M(Ig), has also been proposed [8]. Pigs share some anatomical and physiological similarities with humans, especially in the digestive, urinary, integumentary, and immune systems [9,10]. These similarities, combined with their manageable behavior and size, mean that pigs have been widely used in translational studies, such as preclinical evaluation of vaccine candidates and therapeutics [11,12] and preclinical toxicologic testing of pharmaceuticals or other chemicals [9,10]. The porcine model has been particularly relevant in studies focused on human sexually transmitted infection [13], as well as in nanomedicine-based studies [14,15]. Several studies have suggested that pig models are better than mouse models for understanding human innate immunity, and pigs have presented higher predictive values than rodents in preclinical studies [16]. For example, it has been described that porcine macrophages resemble human macrophages in their response to LPS, with a similar inducible gene expression profile [17,18]. Macrophage polarization in pigs has not been extensively analyzed. A better understanding of porcine macrophage polarization could help to improve translational studies and could aid the interpretation of in vitro and in vivo studies of host–pathogen interactions. In order to better benefit translational studies using this large animal model, we performed a detailed characterization of porcine macrophages following exposure to different polarizing stimuli. The ability of IFN-γ and LPS (classical activation) and “M2-related” polarizing factors to modulate porcine moMΦ phenotype and functionality was assessed though an integrative analytical approach, spanning microscopy, flow cytometry, multiplex ELISA, RT-qPCR, and qPCR array. Monocyte-derived macrophages (moMΦ) were left untreated, or stimulated with IFN-γ + LPS to generate classically activated macrophages (moM1). In parallel, moMΦ were stimulated with “M2 polarizing factors”, i.e., IL-4, IL-10, TGF-β, or dexamethasone. Twenty-four hours post-stimulation, the phenotypes of macrophage subsets were investigated with microscopy and flow cytometry. Microscopy revealed that all macrophage subsets presented with a spherical shape with short “hairy” protrusions on their surface (Figure 1 and Figure S1), in agreement with our previous work [19,20]. We observed that 24 h treatment with IFN-γ and LPS, IL-4, IL-10, TGF-β, or dexamethasone did not alter the dimension or granularity of the moMΦ (Figure 1), in agreement with our previous work [19,20]. Flow cytometry was employed to determine the phenotypic differences between macrophage subsets. Classical activation (IFN-γ and LPS) resulted in upregulation of MHC I, MHC II DR, and CD169, the last two both in terms of percentages of positive cells and mean fluorescence intensity (MFI) of positive cells (Figure 2 and Figure S2). IL-4 did not modulate expression of the tested surface markers, except for a downregulation of CD14 (in terms of MFI of positive cells), and CD163 (decrease percentage of positive cells), although the latter without statistical significance (Figure 2 and Figure S2). Stimulation with IL-10 modulated the surface expression of MHC I, MHC II DR, CD14, CD16, and CD163. As displayed in Figure 2 and Figure S2, IL-10 induced downregulation of CD14, and upregulation of CD163 and CD16 (all in terms of MFI), in agreement with our previous work [20]. Interestingly, in this study, we observed that IL-10 significantly upregulated MHC I but downregulated MHC II DR expression (Figure 2). In agreement with our previous work [20], we observed that TGF-β downregulated expression of CD14, MHC II DR, and CD163, but did not alter expression of MHC I and CD169 (Figure 2 and Figure S2). Stimulation of moMΦ with dexamethasone resulted in MHC II DR downregulation (MFI of positive cells), but enhanced expression of CD163 and CD14, both in terms of percentages of positive and MFI of positive cells (Figure 2 and Figure S2). To evaluate how macrophage stimulation with IFN-γ and LPS or diverse M2-related polarizing factors (IL-4, IL-10, TGF-β, and dexamethasone) modulated innate immunity, the RT2 Profiler PCR Array System covering 84 porcine cytokine and chemokine genes was employed: expression of several proinflammatory and anti-inflammatory interleukins (IL), chemokines, interferons (IFN), and members of the tumor necrosis factor family genes were investigated. The gene expression in each group was first normalized to the untreated control (moMΦ), and in Figure 3 up- and downregulated cytokine genes are presented. For each gene, the fold change normalized to the untreated control and the corresponding p-value are presented (Figure 3 and Table S4); fold changes >2.0 and p-value < 0.05 were considered to be significant variations. Scatter plots presenting fold changes of all 84 genes in each macrophage subsets compared to the untreated control are presented in Figures S3–S7, whereas the unsupervised hierarchical clustering analysis of gene expression changes in moMΦ stimulated with diverse polarizing factors is presented in Figure S8. Our results showed that stimulation with IFN-γ and LPS resulted in upregulation with fold change >2.0 of cytokine genes, including AMCF-II, CCL17, CCL19, CCL2, CCL20, CCL22, CCL3L1, CCL4, CCL5, CCL8, CSF2, CSF3, CXCL10, CXCL11, LOC396594, CXCL9, FASLG, IFNB1, IFNG, IL10, IL12A, IL12B, IL15, IL17F, IL18, IL1α, IL1β, IL2, IL22, IL23A, IL27, IL4, IL6, IL7, CXCL8, INHBA, LIF, LOC100515857, CCL23, CCL16, CXCL13, LTA, LTB, MSTN, SPP1, TNF, TGFβ1, TNFSF10, and VEGFA, with statistical significance (p < 0.05) for CCL2, CCL5, CCL8, CXCL10, LOC396594, IL10, IL7, and SPP1. Only three genes were downregulated in moM1 compared to the untreated control with fold change >2.0: CCL21 (p = 0.053818), IFN-ALPHA5 (p = 0.659246), and TGFβ2 (p = 0.030825) (Figure 3, Table S4, and Figure S3). Instead, stimulation with IL-4 resulted in enhanced expression (fold change > 2.0) of ADIPQ, BMP2, CCL17, CCL22, CCL3L1, CCL8, FASLG, IL18, IL27, IL6, CCL16, CXCL13, and TNFSF10, although with statistical significance only for BMP2 (p = 0.041345), and IL18 (p = 0.0362872). Six genes were downregulated in moM(IL-4) compared to the untreated control (fold changes > 2.0): CCL20, CCL21, CSF1, IL1β, IL2, and SSP1, all without statistical significance. A p-value < 0.1 was observed for CCL21 (p = 0.065265) (Figure 3, Table S4, and Figure S4). Our data revealed that stimulation with IL-10 led to enhanced expression (fold changes > 2.0) of CCL8, LOC396594, IL18, CXCL8, CXCL13, and TNFSF13B, with statistical significance only for LOC396594 (p = 0.018069), IL18 (p = 0.013221), and TNFSF13B (0.002243). Several cytokine genes were instead downregulated (with fold change > 2.0) in moM(IL-10) compared to the untreated control: ADIPOQ, CCL17, CCL2, CCL20, CCL21, CCL22, CCL3IL1, CCL4, CXCL10, CXCL11, CXCL9, IFN-ALPHA-5, IFNβ1, IL12β, IL13, IL1α, IL1β, CCL24, and MSTN, although none with statistical significance (Figure 3, Table S4, and Figure S5). Stimulation with TGF-β triggered significantly enhanced expression of BMP2, BMP3, CCL21, and TGF-β2, although with statistical significance only for TGF-β2 (p = 0.022099). Several cytokine genes were downregulated in moM(TGF-β) compared to the untreated control (fold change > 2.0): ADIPQ, AMCF-II, CCL1, CCL17, CCL20, CCL22, CCL3L1, CCL4, CCL8, CSF2, CXCL10, CXCL11, CXCL9, IFN-ALPHA-5, IFNβ1, IL13, IL15, IL18, IL1α, IL2, IL27, CXCL13, CCL24, LTA, and TNF, although with statistical significance only for IL15 (p = 0.0481119) (Figure 3, Table S4, and Figure S6). Stimulation with dexamethasone resulted in substantial upregulation of only two cytokine genes (fold change > 2.0): CCL23 (p = 0.008826) and CCL16 (p = 0.064898), whereas it triggered downregulation (fold change > 2.0) of 32 cytokine genes: ADIPQ, CCL1, CCL17, CCL2, CCL20, CCL22, CCL3L1, CCL4, CCL8, CD40LG, CSF1, CSF2, CXCL10, CXCL11, CXCL9, FASLG, IL18, IL1α, IL1β, IL2, IL4, IL7, CXCL8, INHBA, LIF, CXCL13, LTA, LTB, SPP1, TNF, and TNFSF10, although without statistical significance; a p-value < 0.1 was observed for IL18 (p = 0.063833), IL1α (p = 0.081704), and SPP1 (p = 0.084537) (Figure 3, Table S4, and Figure S7). Quantitative RT-PCR was then employed to investigate gene expression of selected cytokines over time (4, 8, and 24 h post-stimulation). First, we monitored induction of two major anti-inflammatory cytokines: IL-10 and IL-1Ra. In our previous study [20], we surprisingly observed that IL-10 expression was not released or induced in response to stimulation with IL-4, IL-10, or TGF-β. In this study, we observed that IL-10 was enhanced in moM1 compared to the untreated control, but was not enhanced following stimulation with the other cytokines (Figure 3 and Figure 4). In addition, RT-PCR data revealed that IL-4, IL-10, TGF-β, and dexamethasone induced IL-10 downregulation (Figure 4). We observed that stimulation with IFN-γ and LPS also induced expression of IL-1Ra at all tested timepoints, whereas it was upregulated at 4 h post IL-4 response (Figure 4). TGF-β stimulation resulted in a small but statistically enhanced expression of IL-1Ra, whereas it was downregulated by stimulation with IL-10 and dexamethasone (Figure 4). Modulation of two other members of the IL-1 superfamily, IL-1β and IL-18, was monitored. As expected, stimulation with IFN-γ and LPS enhanced expression of the proinflammatory IL-1β at all tested timepoints, whereas downregulation was observed in the other subsets. A similar trend was observed for two other proinflammatory cytokines, IL-6 and TNF (Figure S9). In agreement with the array data, RT-PCR results showed that IL-18 was upregulated in moM(IL4) and moM(IL10) compared to the untreated control (moMΦ), whereas the expression of this IL-18 was downregulated after stimulation with TGF-β (24 h) or dexamethasone (all timepoints) (Figure 4). Finally, we monitored expression of the chemokines CXCL13 and CCL23, and the TGF-β superfamily member TGF-β2. Array data revealed that CXCL13 expression was enhanced following 24 h stimulation with either IFN-γ + LPS, IL4, or IL10, although without statistical significance. Nevertheless, a 388.82-fold change was observed in moM(IL-10) compared to the untreated control, with a p-value of 0.084008 (Table S4). The expression of this chemokine was monitored over time on five different pigs and RT-PCR data showed that IFN-γ + LPS, IL-4, or IL-10 enhanced expression of this chemokine, at all tested timepoints (Figure 5). On the contrary, we observed CXCL13 downregulation 24 h post-stimulation with TGF-β and dexamethasone (Figure 5). Instead, we observed that CCL23 was significantly upregulated following stimulation with dexamethasone (Table S4); thus, RT-PCR was employed to monitor expression of this chemokine over time. Although we observed that this chemokine was upregulated following dexamethasone stimulation, upregulation was also observed after stimulation with IFN-γ + LPS (Figure 5). TGF-β2 was significantly upregulated 24 h post-stimulation with TGF-β, whereas it was downregulated in response to classical activation (IFN-γ + LPS). In agreement, RT-PCR data showed that IFN-γ + LPS triggered TGF-β2 downregulation, whereas TGF-β and dexamethasone both enhanced its expression of all tested timepoints (Figure 5). Multiplex ELISA was used to evaluate cytokine content in culture supernatants of moMΦ stimulated with diverse polarizing factors (24 h post-stimulation). In agreement with both array and qPCR results, we observed that stimulation with IFN-γ + LPS resulted in enhanced release of several proinflammatory cytokines: IL-1α, IL-1β, IL-6, CXCL8, IL-12, and TNF (Figure 6). A weak release of IL-18 was also detected in response to the IFN-γ + LPS treatment (Figure 6). Production of these cytokines was not observed in response to the either IL-4, IL-10, TGF-β, or dexamethasone treatment, with the exception of a small but statistically significant release of CXCL8 in response to IL-10 stimulation (Figure 6). In agreement with the gene expression data, small amounts of IL-10 were detected in culture supernatant of moMΦ stimulated with IFN-γ and LPS, but not following stimulation with either IL-4, TGF-β, or dexamethasone (Figure 6). In agreement with our previous work [20], significant higher levels of IL-10 were detected in the supernatants of IL-10-stimulated moMΦ; however, the amount detected 24 h post-stimulation (5.28 ± 1.68 ng/mL) was below the amount added to culture media at time 0 (20 ng/mL), suggesting that there was no de novo synthesis of this cytokine (Figure 6). A significant release of IL-1Ra was observed in response to stimulation with IFN-γ + LPS, but not IL-10, TGF-β, or dexamethasone (Figure 6). A small but statistically significant release of IL-1Ra was also observed in response to IL-4 stimulation (Figure 6). We employed multiplex ELISA to evaluate the impact of diverse polarizing factors on subsequent macrophage responses to Toll-like receptor (TLR) agonists. The moMΦ cells were left untreated, or they were stimulated with IFN-γ + LPS, IL-4, IL-10, TGF-β, or dexamethasone. Then, 24 h later, supernatants were removed, and cells were left untreated or activated with TLR ligands. After 24 h, culture supernatants were collected, and levels of proinflammatory and anti-inflammatory cytokines were determined using multiplex ELISA. As expected, TLR2 and TLR3 genes were both highly expressed in porcine moMΦs (Table S5), and thus ligands against both receptors were used in this study: the diacylated lipopeptide MagPam2Cys_P80 was used as a TLR2 ligand [21], and polyinosinic-polycytidylic acid (Poly I:C) was employed as a TLR3 ligand. Levels of proinflammatory (IL-1α, IL-1β, IL-6, CXCL8, IL-12, and TNF) or anti-inflammatory (IL-10 and IL-1Ra) in culture supernatants of macrophage subsets untreated or stimulated with MagPam2Cys_P80 or Poly I:C are presented in Figure 7 and Figure 8, respectively. We observed higher levels of IL-1α, Il-1β, CXCL8, and IL-12, in culture supernatants of macrophages stimulated with IFN-γ + LPS (moM1) compared to the untreated control (moMΦ) in the absence of subsequent stimulation. This was expected, because stimulation with IFN-γ + LPS triggered release of several proinflammatory cytokines, as presented in Figure 6, and release of some of them continued beyond 24 h post-stimulation. MoM1 presented an enhanced ability to release IL-12 compared to the untreated control (moMΦ) in response to either MagPam2Cys_P80 or Poly I:C (Figure 7 and Figure 8). Interestingly, our data revealed that moM1 possessed a reduced ability to release TNF in response to both of the agonists (Figure 7 and Figure 8). This might be linked to the reduced expression of TLR2 and TLR3 genes in moM1 compared to the untreated control (moMΦ) at the time of treatment with TLR agonists (24 h post-stimulation with IFN-γ + LPS) (Figure S10). Stimulation with IL-4 did not statistically significantly impair the ability of moMΦs to release IL-1α, IL-1β, IL-6, CXCL8, and IL-12 in response to MagPam2Cys_P80 lipopeptide (Figure 7), although a trend was observed for IL-1β and IL-12. Nevertheless, moM(IL-4) presented a statistically significant lower ability to release TNF in response to the TLR2 agonist compared to the untreated control (moMΦ). This may be linked to the reduced expression of TLR2 in moM(IL-4) compared to the untreated control (moMΦ) at the time of treatment with MagPam2Cys_P80 lipopeptide (Figure S10). Treatment with this cytokine did not alter macrophage ability to release proinflammatory cytokines in response to Poly I:C (Figure 8). In accordance with our previous study [20], we observed that MoM(IL-10) presented a reduced ability to release IL-1α, IL-1β, IL-6, CXCL8, IL-12, and TNF in response to MagPam2Cys_P80 compared to the untreated control (moMΦ), although without statistical significance only for IL-1α, IL-1β, and IL-6 (Figure 7). Treatment with this immunosuppressive cytokine also resulted in a statistically significant reduced ability to release IL-12 and TNF in response to Poly I:C stimulation (Figure 8). Stimulation with TGF-β did not statistically significantly impair the ability of moMΦs to release IL-1α and IL-1β, in response to MagPam2Cys_P80 lipopeptide (Figure 7), in agreement with our previous work [20]. Nevertheless, moM(TGF-β) presented a reduced ability to release IL-6, IL-12, and TNF in response to the TLR2 agonist compared to the untreated control (moMΦ), although without statistical significance for IL-12 (Figure 7). TGF-β treatment did not alter the release of CXCL8 in response to either MagPam2Cys_P80 or Poly I:C (Figure 7 and Figure 8), and no differences were observed between the untreated control (moMΦ) and moM(TGF-β) in the release of IL-6, IL-12, and TNF in response to Poly I:C stimulation (Figure 8). Treatment with dexamethasone reduced the ability of macrophages to release proinflammatory cytokines in response to external stimuli. The moM(dexamethasone) presented a reduced ability to release IL-12 compared to the untreated control (moMΦ) in response to either MagPam2Cys_P80 or Poly I:C, with statistical significance (Figure 7 and Figure 8). In addition, treatment with this glucocorticoid reduced the release of IL-1α and IL-6 in response to stimulation with MagPam2Cys_P80, although IL-6 without statistical significance (Figure 8). Interestingly, moM(dexamethasone) released statistically significant lower levels of TNF compared to the untreated control (moMΦ) in response to MagPam2Cys_P80, but not Poly I:C (Figure 7 and Figure 8). Very weak release of IL-18 was detected in response to both TLR agonists and we did not detect statistically significant differences between macrophage subsets (Figure S11). We observed higher levels of IL-10 culture supernatant of the moM(IL-10) subset (Figure 6). Levels detected were extremely low (<0.2 ng/mL); thus, we might speculate that was not the result of de novo synthesis of this cytokine, but rather a residual of the original quantity added at time 0 (20 ng/mL). Similar levels were also observed in culture supernatants of moM(IL-10) after stimulation with either MagPam2Cys_P80 or Poly I:C. The moM1 presented enhanced ability to release low levels of IL-10 in response to TLR2 stimulation compared to the untreated control (moMΦ). On the contrary, moM(IL-4) and moM(TGF-β) both released lower levels of this immunosuppressive cytokine compared to the untreated control, in response to either the TLR2 or TLR3 agonist. Stimulation with dexamethasone resulted in decreased levels of IL-10 in culture supernatants compared to the untreated control (moMΦ) following stimulation with Poly I:C (Figure 7 and Figure 8). Higher levels of the receptor antagonist IL-1Ra were detected in culture supernatants of macrophages stimulated with IFN-γ + LPS (moM1) compared to the untreated control (moMΦ) in the absence of subsequent stimulation (Figure 7). This was expected, because stimulation with IFN-γ + LPS triggered release of this cytokine (Figure 6), and its release likely continued beyond 24 h post-stimulation. Stimulation with MagPam2Cys_P80 triggered little release of IL-1Ra, which was reduced by pretreatment with IL-4 or IL-10. Instead, stimulation with Poly I:C promoted a substantial release of IL-1Ra, which was reduced, with statistical significance, by pretreatment with all the tested polarizing factors (IFN-γ + LPS, IL-4, IL-10, and dexamethasone), except for TGF-β (Figure 7 and Figure 8). Macrophages are a heterogeneous family of cells which are characterized by remarkable plasticity and versatility and are capable of responding to different microenvironmental signals by quickly modifying their phenotype and function [4]. Diverse macrophage subsets can either orchestrate or counteract inflammation [4]. Despite the increasing importance of pig biomedical models, very few studies have investigated macrophage polarization in this species. Previous studies have reported that classically activated porcine macrophages are characterized by enhanced expression of MHC class I and II molecules, activation markers (CD25), and co-stimulatory molecules [22], whereas few studies have investigated the impact of IL-4 or others “M2-related” polarizing factors in pigs [20,22,23]. In this study, we aimed to provide a deeper portrait of the phenotypic and functional changes of porcine moMΦ triggered by either IFN-γ + LPS (classical activation) or by diverse “M2-related” polarizing factors: IL-4, IL-10, TGF-β, or dexamethasone. Microscopy and flow cytometry were employed to analyze the effects of these five polarizing factors on moMΦ shape. We observed that exposure to IFN-γ + LPS resulted in slightly enhanced formation of cell clusters, as previously described [22], and we reported that neither IL-4, IL-10, TGF-β, nor dexamethasone altered moMΦ dimension or granularity, in agreement with our previous studies [19,20]. Singleton and colleagues reported that stimulation with IL-4 increased the numbers of elongated projections in macrophages [22], although we were unable to appreciate them in our study. Flow cytometry was employed to analyze the effects of the diverse stimuli on the expression of six surface markers. MHC class I and II DR expression was investigated since this can influence antigen presentation. MHC I and MHC II DR were upregulated by stimulation with IFN-γ + LPS, but not IL-4, in agreement with results previously published in pigs [19,23]. MHC II DR expression was downregulated by stimulation with IL-10, TGF-β, or dexamethasone, in line with the immune-suppressive activities of these molecules. CD14 is the receptor for LPS, and it is involved in clearance of Gram-negative bacteria [24]. We observed that this marker was downregulated by IL-4 (in agreement with that observed by Garcia-Nicolas and colleagues (2014) [23]), IL-10, or TGF-β stimulation, in agreement with our previously published work [20]. In this work, we observed that dexamethasone substantially upregulated CD14 expression, which contrasted with observations that have been described in humans, where researchers have observed that this glucocorticoid downregulated surface levels of CD14 on the human-transformed cell line THP-1 (a leukemia monocytic cell line) [25]. Further studies should investigate this peculiarity of pigs and whether higher doses of this glucocorticoid might have different impacts on this glycoprotein expression. CD16 is a low-affinity receptor for the IgG Fc, which facilitates antibody opsonization and antibody-dependent cellular cytotoxicity [26]. Our data revealed that stimulation with IL-10 and dexamethasone, but not TGF-β or IL-4, resulted in enhanced expression of CD16, in agreement with other previous publications in pigs [20,23]. Human macrophages exposed to IL-10 similarly presented enhanced expression of these markers compared to untreated macrophages or those exposed to IFN-γ + LPS [27,28]. CD163 is a scavenger receptor and it is often associated with anti-inflammatory macrophage phenotype [29]. In pigs, it has been reported that IL-4 stimulation triggered CD163 downregulation on macrophages [23], and we also observed little decrease in the expression of this scavenger receptor in moM(IL-4) compared to the untreated control (moMΦ), although without statistical significance. We observed that stimulation with IL-10, but not TGF-β, resulted in enhanced expression of this scavenger receptor, in agreement with our previous publication [20]. Porcine moMΦ treated with dexamethasone also presented increased CD163 expression, similarly to observations reported in pig monocytes and derived macrophages [22,30] and the immortalized porcine macrophage cell line IPKM [31]. As stated above, human M2 macrophages are characterized by high level expression of this scavenger receptor [32], but differences between subsets have been observed; it has been described that stimulation with IL-10 or dexamethasone, but not TGF-β, enhanced surface expression of this marker on human macrophages [33,34,35], similar to our observations in pigs. CD169 (SIGLEC1) contributes to antigen presentation and lymphocyte activation [36,37]. We observed that CD169 expression was significantly enhanced only after stimulation with IFN-γ + LPS. This is line with descriptions in humans and rodents, where CD169 upregulation on macrophages has been achieved by stimulation with either type I or type II IFNs [37]. In humans, it has been described that glucocorticoids could increase the expression of CD169 [7], and in pigs, Singleton et al. (2018) observed that dexamethasone enhanced the surface levels of this molecule on monocytes, although at notably higher doses than used in this study [30]. We further assessed the immunomodulatory effects of IFN-γ + LPS, IL-4, IL-10, TGF-β, or dexamethasone on porcine moMΦ through gene expression studies. The expression of 84 cytokine genes, including several proinflammatory or anti-inflammatory interleukins, chemokines, interferons, and tumor necrosis factor family members, were evaluated using PCR arrays 24 h post-stimulation. Expression of selected genes was also monitored over time with RT-PCR, as well as release of key immune cytokines through ELISA. As expected, classical activation enhanced expression and release of several proinflammatory cytokines; elevated levels of IL-1β, IL-6, IL-12, IL-23, and TNF are indeed regarded as a hallmark of M1 polarization in humans and mice [32,38]. Increased expression of several chemokines, CCL2, CCL4, CCL5, CCL8, CCL20, CCL23, CXCL8, and CXCL10 was observed, which reflected the proinflammatory phenotype of these cells. Only a few genes were downregulated in moM1 compared to the untreated control with p-value < 0.1: CCL21 and TGF-β2. TGF-β2 is one of the three isoforms of TGF-β [39] and in humans it has been observed that IFN-γ reduced both basal- and IL-4-stimulated release of TGF-β2 by bronchial epithelial cells [40]. However, CCL21 downregulation was unexpected, since in humans this chemokine has promoted chemotaxis of M1 but not M2 macrophages [41]. CCL21 downregulation might be a protective mechanism as it may limit recruitment of M1 in the inflammatory sites, preventing exacerbated and pathological inflammation. IL-4 stimulation of macrophages gave rise to a different phenotype, characterized by significant (p < 0.05) upregulation of just two cytokine genes: BMP2 and IL-18. Bone morphogenetic protein 2 (BMP-2) is a member of the TGF-β superfamily and it plays an important role in the development of bone and cartilage [42]. Enhanced levels of this cytokines are in line with “M2 polarization”, which is associated with osteogenesis and promotion of bone mineralization [43]. In addition, in mice, it has been described that BMP-2 decreased expression of M1 phenotypic markers, such as IL-1β, IL-6, and iNOS, in M1-polarized macrophages, whereas it enhanced expression of the enzyme Arginase 1 (Arg-1), suggesting this protein may shift macrophages to M2-like phenotypes [44]. IL-18 is a member of the IL-1 superfamily and a potent inducer of IFN-γ; it is a proinflammatory, but not pyrogenic, cytokine. It synergizes with IL-12 to activate NK cells and cytotoxic T cells [45], but it has been described that it can enhance other T-cell responses, such as Th17 cells, in synergy with IL-23 or Th2 responses [46]. In humans, classical (M1) and not alternative (M2) activation triggers upregulation of this proinflammatory cytokine [32], whereas in pigs we observed that IL-4 and IL-10 both enhanced its expression. However, increased IL-18 gene expression in response to IL-4 or IL-10 treatments was not associated with enhanced IL-18 protein levels in culture supernatants of moM(IL-4) or moM(IL-10) compared to the untreated control (moMΦ). This suggests that factors at a post-transcriptional level counteract the release of this cytokine. In humans and rodents, it has been described that activation with IL-4 was characterized by enhanced expressions of IL-10 and the chemokines CCL17 and CCL22, the latter two inhibited by IFN-γ [1,32,38]; however, in this study, we observed that IL-4 did not enhance expression of IL-10. ELISA data confirmed the absence of IL-10 release in response to IL-4 stimulation, whereas a small but statistically significant release was seen in culture supernatants of moM1. Array data revealed that IL-4 enhanced (fold changes > 2.0) CCL17 and CCL22 expressions, although without statistical significance. In addition, stimulation with IFN-γ + LPS also resulted in enhanced expression of both chemokine genes. Our data highlighted interesting peculiarities of this species and suggest that neither IL-10, CCL17, nor CCL22 can be used as hallmarks of M(IL-4) polarization in pigs. As stated above, IL-10 is regarded as a potent immune-suppressive cytokine, which limits production of proinflammatory interleukins, chemokines, and TNF (formerly known as TNF-α) [47]. In line with this immunosuppressive phenotype, our array data revealed that IL-10 stimulation promoted downregulation of several proinflammatory cytokines, and triggered significant upregulation of a few cytokine genes, including IL-18. We unexpectedly observed upregulation of this proinflammatory IL-1 family member 24 h post-stimulation with IL-10, similar to that observed in moM(IL-4), although no enhanced levels of IL-18 protein were observed in culture supernatants. This is an interesting peculiarity of pigs, and future studies should better investigate whether alternative macrophage activation in this species is characterized by induction of IL-18 and not IL-10, which is the opposite of that observed in humans and mice [32,47]. Exposure to TGF-β resulted in downregulation of several proinflammatory cytokines, in line with the immunosuppressive action of these molecules on macrophages described either in humans [48] or in pigs [20]. Array data showed that only one cytokine gene was upregulated with p-value < 0.05: TGF-β2. TGF-β2 is a member of the TGFβ superfamily [39] and it is characterized by anti-inflammatory activity [49]. Accordingly, its enhancement reflects the immunosuppressive phenotype of moM(TGF-β). Glucocorticoids are drugs that have been developed to switch inflammation off [7]; thus, it was not unexpected to observed that stimulation with dexamethasone gave rise to a macrophage phenotype characterized by downregulation (fold change > 2) of 32 out of 84 tested cytokine genes. Only one gene was upregulated with statistical significance (p < 0.05): CCL23. CCL23 is a chemokine with immunosuppressive activity that, in humans, inhibits myeloid progenitor cell development and promotes selective recruitment resting T lymphocytes and not activated T lymphocyte monocytes [50,51]. Although this is in line with the anti-inflammatory phenotype of moM(dexamethasone), it was interesting to observe that none of the other tested “M2-related” polarizing molecules enhanced CCL23 expression. In humans, instead, it has been reported that IL-4 and IL-13 could both induce CCL23 production by monocytes [52]. In addition, our RT-PCR data showed that CCL23 was upregulated following IFN-γ + LPS stimulation. These results further emphasized the heterogeneity of the macrophage family and revealed further species differences. In humans and mice, stimulation of macrophages with IL-10, TGF-β, and glucocorticoids are associated with enhanced expression and release of IL-10 [32], but we did not observe this in pigs. These data agree with our previous studies on IL-10 and TGF-β [20], and here, we expanded our observation to dexamethasone. Thus, we tested induction and release of another potent immunosuppressive cytokine: IL-1Ra. IL-1Ra is a receptor antagonist. It binds IL-1R1 with higher affinity than that of IL-1α or IL-1β, but without activation of the IL-1 signaling and the subsequent activation of inflammatory responses [45,53]. High levels of IL-1Ra were released following stimulation with IFN-γ + LPS, and it could be speculated that this was a protective mechanism developed by macrophages. MoM1 are characterized by elevated release of IL-1α, IL-1β, and other proinflammatory cytokines (IL-6, CXCL8, and IL-12); thus, IL-1Ra is likely released to counteract their activity, in order to avoid pathogenic inflammatory responses. We observed that IL-1Ra was only modestly expressed and released by moM(IL-4) compared to the untreated control, and none of the tested immunosuppressive molecules enhanced its release. Stimulation with IL-10, but not TGF-β or dexamethasone, promoted its expression over time. In other species, in contrast, IL-1Ra is associated with alternative (IL-4) and not classical activation of macrophages [1,32,54]. It is interesting to observe that stimulation of porcine macrophages with IL-4 induced only a little induction/release of IL-1Ra, which was sustained in moM1, but instead promoted expression of another IL-1 family member: IL-18. Future studies should better understand factors underling this peculiarity of pigs and whether it is extended to other members of the IL-1 family. In the final part of the study, we investigated the functionality of the different macrophage subsets generated by exposure to diverse stimuli. TLRs are a family of pattern recognition receptors that recognize pathogen-associated molecular patterns (PAMPs), with subsequent activation of signaling cascades which culminate in inflammasome activation, and consequent inflammatory responses [55,56]. In this study, we investigated the ability of the six diverse macrophage subsets to release proinflammatory cytokines in response to either a TLR2 ligand (MagPam2Cys_P80) or a TLR3 ligand (Poly I:C). In our previous studies, we observed that moM(IL-10) and moM(TGF-β) differed in their ability to release proinflammatory cytokines in response to both the TLR2 and the TLR4 agonist stimulation; proinflammatory cytokine release was drastically impaired by IL-10, but to a much lower extent by TGF-β [20]. Although differences between tested animals were observed, our data revealed that IL-4 presented only a limited impact on the macrophage’s ability to respond to external stimuli, whereas moM(IL-10) presented a marked anti-inflammatory phenotype, with reduced ability to release proinflammatory cytokines in response to either MagPam2Cys or Poly I:C stimulation, in agreement with our previous work [20]. MoM(TGF-β) presented a less marked anti-inflammatory phenotype compared to moM(IL-10): exposure to TGF-β did not statistically significantly impair the ability of moMΦs to release IL-1α and IL-1β in response to MagPam2Cys_P80 lipopeptide, in agreement with our previous work [20], and it downregulated IL-12 release in response to the tested TLR ligand with less intensity compared to IL-10 or dexamethasone. These differences are in line with the pleiotropic nature of TGF-β that possesses regulatory and inflammatory activities (in the presence of IL-6, this cytokine can indeed drive the differentiation of Th17 cells, further promoting inflammation) [57]. In this work, the ability of dexamethasone to impair porcine macrophage response to either TLR2 or TLR3 ligands was also analyzed, and we observed that this glucocorticoid presented a reduced ability of macrophages to release proinflammatory cytokines in response to the tested PAMPs in a similar manner compared to IL-10. These data are in line with the anti-inflammatory activity of these types of molecules. Finally, the release of anti-inflammatory cytokines was tested. Although we observed differences between the three tested blood donor pigs, our data revealed that neither MagPam2Cys_p80 nor Poly I:C promoted release of IL-10, as expected, whereas Poly I:C induced enhanced release of IL-1Ra from macrophages. This is in line with results described in humans and mice, where researchers have observed that stimulation with Poly I:C activated TLR3, with subsequent intracellular signaling that resulted in activation of transcription factors IRF3 and NF-κβ, triggering enhanced expression of the receptor antagonist IL-1Ra [58]. We observed that either classical activation (IFN-γ and LPS) or “M2 polarizing factors” decreased TLR3-mediated IL-1Ra release, with the exception of TGF-β. It has been described that TGF-β promoted the induction of IL-1Ra, likely in an IL-1 dependent manner [59]; thus, it was perhaps not unexpected that IL-1Ra release from TLR3 stimulated porcine moM(TGF-β) was unaffected. Overall, we observed differences between stimulation with IFN-γ + LPS (M1) and “M2-related” factors, and also between immunosuppressive molecules, such as IL-10, TGF, and dexamethasone. Our data also suggest it would be more appropriate to apply nomenclature linked to the activator(s) used, such as M(IL-10), M(IL-10), M(TGF-β), M(dexamethasone), as suggested by Murray et al. (2014) [8], to porcine macrophages. Six cross-bred pigs (Sus scrofa domesticus) of either sex, aged 6–18 months old, were used as blood donors for in vitro experiments. Pigs were housed at the Experimental Station of Istituto Zooprofilattico Sperimentale (IZS) of Sardinia (“Surigheddu”, Sassari, Italy). Animal husbandry, handling, and procedures (bleeding) were carried out according to the Italian Legislative Decree No. 26 dated 4 March 2014 and in agreement with the Guide of Use of Laboratory Animals issued by the Italian Ministry of Health (authorization No. 1232/2020-PR). Heparinized blood samples were used for generation of monocyte-derived macrophages (moMΦ) (described in Section 4.2). Animal health was routinely monitored by trained veterinarians, and blood samples were screened for several porcine pathogens. The absence of African swine fever (ASFV), porcine parvovirus (PPV), and porcine circovirus 2 (PCV2) genome was evaluated though qualitative real-time PCR, as previously described [21,60], with primers reported in the Table S1 [61,62,63]. The absence of the porcine reproductive and respiratory syndrome virus (PRRSV) and Mycoplasma hyopneumoniae was monitored using commercial real-time PCR kits (LSI VetMAX™ PRRSV EU/NA and VetMAX™-Plus qPCR Master Mix, both Thermo Fisher Scientific, respectively), following the manufacturer’s instructions [21]. Monocyte-derived macrophage (moMΦ) cultures were obtained from blood leukocytes using Petri dishes and through the addition of 50 ng/mL of recombinant human M-CSF (hM-CSF) (Thermo Fisher Scientific, Waltham, MA, USA) to the culture media (RPMI-1640 supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin, and 100 μg/mL streptomycin (complete RPMI, cRPMI), as we previously described [21,64,65]. The moMΦ cells were seeded in 12-well plates (Greiner CELLSTAR, Sigma-Aldrich, Saint Louis, MO, USA) (1 × 106 live cells per well) or 4-well chamber slides (Nunc Lab-Tek chamber slide system, Thermo Fisher Scientific) (3 × 105 live cells per well). After seeding, cells were cultured in unsupplemented fresh cRPMI at 37 °C, 5% CO2, then 24 h later, the moMΦs were left untreated, or they were stimulated for 24 h with several polarizing factors. The moM1 cells were generated using recombinant porcine IFN-γ (Raybiotech Inc, Norcross, GA, USA) and LPS (lipopolysaccharide from Escherichia coli 0111:B, Sigma-Aldrich), both at 100 ng/mL [19,22,34,65]. Other monocyte-derived macrophage subsets were generated though supplementation of the culture media with “M2-related” polarizing factors, recombinant porcine IL-4, IL-10, TGF-β (all R&D Systems, Minneapolis, MN, USA) [19,20,65], or dexamethasone (Sigma-Aldrich), all at 20 ng/mL. Cell morphology was investigated on macrophage subsets seeded in 4-well chamber slides, 24 h post-stimulation, by either fluorescence or phase-contrast microscopy. For fluorescence microscopy, macrophages were fixed with 4% paraformaldehyde, washed with PBS, and subsequently labeled with Alexa Fluor 488 conjugated phalloidin and Hoechst (both Molecular Probes, Thermo Fisher Scientific, Rockford, IL, USA) to visualize actin cytoskeleton or nuclei, respectively [20]. Microscopy was carried out using an inverted stereo microscope (Olympus IX 70, Segrate, Italy) with magnification 40× objective and processed with the LAS AF Lite software 1.0.0(Leica Microsystem, Wetzlar, Germany), as previously reported [20]. For light microscopy, macrophage subsets were fixed with 4% paraformaldehyde, washed with PBS, and phase-contrast images were acquired using an inverted microscope (Olympus IX70, Segrate, Italy) equipped with a 20×/0.40 numeric aperture objective lens [21]. Flow cytometry was performed to determine the expression of cell surface markers, as well as dimension and granularity, as previously published [20,21]. In detail, the moMΦ were seeded in 12-well plates, and then they were stimulated (see Section 4.2). Then, the cells were harvested with 10 mM EDTA in PBS and transferred to 5 mL round bottom tubes (Corning, Corning, NY, USA). Cells were first stained with Zombie Aqua viability dye (BioLegend, San Diego, CA, USA) (30 min, room temperature), then they were washed with PBS supplemented with 0.5% bovine serum albumin (BSA), and subsequently stained with several murine monoclonal antibodies (mAbs): anti-porcine CD16-PE (clone G7, Thermo Scientific Pierce, Rockford, IL, USA), anti-human CD14-PerCP-Cy5.5 (clone Tuk4, Miltenyi Biotec, Bergisch Gladbach, Germany) [66], CD163-PE (clone 2A10/11, Bio-Rad Antibodies, Kidlington, UK), CD169-FITC (clone 3B11/11, Bio-Rad Antibodies), anti-pig MHC I (clone JM1E3, Bio-Rad Antibodies), and anti-pig MHC II DR (clone 2E9/13, Bio-Rad Antibodies) (Table S2). MHC I and MHC II DR expressions were visualized by subsequent staining with BV421 rat anti-mouse IgG1 (clone A85-1, BD Horizon BD Biosciences, Franklin Lakes, NJ, USA) or BV786 rat anti-mouse IgG2b (clone R12-3, BD Horizon BD Biosciences), respectively. All mAbs were incubated with cells for 15 min at 4 °C, cells were washed with PBS supplemented with 2% FBS, and resuspended in PBS supplemented with 2 mM EDTA. Analysis was carried out using a FACS Celesta flow cytometer (BD Biosciences), acquiring 5000 live moMΦs. Data analyses were performed using the BD FACS Diva Software 8.0 (BD Biosciences), by exclusion of doublets, gating on viable moMΦ, and then assessing the staining for surface markers [20,21]. Monocyte-derived macrophages (moMΦ) were left untreated or they were stimulated with diverse polarizing factors: IFN-γ + LPS, IL-4, IL-10, TGF-β, or dexamethasone (as described in Section 4.2). Then 24 h later, cytokine contents in culture supernatants were determined using multiplex ELISA, as previously described [21,64,65]. In brief, culture supernatants were removed, centrifuged at 2000× g for 3 min to remove cell debris, and stored at −80 °C until analyzed. Levels of IL-1α, IL-1β, IL-1Ra, IL-6, CXCL8, IL-10, IL-12, IL-18, and TNF were quantified using the Porcine Cytokine/Chemokine Magnetic Bead Panel Multiplex assay (Merck Millipore, Darmstadt, Germany) and a Bioplex MAGPIX Multiplex Reader (Bio-Rad, Hercules, CA, USA), according to the manufacturers’ instructions. The moMΦ cells were seeded in 12-well plates, and then left untreated or they were stimulated with diverse polarizing factors: IFN-γ and LPS, IL-4, IL-10, TGF-β, or dexamethasone (as described in Section 4.2). Then, 4, 8, and 24 h later, cells were harvested to evaluate gene expression of selected cytokines and TLRs. The RNeasy Mini Kit (QIAGEN, Hilden, Germany) was employed to extract total RNA, which was eluted in 50 µL of ultrapure RNase-free water. 250 ng of the obtained purified RNA was used as the template for cDNA synthesis, as previously described [21]. Subsequently, RT-qPCR was employed to determine the expressions of several cytokine genes (IL-1β, IL-1RA, IL-10, IL-18, TGF-β2, CXCL13, CCL23, IL-6, TNF, TLR2, and TLR3), using the primer sets listed in the Table S6 [67,68,69,70,71,72]. For all tested genes, five independent experiments using different blood donor animals were performed. In each sample, the relative gene expression levels were calculated from Cq (quantification cycle) values using the classical and widely adopted 2−∆∆Cq method [21,70,73]. PCR arrays for 84 genes related to pig cytokines and chemokines were measured on macrophage subsets generated using three blood donor pigs. For each animal, six macrophage subsets were obtained: moMΦ, moM1 (IFN-γ + LPS), moM(IL-4), moM(IL-10), moM(TGF-β), and moM(dexamethasone). RNA was extracted from the cell monolayers using an miRNAeasy Mini Kit (QIAGEN). Genomic DNA was digested using an RNase-Free DNase set (QIAGEN). The concentration of RNA was determined using a Qubit 4 fluorometer (Thermo Fisher). Total RNA (500 ng) was used for cDNA synthesis using a RT2 First Strand Kit (QIAGEN). The RNA quality was assessed by an RT2 RNA QC PCR Array (QIAGEN). Real-time PCR was then conducted using an RT2 Profiler PCR Array for pig cytokines and chemokines (QIAGEN, Cat. No. 330231 PASS-150ZC). The data analysis was performed using the GeneGlobe Data Analysis Center available at QIAGEN (https://geneglobe.qiagen.com/us/analyze, accessed on 25 January 2023). A list of genes is shown in Table S3 (according to information provided by the manufacturer). All data were normalized to an average of five housekeeping genes (ACTB, B2M, GAPDH, HPRT1, and RPLP0) (Table S3). The relative gene expression levels compared to the untreated control were then calculated using the classical and widely adopted ∆Ct method (2−∆∆Ct) [73]. Unsupervised hierarchical clustering was performed to indicate the co-regulated genes across groups. The moMΦ cells were seeded in 12-well plates, and then they were left untreated, or they were stimulated with diverse polarizing factors: IFN-γ and LPS, IL-4, IL-10, TGF-β, or dexamethasone (as described in Section 4.2). Then 24 h later, the culture media was removed and replaced with cRPMI supplemented with either a TLR2 agonist (S-[2–bis(palmitoyl)-propyl]cysteine (Pam2Cys) lipopeptide, 100 ng/mL, Espikem, Prato, Italy [21,70]) or a TLR3 agonist (poly I:C, 100 ng/mL, Sigma-Aldrich). Then, 24 h post-stimulation, culture supernatants were removed, centrifuged at 2000× g for 3 min (to remove cell debris), and stored at −80 °C until determination of cytokine levels, as described in Section 4.5. In vitro experiments were performed in technical duplicate and repeated with at least three different blood donor pigs. Data were first checked for normality using the Shapiro–Wilk test, then they were graphically and statistically analyzed with GraphPad Prism 9.01 (GraphPad Software Inc., La Jolla, CA, USA). Flow cytometry, ELISA, and qPCR data were presented as box-and-whisker plots, showing the median and interquartile range (boxes) and minimum and maximum values (whiskers). These data were analyzed using either the parametric unpaired t-test or the nonparametric Mann–Whitney test; p-values lower than 0.05 were considered to be statistically significant (* p < 0.05, ** p < 0.01, and *** p < 0.001). The PCR array data were presented as a heatmap. PCR array for 84 genes were analyzed using the GeneGlobe Data Analysis Center available at QIAGEN (https://geneglobe.qiagen.com/us/analyze, accessed on 25 January 2023), as described in Section 4.7. Student’s t-tests were employed to evaluate statistical differences, and a statistically significant difference was set as p < 0.05. Overall, our data highlighted the remarkable heterogeneity and plasticity of porcine macrophages and showed that even molecules with similar biological functions (IL-10, TGF-β, dexamethasone) gave rise to distinct phenotypes. In addition, some porcine-specific peculiarities were observed, such as no induction or release of IL-10 in response to any of the four “M2-related” polarizing factors tested. In addition, IL-4 and IL-10, unexpectedly, both enhanced expression of proinflammatory IL-18, although this did not translate to increased secretion of this cytokine. Information generated by this study can help researchers to better interpret in vitro and in vivo results of host–pathogen interaction studies and will benefit researchers using pigs as a biomedical model.

PMC10003201

Maria S. Nazarenko,Aleksei A. Sleptcov,Aleksei A. Zarubin,Ramil R. Salakhov,Alexander I. Shevchenko,Narek A. Tmoyan,Eugeny A. Elisaphenko,Ekaterina S. Zubkova,Nina V. Zheltysheva,Marat V. Ezhov,Valery V. Kukharchuk,Yelena V. Parfyonova,Suren M. Zakian,Irina S. Zakharova

Calling and Phasing of Single-Nucleotide and Structural Variants of the LDLR Gene Using Oxford Nanopore MinION

24-02-2023

LDLR,Oxford Nanopore,familial hypercholesterolemia,structural variant,haplotype

The LDLR locus has clinical significance for lipid metabolism, Mendelian familial hypercholesterolemia (FH), and common lipid metabolism-related diseases (coronary artery disease and Alzheimer’s disease), but its intronic and structural variants are underinvestigated. The aim of this study was to design and validate a method for nearly complete sequencing of the LDLR gene using long-read Oxford Nanopore sequencing technology (ONT). Five PCR amplicons from LDLR of three patients with compound heterozygous FH were analyzed. We used standard workflows of EPI2ME Labs for variant calling. All rare missense and small deletion variants detected previously by massively parallel sequencing and Sanger sequencing were identified using ONT. One patient had a 6976 bp deletion (exons 15 and 16) that was detected by ONT with precisely located breakpoints between AluY and AluSx1. Trans-heterozygous associations between mutation c.530C>T and c.1054T>C, c.2141-966_2390-330del, and c.1327T>C, and between mutations c.1246C>T and c.940+3_940+6del of LDLR, were confirmed. We demonstrated the ability of ONT to phase variants, thereby enabling haplotype assignment for LDLR with personalized resolution. The ONT-based method was able to detect exonic variants with the additional benefit of intronic analysis in one run. This method can serve as an efficient and cost-effective tool for diagnosing FH and conducting research on extended LDLR haplotype reconstruction.

Calling and Phasing of Single-Nucleotide and Structural Variants of the LDLR Gene Using Oxford Nanopore MinION The LDLR locus has clinical significance for lipid metabolism, Mendelian familial hypercholesterolemia (FH), and common lipid metabolism-related diseases (coronary artery disease and Alzheimer’s disease), but its intronic and structural variants are underinvestigated. The aim of this study was to design and validate a method for nearly complete sequencing of the LDLR gene using long-read Oxford Nanopore sequencing technology (ONT). Five PCR amplicons from LDLR of three patients with compound heterozygous FH were analyzed. We used standard workflows of EPI2ME Labs for variant calling. All rare missense and small deletion variants detected previously by massively parallel sequencing and Sanger sequencing were identified using ONT. One patient had a 6976 bp deletion (exons 15 and 16) that was detected by ONT with precisely located breakpoints between AluY and AluSx1. Trans-heterozygous associations between mutation c.530C>T and c.1054T>C, c.2141-966_2390-330del, and c.1327T>C, and between mutations c.1246C>T and c.940+3_940+6del of LDLR, were confirmed. We demonstrated the ability of ONT to phase variants, thereby enabling haplotype assignment for LDLR with personalized resolution. The ONT-based method was able to detect exonic variants with the additional benefit of intronic analysis in one run. This method can serve as an efficient and cost-effective tool for diagnosing FH and conducting research on extended LDLR haplotype reconstruction. The LDLR gene encodes the low-density lipoprotein (LDL) receptor protein, which is responsible for receptor-mediated endocytosis of LDL particles, mainly by hepatocytes, and thus maintains the plasma level of LDL. To date, more than 18,000 variants, including 3000 rare variants, have been identified in the LDLR gene [1,2,3]. Common polymorphisms of this gene are associated with abnormal serum lipid levels, coronary artery disease (CAD), angina pectoris, myocardial infarction, abdominal aortic aneurysm, and Alzheimer’s disease, according to genome-wide association studies (GWASs) [4]. Rare pathogenic variants in the LDLR gene cause a type of high blood cholesterol called familial hypercholesterolemia (FH) and are responsible for approximately 84% of FH cases [5]. These mutations have been subdivided into five classes based on biochemical and functional studies on LDLR variants [6]. Most patients with FH have heterozygous loss-of-function mutations in LDLR. In rare cases, homozygous FH results from homozygous or, more often, from compound heterozygous mutations in the LDLR gene [7,8]. The vast majority of FH patients carry a missense mutation which arises from a single-nucleotide variant (SNV) in the coding region of the LDLR gene and affects protein structure and function [6]. Intronic variants of this gene may also impact the disease phenotype [9,10]. According to some studies, structural variants (SVs) account for approximately 10% of mutations in the LDLR gene [11,12]. This finding emphasizes the need to broaden the scope of this research from coding regions of the LDLR gene to complete LDLR gene sequencing that identifies all types of genetic variants, such as SNVs and SVs and including haplotype reconstruction, in one run, especially in patients with a yet unknown genetic cause of FH. Long-read DNA sequencing methods, specifically Oxford Nanopore technology (ONT), have advanced medical genetics by enabling the rapid and low-cost assessment of targeted genes, or even of the clinical exome, by detecting SVs and accurately determining haplotypes [13,14,15,16]. Recently, Soufi M. et al. presented a nanopore-sequencing-based workflow for rapid genetic testing of FH in a clinical service laboratory [15]. They amplified the LDLR gene in five fragments, covering the promoter region and coding sequences of all 18 exons. Therefore, this workflow may miss patients with deep intronic variants. There is also a problem with the phasing of genetic variants and direct haplotype analysis in the case of compound heterozygosity. Such information is important not only for index patients to confirm the FH diagnosis but also for potential diagnostic tools, preventative lifestyle interventions, and therapeutic management of family members to reduce their risk of CAD. For these reasons, we aimed to evaluate nanopore sequencing for calling and phasing SNVs and SVs of the LDLR gene. As a result, a workflow of long-range amplification of the LDLR gene comprising all types of genetic variants from exon 2 to exon 18 with introns was developed and validated on monomolecular sequencing technology. We applied the method to three patients with compound heterozygous mutations in the LDLR gene. We demonstrated that complete resolution of all variant types in LDLR by targeted ONT sequencing is possible. The advantage of long-read sequencing is direct and precise identification of a haplotype of the LDLR gene. The LDLR gene is located on the short arm of chromosome 19 (19p13.2) [17]. This gene spans ~45 kb of genomic DNA and contains 18 exons. The transcript (GenBank accession No. NM_000527.5) is 5.173 kb long and encodes a peptide consisting of 860 amino acids, including a 21-residue signal peptide [18]. Exon 1 of LDLR comprises a signal sequence that localizes the receptor to the endoplasmic reticulum for transport to the cell surface. The other exons encode five domains of LDLR: the ligand-binding domain (exons 2–6), epidermal growth factor (EGF) precursor homology domain (exons 7–14), a domain with O-linked carbohydrates (exon 15), a membrane-spanning domain, and a cytoplasmatic part of the receptor (exons 16–18; Figure 1). Primer pair 1 is designed to amplify the promoter and exon 1 of the LDLR gene (Figure 1). The first amplicon’s length is 587 bp. Primer pairs 2, 3, 4, and 5 were used to detect exons 2–6, 4–11, 7–14, and 13–18, respectively. There were considerable overlaps between the amplicons, and the total amplicon size was 42,316 bp. We conducted long-range PCR to amplify four fragments (P2, P3, P4, and P5) of the LDLR sequence from three unrelated probands that each carry two pathogenic variants in this gene. The large size (>10 kb) and the complexity of intron 1 prevented its efficient long-range amplification. Therefore, the promoter region, including exon 1, was amplified by classic PCR (587 bp) and analyzed by Sanger sequencing. Sequencing of the pooled PCR products of each of the three DNA samples on one MinION flow cell yielded an average of 21,450 reads per sample. The mean read length was 7372 bp and the GC content was 52%. Mapping the reads to the human reference genome showed an average coverage of 5297× per sample around the LDLR region. Mean mapping quality of three DNA samples was 59.28. Using the long-range PCR of four fragments of the LDLR gene and nanopore sequencing, we correctly identified all six pathogenic variants and their correct zygosity in the three DNA samples in which variants had previously been detected by massively parallel sequencing (MPS) or Sanger sequencing. In all three DNA samples analyzed, we identified four heterozygous pathogenic exonic SNVs (c.530C>T, c.1054T>C, c.1246C>T, and c.1327T>C) and one heterozygous likely pathogenic short deletion in intron 6: c.940+3_940+6del (Figure 2). LDLR is especially susceptible to SVs with breakpoints that are typically located within introns owing to the high density of Alu repeats [11,12,19,20]. The ability of our workflow to detect SVs can be illustrated using the results from sample T.02. We obtained two PCR products with primer pairs P5 and PX. A heterozygous 6976 bp deletion was found in sample T.02 between introns 14 and 16; it completely removed exons 15 and 16 (Figure 3A). The deletion removed amino acid residues 714 to 796 (without shifting the reading frame) located within the O-linked carbohydrate and membrane-spanning domains. This change to the protein is likely pathogenic. Approximate breakpoints of this large deletion were determined by MPS. Through nanopore sequencing, we identified the precise location of the breakpoints: chr19:11,122,202-11,129,177 (GRCh38). Both deletion breakpoints are localized to repetitive elements AluY and AluSx1 (Figure 3B). There is extensive sequence identity between the deletion breakpoints; this observation points to the mechanism of nonallelic homologous recombination (NAHR) between similar Alu elements. No other pathogenic SVs were found in our patients. One of advantages of using ONT in this study is the phasing of all types of genetic variants. We found that all six pathogenic variants of three patients with compound heterozygous FH are in a trans configuration. For example, the LDLR gene fragment from exon 7 to exon 18 was PCR-amplified from genomic DNA (sample T.02) with primers (P4, P5, and PX). We detected missense mutation c.1327T>C (mut) in exon 9 and the 6976 bp deletion of exons 15 and 16 in different alleles (Figure 3A). These mutations are ~8.8 kb apart. The trans-heterozygous association between mutations c.1246C>T (exon 9) and c.940+3_940+6del (intron 6) of LDLR was also confirmed in patient Sh.03 (Figure 4; Table S1). Patient S.01 has one mutation, c.530C>T, in exon 4, and a second one (c.1054T>C) in exon 7 in a trans configuration (Figure 4; Table S1). It should be noted that parents of two probands (T.02 and Sh.03) are presumed to be heterozygous for one pathogenic variant of the LDLR gene according to pedigree analysis. Unfortunately, biological samples from parents of all patients with compound heterozygous FH are not available. At the next step of our analysis, we used the CADD tool to predict the deleteriousness of both exonic and intronic variants of the LDLR gene in the three patients with FH. All five rare pathogenic variants have high PHRED scores (greater than 24); these are missense mutations c.530C>T, c.1054T>C, c.1246C>T, and c.1327T>C, and one noncoding short deletion c.940+3_940+6del (Figure 4; Table S1). In addition to analyzing rare mutations, we also examined haplotype structure of the LDLR gene in our three patients with FH by means of the common single-nucleotide polymorphisms (SNPs) that are associated with relevant traits according to GWASs. We also calculated the CADD score statistic for all of these patients’ genetic variants and visualized SNPs with the highest PHRED scores (Figure 4; Table S1). We noted extended haplotypes comprising 24 common SNPs across a 26.2 kb region (Figure 4; Table S1). Most of these SNPs are noncoding, except for five synonymous variants rs5930 (p.Arg471=), rs1799898 (p.Leu575=), rs688 (p.Asn591=), rs5925 (p.Val653=), and rs5927 (p.Arg744=). Thirteen SNPs correlate with lipid traits (total cholesterol, LDL cholesterol [LDL-C], and ApoB levels) according to the GWAS catalog. SNPs rs2738447 and rs2738464 are also associated with CAD. Two common variants [rs5927 (p.Arg744=) and rs2569540] correlate with cortisol levels (saliva) and an Alzheimer’s disease polygenic risk score and with hepatitis C virus load, respectively. Nine SNPs (rs12983082, rs35878749, rs34444274, rs34554139, rs5925, rs6511724, rs12459476, rs2116899, and rs2116897) have a PHRED score 5–10. Four SNPs (rs35878749, rs34444274, rs34554139, and rs6511724) are located in Alu elements (AluSz6, AluSg, and AluSx3). Eight SNPs are intronic variants, and rs5925 is a synonymous mutation. These SNPs are expression quantitative trait loci (eQTLs) for LDLR and SMARCA4 in the blood according to the NESDA NTR Conditional eQTL Catalog [21]. Judging by HaploReg data, synonymous SNP rs5925 overlaps an RNA polymerase II–binding site in a liver cell line (HepG2); this location may indicate an enhancer site that could mediate altered LDLR expression [22]. Two SNPs, rs35878749 and rs34444274, are located in AluSz6 elements within intron 12 having enhancer activity in the liver, fetal adrenal glands, and brain; these SNPs change the motif of transcription factors, including SREBP and HNF4, known to regulate transcription of LDLR in the liver. Two common variants—rs2116899 and rs2116897—are located in intron 17 of LDLR and are bound by proteins CTCF, ELF1, HEY1, HNF4A, HNF4G, P300, POL2, and RAD21 in the HepG2 cell line [22]. Mutations c.530C>T (p.Ser177Leu) and c.1327T>C (p.Trp443Arg) are on the haplotype that contains mainly alternative alleles. The other two rare coding variants are c.1054T>C (p.Cys352Arg) and the 6976 bp deletion of exons 15 and 16 and are affiliated with a different haplotype, which mainly contains reference alleles. The genotype of patient Sh.03 has fewer alternative alleles of common SNPs than patients S.01 and T.02. It should be noted that LDLR haplotypes having rare pathogenic variants contain both SNPs associated by GWASs with altered lipid levels and potentially functional SNPs that modulate LDLR expression or splicing. In recent years, a number of molecular diagnostic techniques for FH were created, including MPS, which is the most robust method for high-throughput sequencing of short DNA fragments [12]. There are several pipelines for targeted LDLR sequencing by MPS with relatively high sensitivity of SV detection owing to enrichment of the panel with the intronic content and optimization of bioinformatic algorithms [12,20]. Nevertheless, the main disadvantage of MPS is poor power for SV detection and the inability to phase genetic variants. The long-read sequencing method, on the contrary, can be applied to SV calling and direct haplotype reconstruction. To date, however, there has been only one study involving a practical application of long-read sequencing of a promotor and all coding regions of the LDLR gene by ONT [15]. However, the sequencing of introns 1, 6, 12, and 15 has not been performed in this work. Thus, it has not been possible to obtain information covering 20 kb of the LDLR gene in total. Before our work, there was also a problem with the phasing of genetic variants and direct haplotype analysis because of a lack of overlap among amplicons. In our study, we designed five long-range PCRs to cover the LDLR gene from exon 2 to exon 18, including intronic sequences. We carefully designed the primers for long-range PCR because intron sequences of the LDLR gene are rich in Alu repeats [9,18]. Primer pairs were designed to detect exons 2–6, 4–11, 7–14, and 13–18. There was solid overlapping among four amplicons. Thus, we were able to detect the full spectrum of genetic variants in the LDLR gene from exon 2 to exon 18 with introns and to phase these variants in one run. Then, long-range LDLR amplicons of three patients with compound heterozygous FH were sequenced using Oxford Nanopore MinION. As a result, all causative variants, including SNVs (c.530C>T, c.1054T>C, c.1246C>T, and c.1327T>C), small and large deletions (c.940+3_940+6del and the 6976 bp deletion of exons 15 and 16) and their correct zygosity were identified; these data showed high concordance with the results of MPS and Sanger sequencing. It was also possible to accurately determine breakpoints of the 6976 bp deletion. We found that the origin of this LDLR deletion is related to Alu elements, and that NAHR is responsible for this SV. NAHR has been described as a prevalent mechanism affecting SVs of the LDLR gene [11]. Judging by other reports, missense mutations c.530C>T, c.1054T>C, c.1246C>T, and c.1327T>C in LDLR can cause FH independently. For example, heterozygosity of the c.530C>T mutation in the LDLR gene is associated with FH in different countries, such as India [23], Portugal [24], Spain [25], Poland [26], and the Czech Republic [27]. Furthermore, this mutation in compound heterozygosity with EX7_EX10del (c.941-?_1186+?del) of the LDLR gene has been reported in Brazil [28] and in combination with p.Asp19His of the ABCG8 gene in FH patients in Malaysia [29]. Pathogenic variant c.1054T>C has been found in heterozygous FH in Taiwan [30] and Russia [31], and in compound heterozygosity with p.Asp266Asn in a patient with FH in Western Siberia (Russia) [32]. Furthermore, heterozygosity of the c.1327T>C mutation of the LDLR gene correlates with FH in Russia [31,33]. There is evidence of mutation c.1246C>T in patients with heterozygous FH in Russia [31,32], Korea [34], and Taiwan [30]. Finally, large (6976 bp, exons 15–16) and small (4 bp, intron 6) deletions have been documented only in Russian patients [31,35]. In our study, we show that parents of patients T.02 and Sh.03 had FH. Thus, we can guess that mutations reside in different alleles (in a trans configuration). Long-read sequencing helped us phase all six genetic variants and confirmed their trans arrangement. To our knowledge, the exact trans positioning of these compound heterozygous mutations of the LDLR gene has not been reported elsewhere. The present study also confirms that these compound heterozygous mutations result in a severe clinical manifestation of FH. For example, a 36-year-old female (patient S.01) with severe FH and CAD investigated in our study carries two missense mutations: c.530C>T (rs121908026) in exon 4 and c.1054T>C (rs879254769) in exon 7 (Table 1). The proband presented with myocardial infarction at 30 years of age in addition to tendon xanthomas, xanthelasma, lipoic corneal arcus, and high levels of total cholesterol and LDL-C. Proband T.02 is a 31-year-old woman with xanthomas and severe coronary and carotid atherosclerosis with an extremely high concentration of total cholesterol and LDL-C before and even after treatment (23 and 17.6/15.2 mmol/L, Table 1). She was found to be compound heterozygous for a large deletion (c.2141-966_2390-330del, 6976 bp, exons 15 and 16) and a pathogenic missense variant (c.1327T>C, rs773566855) in exon 9 of the LDLR gene. The third patient, Sh.03, is a 36-year-old woman with severe FH and CAD. It should be pointed out that she manifested a better response to lipid-lowering therapy than the other two patients (S.01 and T.02; Table 1). Patient Sh.03 carries two pathogenic variants—c.1246C>T (rs570942190) and c.940+3_940+6del (4 bp, intron 6)—of the LDLR gene in a trans configuration. It is believed that LDLR mutations are concentrated in exon 4 because it is the largest exon in the gene, or because variants in this exon (encoding the ligand-binding domain) have a highly deleterious effect on gene function [36]. Patient S.01 carries pathogenic variant c.530C>T, which results in a substitution of serine by a leucine residue at position 177 (p.Ser177Leu) and affects the ligand-binding domain of LDLR. It has been demonstrated that this amino acid change has the most substantial impact on this protein’s function because of impaired LDL-C–binding activity and lowered LDL-C uptake; therefore, it is classified as a type 3 mutation [37,38]. In contrast, the mutation frequency in exons 15 and 16 is extremely low [36]. The effect of these mutations on FH pathophysiology has not been fully elucidated [39,40,41]. According to our study, patient T.02 has a deletion of LDLR exons 15 and 16 that eliminates amino acid residues 714 to 796, which are located within the O-linked carbohydrate and membrane-spanning domains of the protein. We can theorize that this deletion causes the retention of the mutant LDLR in the Golgi apparatus, underexpression of this protein on the plasma membrane, and a reduced ability of the LDLR protein to take up LDL-C. Unfortunately, the lack of information on precise breakpoints of most SVs of the LDLR gene makes it impossible to establish whether the deletions we describe are identical to the ones reported from other populations. Nevertheless, deletions involving exon 15 (FH-Espoo) and exons 16 and 17 (FH-Helsinki) in the LDLR gene in a heterozygous state have also been seen in Russia and other populations, mainly in Northern Europe [32,42,43,44]. Mutations in the EGF precursor homology domain constitute 51.7% of all the missense variants described in LDLR [6]. It has been shown that these mutations are class 2 (partial or complete retention of LDLR in the endoplasmic reticulum), class 3 (defective binding to apolipoprotein B [apoB]), and class 5 (diminished LDLR recycling capacity). Our three patients carry missense mutations [c.1054T>C (p.Cys352Arg), c.1246C>T (p.Arg416Trp), and c.1327T>C (p.Trp443Arg)] in the EGF precursor homology domain. Missense variant c.1246C>T (in exon 9) replaces arginine with tryptophan in codon 416 (p.Arg416Trp) in the β-propeller of the EGF precursor homology domain, and consequently LDLR fails to release LDL in the endosome, and thus the mutant receptor is not recycled to the cell surface; therefore, this variant is classified as a type 5 mutation [45]. Further functional studies are necessary to identify the mechanism of action of another two mutations—p.Cys352Arg and p.Trp443Arg—in this domain of the LDLR. Patient Sh.03 has both missense variants c.1246C>T in exon 9 and a 4 bp deletion in intron 6 (c.940+3_940+6del) of the LDLR gene. According to SpliceAI, this variant has a score of 0.98 in terms of a donor loss and may influence splicing via skipping of exon 6 and the loss of extracellular LDLR class A repeat 7; these data confirm Semenova et al.’s in silico functional annotation [35]. Further biological research is needed to determine the mechanism underlying impairments of protein functions for these compound heterozygous mutations. It has been shown that common SNPs in the LDLR gene have multiple effects on LDL receptor function. For example, the minor allele of synonymous SNP rs688, which is located in the β-propeller region of LDLR, correlates with increased alternative splicing of exon 12 and an altered gene transcript as well as impairment of LDLR endosomal recycling and/or PCSK9 binding [46,47]. Furthermore, there is evidence of mutual effects between rs688 and another synonymous SNP (rs5925) in the regulation of LDLR splicing efficiency, both in vitro and in vivo [48]. Noncoding SNPs in LDLR have also been reported to be functional; for example, rare and common variants located in the promoter region or intronic enhancer elements can abrogate or modify binding of nuclear transcription factors thereby leading to changes in LDLR expression [49,50]. On the other hand, the analysis of biological functional significance of such variants is complex because of a linkage disequilibrium (LD) between the SNPs that are coinherited with causal variants. For the first time, we reconstructed ONT-based haplotypes of the LDLR gene of three patients with compound heterozygous FH on the basis of common SNPs associated mainly with LDL-C levels in GWASs and SNPs with the highest PHRED score (5–10) [4,51]. Finally, to test whether these SNPs affect gene expression levels, we searched for relevant data in NESDA NTR Conditional eQTL Catalog and HaploReg. In doing so, we found putative functional effects related to common SNPs rs5925 (exon 13), rs35878749, and rs34444274 (intron 12), rs2116899, and rs2116897 (intron 17). These SNPs have not been reported to be associated with lipid levels in a GWAS. Nonetheless, there is LD between these potentially functional SNPs and GWAS SNPs. For example, a minor allele of variant rs688, an exon-splicing enhancer, has been reported to correlate with an increase in plasma total cholesterol and LDL-C levels in several independent populations [4]. High LD between rs688 and rs5925 among Europeans has been documented by Gao F. et al. and Caruz A. [46,52]. In the present study, we detected an LDLR haplotype that contains minor alleles of both synonymous SNPs rs688 and rs5925 but reference alleles of rs35878749 and rs34444274 (Figure 4; Table S1). LDLR gene expression is controlled mainly by cis-regulatory elements in the 3′ untranslated region (UTR) via changes in mRNA stability [53]. Variant rs2738464 is present in the 2.5-kb 3′UTR of the LDLR gene and correlates with total cholesterol and LDL-C levels as well as risks of CAD and myocardial infarction [4]. In our study, two SNPs—rs2116899 and rs2116897—located in intron 17 affect the binding of various transcription factors in the HepG2 cell line and alter LDLR expression in the blood [21,22]. Recently, it was found that there are large effects of rare LDLR variants in introns 2, 3, 16, and 17, namely, markedly elevated LDL-C levels in ancestrally diverse individuals; these effects are similar to those of rare coding mutations [54]. Rare noncoding variants have been identified in intron 14 in patients with FH [10,55]. In our paper, we identified common SNPs in introns 12, 15, and 17, which can be functionally significant in the regulation of LDLR expression and alternative splicing. Intronic Alu elements may contribute to alternative splicing and natural mRNA isoform diversity and can alter splicing efficiency and transcript levels in disease phenotypes [56,57]. Notably, we found that intronic SNPs rs35878749, rs34444274, rs34554139, and rs6511724, which are located in Alu elements (AluSz6, AluSg, and AluSx3), have the highest PHRED scores among other common SNPs. On the basis of in silico prediction tools (NESDA NTR Conditional eQTL Catalog and HaploReg), we can hypothesize that these Alu-associated genetic variants can have regulatory potential and are interesting research directions to pursue. There are several limitations of the present study that must be considered. Due to the large size and Alu complexity of the analyzed genomic locus, we could not amplify the region encompassing intron 1 of the LDLR gene, where cis-acting gene regulatory sites are commonly found. The mechanism of detrimental effects of six pathogenic variants and common potentially functional SNPs of the LDLR gene were analyzed here only using literature sources and bioinformatic tools. Unfortunately, family-based cascade genetic screening of FH could be performed only for patient S.01. Her mother and daughter with FH carry the p.Ser177Leu mutation in exon 4 of the LDLR gene. Further research into the specific function of these genetic variants, both individually and in a phasing state, would be of great value in determining the extent to which they regulate lipid levels. Lastly, analyses involving a larger number of healthy individuals and patients with Mendelian FH, common lipid-metabolism-related disorders such as CAD, and Alzheimer’s disease can give us a greater insight into variations of the LDLR gene at the population level in different ethnic groups and will be helpful for early prevention or prognosis of these disorders. We think that directly extended haplotype reconstruction of the LDLR-SMARCA4 locus of patients with FH may explain its negative association with CAD [58]. Because LDLR contributes to both cholesterol and amyloid-β homeostasis, insights into the variation of LDLR and splicing regulation in different cell types of target organs may clarify the co-occurrence of cardiovascular diseases and Alzheimer’s disease. Three adult female patients (age range 31–36 years) with genetically confirmed FH, who were regularly followed at a specialized FH center of the Federal State Budgetary Institution National Medical Research Center of Cardiology Named after Academician E.I. Chazov (Ministry of Health of the Russian Federation; Moscow), were recruited into the study during their annual medical examinations. The FH patients had previously gotten this diagnosis in accordance with accepted standard criteria as described in ref. [59]. Clinical signs of FH in these patients are presented in Table 1. For the current study, all clinical and laboratory data were collected from the patient’s medical histories. LDLR mutations were found by MPS using a custom capture library (63 dyslipidemia genes) and Illumina HiSeq 1500 [31,35,60,61]. All genetic variants, except the large deletion (c.2141-966_2390-330del, 6976 bp, introns 14–16), were confirmed by Sanger sequencing as described before [62]. Genomic DNA of patients was isolated from peripheral-blood samples using the Monarch® HMW DNA Extraction Kit for Cells & Blood (New England BioLabs, Ipswich, MA, USA), followed by assessment of the concentration and purity of the isolated DNA on NanoDrop 8000 (Thermo Fisher Scientific, Waltham, MA, USA) and by electrophoresis in a 0.8% agarose gel. The LDLR primers for the long-range PCR were designed by means of PrimerQuest [63] and checked in the OligoAnalyzer Tool (https://eu.idtdna.com/pages/tools/oligoanalyzer, accessed on 28 April 2022) [64]. The long-range PCR for amplifying each LDLR gene fragment was conducted in a 25 μL reaction mixture containing 12.5 μL of LongAmp Taq 2X Master Mix (New England BioLabs), 5.0 μL of 5X SE PCR Stabilizer (SibEnzyme, Novosibirsk, Russia), 0.5 μM (final concentration of) each primer in a pair (Table 2), and 50 ng of genomic DNA. The long-range-PCR program was as follows: initial denaturation at 94 °C for 4 min; 35 cycles of denaturation at 94 °C for 20 s, primer annealing at 60 °C for 20 s, and elongation at 68 °C for 12 min (after 10 cycles, adding an increment of +10 s/cycle to the elongation step), followed by final elongation for 10 min at 68 °C. The PCR products were visualized by 1% agarose gel electrophoresis. Concentrations of the amplified gene fragments were evaluated using the BR dsDNA Qubit Kit (Thermo Fisher Scientific). For each patient, all PCR products (100 fmol each) were pooled at equimolar concentrations (48 µL final volume) and used for library preparation using the Native Barcoding Amplicons Kit (EXP-NBD104, EXP-NBD114, and SQK-LSK109; Oxford Nanopore Technologies, Oxford, United Kingdom) according to the manufacturer’s protocol. The prepared library was loaded into a MinION flow cell (FLO-MIN106D; Oxford Nanopore Technologies), and the sequencing was carried out for 48 h. Base calling and demultiplexing of the data were performed in the Guppy v.5.0.7 software [65]. Reads of the amplicons of the LDLR gene were aligned to the human genome build GRCh38.p13 using MiniMap2 [66]. Generated SAM files were converted to BAM format in SAMtools [67]. The minimum sequencing depth was found to never dip below 150× according to Bedtools “coverage” [68]. The variant-calling and phasing steps were performed by algorithms Clair3 and Sniffles2 [69]. Data were viewed in IGV v.2.15.2 [70]. MultiQC v.1.12 was used to generate data sequencing statistics and quality metrics [71]. For the promoter and exon 1 of the LDLR gene, we carried out classic PCR to enrich this part of the gene with primers P1 F: 5′-CGGAGACCCAAATACAACAAATC-3′ and R: 5′-TTTCCCTTAAATCCCTCAGACTC-3′. The amplicon size was 587 bp. The DNA samples were sequenced with the BigDye Terminator v3.1 Cycle Sequencing Kit on an Applied Biosystems 3730 Genetic Analyzer (Thermo Fisher Scientific). The results were interpreted with the help of Chromas 2.6.3 software (Technelysium, South Brisbane, QLD, Australia). The identified genetic variants were evaluated in terms of their effect on protein structure and/or function using web-based annotation tools and databases (Annovar, PolyPhen2, SIFT, Mutation Tester, MutPred, gnomAD, RUSeq, dbSNP, and HGMD). Pathogenic variants were also manually subjected to searches in PubMed and VarSome [72]. The pathogenicity of the genetic variants was assessed based on guidelines for the interpretation of high-throughput sequencing data [73,74]. In addition, potential splice effects of intronic variants were assessed in SpliceAI [75]. The Δ Score was obtained with default parameters. CADD v.1.6 was utilized for predicting the deleteriousness of both exonic and intronic variants [51]. Common SNPs were run through HaploReg v4.1 and NESDA NTR Conditional eQTL Catalog to assess their functional consequences [21,22]. To identify rare pathogenic genetic variants and common potentially functional SNPs, we chose variants with the highest CADD score statistic (PHRED) and integrated them with the sequence context (Alu elements), transcription factors and histone marks (HaploReg v4.1), and blood eQTLs (NESDA NTR Conditional eQTL Catalog). To the best of our knowledge, this is the first ONT study on FH to cover the LDLR gene from exon 2 to exon 18 with introns, and it should make it efficient to determine a nearly complete analysis of this gene. Therefore, we were able to detect both coding and noncoding variants, such as SNVs and small and large deletions. In introns 12, 15, and 17, we also identified common SNPs that can be functionally significant in the regulation of LDLR expression and alternative splicing. The long reads allowed for the phasing of the genetic variants and for direct haplotype analysis of the LDLR gene at an individual level without knowledge about their inheritance from parents. The ability to detect the full spectrum of genetic variants in LDLR is critical not only for making a molecular diagnosis of FH but also for research. This is because the variation and extended haplotype structure of LDLR in different ethnic groups remains largely unknown, for example, in patients with altered lipid metabolism, Mendelian FH, and common diseases (CAD and Alzheimer’s disease).

PMC10003206

Xiaoyu Huang,Xiaojun Qiu,Yue Wang,Aminu Shehu Abubakar,Ping Chen,Jikang Chen,Kunmei Chen,Chunming Yu,Xiaofei Wang,Gang Gao,Aiguo Zhu

Genome-Wide Investigation of the NAC Transcription Factor Family in Apocynum venetum Revealed Their Synergistic Roles in Abiotic Stress Response and Trehalose Metabolism

26-02-2023

NAC transcription factor,drought stress,salt stress,trehalose metabolism pathway

NAC (NAM, ATAF1/2, and CUC2) transcription factors (TFs) are one of the most prominent plant-specific TF families and play essential roles in plant growth, development and adaptation to abiotic stress. Although the NAC gene family has been extensively characterized in many species, systematic analysis is still relatively lacking in Apocynum venetum (A. venetum). In this study, 74 AvNAC proteins were identified from the A. venetum genome and were classified into 16 subgroups. This classification was consistently supported by their gene structures, conserved motifs and subcellular localizations. Nucleotide substitution analysis (Ka/Ks) showed the AvNACs to be under the influence of strong purifying selection, and segmental duplication events were found to play the dominant roles in the AvNAC TF family expansion. Cis-elements analysis demonstrated that the light-, stress-, and phytohormone-responsive elements being dominant in the AvNAC promoters, and potential TFs including Dof, BBR-BPC, ERF and MIKC_MADS were visualized in the TF regulatory network. Among these AvNACs, AvNAC58 and AvNAC69 exhibited significant differential expression in response to drought and salt stresses. The protein interaction prediction further confirmed their potential roles in the trehalose metabolism pathway with respect to drought and salt resistance. This study provides a reference for further understanding the functional characteristics of NAC genes in the stress-response mechanism and development of A. venetum.

Genome-Wide Investigation of the NAC Transcription Factor Family in Apocynum venetum Revealed Their Synergistic Roles in Abiotic Stress Response and Trehalose Metabolism NAC (NAM, ATAF1/2, and CUC2) transcription factors (TFs) are one of the most prominent plant-specific TF families and play essential roles in plant growth, development and adaptation to abiotic stress. Although the NAC gene family has been extensively characterized in many species, systematic analysis is still relatively lacking in Apocynum venetum (A. venetum). In this study, 74 AvNAC proteins were identified from the A. venetum genome and were classified into 16 subgroups. This classification was consistently supported by their gene structures, conserved motifs and subcellular localizations. Nucleotide substitution analysis (Ka/Ks) showed the AvNACs to be under the influence of strong purifying selection, and segmental duplication events were found to play the dominant roles in the AvNAC TF family expansion. Cis-elements analysis demonstrated that the light-, stress-, and phytohormone-responsive elements being dominant in the AvNAC promoters, and potential TFs including Dof, BBR-BPC, ERF and MIKC_MADS were visualized in the TF regulatory network. Among these AvNACs, AvNAC58 and AvNAC69 exhibited significant differential expression in response to drought and salt stresses. The protein interaction prediction further confirmed their potential roles in the trehalose metabolism pathway with respect to drought and salt resistance. This study provides a reference for further understanding the functional characteristics of NAC genes in the stress-response mechanism and development of A. venetum. In nature, plants are challenged by a variety of adverse abiotic stress conditions such as drought, salinity and extreme temperatures. These abiotic stresses limit the area of arable lands for agriculture and negatively affect crop productivity. To resist these stresses, plants have evolved complex and sophisticated regulatory pathways to sense and adapt to these stresses in a timely manner, which are regulated by promoting the expression of stress-responsive genes [1]. Transcription factors are the core of regulating gene expression by specifically binding to cis-elements of the target gene promoter to regulate the expression of downstream genes [2]. The NAC family first identified in Petunia hybrida [3] is a plant-specific TF family with its domain comprises a DNA-binding domain at N-terminal, a nuclear localization signal (NLS) and a transcriptional activation domain (AD) at C-terminal. The N-terminal region is a conserved domain containing about 160 amino acids. The C-terminal region, however, is highly variable, interacting with other transcription factors that may play a role in various developmental functions [4]. NAC TFs have been found to be involved in various growth and developmental processes, including cell division, seed development, root construction and control senescence [5,6,7,8,9,10,11]. In addition, they also positively response to salinity, drought, heat, cold and so forth [6,12,13,14]. The overexpression of OsNAC5, OsNAC6, OsNAC9 and OsNAC10 increased the root number and altered root architecture, thereby improving drought tolerance and grain yield in transgenic plants [15,16]. Rice NAC genes ONAC022, ONAC045 and ONAC066 were induced by drought, salt and abscisic acid (ABA) treatments, and positively regulated ABA-mediated pathway [17,18]. Similarly, overexpression of LpNAC17 (from Lilium pumilum) in tobacco, HhNAC54 (from Hibiscus hamabo Sieb. et Zucc.) in Arabidopsis enhanced salt tolerance, and SlNAC10 (from Suaeda liaotungensis) in Arabidopsis in addition to salt enhanced drought tolerance [1,19,20]. Additionally, the NAC transcription factor ATAF1 (Arabidopsis Transcription Activation Factor 1) was found to respond to carbon starvation by participating in trehalose metabolism. Overexpression of ATAF1 directly activates the only trehalase-encoding gene TREHALASE1, reducing the trehalose-6-phosphate (Tre6P) levels and sugar starvation metabolome [21]. In contrast, rice NAC transcription factor OsNAC23 regulated carbon allocation by directly repressing the transcription of the trehalose-6-phosphate phosphatase (TPP) gene TPP1 to increase Tre6P level and reduce trehalose content. Moreover, overexpression of OsNAC23 gene in rice increased photosynthetic rate, sugar transportation and sink organ size, thus increasing grain yield [22]. These reports indicate that the NAC TFs are involved in forming a complicated regulatory network for plant response to external adversity with key roles in plant growth and development. Apocynum venetum L., a member of the Apocynaceae family, is an important source of natural bast fiber. It has a wide range of pharmacological activities and is used for the prevention and treatment of cardiovascular and neurological diseases [23,24,25]. A. venetum is widely distributed throughout the saline–alkaline soils and sandy soils of northwestern China and the Mediterranean area [26]. It has a relatively high tolerance to various abiotic stresses, including drought, salt, cold, high temperature and wind, playing a crucial role in sand fixation and soil and water conservation [25]. Therefore, the exploration of the contributions of A. venetum NACs to drought and salinity tolerance is of great importance. However, a systematic analysis of NAC gene family in A. venetum has not been completed. In the present study, genome-wide identification and analysis of the NAC family members were performed in the A. venetum genome. The physicochemical characteristics, chromosome localization, gene duplication, collinearity, phylogenetic relationship, cis-acting elements, gene structure and conserved motifs were analyzed comprehensively. Moreover, the protein–protein interaction prediction was also conducted to unravel their potential functions. The NAC gene expression pattern in various tissues were analyzed based on existing transcriptome data and, in response to drought and salt stresses, were investigated by quantitative real-time PCR (qPCR). Our results will contribute to further functional studies of the NACs, as well as provide a valuable reference for the genetic improvement of rooibos. A total of 74 NAC TF members named AvNAC1–AvNAC74 according to their positions on the chromosomes were identified in A. venetum by the HMM search and complete domain analysis (Figure 1). AvNAC genes were unevenly distributed on chromosomes, with a high enrichment on chromosome 8 with 14 AvNAC members. Each of the A. venetum eleven chromosomes has at least three AvNAC members, reflecting its diversity and complexity, except for chromosome 5, which contained no AvNAC gene. The physicochemical properties of AvNAC genes are listed in Supplementary Table S1. The sequence length ranged from 164 to 688 amino acids with molecular weight from 19.36 to 76.26 kDa, and isoelectric point (pI) 4.39 to 9.58. Subcellular location prediction showed that sixty-four AvNAC proteins were nucleoprotein, eight members were cytoplasmic protein, and only one each in the chloroplast and cell membrane. These results suggested that AvNAC TFs might be involved in regulating the nuclear gene expression and have various functions to adapt to different environments. Replication events, including tandem and segmental replication, are responsible for the expansion of gene families and the complexity of genomes during plant evolution. A duplication analysis of 74 AvNAC genes revealed four pairs of tandem duplicated genes distributed on three chromosomes (LG01, LG02 and LG08) (Figure 1), seven pairs of segmental duplicated genes unevenly distributed on the remaining chromosomes, except for LG05 and LG09 (Supplementary Table S2 and Figure 2). In addition, the causes of divergence were measured by Ka and Ks, and Ka/Ks ratios analysis to determine the positive pressure after duplication (Supplementary Table S2). Normally, the Ka/Ks > 1 indicates positive selection, Ka/Ks = 1 represents neutral selection, while Ka/Ks ≤ 1 means purifying selection. The result showed that the Ka/Ks values of all segmental and tandem duplicated AvNAC gene pairs were less than 1, except for four gene pairs with significant sequence divergence and long evolutionary distance. These results indicated that most AvNACs evolved mainly under purifying selection, and the segmental duplications were the main driving force during the evolution process. To further understand the evolutionary relationship between A. venetum and other plant species, we selected three dicotyledons (Arabidopsis thaliana, Medicago sativa and Solanum lycopersicum) and three monocotyledons (Oryza sativa, Zea mays and Mauremys sinensis) to establish collinearity analysis (Figure 3). The results showed A. venetum to have 63, 56 and 68 orthologous gene pairs with A. thaliana, M. sativa and S. lycopersicum, respectively. In contrast, there were fewer orthologous gene pairs between A. venetum and the monocotyledons O. sativa, Z. mays and M. sinensis, with 25, 18, and 22 pairs, respectively (Supplementary Table S3). Among these plant species, A. venetum had most orthologous gene pairs with S. lycopersicum, showing a closer evolutionary relationship, suggesting that the two species might have shared the similar phylogenetic divergence time. We found five orthologous gene pairs common to all the six species, suggesting that they might have existed before ancestral divergence. In addition, a total of 28 AvNAC genes were present only in dicotyledons, suggesting that these genes may have evolved after the divergence of the two classes of plants. To explore the evolutionary relationship among the NAC TFs, we constructed a phylogenetic tree consisting of 179 NAC protein sequences (105 from Arabidopsis and 74 from A. venetum). A total of 74 AvNACs were divided into 16 subgroups according to the classification of NAC gene family in Arabidopsis (Figure 4). All groups contained AvNAC members except ANAC001, which only consisted of NACs from Arabidopsis (ANACs). ANAC063 contained the largest AvNAC members (20), while TIP, OsNAC8, SENU5 and AtNAC3 each had only one AvNAC member. Remarkably, the AvNAC members clustered into the same groups as ANACs, indicating higher homologies and may possibly have similar function. For example, some groups contained several ANACs that were known to be associated with stress responses, including ANAC19, ANAC55 and ANAC72 in group AtNAC3, ANAC56 in group NAP, and ANAC2 and ANAC81 in group ATAF. A total of eight AvNACs were distributed in these three groups, suggesting that they may respond to stress in A. venetum. To further investigate the relationship among 74 AvNAC genes, the phylogeny, gene structure and conserved motifs were analyzed (Figure 5). Fifteen conserved motifs were identified with amino acid lengths ranging from 11 to 99, and the number of motifs in the AvNAC proteins ranged from a minimum of three to a maximum of nine (Figure 5B). The most remarkable motifs were motif 1-6, which were found in 44 AvNAC proteins. Among all AvNAC proteins, AvNAC50, AvNAC53 and AvNAC54 contained nine motifs, whereas AvNAC46, AvNAC63, and AvNAC70 contained only three motifs. As expected, closely related members within the same subgroup possessed a relatively consistent motif composition, implying that they had similar functions. These conserved motifs may indicate potential functional site for the genes and, thus, may be involved in inducing similar downstream functions (Figure 5A). Motif 6 may be the most critical motif since it was present in all proteins but AvNAC46. In contrast, motif 13 was the least common and was only found in AvNAC11. The variable distribution of motifs may contribute to the functional diversity of the AvNAC gene family. A gene structure analysis revealed that the intron number of AvNAC genes ranged from 0 to 10, of which seven genes lacked intron, while AvNAC67 contained 10 introns (Figure 5C). The number and distribution of exon-intron within the same subgroup displayed some similarities; for example, AvNAC29 and AvNAC20 are assembled together in the phylogeny tree, both of them had two introns with similar distribution patterns. Notably, most of the intron insertions occurred in the conserved domains of the NAM, indicating their importance in plants. These results not only strongly support the reliability of the classification but also further reveal that AvNACs within the same group may play similar functional roles. To explore the potential function of AvNACs, the prediction of cis-element 1500 bp upstream of the AvNACs transcription start site was performed. A total of 51 types of cis-elements were detected and classified into four categories, among which the most abundant was light responsive (19 types), followed by phytohormone responsive (13 types), stress-responsive (13 types) and plant growth and development (6 types) (Figure 6 and Supplementary Table S4). Among the light-responsive, Box 4 was the dominant element followed by G-box. The cis-elements responsive to phytohormone were mainly methyl jasmonate (MeJA), abscisic acid (ABA), ethylene (ERE) and gibberellic acid (GA) responsive elements. Among them, ABRE elements were the most abundant (104 in total), followed by ERE (101 in total), TGACG-motifs (61 in total, MeJA responsive) and CGTCA-motifs (61 in total, MeJA responsive). In terms of stress responsiveness, MYC elements (179 in total, drought responsiveness) were the prominent elements, appearing in 68 AvNAC genes, followed by STRE (106 in total, stress responsiveness). Notably, drought-responsive elements were present in almost all AvNAC genes except AvNAC34 and AvNAC43. At the same time, other elements important for stress response, including cold/dehydration responsive, wound responsive, low-temperature and anaerobic induction elements, were also detected. In addition, several elements related to plant growth and development were identified, with seed-specific expression elements being the most abundant. Notably, the AvNAC genes with similar cis-elements types and numbers were shown to have close phylogenetic relationships, such as AvNAC4 (11 ABRE and 12 G-box), AvNAC58 (10 ABRE and 11 G-box) and AvNAC69 (5 ABRE and 5 G-box), suggesting that this subgroup of AvNAC genes might be important in ABA signaling pathway and light response. These results further reveal the potential function of the AvNAC genes and their roles in plant development and environmental stress responses. To understand the expression patterns of the AvNACs, transcript levels in different tissues (root, stem and leaf) were analyzed based on the transcriptome data (SMAN23766539, SMAN23766540 and SMAN23766541). The results showed that thirty-five of the AvNACs were expressed in all the three tissues, with AvNAC11, AvNAC15 and AvNAC16 showing significant expression levels (Figure 7), indicating that these genes may widely participate and play an important role in plant growth and development. Fourteen of the AvNACs showed tissue-specific expression, five expressed in only one tissue and nine in two tissues. For example, AvNAC31 had a higher expression level in stem and leaf, AvNAC71 in root and stem, AvNAC35 in root and leaf, whereas AvNAC3, AvNAC28 and AvNAC74 were only expressed in root. Twenty-five of the AvNACs were not expressed in any tissue, suggesting that the expression of these genes requires a specific development stage or environmental induction. Taken together, these findings indicate that different AvNACs play distinct roles in different tissues. Based on phylogenetic analysis and homology with known NAC genes in A. thaliana, 15 and 20 AvNAC genes associated with drought and salt stress response were selected, respectively, and their expression patterns under drought and salt stress were investigated by qPCR. Under drought stress, AvNAC1 had a similar expression pattern in the leaf, stem and root. Its expression improved with increasing PEG concentration (from 0 to 20%) and reached the highest level at 20%, where the expression level in stem and leaf was 200- and 100-fold higher than that of the control, respectively (Figure 8 and Supplementary Figure S1). The expression of AvNAC4 and AvNAC43 was also induced by drought stress. AvNAC4 in leaf and AvNAC43 in root and stem increased, while AvNAC4 in root and stem and AvNAC43 in leaf showed a trend of increasing and then decreasing, but were still higher than the control. Conversely, the expression levels of some genes gradually decreased with increasing PEG concentration, including AvNAC6, AvNAC10 and AvNAC23 in the root, and AvNAC2 in the leaf. AvNAC58 and AvNAC69 showed a similar expression pattern in root, decreasing rapidly and then increasing, but overall was lower than the control. In contrast, their expression in the stem and leaf was generally elevated. Notably, some genes were highly expressed in specific tissue. For example, under 5% PEG treatment, AvNAC32 in root and AvNAC43 in leaf were 150- and 100-fold higher than the control, while under 10% PEG treatment, AvNAC6 in leaves and AvNAC43 in root were 100- and 80-fold higher than the control, respectively. Under salt stress, AvNAC58 and AvNAC69 showed similar expression patterns, with increasing NaCl concentrations (from 0 to 200 mM), their expression in all analyzed tissues were gradually increased, and reached the highest level at 200 mM (Figure 9 and Supplementary Figure S2). The expression of AvNAC4, AvNAC43 and AvNAC44 in all analyzed tissues were also induced by salt stress. Among them, the expression of AvNAC4 in root, AvNAC43 in root and stem, and AvNAC44 in stem and leaf all reached the highest at 100 mM NaCl treatment and then decreased, but were higher than the control. Otherwise, their expression in other tissues gradually increased and reached the highest at 200 mM NaCl treatment. In contrast, the expression of AvNAC6 in root and stem decreased with increasing NaCl concentration, reaching a minimum at 200 mM treatment. Similar situations were observed in the expression of AvNAC23 in the root and AvNAC2 in the leaf. Notably, the expression of some AvNAC genes was significantly increased in root under salt stress, including AvNAC1, AvNAC4, AvNAC7, AvNAC32 and AvNAC69. Among them, the expression levels of AvNAC1 and AvNAC69 were 100-fold higher than the control under 200 mM NaCl treatment, and the expression levels of AvNAC4, AvNAC7 and AvNAC32 were 200-, 100- and 40-fold higher than the control under 100 mM NaCl treatment, respectively. Taken together, some genes showed similar expression patterns under drought and salt stress; for example, AvNAC4 and AvNAC43 showed increased expression levels in roots, stems and leaves, especially in roots. In contrast, the expression patterns of AvNAC58 and AvNAC69 in roots were different under different stresses, decreasing under drought stress while increasing under salt stress. Moreover, some genes, including AvNAC32 and AvNAC43, were only expressed under stresses. These results suggest that AvNAC genes possess various expression patterns under different stresses, indicating their functional specificity. In addition, we found that the expression levels of many AvNAC genes were significantly altered in roots under stresses, including AvNAC1, AvNAC4, AvNAC32, AvNAC43 and AvNAC69, indicating their important roles in stress resistance in A. venetum. To further explore the functions of the AvNAC genes, a protein–protein interaction network of AvNAC protein was performed based on their homologs in A. thaliana. As shown in Figure 10, the majority of the AvNAC proteins are homologous and interact with known Arabidopsis proteins, including AtNST1, AtXND1, AtNAC073, AtNAC083, AtRD26, AtNAC1, AtVND1/7, AtCUC2/3, AtNAC007 and AtNAC059, of which different groups may had different functions. AvNAC4 was homologous to AtRD26, which interacted with KIN10 (SnRK1.1) and SOS2 protein, while AvNAC32 was homologous to AtNAC047, which interacted with CIPK20 (SOS3) protein. SOS2 and SOS3 are important protein kinases of SOS pathway, which control the expression and activity of SOS1 to regulate salt stress response in plant [27]. Both ATAF1 and ATAF2 interacted with KIN10 (SnRK1.1) and KIN11 (SnRK1.2), which in turn interacted with TPS1. In addition, ATAF1 also interacted with TPPA and TPPJ, which belongs to a cluster of proteins related to the trehalose metabolism pathway. The result indicates that the homologs of these proteins in A. venetum may also possess similar functions. TFs can regulate gene expression by binding to specific sequences upstream of the start codon of target genes. Potential TFs were investigated in the upstream regions of all 74 AvNAC genes and a TF regulatory network was established. A total of 3820 TFs were detected and belonged to 40 TF families (Figure 11A and Supplementary Table S5). Among these TF families, Dof (637) contained the maximum number of members followed by BBR-BPC (593), ERF (497), NAC (312) and MIKC_MADS (298), while WOX (4), LFY (2) and RAV (2) contained only a few members. Among 74 AvNAC genes, AvNAC58 was targeted by 206 TFs, which was the most abundant, and followed by AvNAC9 (198), AvNAC64 (196), AvNAC23 (188) and AvNAC19 (147) (Figure 11B and Supplementary Table S5). Furthermore, the AvNAC genes were targeted by different types and numbers of TF families that are associated with plant growth, development and response to biotic/abiotic stress. For instance, AvNAC58 was targeted by ERF, BBR_BPC, bZIP, bHLH, TCP and MYB family simultaneously. In the present study, 74 NAC genes were identified from A. venetum, divided into 16 subgroups and distributed unevenly on 11 chromosomes (Figure 1, Figure 2 and Figure 4). A majority of AvNACs (64/74) were predicted to be nuclear proteins that may respond to drought stress by regulating the expression of genes related to stress-, lipid transport-, and lipid localization-related genes (Supplementary Table S1). Gene structural diversity is significant for gene evolution. AvNAC genes within the same subgroup shared a similar intron/exon composition, and the proteins they encode had a similar motif component (Figure 5), which was consistent with what was reported in sunflower [7], Vigna radiata L. [28] and Zanthoxylum bungeanum [29], suggesting that the NAC gene family was highly conserved. In particular, among the 15 motifs identified, motif 13 appeared in three NAC members clustered in the same subgroup and it was predicted to be localized in the cytoplasm. Similar situations were found in motif 15, suggesting that these members may possess a specific function. The number of AvNAC gene family member was the same as in Vitis vinifera (74) [30], more than in Lagerstroemia indica (21) [31] and Lolium perenne (72) [1] but less than in O. sativa (151) [8], Z. mays (152) [9], Vigna radiata L. (81) [28] and Passiflora edulis (105) [32]. The variation may be related to gene duplication during the evolution of the species. Segmental and tandem duplication are the dominant driving forces of evolution and expansion of family genes [33]. We identified seven segmental pairs and four tandem pairs in A. venetum (Figure 1 and Figure 2). A total of 15 segmental duplications were reported in the mung bean (V. radiata) NAC gene family [28]. ZbNAC (Z. bungeanum) gene family had forty-two segmental duplication pairs and nine tandem duplication pairs [29]. A total of one-hundred-and-twenty-one pairs of segmental duplication and nine pairs of tandem duplication pairs were presented in the M. sinensis NAC gene family [34]. Therefore, it is speculated that the segmental duplication is the dominant force driving the evolution and expansion of NAC gene family. Selective pressure analysis revealed that AvNAC genes evolved under purifying selection (Supplementary Table S2). Additionally, the collinearity analysis (Figure 3) indicated that extensive evolution and duplication of the AvNAC genes may have occurred after the divergence of monocotyledons and dicotyledons. Abiotic stress triggers a wide range of plant responses, including the expression of related genes, accumulation of metabolites, plant growth and development state, and crop yield changes. Thus, mining key genes for drought and salt resistance is of great importance to agricultural production and provides theoretical data for further research on the mechanism. Considering the strong drought and salinity tolerance in A. venetum, we treated the species with varying drought and salt concentrations to study the expression pattern of AvNAC genes under these stresses, respectively. The expression of AvNAC4 in all analyzed tissues increased under both drought and salt stresses (Figure 8 and Figure 9). It was classified into the ATNAC3 subgroup along with ANAC019, ANAC055 (AtNAC3) and ANAC072 (RD26), which were reported to be induced by drought, high salinity and ABA, and their overexpression improved the drought tolerance of transgenic plants [35]. Moreover, AvNAC4 was homologous to ANAC072 (RD26) (Figure 10), which is thought to be involved in a novel ABA-dependent stress signal pathway [36]. Under drought stress, ABA primarily promotes stomatal closure to minimize transpiration, while activating stress-responsive genes that work together to improve plant stress tolerance [37]. In addition, more studies reported that ABA enables plants to recover from salt stress and water-deficit environment by increasing hydraulic conductivity or promoting root cell elongation [37,38,39]. This might be attributed to the fact that the expression levels of AvNAC4 in roots significantly increased under salt and drought stress, suggesting that AvNAC4 might be involved in stress responses and ABA signal pathways to enhance plant tolerance. The substantial presence of ABRE and MYC elements in the AvNAC4 promoter region (Figure 6) further supported its involvement in stress responses. In addition, the expression levels of AvNAC58 and AvNAC69 were increased in leaf and stem but decreased in root under drought stress, while they were increased in all analyzed tissues under salt stress (Figure 8 and Figure 9). AvNAC58 and AvANC69, clustered in the ATAF subgroup, were homologous to ANAC002 (ATAF1) and ANAC081 (ATAF2), respectively (Figure 4 and Figure 10). The overexpression of ATAF1, ATAF2 or their homologues in plants were reported to improve the transcription of some stress-related genes, thus enhancing the tolerance of plants to drought or salt stress [40,41]. Additionally, allogeneic overexpression of CaNAC46 (Capsicum annuum), belonging to the ATAF family in Arabidopsis, increased the tolerance of transgenic plants to drought and salt stress as well [42]. Thus, AvNAC58 and AvNAC69 may also have the same function. Our research found that there were multiple TFBSs in the promoter region of AvNAC genes, among which AvNAC58 was simultaneously targeted by Dof, ERF, BBR_BPC, bZIP, bHLH, TCP and MYB family for a total of 206 TFs, which was the most abundant (Figure 11 and Supplementary Table S5). Dof, AP2/ERF, bZIP, MYB and bHLH TFs play important regulatory roles in various abiotic stresses [43,44,45,46,47]. These results supported that AvNAC58 and AvNAC69 are involved in drought and salt stress responses, and they may have different mechanisms of action under various stresses. ATAF1 interacts with the catalytic subunits AKIN10 and AKIN11 of SnRK1 (SNF1-RELATED KINASE 1), and it is a key regulator of ABA signaling pathways [48]. Our protein–protein interaction analysis further confirmed this, where ATAF1 (AvNAC58) and ATAF2 (AvNAC69) interacted with AKIN10 and AKIN11. In addition, RD26 was predicted to interact with AKIN10 (Figure 10). Notably, AKIN10 and AKIN11 interact with ATTPS1, ATAF1 interacts with ATTPPA and ATTPPD, while TPS and TPP are essential enzyme genes in trehalose biosynthesis pathway in plants [49]. This further associates the stress response with trehalose metabolism. Moreover, ATAF1 and ANAC032 regulate trehalose metabolism through the direct regulation of TRE1 expression, while OsNAC23 regulates Tre6P and trehalose levels by repressing TPP1 transcription, all of which are induced by carbon starvation [21,22,41]. These results indicated that AvNAC4, AvNAC58 and AvNAC69 might enhance the stress tolerance of A. venetum by participating in the trehalose metabolism. In plants, the trehalose biosynthetic pathway plays a key role in regulating carbon allocation and stress adaptation [50]. Meanwhile, trehalose is an important signal linking plant metabolism, growth and development [49]. Tre6P, an intermediate product of trehalose synthesis, is involved in photosynthesis regulation, embryo formation, cell differentiation and starch synthesis. The upregulation of TRE1 expression leads to a decrease in Tre6P and trehalose level, which results in the activation of SnRK1 activity that is inhibited by Tre6P [51]. TPS is a key enzyme gene for Tre6P synthesis and has a central role in trehalose biosynthesis [49]. Taken together, SnRK1 interacts with ATAF1, ATAF2, and TPS1, which links stress response, ABA signaling pathway and trehalose metabolism. On the one hand, AvNAC4, AvNAC58 and AvNAC69 may be involved in the ABA signaling pathway through interaction with the key regulator SnRK1. On the other hand, AvNAC58 and AvNAC69 may be involved in trehalose metabolism pathway through direct regulation of TRE1, while the decreased Tre6P level alleviated its inhibition of SnRK1 activity, thus affecting the ABA signaling pathway. In summary, plant resistance to environmental stress is an integrated regulatory network. The ability to withstand drought and salt stress is also the result of the combined action of various mechanisms. AvNAC4, AvNAC58 and AvNAC69 are potential candidate genes for improving the drought and salt tolerance of A. venetum and further studies are needed for verification. The NAC TF members were identified from the A. venetum genome derived from the whole genome data sequenced by our laboratory. To find the putative members of the NAC family in A. venetum, we used two methods, HMM (Hidden Markov Models) and BLASTp (Basic Local Alignment Search Tool for proteins). The HMM file of the NAM domain (PF02365) was obtained from Pfam (https://pfam.xfam.org/, accessed on 19 September 2022) [52], and the target genes were searched using HMMER 3.0 software with a threshold of e-value ≤ 10−5. Meanwhile, the NAC protein sequences of Arabidopsis (ANACs) were downloaded from TAIR (The Arabidopsis Information Resource, https://www.arabidopsis.org/, accessed on 19 September 2022) [53] and blast against the A. venetum genome by local BLASTp program with e-value ≤ 10−5. The outcomes of the two methods were merged and further verified by NCBI batch CD-search (https://www.ncbi.nlm.nih.gov/cdd (accessed on 20 September 2022)) with e-value ≤ 10−5 and SMART (Simple Modular Architecture Research Tool, http://smart.embl-heidelberg.de/, accessed on 29 September 2022) [54] to ensure that the sequences contained the complete NAM domain. The physical and chemical properties of the AvNAC proteins including amino acid number, molecular weight (MW) and isoelectric point (pI), were analyzed by ExPasy (https://www.expasy.org/, accessed on 11 October 2022) [55]. The CELLO v.2.5 (http://cello.life.nctu.edu.tw/, accessed on 11 October 2022) [56] was utilized for subcellular localization prediction of the AvNACs. The amino acid sequences of ANACs and identified AvNACs were merged and then aligned using MAFFT (L-INS-i algorithm) [57]. Subsequently, a phylogeny was generated by MEGA 11 with the Poisson model, using the neighbor-joining method with 1000 bootstraps and pairwise gaps deletion [58]. According to the classification of ANACs, the A. venetum NAC proteins were sub-divided into different subgroups. The iTOL (Interactive Tree of Life, https://itol.embl.de/, accessed on 20 October 2022) [59] was used to visualize the phylogenetic tree. Gene structures of AvNACs were characterized by the GSDS (Gene Structure Display Server, http://gsds.gao-lab.org/, accessed on 27 October 2022) [60] and the conserved motifs of AvNACs were identified using MEME (Multiple Em for Motif Elicitation, https://meme-suite.org/meme/tools/meme, accessed on 28 October 2022) [61] with the following parameters: maximal e-value = 1 × 10−5 and a range of motif widths from 6 to 50. The 1500 bp upstream sequences of the start codon (ATG) of each AvNAC gene were extracted from the A. venetum genome data using TBtools [62] and subjected to cis-element analysis using PlantCARE (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 03 November 2022) [63]. Additionally, the 1,000 bp upstream sequences of each AvNAC gene were subjected to transcription factor binding sites prediction analysis using PTRM (Plant Transcriptional Regulatory Map, http://plantregmap.gao-lab.org/binding_site_prediction.php, accessed on 08 November 2022) online tool with p-value ≤ 1 × 10−5, and the regulatory network was constructed by Cytoscape v.3.9 software [64]. Prediction of protein–protein interaction was performed by the online program STRING v.11.5 (https://cn.string-db.org/, accessed on 23 November 2022) [65], using AvNAC proteins as the queries and the Arabidopsis proteins as references. The chromosome distribution information was acquired from the A. venetum genome annotations, and the chromosomal map with gene positions was drafted using TBtools [62]. All the A. venetum protein sequences were aligned using the local BLASTp program with e-value ≤ 1 × 10−5, number of alignments of 5. Then, the BLASTp result and GFF file of genomic annotation were used to generate collinearity and tandem files by using MCScanX software to screen segmental and tandem duplication genes of AvNACs [66]. The non-synonymous (Ka) and synonymous (Ks) values of duplicated AvNAC gene pairs were calculated using KaKs Calculator 2.0 software and the selection model of gene pairs was estimated based on the Ka/Ks ratio [67]. The synteny analysis map between A. venetum and other species was constructed using TBtools [62]. The transcriptome data of three tissues comprising root, stem and leaf of A. venetum were obtained (SMAN23766539, SMAN23766540 and SMAN23766541) and the FPKM (fragments per kilobase of transcript per million mapped reads) values representing the expression levels of AvNACs were extracted to generate the heatmap by TBtools [62]. A. venetum seedlings were cultured under a hydroponic system following the procedure [68]. Three-week-old seedlings of similar size were selected and divided into two groups, one for drought treatment and the other for salt treatment. The seedlings were subjected to drought- (5, 10, and 20% PEG6000) and salt- (50, 100, and 200 mM NaCl) stress treatment for 24 h, while the control was treated with only water. The roots, stems and leaves were collected, frozen in liquid nitrogen and stored at −80 °C. Total RNA was extracted using SteadyPure Plant RNA Extraction Kit (Accurate Biotechnology (Changsha, China) Co., Ltd.), and the purity and concentration of total RNA were measured with NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). First-strand cDNA was synthesized using Evo M-MLV One Step RT-PCR Kit and used as a template for qPCR together with gene-specific primers. The b-tubulin (Tu) gene was used as a reference [69] (Supplement Table S6). Based on the reported NAC members associated with drought and salt stress in Arabidopsis and rice, the AvNAC genes were selected for qPCR by searching for their homologous sequences in A. venetum. qPCR was performed on CFX96 Touch Deep Well Real-Time PCR System (Bio-Rad, USA) using SYBR® Green Premix Pro Taq HS qPCR Kit II (Accurate Biotechnology (Changsha, China) Co., Ltd.). The reaction procedure consisted of an initial denaturation at 95 °C for 30 s, followed by 40 cycles for 5 s at 95 °C and 60 °C for 30 s. All experiments were performed in three independent biological replicates and each in three technical replicates. The relative gene expression level was calculated by the 2−ΔΔCT method. A genome-wide identification and analysis of the NAC family members were performed in the A. venetum genome. In this research, a total of 74 AvNAC TF members were identified and classified into 16 subgroups with NAC proteins from A. thaliana, and this classification was consistently supported by further analysis, including gene structures, conserved motifs and subcellular localizations. The inter-species synteny analysis of NAC genes indicated the close evolutionary relationship between A. venetum and S. lycopersicum. Analysis of gene promoter cis-elements revealed the potential function of the AvNAC genes and their roles in plant development and environmental stress responses. Moreover, ten AvNACs exhibited significant differential expression in response to drought and salt stresses, and the protein interaction prediction further confirmed the potential roles of AvNAC58 and AvNAC69 proteins in the trehalose metabolism pathway with respect to drought and salt resistance. In general, these results provide a reference for further functional studies of the NAC genes and promote the genetic improvement of growth, development and stress resistance in A. venetum.

PMC10003208

Bhaskar Roy,Shinichiro Ochi,Yogesh Dwivedi

Potential of Circulating miRNAs as Molecular Markers in Mood Disorders and Associated Suicidal Behavior

28-02-2023

biomarker,miRNA,depression,bipolar disorder,suicidal behavior

Mood disorders are the most prevalent psychiatric disorders associated with significant disability, morbidity, and mortality. The risk of suicide is associated with severe or mixed depressive episodes in patients with mood disorders. However, the risk of suicide increases with the severity of depressive episodes and is often presented with higher incidences in bipolar disorder (BD) patients than in patients with major depression (MDD). Biomarker study in neuropsychiatric disorders is critical for developing better treatment plans by facilitating more accurate diagnosis. At the same time, biomarker discovery also provides more objectivity to develop state-of-the-art personalized medicine with increased accuracy through clinical interventions. Recently, colinear changes in miRNA expression between brain and systemic circulation have added great interest in examining their potential as molecular markers in mental disorders, including MDD, BD, and suicidality. A present understanding of circulating miRNAs in body fluids implicates their role in managing neuropsychiatric conditions. Most notably, their use as prognostic and diagnostic markers and their potential role in treatment response have significantly advanced our knowledge base. The present review discusses circulatory miRNAs and their underlying possibilities to be used as a screening tool for assessing major psychiatric conditions, including MDD, BD, and suicidal behavior.

Potential of Circulating miRNAs as Molecular Markers in Mood Disorders and Associated Suicidal Behavior Mood disorders are the most prevalent psychiatric disorders associated with significant disability, morbidity, and mortality. The risk of suicide is associated with severe or mixed depressive episodes in patients with mood disorders. However, the risk of suicide increases with the severity of depressive episodes and is often presented with higher incidences in bipolar disorder (BD) patients than in patients with major depression (MDD). Biomarker study in neuropsychiatric disorders is critical for developing better treatment plans by facilitating more accurate diagnosis. At the same time, biomarker discovery also provides more objectivity to develop state-of-the-art personalized medicine with increased accuracy through clinical interventions. Recently, colinear changes in miRNA expression between brain and systemic circulation have added great interest in examining their potential as molecular markers in mental disorders, including MDD, BD, and suicidality. A present understanding of circulating miRNAs in body fluids implicates their role in managing neuropsychiatric conditions. Most notably, their use as prognostic and diagnostic markers and their potential role in treatment response have significantly advanced our knowledge base. The present review discusses circulatory miRNAs and their underlying possibilities to be used as a screening tool for assessing major psychiatric conditions, including MDD, BD, and suicidal behavior. Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders, affecting about 15–17% of the population in the United States, and is associated with significant disability, morbidity, and mortality. Bipolar I disorder, characterized by recurrent manic and depressive episodes, is estimated to have a 12-month prevalence of 0.6% to 2.8% [1,2]. Bipolar II disorder, characterized by a history of a hypomanic episode without mania, along with depressive episodes, has an estimated 12-month prevalence of 0.8% [1]. Patients with MDD and BD, especially those who are untreated, are at high risk for suicide. Most people with MDD or BD do not attempt or die by suicide, but both these disorders are linked to a greater risk of suicide. The estimated lifetime risk of suicide among MDD and BD patients is around 20% [3,4]; however, individuals with bipolar disorder are up to 20 times more likely to attempt suicide [5]. One of the challenges in the mental health field is the lack of consensus on the diagnosis. Also, a considerable number of mood disorder patients do not respond to the available medications. The primary reason is an incomplete understanding of the processes underlying these disorders, along with the limited availability of biologically based guidance for clinicians to effectively predict the development of mood disorders in patients at risk and prescribe medications that can effectively treat these patients. Changes in miRNA expression in plasma, serum, and cerebrospinal fluid (CSF) are an early indication of pathological changes in the brain. Unlike many other disciplines of medicine, the potential use of miRNAs as peripheral biomarkers is less appreciated in the psychopathological evaluations of mental disorders [6]. Lately, a significant number of clinical studies have shown coherent changes in miRNA expression between circulating blood and the brains of patients with psychiatric illnesses [7,8,9]. Over the past decade, increasing knowledge has helped understand miRNAs’ role in controlling gene expression by targeting RNA transcripts and diminishing their post-transcriptional output [10,11]. The altered genetic turnover can cause collateral changes in key cellular pathways [12]. Often these changes are associated with molecular pathologies related to disease development and progression [13]. Protracted miRNA expression modulation causes rippling effects ranging from gene expression alteration to a shift in cellular and behavioral phenotypes [14,15]. Similarly, the role of miRNAs in the brain is associated with the repatterning of gene expression changes and is the cause of improper neuronal functioning [16]. Empirically, several human postmortem brain studies have shown a divergent role of miRNAs in modulating gene functionalities in subjects with affective disorders and those having suicidal behavior or who died by suicide [17]. Based on these studies, the ability of miRNAs to change gene function has been a focus of the recent investigation to understand their role as an epigenetic modifier in the pathogenicity of mood disorders and vulnerability to developing suicidal behavior [18,19]. With remarkable breakthroughs in disease diagnosis and treatment development, biomarker discovery has become increasingly popular in the early detection of diseases and the timely limiting of their progression through drug discoveries [20]. Colinear changes in miRNA expression between the brain and systemic circulation have added great interest to examining their potential as molecular markers in mental disorders, including MDD, BD, and, most importantly, suicide [6]. There are multifold advantages of using miRNAs as biomarkers in psychopathology. For example, in addition to the correlative changes between brain and blood, the relative ease in assaying miRNAs in systemic circulation (including plasma, serum, saliva, and CSF) potentially positions them as prominent diagnostic and prognostic markers [21]. There is another salient feature of miRNAs that makes them excellent biomarkers. miRNAs are secreted in peripheral circulation in an enclosed vesicular structure or extracellular vesicles [22]. Vesicle-bound miRNAs often carry the molecular signature associated with the tissue of origin. In other words, miRNAs in free-floating extracellular vesicles are postmarked by their source tissue. This gives another dimension to the miRNA-based biomarker discovery. Besides extravesicular cargo, miRNAs in circulation can also be traced that are conjugated with proteins such as argonaute 2 (Ago2) and high-density lipoprotein (HDL). Most of the time, the role of these conjugated proteins is to provide stability and protection to miRNAs from nuclease activity [23]. Collectively, both classes constitute the family of circulating miRNAs with the potential to be used as peripheral biomarkers in neuropsychiatric disorders, such as MDD, BD, and suicidal behavior. The present review intends to spotlight the studies that have drawn significant attention to our understanding of the role of circulating miRNAs as potential biomarkers in three major neuropsychiatric conditions: MDD, BD, and associated suicidal behavior. Some of these miRNAs have the ability to be used as predictive biomarkers. In contrast, some have the potential to be categorized as treatment response biomarkers and are likely to be associated with risk prediction. This review also examined the similarities and differences of dysregulated circulating miRNAs between MDD and BD. Altogether, we have made a comprehensive overview of the literature to summarize the role of miRNAs in circulation and their potential value in diagnosing MDD, BD, and suicidal behavior based on their peripheral screening. The primary criteria used to search the circulating miRNA-associated reports were studies highlighting the role of circulating miRNA as peripheral biomarkers in MDD, BD and suicidality. With the help of PubMed database the search was performed to primarily include original articles for the last ten years using various keywords to increase the chance of article retrieval, falling under the criteria mentioned previously. The following keywords were used for retrieval: “circulating microRNAs” AND “Major depressive disorder” OR “MDD” OR “Major depression” AND “Bipolar disorder” OR “BD” AND “Suicide” OR “Suicidality” AND “Biomarker.” Mammalian miRNA biogenesis is a programmed cellular event and starts with their transcription in the nucleus with the help of RNA polymerase II/IIII (RNA Pol II/Pol III) [24]. The transcription often starts in the genomic loci, where miRNA coding units are engraved alongside mRNA coding units. The immediate product of transcription is the primary transcript (pri-miRNA) with a relatively larger size of ~1kilobase (kb). The pri-miRNAs structure consists of a stem terminal loop flanking overhang on both 5′ and 3′ ends. In the nucleus, the pri-miRNA triggers a self-cleaving process with the help of ribonuclease III enzyme Drosha and ancillary protein factor Dgcr8. Together, they form a microprocessor complex to crop off the overhangs on both sides of the pri-miRNA. The activity helps to release a shorter hairpin 65 nucleotides long and is called precursor miRNA or pre-miRNA [25,26]. This marks their exit from the nuclear environment toward cytosol with the help of active transportation by the Exportin 5 nuclear membrane complex. The release of pre-miRNA into the cytoplasm facilitates further enzymatic processing by the RNase III Dicer. The cleavage by Dicer finally generates mature miRNAs and makes them accessible to the argonaut 2 family protein. Finally, mature miRNAs are incorporated into the RNA-induced silencing complex (RISC), which helps them to regulate the fate of target gene expression by pairing primarily to the 3′untranslated region (3′UTR) of protein-coding mRNAs [27]. Once available in mature form, miRNAs participate in the post-transcriptional regulation of target transcripts by either depleting their endogenous level with the help of RNA RISC or by modulating translation machinery recruited on the coding transcript. MiRNAs function as master regulators of gene expression at the post-transcriptional level either by modulating the mRNA translation or transcript degradation by targeting the 3′UTR region [28]. Being a complex structure, the brain constantly faces countless challenges to maintain its homeostatic stability [13]. Most of the time, these challenges are associated with aversive environmental stimuli and carry the potential to discourse normal brain functioning via epigenetic factors such as miRNAs [29,30]. Aberrant gene expression regulation is often correlated with abnormal brain functioning and, to a large extent, targeted by miRNA molecules [29,31]. miRNAs act as molecular switches to flip the sides of gene regulatory workflow from a normal to a disease state [18]. Most prevalent neuropsychiatric illnesses, including MDD, BD, and suicidal behavior, have often shown discernable changes in miRNA expression [17,32]. Most of the time, the changes result from converging environmental challenges considered to be the precipitating factors associated with these mental disorders [33]. Over the years, an increasing number of studies have pointed out the neuropathogenic roles of miRNAs in MDD, which act in various capacities spanning from mRNA transcript sequestration to the competitive endogenous inhibition of coding genes [34,35]. However, most of the activities are associated with either anomalous gene expression regulation at the candidate level or the desynchronization of a large-scale gene regulatory network at the genomic level [35]. Some of the notable reports of miRNA changes in the MDD brain include the anterior cingulate cortex [ACC], dorsolateral prefrontal cortex [BA] 9, other prefrontal cortical areas (BA10, BA44, BA46), and the locus coeruleus [LC]), which are known for their roles in mood disorders [17,36,37]. Studies from our lab have provided an advanced understanding on how miRNA, being a small epigenetic regulator, can be associated with underlying molecular changes in the MDD brain [7,38]. Our group, for the first time, explored miRNA expression changes in the brain of suicide subjects diagnosed with MDD. A total of 21 miRNAs were found significantly downregulated compared to healthy control subjects [39]. Surprisingly, the overall change in miRNA expression had a decreasing trend in MDD-suicide subjects. In the same report, several overlapping target genes were found among 21 dysregulated miRNAs. Later, we studied synaptosomal miRNAs from BA10 of the MDD brain [40]. The expression of miR-508-3p and miR-152-3p was significantly downregulated in the MDD brain compared to control subjects. However, miR-508-3p expression in suicide subjects was significantly lower than in non-suicide MDD subjects. In another study, we showed the downregulation of miR-124-3p expression in BA46 of MDD subjects [7]. For the same miRNA, parallel expression changes were found in the serum of antidepressant-free MDD patients. Moreover, the expression of miR-124-3p was suppressed by fluoxetine treatment [7]. Recently, we also explored the miRNA-related changes in LC of MDD suicide subjects on a semi-high throughput expression platform [17]. A total of ten upregulated and three downregulated miRNAs were detected in MDD subjects. Based on target gene prediction using the upregulated miRNAs, we narrowed our study to genes with a robust neuropsychiatric relationship (RELN, GSK-3β, MAOA, CHRM1, PLCB1, and GRIK1). Of those, reduced expression levels were found for RELN, GSK-3β, and MAOA genes [17]. Recently, a sizeable number of studies have been published to highlight the true potential of miRNAs to be used as biomarkers in circulation for MDD, BD, and suicidal behavior. Although it is rather impossible to track down peripheral changes in patients who died by suicide, a few studies have shown altered miRNA responses in circulation to be associated with an increased risk of suicide. In the following section, we have described some key findings published over the past few years that have contributed substantially to understanding circulating miRNAs’ role as molecular biomarkers in MDD diagnosis (Table 1). Maffioletti et al. [41] tested the whole blood expression of 1733 miRNAs using microarrays in patients with MDD (n = 20) as compared to those with BD (n = 20) and healthy controls (n = 20). Ten miRNAs were altered in MDD compared to controls. More precisely, the authors noted MDD-specific changes in let-7a-5p, let-7d-5p, let-7f-5p, miR-24-3p, and miR-425-3p. The authors also used bioinformatic analysis to determine signaling pathways targeted by these miRNAs and found that Wnt and mTOR signaling were the main targets. In a separate study, an Affymetrix expression array was used to determine miRNA expression changes in blood mononuclear cells (PBMC) [42]. The array identified 26 miRNAs with significant changes in expression in MDD patients. The data were further validated in a larger cohort of 81 MDD patients and 46 healthy controls. The qPCR-based outcome confirmed the upregulated expression of five miRNAs (miRNA-26b, miRNA-1972, miRNA-4485, miRNA-4498, and miRNA-4743). Receiver operating characteristic (ROC) curve analysis determined a confidence level of 0.636 (95% confidence interval (CI): 0.58e0.90) for those five miRNAs. The authors also used these miRNAs in target gene prediction and their functional annotation. The functional analysis identified pathways associated with the nervous system and brain functions. Collectively, the report supports the principle of using blood-based miRNA expression changes in MDD diagnosis [42]. In another study, Camkurt et al. [43] investigated miRNA expression changes in MDD patients using plasma drawn from the venous blood of 50 depressed patients and 41 healthy controls. qPCR-based expression analysis showed significant changes in four miRNAs when MDD patients were compared with healthy controls. The three in the upregulated group were miR-451a, miR-17-5p, miR-223-3p, and the downregulated one was miR-320a. According to the authors, miR-451a could be a candidate biomarker for depression. Our lab showed the expression changes of miR-124-3p in the postmortem brain samples from MDD patients [7]. Following the same trend, a significant ~3.5-fold increased expression in miR-124-3p was noted in the serum of MDD patients free from any antidepressant treatment. Our study implicated for the first time the role of stress-induced miR-124-3p as a potential biomarker in MDD pathogenesis. The role of miR-124 was further supported by another peripheral study in MDD patients [44]. This study investigated the expression changes in miR-124 in the peripheral blood mononuclear cells (PBMCs). The expression changes were examined in 32 pre- and post-treatment MDD patients and 30 healthy controls. The results showed significantly higher expression of miR-124 in MDD patients, and the sensitivity was determined as 83.33% with ROC analysis. Interestingly, the specificity for MDD patients was 66.67%, clearly distinguishing them from healthy controls. More interestingly, the level of miR-124 expression was significantly downregulated in MDD patients after eight weeks of antidepressant treatment. These results further consolidate the potential use of miR-124 as a blood-based biomarker for MDD diagnosis and treatment response [44]. In another study, the authors were interested in determining miRNA changes in the serum of perioperative patients who had developed depression [45]. They primarily examined if specific miR-221-3p could be used as a biomarker for depressed mood in perioperative patients. In their study plan, two sets of perioperative patients were included having either mild depressive mood or moderate to severe depressive mood. Serum-based qPCR data suggested a greater than 2-fold significant expression upregulation of miR-221-3p in both the depressed groups compared to the control group. Correlation analysis between serum-based miR-221-3p expression and depressed mood score established a positive relationship, suggesting that the elevated expression of miR-221-3p can serve as a biomarker for depressive mood in perioperative patients. The authors further pointed out the ability of miR-221-3p to induce the expression of interferon (IFN)-α in astrocytes by targeting IRF2. The miR-221-3p could be mechanistically connected with anti-inflammatory pathways via the IFN- α signaling cascade [45]. Besides blood, CSF has also been used to study the level of miRNA changes in depression. A study by Wan et al. [46] analyzed the expression of 179 miRNAs from a PCR panel using CSF from MDD patients. The PCR data detected significant changes in CSF miRNAs; eleven were upregulated, and five were downregulated. The CSF results were further verified in the same patient serum samples, and the results found similar changes in three miRNAs (out of eleven miRNAs) from the upregulated group but only one miRNA (out of five miRNAs) from the downregulated group. All four miRNAs (upregulated: miR-221-3p, miR-34a-5p, let-7d-3p, and downregulated: miR-451a) were further validated in a larger cohort of thirty-two MDD patients. The ROC analysis responded with a higher degree of sensitivity and specificity (the majority were above the 80% scale) for all four miRNAs in MDD diagnosis. A similar study showed a strong anti-correlation of CSF miR-16 with MDD [47]. This study found a significantly lower level of miR-16 expression in the CSF of 36 drug-free patients and a significantly lower amount of serotonin in the same CSF samples. However, testing the miR-16 expression in the blood sample of the same MDD patients did not identify any significant changes when compared with healthy control subjects. For the first time, the study showed a direct relationship between miR-16 and serotonin levels using CSF from MDD patients. In a separate report by Sun et al. [48], changes in two miRNAs (miR-34b–5p and miR-34c–5p) based on peripheral blood leukocytes were strongly associated with MDD. In addition, the study also determined an increased risk of suicide and cognitive decline associated with miR-34b–5p and miR-34c–5p expression levels. The study included 32 MDD patients with a matching number of healthy controls and analyzed the expression of miR-369-3p, miR- 34b-5p, miR-34c–5p, miR-381, and miR-107 in blood leukocytes. The study concluded that defective Notch signaling functions could potentially be associated with miR-34b-5p and miR-34c-5p out of the five miRNAs studied in MDD patients. Instead of showing the potential of known and characterized miRNAs as biomarkers in MDD diagnosis, a study by Zhao et al. [83], for the first time, reported a novel miRNA, pmiR-chr11, in MDD patient blood. The study was designed to explore the miRNome-wide changes in a small exploratory cohort of 10 MDD and 10 control subjects. The significant findings from the exploratory cohort were further validated in a larger cohort size of 72 MDD and 75 control cases. Among 10 significantly altered miRNAs from the exploratory cohort, only pmiR-chr11 was found to be significantly upregulated in MDD patients as compared to controls. Prediction analysis identified Bromodomain and PHD finger-containing protein 1 (BRPF1) as potential target genes strongly associated with hippocampal volume. In vitro validation experiments further supported BRPF1 as the direct target of novel pmiR-chr11. Taking the lead from blood-based miRNA changes, the authors suggested a possible role of BRPF1 in hippocampal neurogenesis, which could be affected by the increased expression of pmiR-chr11 in the MDD brain. Early life adversities in the form of childhood maltreatment (CM) could be a major risk factor for developing depression during adulthood. He et al. [49] found an association of miR-9 with CM in the peripheral blood of 40 untreated MDD patients and 34 healthy controls. The study also found miR-9 to play a potential role in making changes in the functions of the prefrontal limbic regions of MDD patients examined through resting-state fMRI scans, which could be associated with early CM experience. A recent study investigating the miRNA expression changes in the plasma samples of MDD patients (84 MDD cases) found 11 miRNAs to be upregulated from miRNA sequencing data [50]. After adjusting the odds and considering the expression detection limit following qPCR, only two miRNAs (let-7e-5p and miR-125a-5p) were found to be potentially associated with MDD. Both let-7e-5p and miR-125a-5p were upregulated with moderate diagnostic sensitivity and specificity. From these results, let-7e-5p and miR-125a-5p could be added to the potential list of biomarkers in MDD diagnosis. Understanding the role of inflammation in MDD has been a long-standing interest; however, only a few studies have attempted to discover the association of peripheral blood miRNAs with depression and its severity related to inflammatory signaling. A study published by Hung et al. [51] analyzed the expression of let-7e, miR-21-5p miR-145, miR-223, miR-146a, and miR-155 in the PBMC of 84 MDD patients before and after antidepressant treatment. The PBMC data showed lower levels of let-7e, miR-146a, and miR-155 in MDD patients than in healthy controls and were significantly higher in patients after four weeks of antidepressant treatment. On the contrary, miR-146a and miR-155 in PBMC were lower in MDD patients and increased after receiving antidepressant treatment. Interestingly, the depression severity was found to be inversely correlated with let-7e and miR-146a expression, whereas a direct correlation was found for miR-155. These miRNAs are part of toll-like receptor signaling pathways directed toward the TLR4 system. Therefore, the changes in these TLR4-regulating miRNAs in MDD patients and their association with depression severity and their responsiveness to AD treatment could be used as biomarkers in diagnosis and treatment response. An intriguing part of devising MDD treatment is understanding the periodic relapse common in patients formerly treated with antidepressants. Analyzing miRNA expression changes in the peripheral circulation of MDD-relapsed cases could be valuable in developing potential biomarkers for recurring MDD. One such study by Li et al. [52] examined miRNA expression changes in the serum samples of 63 relapsed and 154 non-relapsed MDD patients. A lower level of expression was noted for four miRNAs (miR-199b- 5p, miR-143-3p, miR-200a-3p, and miR-215-5p). The low expression levels of these four miRNAs were also associated with a lower risk of future relapse. The predicted targets of these four miRNAs and their functional clustering identified several neurobiological functions and pathways that included neurogenesis, response to cytokine, neurotrophin signaling, vascular endothelial growth factor signaling, relaxin signaling, and cellular senescence pathways. Interestingly, miRNA can be used as a biomarker for predicting the disease development trajectory, as reported in a nested case-control study by Roumans et al. [53]. In this study, 104 cases were enrolled as MDD-free and 52 of them developed MDD in the course of the following five years. The remaining 52 participants did not develop any MDD and were treated as a control to compare the miRNA findings. The expression levels of five miRNAs (miR-17-5p, miR-134-5p, miR-144-5p, let-7b-5p, and let-7c-5p) were analyzed from plasma at the baseline. After adjustments of all odds, the expression level of let-7b-5p was significantly lower at the baseline. Interestingly, the level of let-7b-5p remained significantly lower and was negatively associated with developing MDD. This is one of the notable studies showing that the future risk of developing MDD can be related to peripheral miRNA expression and could be used as a biomarker for MDD risk prediction. A study published by Gururajan et al. [54] showed miRNAs’ relationship with two effective therapies in MDD patients who had an inadequate response to two consecutive antidepressant treatment regimens of different pharmacological classes. The study was conducted to identify changes in peripheral miRNA expression in 40 MDD patients who were clinically diagnosed with TRD and received electroconvulsive therapy (ECT) and ketamine infusion. In the ECT group, 24 patients were tested for genome-wide miRNA expression in blood. The same procedure was followed in the ketamine treatment group, where 16 patients were screened for miRNA changes. Expression data were compared between cases and controls at baseline and after treatments. Although decreased levels were noted for let-7b and let-7c at baseline and after ECT, no significant miRNA changes were noted for ketamine treatments as determined by qPCR. This study concluded that the baseline expression of miRNAs could not be a good predictor of treatment response. However, the trending changes in let-7b and let-7c expression could potentially be used as biomarkers for TRD. Another study examined changes in miR-134 in 100 MDD patients treated with antidepressants [55]. At the baseline, the plasma miR-134 was significantly downregulated in the MDD group compared to the control group. After eight weeks of follow-up with AD treatment, significant expression upregulation of miR-134 was noted in partially responsive and fully responsive MDD subjects. However, a non-significant change was found in the mean plasma level of miR-134 when the non-responders were considered independently. The diagnostic accuracy of miR-134 was determined in MDD patients following ROC and was found to be 0.901 with an AUC. The sensitivity and specificity of miR-134 in diagnosing MDD were 79 and 84%, respectively. Overall, the study suggested a reduced level of plasma miR-134 in the acute phase of MDD independent of any AD treatments. Additionally, the study found an increasing level of plasma miR-134 with the symptomatic improvement of MDD following eight weeks of AD treatment. However, it has also been noted that patients with minimal plasma miR-134 may not respond well to conventional AD treatments. Altogether, responses in miR-134 can be effectively used as a state-dependent biomarker in MDD prognosis. Recently, circulating miR-144-3p has been identified as a molecular marker to predict depression severity and treatment response biomarker to ketamine [56]. The study determined a sex-independent higher level of miR-144-3p expression at the baseline of MDD and a positive correlation with depression severity. However, a male-specific reduction in miR-144-3p expression was determined based on a correlation with ketamine treatment response. Similar changes in miR-144-3p were noted in the mouse model of chronic social defeat stress. The reversal in expression was evident when chronically stressed mice were treated with repeated doses of imipramine or a single dose of ketamine. The study also successfully antagonized the stress-inducing effect of miR-144-3p by systematically injecting antisense miR-144-3p locked nucleic acid in mouse blood. The systemic knockdown of miR-144-3p was sufficient to reduce the depression-like phenotype in mice. Understanding the role of miRNAs in the mechanism of antidepressant treatment response has been a field of interest for a long time. For the first time, Bocchio-Chiavetto et al. [57] analyzed the global miRNA expression in 10 depressed subjects after ten weeks of escitalopram treatment. Genome-wide miRNA expression data suggested changes in 30 miRNAs in AD-treated MDD subjects. Among 30 analyzed miRNAs, 28 were upregulated, and the remaining 2 were downregulated. This study also noted that the potential targets of all the altered miRNAs had demonstrated functional enrichment for neuronal pathways, including neuroactive ligand–receptor interaction, axon guidance, long-term potentiation, and long-term depression. Lopez et al. [58] used next-generation sequencing in MDD patients treated with duloxetine and found the downregulation of several miRNAs that targeted Wnt and MAPK signaling. They found that six miRNAs were altered by treatment and placebo and hypothesized that they might be responsible for a common response to antidepressant treatment. After replication in patients treated with escitalopram and in human postmortem brains, their study showed that miR-146b-5p, miR-24- 3p, and miR-425-3p were downregulated by AD treatment and upregulated in the brains of patients who died by suicide. The MAPK and WNT signaling pathways were found to be strongly associated with these miRNAs. This evidence supports that the downregulation of miR-146b-5p, miR-24-3p, and miR-425-3p may be related to improved symptomatology via increased MAPK and WNT signaling. These miRNAs also seem to be consistently and significantly associated with behavioral responses to antidepressants and showed strong promise as clinical biomarkers. Receptors for neurotransmitters remain key targets for pharmacological manipulation and potential drug development in MDD. Glutamatergic receptor GRM4 is one such target with a role in MDD pathogenesis. Interestingly, miR-335 has been reported to play a significant role in modulating the GRM4 receptor using [59]. The authors in this study showed the significant downregulation of miR-335 in the blood samples of MDD patients compared with healthy controls. Measuring miR-335 and GRM4 in the peripheral blood samples of MDD patients treated with citalopram showed that the expression of miR-335 was upregulated. In contrast, the GRM4 level was decreased significantly in MDD patients compared to healthy controls. This was the first study to show a mechanistic relationship between a miRNA and a neurotransmitter receptor and highlighted the use of miRNAs as potential biomarkers in predicting treatment response in MDD patients. A small study by Enatescu et al. [60] analyzed the expression of 222 miRNAs in the plasma samples of five MDD patients to identify treatment-specific miRNA changes. The results from the analysis determined differential changes in 40 miRNAs in response to AD treatment. Among 40 differentially expressed miRNAs, 23 were significantly upregulated, and 17 were significantly downregulated in MDD patients compared to control subjects. In further analysis to understand the functional contribution of the 40 dysregulated miRNAs, a prediction algorithm identified pathways related to Wnt signaling, endocytosis, axon guidance, and MAPK signaling. The authors found six key miRNAs primarily enriching four of the five above-mentioned functional pathways. A later study based on the plasma samples of MDD patients identified the responsiveness of miR-132 and miR-124 to treatment [61]. The results showed the significant enrichment of miR-132 expression in MDD patients compared to control subjects and MDD patients treated with citalopram for two months. On the other hand, changes in miR-124 expression in untreated and citalopram-treated MDD patients were significantly higher than in control subjects. The authors also examined the BDNF level in the plasma samples of both MDD groups following the immunosorbent assay and found a trending increase. Additionally, the authors determined a positive correlation between increasing miR-132 levels in plasma and depression severity based on HAMD and HAMA scales. The authors concluded that plasma-based expression changes in miR-132 could be used as a diagnostic biomarker in determining depression status in clinical settings. Another study analyzed ten miRNAs (miR-16, miR-30, miR-34, miR-128, miR-132, miR-134, miR-182, miR-183, miR-185, and miR-212) in the serum of MDD patients treated with either selective serotonin reuptake inhibitor (SSRI) or serotonin–norepinephrine reuptake inhibitor (SNRI) [62]. The study aimed to determine the peripheral changes in miRNAs associated with the BDNF signaling pathway. In the study, 13 patients received SSRI treatments, whereas 20 were given SNRIs. After analyzing all data sets from the two treatment groups, only miR-16 showed a significant increase in the SSRI-treated group. After adjustment and multiple corrections, no significant changes were identified for other miRNAs in both SSRI and SNRI groups. However, after four weeks of AD treatments, the Wilcoxon signed rank test identified an overall significant increase in miR-183 and miR-212 levels in MDD patients. The findings from this study are critical to understanding the role of miRNAs as predictors of AD treatment. Their differential responsive pattern under different pharmacological agents could be vital in selecting the biomarker panel for proper clinical management. This section presents a series of studies showing how circulating miRNAs could be associated with BD. A list of miRNAs related to BD is shown in Table 1. In the plasma of 66 BD patients who were treated with lithium and 66 control subjects, Tekdemir et al. [69] investigated plasma miRNAs and found a significant increase in miR-132, miR-134, miR-152, miR-607, miR-633, and miR-652, and a significant decrease in miR-15b and miR-155 levels in BD patients. They suggested that an increase in miR-134-5p, miR-652-3p, and a decrease in miR-15b and miR-155-5p were associated with the risk of BD. They found that miR-155-5p was explicitly associated with the disease burden and severity. Fatty acid biosynthesis and metabolism, viral carcinogenesis, the EBV infection, and extracellular matrix and adhesion pathways were highlighted as target pathways. In whole peripheral blood from 56 (25 females and 31 males) BD-I patients and 52 (26 females and 26 males) control subjects, Tekin et al. [72] demonstrated a significant increase in miR-376a-3p, miR-3680-5p, miR-4253-5p, and miR-4482-3p levels and a significant decrease in miR-145-5p level in BD-I patients. They also revealed that miR-145-5p targeted the dopamine decarboxylase (DDC) gene, which could serve as a biomarker for BD-I. Interestingly, Lee et al. [71] explored the possibility of serum miRNAs as specific biomarkers for BD-II. Using next-generation sequencing, they identified six miRNAs to be differentially regulated that can differentiate BD-II patients from controls. These candidate miRNAs were confirmed with real-time PCR in a cohort of 79 BD-II and 95 controls. A diagnostic model was built based on these candidate miRNAs and then tested on an individual testing group (BD-II: n = 20, controls: n = 20). They found that the serum levels of miR-7-5p, miR-23b-3p, miR-142-3p, miR-221-5p, and miR-370-3p were significantly increased, whereas miR-145-5p had no significant difference in BD-II patients compared with controls. Support vector machine measurements revealed that a combination of the significant miRNAs reached good diagnostic accuracy (AUC: 0.907). In a follow-up study, the same group investigated the correlation between miR-7-5p, miR-142-3p, miR-221-5p, and miR-370-3p with BDNF levels using the serum of 98 (65 females and 33 males) BD-II patients [77]. They revealed that miR7-5p, miR221-5p, and miR370-3p were significantly correlated with the plasma BDNF levels, and miR142-3p was significantly correlated with durations of illness. They also analyzed a correlation of these miRNAs with BDNF Val66Met polymorphism and found that miR-221-5p and miR-370-3p were significantly correlated with BDNF in only the Val/Met genotype and miR-7-5p in all three genotypes. Another group of investigators examined miRNAs in BD patients using plasma [67]. In 69 BD patients and 41 controls, they reported a significant increase in miR-185-5p, miR-25-3p, miR-92a-3p, miR-376b-3p, and let-7i-5p and a significant decrease in miR-484, miR-652-3p, miR-142-3p, miR-30b-5p, miR-126-3p, miR-15a-5p, miR-126-5p, and miR-301a-3p levels in BD patients. From Benjamini–Hochberg correction, they revealed that miR-185–5p was significantly increased, and miR-484, miR-652–3p, and miR-142–3p were significantly decreased and suggested that these four microRNAs could be used as biomarkers with a specificity of 75.0% and a sensitivity of 87.1%. In a similar fashion, Fries et al. [68] examined miRNAs in the plasma of 20 BD-I patients and 21 controls. They revealed that a set of 33 microRNAs were significantly different in the BD group compared to the control group and were associated with netrin and endothelin signaling, 5HT2 receptor-mediated signaling, β1 and β2 adrenergic receptor signaling, and androgen receptor signaling. Most of these miRNAs differed from what was previously reported by Ceylan et al. [67]. More recently, using a comprehensive literature search and data mining approach, a report suggested that miR-106b, miR-125a, miR-142, miR-221, and miR-652 can be used as circulating miRNAs for diagnosing BD [84]. A few studies have independently examined mania and euthymia’s impact on miRNA expression. To determine if specific miRNAs are associated with psychotic manic episodes in BD patients, in plasma samples from a group of 15 BD patients and 9 control subjects, Tabano et al. [70] reported a significant increase in miR-150-5p, miR-25-3p, miR-451a, and miR-144-3p, and a significant decrease in miR-363-3p, miR-4454, miR-7975, miR-873-3p, miR-548, miR-598-3p, miR-4443, miR-551a, and miR-6721-5p, suggesting that miRNA changes may differ in manic patients within the BD group. Functionally, the increased miRNAs were associated with metabolic regulation and the decreased ones with neurogenesis and neurodevelopment. In a similar line of investigation, another study examined miRNAs in plasma from 58 BD-I patients with manic and euthymic episodes (19 with mania and 39 with euthymia) and 51 controls [74]. It was found that compared to controls there was a significant increase in miR-9-5p, miR-29a-3p, miR-106a-5p, miR-106b-5p, miR-107, miR-125a-3p, and miR-125b-5p in BD patients with manic episodes, and a significant increase in miR-29a-3p, miR-106b-5p, miR-107, and miR-125a-3p in BD patients with euthymic episodes. They also showed that miR-106a-5p and miR-107 in BD with manic episodes were more significantly increased than in the euthymic episodes. This study clearly demonstrates state-specific miRNAs in BD patients. Interesting results were noted when miRNAs were examined in BD patients with and without treatment. An examination of plasma miRNAs from 21 (7 females and 14 males) BD patients with manic episodes who did not receive any medication and 21 (7 females and 14 males) healthy controls found that the level of miR-134 was significantly decreased in BD patients [85]. Interestingly, following medication, miR-134 levels gradually increased from baseline. After four weeks of medication, miR-134 levels were significantly increased from baseline, but compared to controls miR-134 levels in BD patients were still considerably lower. Another study investigated changes in miRNAs before and 12 weeks after asenapine or risperidone treatment from blood samples of 10 BD-I patients with manic episodes [75]. The investigators reported a significant increase in miR-15a-5p, miR-17-3p, miR-17-5p, miR-18a-5p, miR-19b-3p, miR-20a-5p, miR-27a-3p, miR-30b-5p, miR-106a-5p, miR-106b-5p, miR-145-5p, miR-148b-3p, miR-210-3p, and miR-339-5p, and a significant decrease in miR-92b-5p and miR-1343-5p in the asenapine group from baseline. There was a significant decrease in miR-146b-5p, miR-664b-5p, and miR-6778-5p in the risperidone group. Examining the differences in miRNA expression between MDD and BD is critical. A few studies have attempted to explore this differentiation by paralleling examing miRNA expression in circulatory blood samples from BD and MDD patients. A study investigated miRNAs in blood samples from 20 BD patients, 20 MDD patients, and 20 controls [41]. In this study, compared to controls, a significant increase in miR-21-3p, miR-29c-5p, miR-30d-5p, miR-140-3p, miR-330-3p, miR-330-5p, miR-345-5p, miR-378a-5p, miR-720-5p, miR-1973-5p, miR-3158-3p, and miR-4521-5p was observed in BD patients. In addition, a significant decrease in miR-1915-5p, miR-1972-5p, miR-4440-5p, and miR-4793-3p was also found in BD patients. Interestingly, miR29c-5p, miR-330-3p, and miR-345-5p were increased in both MDD and BD compared with controls. The study also found a more significant upregulation of miR-21-3p, miR-30d-5p, miR140-3p, miR-330-5p, and miR378a-5p in BD patients than MDD and controls. miRNA expression levels were also examined in PBMC from 63 (26 females and 37 males) BD patients, 42 (18 females and 24 males) MDD patients, and 57 (26 females and 31 males) controls [73]. The study revealed a significant increase in miR-499-5p in BD patients but not MDD patients compared to controls. This miRNA was found to regulate calcium voltage-gated channel auxiliary subunit beta 2 (CACNB2) in the mouse hippocampus, which has been implicated in BD. In addition to comparing miRNAs between MDD and BD, one study examined specific miR-134 in BD, MDD, and schizophrenia patients [55]. In a cohort of 50 BD, 100 MDD, 50 schizophrenia, and 100 control subjects, the study found that plasma miR-134 was significantly downregulated in MDD patients and plasma miR-134 levels could effectively distinguish MDD from controls with 79% sensitivity and 84% specificity, while distinguishing MDD from controls, BD, and schizophrenia subjects with 79% sensitivity and 76.5% specificity. A relatively small study in the plasma of seven BD, seven MDDD, and six control subjects found a more significantly decreased level of miR-19b-3p in BD than in MDD and control groups [76]. The study also found that the expression of miR-19b-3p in BD was significantly associated with early life stress. Interestingly, while examining plasma samples from 26 BD patients, 84 MDD patients, and 74 controls, Let-7e-5p and miR-125a-5p showed a significant increase in both BD patients and MDD patients compared with controls, these two miRNAs were not different between BD and MDD patients [50]. Interestingly, an independent study showed that miR-15b, miR-132, and miR-652 were significantly upregulated in the blood samples of high-risk mood disorder patients when examined in 34 high genetic risk mood disorder patients and 46 control subjects [78]. There is an overarching need for future miRNA biomarker discovery that can effectively articulate the risk of suicidality, including suicidal ideation (SI) and recovery from suicidal intent. As shown in Table 1, circulating miRNA in suicidality is a less studied area. A genome-wide miRNA expression profiling study determined changes in miRNA levels from 42 inpatients admitted for strong suicidal ideation [79]. The expression analysis was primarily focused on understanding the miRNA expression changes in the plasma of 42 SI patients who later recovered. The SI patients showed the decreased expression of four miRNAs (miR-424-5p, miR-378i, miR-6724-5p, and miR-10b-5p) after their recovery from SI. The authors found a close association of these miRNAs with key brain functions involving the MAPK, ErbB, AMPK, Ras, p53, and PI3K-Ak pathways. These pathways have previously been shown to be related to depression and suicidality. This exciting finding could unfold the potential of circulating miRNAs to be used as markers for the symptomatic remission of suicidal intent in the recovery phase. A few recent reviews compiled studies and speculated that miRNAs could be associated with suicidal behavior [6,86]. For example, an algorithm search through the miRNA database identified miR-27b-3p, miR-124-3p, miR-129-5p, miR-381-3p, miR-3135b, miR-4516, and miR-4286 that were most related to suicide [80]. A clinical study investigated miRNAs in the PBMC of 12 MDD patients with severe suicidal ideation and 12 controls [81]. The study reported that miR-19a-3p was significantly associated with suicidal behavior. This miRNA was found to regulate TNF-α, a proinflammatory gene implicated in mood disorders and suicide. To examine if miRNAs could be used as predictors of the treatment-worsening of suicidal ideation (TWSI), a recent study investigated miRNAs in the whole blood of 237 MDD patients (112 with duloxetine and 125 with placebo) [82]. A total of 11 patients with duloxetine showed TWSI, and miR-3688 and miR-5695 were significantly associated with the worsening of suicidal ideation. As mentioned above, a majority of the studies on suicidal patients have been conducted in the context of MDD. Of miRNAs that are studied in suicidal patients, miR-124-3p and miR-129-5p are associated with MDD [7,60,80], and miR-3135b and miR-4516 are associated with BD [68,80]. However, no previous study reported common suicide-associated miRNAs in both disorders. It will be important to dissect miRNAs associated with suicidal behavior that are common to both disorders. Also, distinguishing miRNAs that are associated with suicidality in BD patients vs. those in MDD patients will also provide a clear distinction of disease-specific suicidality-related miRNAs, given that BD patients have a higher potential for suicide than patients with MDD [87,88]. Pathophysiological changes in MDD and BD could result from genes that lose their harmonized expression patterns due to regulatory influence by miRNAs. Based on the literature discussed in this review, we compared the list of circulatory miRNAs found to be altered in MDD and BD patients. We determined that 129 miRNAs were uniquely associated with the MDD group, 91 miRNAs were uniquely associated with the BD group, and 23 miRNAs were shared between MDD and BD groups (Figure 1A). The chromosomal coordinates, full sequences, and their current miRBase ID of the two sets of miRNAs uniquely associated with MDD and BD are provided in Table 2. We further used the unique miRNA sets from the MDD and BD groups to predict their targets independently. All predicted targets were filtered based on the brain enrichment database and independently used in functional analysis to determine the biological pathways following the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. In Figure 1B,C, we have shown the individual pathways targeted by miRNA sets for MDD and BD, respectively. The pathway lists were modified to incorporate the key pathways enriched for neurobiological functions and neuropsychiatric disorders. Each bar in the bar diagram (Figure 1B,C) also represents the number of miRNA-targeted genes associated with individual pathways. In the figures, the bar plots are further classified in four separate colors to show their general biological relevance in metabolism, environmental information processing, cellular processes, the organismal system, and human disease. Interestingly, our analysis retrieved most of the pathways (both in MDD and BD) as part of the environmental information processing clan. This is an intriguing finding, given that both MDD and bipolar disorders are the results of environmental insults and are mediated through epigenetic modifiers in the brain [89]. It is equally interesting to highlight that the maximum number of targeted genes is also part of the environmental information processing category. This gives an idea of how peripherally screened miRNAs from MDD and BD patients and their corresponding biological axis in the brain can be epigenetically involved in disease pathogenesis and progression. From the bar plots, we can also notice that PI3-AKT signaling had the maximum number of genes (30) targeted by miRNAs in MDD. Earlier reports from both preclinical and clinical models have suggested the cortico-limbic deficits of PI3-AKT signaling in affective disorders, especially in MDD [90,91]. In BD, we can see the maximum number of target genes (22) as part of the MAPK signaling pathway. Interestingly, the two most common bipolar treatments (e.g., valproic acid and lithium) target MAPK signaling and regulate MAP kinase activity. Mechanistically, valproic acid helps activate the MAPK pathway in the brain [92]. Thus, the biological role of miRNAs in the BD brains relates to their peripheral counterpart, as we found them to be altered in blood circulation. Part of our analysis was also dedicated to mapping the target genes and how they are cross connected with various pathways. In Figure 2A,B, we have presented two Sankey plots showing the connectedness of individual genes (targeted by miRNAs) with shared and/or unique pathways in MDD and BD, respectively. In preparing the graphs, we limited the number of genes to not more than 25 from each pathway to enhance the clarity of the plots. A bubble diagram has also been appended to show the gene counts for respective pathways (Figure 2C). Additionally, we wanted to understand the singularity and relatedness of the two disorders by comparing the targeted pathway they may share. We found that in the BD group a lesser number of genes are targeted by the miRNAs for some of the pathways, including Rap1, Relaxin, actin cytoskeleton, TNF signaling, synaptic vesicle, T-cell receptor signaling, dopaminergic synapse, and calcium signaling compared to the MDD group. However, we want to caution that this does not mean those pathways are not affected in BD. It could be due to the target prediction algorithm and their subsequent functional clustering, which finally adopted fewer pathways associated with genes in the BD group compared to the MDD group. On the other hand, besides PI3-AKT signaling, a sizable gene enrichment can be seen for MAPK and Ras signaling pathways in both the MDD and BD groups. Finally, in Figure 3A,B, we presented the miRNA-target gene network based on a prediction scheme. The networks from the MDD and BD groups were prepared to highlight the degree of connectedness between the miRNAs and their predicted targets. The two networks were filtered to include target genes from the brain database. To increase the strength of the edges (connections) between the nodes, we applied a degree threshold power of 2.0 in the degree filter parameter and plotted the connections by applying the edge bundling feature. Due to the higher degree threshold, the network only included the miRNAs with the strongest connection to their target genes. The network maps highlight the density of the connections, which is more prominent in the MDD group than in the BD group. This could be due to the smaller number of miRNAs in our literature review based on BD. Altogether, our meta-analysis based on the circulating miRNAs from MDD and BD patients reverberate their biological importance in affecting various brain functions under pathological conditions. The biggest challenge of using miRNAs as biomarkers in neuropsychiatry is associated with genetic heterogeneity and extrinsic factors, such as medication, nutrition, or exposure to specific environmental conditions. In some instances, a single miRNA could provide a correlation with disease development and progression. However, in other instances, a combined panel of miRNAs could provide a more effective prognosis of the disease state. However, it remains a critical issue to choose the sources for the reliable discovery and reproducible detection of miRNAs as a biomarker in the peripheral circulation. One of the major concerns is the heterogeneity of the sources contributing to peripheral circulation [93]. Thus far, blood-based serum or plasma remains the preferred source of biomarker discovery and analysis. The same remains true for circulatory miRNA studies in many other clinical settings such as oncology, cardiac, pulmonary, and many more [94]. However, the CSF-based analysis of circulatory miRNAs has proven more encouraging in neuropsychiatric conditions due to its higher specificity and sensitivity to the disease conditions. The primary drawback associated with CSF-based studies is the highly invasive nature of the procedure to collect samples. Nevertheless, other factors associated with CSF-based circulatory miRNA study may prove advantageous, especially for CNS-based disorders and neuropsychiatric conditions. An additional factor in the successful discovery and validation of circulating miRNA as a biomarker is the development of a highly sensitive detection assay. This is critical due to the invasive nature of the peripheral blood collection process, which limits the amount of blood drawn from the patients, and the low abundance of miRNA expression in circulating blood. Therefore, applying highly sensitive miRNA detection assay methods such as next-generation sequencing is strongly recommended, and helps analyze thousands of miRNA expressions in parallel [95]. The costs of such high-throughput experiments may impose a limitation. On the contrary, that will also authenticate the results with the detection of a panel of miRNAs while reducing the false positive outcomes [96,97]. It is interesting to highlight the ability of miRNAs to cross the blood–brain barrier and reach systemic flow. However, several factors can diminish the level of miRNAs in the peripheral circulation and may significantly compromise their sensitivity as a circulating biomarker. It has recently been suggested that the actively secreted miRNAs enclosed in exosomes can cross the blood–brain barrier (BBB) and are well protected from degradation [98]. However, it is not very clear how the efflux of exosome happens from brain to circulation and many hypotheses have been put forward to understand the mechanisms [99]. The latest research also highlighted that exosomal miRNAs could be processed by the same machinery used in miRNA biogenesis and thus have widespread consequences within the cell by inhibiting the expression of target protein-coding genes [66]. Evidence shows that exosomal miRNAs are excreted physiologically in response to stress and can be ideally used as potential biomarkers. Due to their biogenesis from cellular endocytosis, exosomes contain specific protein markers on their surfaces and often represent their tissue of origin. With this, the neuron-derived exosomal fraction found in peripheral circulation can be selectively immuno-enriched and used in downstream analysis for the successful and reliable detection of brain-derived miRNAs in circulation. Thus, exosomal miRNA cargo originated in the brain can make a significant difference in the peripheral circulation, and boosts confidence for their increased potentiality as a robust molecular biomarker in the diagnosis of most common neuropsychiatric conditions such as MDD, BD, and suicidality. Finally, to ascertain the diagnostic value, a more heuristic approach is needed. An association of miRNAs needs to be established with various endophenotypes, given the heterogeneity associated with depression and other psychiatric disorders. Some recent studies suggested that miRNAs play a role in causing susceptibility to developing depression associated with early life trauma [100,101,102]. In this connection, it is highly likely that identifying unique miRNAs may serve as a potential source of screening and they could be used as predictive biomarkers for the early detection of the severity of depression and the treatment response. Major depression is an episodic disorder with future relapses and complex clinical presentation, including the stratification of different subtypes (melancholic vs. atypical) and responder and non-responder groups [103]. Therefore, identifying objective biomarkers such as circulating miRNAs for improving diagnostic accuracy is critical for designing an effective framework of therapeutic intervention. However, at this point we are yet to distinguish such changes in miRNA expression from the peripheral circulation of MDD patients who are presented with syndrome stratifications. Future research is required to develop more advanced diagnostic panels of miRNAs that can align well with symptomatic peculiarities. Similarly, BD is a complicated disorder. Compared to the general population, BD patients are approximately more than 20 times more likely to die by suicide [104], and the pathogenesis of BD is still not clearly understood. The findings pointed out in this review suggest that circulating miRNAs could serve as biomarkers for BD and can be linked to novel treatment approaches and the prediction of the onset of symptoms. However, compared to MDD, there are fewer studies on BD. The same is true for suicidal behavior. Most often, suicidality is considered endophenotypic of various neuropsychiatric conditions and partly results from behavioral traits, including borderline personality disorder, impulsivity, and adjustment disorder [105]. Such traits are the mediators of suicide risk but are equally influenced by the patient’s clinical state, including how they cope with life stress and alcohol and substance abuse [106,107]. It is believed that under every single condition the miRNA response should be different and can distinctly mark the onset and progression of phenotypic changes that collectively lead to increased risk of suicide [80,108]. Thus, miRNAs can provide a wide spectrum of diagnostic windows as well as predictive biomarkers for the early detection of the risks associated with suicidality. Nonetheless, the predictive values of miRNAs as circulating biomarkers could be further rationalized in future diagnosis and treatment response with careful longitudinal study design that may help to determine subjective changes based on the prognosis of the disease and treatment regime.

PMC10003209

Xue Wan,Zhiqiang Wang,Wenhui Duan,Taishan Huang,Hongmiao Song,Xiangbin Xu

Knockdown of Sly-miR164a Enhanced Plant Salt Tolerance and Improved Preharvest and Postharvest Fruit Nutrition of Tomato

27-02-2023

tomato,miR164a,salt tolerance,fruit nutrition

Salinity stress is a serious limitation to tomato growth and development. The aim of this study was to investigate the effects of Sly-miR164a on tomato growth and fruit nutritional quality under salt stress. The results showed that the root length, fresh weight, plant height, stem diameter and ABA content of miR164a#STTM (knockdown of Sly-miR164a) lines were higher than those of WT and miR164a#OE (overexpression of Sly-miR164a) lines under salt stress. Compared with WT, miR164a#STTM tomato lines exhibited lower ROS accumulation under salt stress. In addition, the fruits of miR164a#STTM tomato lines had higher soluble solids, lycopene, ascorbic acid (ASA) and carotenoid content compared with WT. The study indicated that tomato plants were more sensitive to salt when Sly-miR164a was overexpressed, while knockdown of Sly-miR164a enhanced plant salt tolerance and improved fruit nutritional value.

Knockdown of Sly-miR164a Enhanced Plant Salt Tolerance and Improved Preharvest and Postharvest Fruit Nutrition of Tomato Salinity stress is a serious limitation to tomato growth and development. The aim of this study was to investigate the effects of Sly-miR164a on tomato growth and fruit nutritional quality under salt stress. The results showed that the root length, fresh weight, plant height, stem diameter and ABA content of miR164a#STTM (knockdown of Sly-miR164a) lines were higher than those of WT and miR164a#OE (overexpression of Sly-miR164a) lines under salt stress. Compared with WT, miR164a#STTM tomato lines exhibited lower ROS accumulation under salt stress. In addition, the fruits of miR164a#STTM tomato lines had higher soluble solids, lycopene, ascorbic acid (ASA) and carotenoid content compared with WT. The study indicated that tomato plants were more sensitive to salt when Sly-miR164a was overexpressed, while knockdown of Sly-miR164a enhanced plant salt tolerance and improved fruit nutritional value. Tomato is an immensely popular food, which is rich in ASA, lycopene, carotenoids, and other beneficial active components, and also is one of the main cash crops in the world [1]. However, adverse environmental conditions during their life cycle, such as salinity, drought and extreme temperatures, can pose a serious threat to tomato seed germination, plant growth and fruit yield [2]. Among them, salt stress induces osmotic stress by reducing soil water potential and water supply, which produces excess toxic reactive oxygen species (ROS) and malondialdehyde (MAD), affecting crop physiological and biochemical pathways, inhibiting crop growth and reducing yields [3,4]. Plants have established various biochemical, physiological and molecular mechanisms to respond to salt stress rapidly [5]. MicroRNAs (miRNAs) are small endogenous non-coding RNAs with a length of 18–24 nt and widely found in plants [6,7,8]. The miRNAs perform a critical role in abiotic responses by regulating levels of transcription factors [9]. During salt stress, miRNAs and the transcription factors of their targets are involved in regulating key metabolic processes in plants [10]. In the salt-tolerant maize line ‘NC286’ and the salt-sensitive maize line ‘Huangzao4’, the miR156, miR164, miR167 and miR396 families downregulated in response to salt stress, and the salt-responsive miRNA was involved in the regulation of metabolism and physiological adaptation in maize seedlings at the post-transcriptional level, indicating that the miRNA expression model was related to salt sensitivity [11]. Under salt stress, overexpression of Osa-miR393 in Arabidopsis thaliana and rice led to a decrease in growth rate and salt tolerance [12]. Liu et al. [13] reported that with overexpressed miR396a in chrysanthemum, the content of proline in leaves increased, and the salt tolerance level increased. Meanwhile, Shan et al. [14] found that down-regulation of Zma-miR164 resulted in the increased expression levels of target genes (GRMZM2G114850 and GRMZM2G008819), which significantly enhanced salt tolerance of maize. These studies suggested that miRNAs mediate target genes to regulate abiotic stress in plants. Therefore, the function of miRNAs under salt stress is of great significance to the sustainable production of tomatoes [5]. The miR164 family is a plant-specific group of miRNAs that directionally regulates the NAC-domain gene [15,16,17,18]. The NAC domain transcription factor is plant-specific, the target of miR164, which has been shown to regulate the development of fruit and respond to abiotic and biotic stresses [19,20]. The expression of miR164 was up-regulated in response to osmotic stress, and the target gene NAC1 was down-regulated in plant salt stress [21]. During the salt stress period, stress genes were up-regulated in SNAC1 overexpressing rice plants, significantly improving rice sensitivity to abscisic acid [22]. Understanding the function of miR164 could have great significance for improving tomato stress tolerance. In this study, the role of miR164a in the salt tolerance of tomato was investigated. The expression pattern of miR164 under salt stress was analyzed and its effects on plant growth and fruit quality were tested. New insights were provided for miR164a-mediated responses to salt stress in tomato. As shown in Figure 1A, there were no significant differences in the growth phenotypes of miR164a#STTM, miR164a#OE and WT lines grown in 0 mM NaCl ½ × MS medium after 14 days. In the presence of 50 mM NaCl, the growth of miR164a#STTM and WT plants was less adversely affected by salinity, but the growth of miR164a#OE transgenic plants was severely affected by salinity. Compared with miR164a#STTM and WT plants, salt stress significantly inhibited the growth of miR164a#OE tomato roots, and the leaves of miR164a#OE-1 showed severe wilting and the plants became smaller. After 14 days of salt stress, the average root lengths of miR164a#STTM, WT and miR164a#OE lines were 9.1, 4.82 and 2.61 cm, respectively (Figure 1B). The average fresh weight of miR164a#STTM was 0.38 g, whereas the average fresh weight of miR164a#OE lines and WT was 0.14 and 0.29 g, respectively (Figure 1C). Compared with WT, the fresh weight of miR164a#STTM lines was 1.11 times that of WT, and the fresh weight of miR164a#OE lines was 0.47 times that of WT. Compared with the WT, the root length and fresh weight measurements showed that the miR164a#OE line was more severely affected by salt stress, but the miR164a#STTM line showed better salt tolerance. As shown in Figure 2A, there was accumulation of dark-brown 3,3-diaminobenzidine (DAB) polymerization and blue nitroblue tetrazolium (NBT) polymerization products in miR164a#STTM, miR164a#OE and WT leaves after 14 days treatment with 100 mM NaCl, but the leaves of miR164a#OE lines exhibited darker staining than WT leaves, and the leaves of miR164a#STTM lines exhibited lighter staining than WT leaves. After treatment with 100 mM NaCl for 14 days, the H2O2 contents in the roots of miR164a#STTM, WT and miR164a#OE lines were 0.18, 0.25, 0.47 μmol g−1, respectively (Figure 2B). The O2•– contents in the roots of miR164a#STTM, WT and miR164a#OE lines were 0.14, 0.19, 0.22 μmol g−1, respectively (Figure 2C). The measurement of H2O2 and O2•– contents showed that miR164a#OE lines exhibited higher accumulation of H2O2 and O2•– than WT, while miR164a#STTM lines exhibited lower accumulation of H2O2 and O2•– than WT. After 14 days of salt stress, the average contents of malondialdehyde (MDA) in roots of miR164a#STTM, WT and miR164a#OE lines were 1.50, 1.93 and 2.03 μmol Kg−1, respectively (Figure 2D). Compared with WT, the contents of MDA in the roots of miR164a#STTM were lower than in the WT, and the contents of MDA in the roots of miR164a#OE were higher than in the WT. The average contents of proline in the roots of miR164a#STTM, WT and miR164a#OE lines were about 531.72, 495.86 and 439.42 mg Kg−1 (Figure 2E). The average content of proline in the roots of miR164a#STTM was relatively higher than that of WT, while in miR164a#OE it was relatively lower than that of WT. As shown in Figure 3A, there were no obvious differences between miR164a#STTM, WT and miR164a#OE in terms of plant height and growth rate under control conditions. After 24 days of salt stress treatment, miR164a#STTM transgenic seedlings were significantly higher than WT, while miR164a#OE transgenic seedlings were significantly shorter. After 24 days of salt stress, the average plant height of miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4 and WT were 18.06, 18.00, 18.13 and 16.23 cm, respectively. However, the average plant height of miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 only reached 14.13, 14.00 and 13.9 cm, respectively (Figure 3C). In terms of plant height, the miR164a#STTM lines were slightly taller than WT, while the miR164a#OE were significantly lower than WT. The average stem diameter of miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4, WT, miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 reached 5.59, 5.55, 5.54, 4.52, 3.73, 3.69, and 3.77 cm, respectively. From the perspective of stem diameter, the average stem diameter of miR164a#STTM lines was 1.23 times thicker than that of WT, and the average stem diameter of miR164a#OE lines was 0.69 times thinner than that of WT (Figure 3B). As shown in Figure 4A, under control treatment, WT and miR164a#STTM fruits began to turn yellow at 36 dpa, while miR164a#OE fruits showed no color change; preharvest fruit discoloration in WT and miR164a#STTM transgenic tomatoes occurred 2 days earlier than in miR164a#OE tomatoes. Fruit discoloration was accelerated by salt stress treatment in comparison to control fruits. Under salt stress treatments, preharvest fruit discoloration in miR164a#STTM transgenic tomatoes occurred 2–3 days earlier than in WT and miR164a#OE tomatoes. Under salt stress treatment, miR164a#STTM fruits began to turn yellow at 36 dpa, while WT and miR164a#OE fruits showed no color change and remained at the mature green stage at that time. Under salt stress treatment, WT and miR164a#STTM tomato fruits were at the red ripening stage at 40 dpa, while miR164a#OE tomato fruits were only at the yellow ripening stage at that time. Under salt stress, the content of soluble solids in miR164a#STTM and WT tomato fruits increased to varying degrees. The content of soluble solids in miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4 and WT fruits increased by 16.6%, 16.7%, 27.9% and 6.7% compared with the control fruits, respectively. The soluble solids content of miR164a#STTM-4 transgenic tomato fruit showed the highest increase under salt stress (Figure 4B). Under 100 mM NaCl stress, the average lycopene content in miR164a#STTM, WT and miR164a#OE tomato fruits were 425.87, 411.16 and 384.53 mg g−1 FW, respectively. The lycopene content of miR164a#STTM fruit was 1.04 times higher than that of WT, and miR164a#OE is 0.94 times that of WT under salt stress (Figure 4C). The average ASA contents in miR164a#STTM, WT and miR164a#OE tomato fruits with salt stress were 122.76, 101.33 and 92.99 mg 100 g−1 FW. The ASA content of miR164a#STTM fruits with salt stress was 1.21 times higher than that of WT, and miR164a#OE is 0.92 times that of WT (Figure 4D). The average carotenoid contents in miR164a#STTM, WT and miR164a#OE tomato fruits with salt stress were 3.00, 2.66 and 2.46 mg mL−1 FW, respectively. The carotenoid content of miR164a#STTM fruit with salt stress was 1.13 times that of WT, and miR164a#OE was 0.92 times that of WT (Figure 4E). The color changes of postharvest tomato fruits during ripening under both control and salt stress are shown in Figure 5A. Under control treatments, the miR164a#STTM fruits changed color more rapidly than WT, but miR164a#OE fruits changed color more slowly than WT. After salt stress treatment, postharvest tomato fruits changed color more rapidly than control fruits. Compared with WT, the color of miR164a#STTM fruits changed more rapidly, while the color of miR164a#OE fruits changed more slowly under salt stress. Under salt stress, the miR164a#STTM tomato fruits completely turned red 5–6 days after color breakage, while WT tomato fruits completely turned red only 7 days after color breakage; miR164a#OE tomato fruit did not completely turn red 7 days after breaking. As shown in Figure 5B–D, the color of fruit gradually changes from green to red with the extension of storage time. The L* value gradually decreased, the a* value gradually increased, and the b* value increased first and then decreased. At Br + 7 day, the L* values of miR164a#STTM, WT and miR164a#OE tomato fruits were 34.04, 43.08 and 48.90, the a* values were 34.59, 29.36 and 25.18, the b* values were 42.09, 42.09 and 43.58, respectively. Under 100 mM NaCl stress, the average soluble solids content of miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4 and WT tomato fruits were 6.57, 6.40, 6.87 and 5.80, respectively. Compared with the control, the soluble solids content of miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4 and WT fruit increased by 14.2%, 13.0%, 21.8% and 6.3%, respectively (Figure 6A). The average lycopene content of miR164a#STTM, WT and miR164a#OE tomato fruits were 373.11, 351.38 and 346.05 mg g−1 FW, respectively. The lycopene content of miR164a#STTM fruit was 1.06 times that of WT, and that of miR164a#OE was 0.98 times that of WT (Figure 6B). The average content of ASA in miR164a#STTM, WT and miR164a#OE tomato fruits were 79.14, 68.91 and 58.34 mg 100 g−1 FW, respectively. The ASA content of miR164a#STTM fruit was 1.15 times that of WT, and miR164a#OE was 0.85 times that of WT (Figure 6C). The average carotenoid content in miR164a#STTM, WT and miR164a#OE tomato fruits were 2.47, 1.90 and 1.44 mg mL−1 FW, respectively. The carotenoid content in miR164a#STTM fruit was 1.30 times that of WT, and miR164a#OE was 0.76 times that of WT (Figure 6D). As shown in Figure 7A, under 100 mM NaCl stress, the relative expression of Sly-miR164a in miR164a#STTM, miR164a#OE and WT tomato roots showed a downward trend. After 24 h of salt stress, the levels of relative expression of Sly-miR164a in miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4, WT, miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 tomato roots were 0.34, 0.33, 0.34, 0.63, 3.89, 4.15 and 3.75, respectively. The relative expression of Sly-miR164a in miR164a#STTM roots was 0.54 times that of WT, while the relative expression of Sly-miR164a in miR164a#OE roots was 6.25 times that of WT. At 6 h of salt stress, the relative expression of NAC1, NAC100 and GOB in miR164a#STTM, WT and miR164a#OE tomato roots reached their highest levels, and then gradually decreased (Figure 7B–D). After 6 h of salt stress, the relative expression of NAC1 in miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4, WT, miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 was 7.10, 7.00, 6.62, 1.78, 1.36, 1.33 and 1.33, respectively. The relative expression of NAC100 in miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4, WT, miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 was 14.67, 13.27, 14.50, 2.29, 1.31, 1.33 and 1.38, respectively. The relative expression of GOB in miR164a#STTM-2, miR164a#STTM-3, miR164a#STTM-4, WT, miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 was 5.44, 5.20, 5.32, 1.76, 1.26, 1.18 and 1.10, respectively. After 24 h of salt stress, the relative expression of NAC1 in miR164a#STTM-2, miR164a#STTM-3 and miR164a#STTM-4 was 3.98, 3.93 and 3.71 times of WT, respectively. The relative expression of NAC100 in miR164a#STTM-2, miR164a#STTM-3 and miR164a#STTM-4 was 6.40, 5.79 and 6.33 times of WT, respectively. The relative expression of GOB in miR164a#STTM-2, miR164a#STTM-3 and miR164a#STTM-4 was 3.09, 2.95 and 3.02 times of WT, respectively. Under salt treatment, the accumulation of ABA in miR164a#STTM transgenic lines was higher than that in WT, while that in miR164a#OE transgenic lines was lower than that in WT. After 24 h of salt stress, the ABA content in miR164a#STTM-2, miR164a#STTM-3 and miR164a#STTM-4 tomato roots was 1.26, 1.21 and 1.17 times that of WT, and the ABA content in miR164a#OE-1, miR164a#OE-2 and miR164a#OE-4 tomato roots was 0.66, 0.68 and 0.68 times that of WT (Figure 7E). Crop development and productivity are greatly hampered by salt stress, which results in significant financial loss. As a critical participant in the response of plants to abiotic stresses, miRNA may improve plant tolerance to these stresses in the process of adapting to adverse environmental conditions [23,24,25]. In maize, cotton and rice plants, some miRNAs have been observed to be overexpressed or silenced to increase plant resistance to various stresses [14,26,27]. The miR164 is a vital plant regulatory factor which is involved in a number of biological processes and is crucial for plant development, growth and stress resistance [28,29]. Previous investigations in wheat found that miR164 reduced wheat seedling tolerance to salt stress by down-regulating the expression of TaNAC14 [30]; however, the salt stress resistance function of miR164 in tomatoes remains unknown. In this study, transgenic plants were obtained using overexpression and the STTM (Short Tandem Target Mimic) methods to analyze the role of miR164a in regulating tomato salt stress, and its impact on improving tomato salt stress tolerance was further examined. The results showed that the overexpression of miR164a tomato lines decreased tolerance to salt stress, while knockdown of Sly-miR164a with STTM enhanced plant salt tolerance. Under salt stress, Sly-miR164a knockdown in tomatoes enhanced fresh weight, stem diameter, root length, and plant height in comparison to WT. Salinity stress will induce osmotic stress, ion toxicity and oxidative stress in plants, which will lead to excessive accumulation of toxic compounds and ROS in plants, resulting in peroxidative damage to cell membranes [31,32]. In plant cells, oxidative stress leads to the buildup of ROS like H2O2 and O2•− and damages the structure of the cell membrane [33]. Under salt stress, the accumulation of MDA in plants increased, which also caused severe membrane lipid oxidative damage [34]. Both are often used to assess plant tolerance to salt. In order to maintain normal metabolic activities and better cope with the environment of salt stress, plants will accumulate some osmotic adjustment substances to alleviate the damage caused by salt stress and enhance plant salt stress tolerance [35]. Proline is an effective organic compound involved in plant stress resistance, which can play a role in relieving plant salt stress [36]. In the present study, H2O2 and O2•– and MDA content in tomato root tissue significantly increased under salt stress. The miR164a#OE lines accumulated more H2O2 and O2•– content than WT, while miR164a#STTM lines accumulated less H2O2 and O2•– content (Figure 2B,C). Compared with WT, the MDA content in miR164a#STTM tomato plants was reduced, while the MDA content in miR164a#OE transgenic plants was significantly increased (Figure 2D). The proline content of the miR164a#STTM strain was significantly higher than that of WT and miR164a#OE (Figure 2E). The results indicated that miR164a#STTM plants enhanced the salt tolerance by increasing the content of proline and maintaining the integrity of the cell membrane of miR164a#STTM tomato plants. Reduced fruit water and an accumulation of solute activity under salt stress resulted in a rise in soluble solids content, which enhanced fruit quality [37]. Li et al. [38] found that moderate salt treatments (20 and 60 mM) increased fresh weight, soluble solids and anthocyanin content and improved overall fruit quality, while high salinity treatments (100 and 150 mM) decreased fruit quality in grape berries. The quality of strawberry fruit was improved by salt stress, which decreased the fruit’s average weight and water content while increasing its ion, ascorbic acid, and soluble solids contents [39]. Moderate saline irrigation increased the content of carotenoids, lycopene and ascorbic acid in tomato fruits, so tomato fruits had higher antioxidant capacity [40]. Massaretto et al. [41] showed that salt stress treatment reduced the yield and fruit size of tomato fruits, but increased the content of carotenoid and soluble solids in fruits, which gave tomato fruits higher antioxidant capacity and improved fruit quality. In addition, vitamin C content in fruit decreased with the increase of salt stress concentration [42]. In the present results, under salt stress, the contents of soluble solids, lycopene, ASA and carotenoid in miR164a#STTM fruits are more than WT, and the fruit quality is superior to WT. The results of previous studies also showed that under salt stress, the yield and quality of salt-tolerant tomato plants were less affected by salt stress, and the accumulation of soluble solids and soluble sugars in salt-tolerant tomato fruits increased, which is consistent with our findings [43]. The results indicated that the improvement of miR164a#STTM fruit quality may be related to the enhancement of salt tolerance of tomato by knockdown of Sly-miR164a. The miRNAs exert an essential action in regulating plant responses to various abiotic stresses at the level of transcription factors that regulate the expression of genes associated with abiotic stress responses and can activate and repress various plant defense pathways [44]. The miR164 is a large family of plant-specific genes that target NAC transcription factors [45]. One of the largest groups of transcriptional regulators is the NAC transcription factor family [46]. Previous studies have found that overexpressing the NAC transcription factor in tomato boosted the accumulation of stress-induced proline and lowered the accumulation of reactive oxygen species, which helped the plant become more tolerant to abiotic stress [47]. Compared with the wild type, the overexpression of OsNAC5 in rice increased stress resistance, enlarged rhizomes, and increased grain yield [48]. Overexpression of cotton SNAC1 improved cotton’s tolerance to salt [49]. Abiotic stress can be directly responded to by the NAC transcription factor family through ABA independent and ABA dependent mechanisms [50]. ABA is an essential phytohormone with a significant function in regulating plant responses to stress [51]. Increased osmotic pressure from salt stress will lower soil water potential, encourage an increase in ABA content, and be crucial in reducing the stress response [52,53]. Under long-term salt stress, stomatal closure and increased proline content were induced by an ABA-dependent pathway to reduce stress [54]. Under mild salt stress, ABA metabolism in strawberries is affected and results in an increase in ABA content, phenols, anthocyanins and ascorbic acid content, as well as an increase in antioxidant activity [55]. The rice stress-responsive NAC gene (ONAC022) increases endogenous ABA, proline, and soluble sugar content by modulating ABA-mediated pathways, and the salt tolerance of transgenic plants is enhanced [56]. The expression of NAC1, NAC100, and GOB was significantly increased in tomato roots of miR164a#STTM under salt stress (Figure 7B–D), and the ABA level was higher than that of WT during salt stress (Figure 7E). Therefore, knockdown of Sly-miR164 in tomato may also improve salt resistance by regulating ABA levels. The mature sequence of tomato Sly-miR164a was derived from miRBase database (http://www.mirbase.org/) accessed on 5 March 2021. To generate Sly-miR164a-knockdown tomato plants, the short tandem target mimic (STTM) was designed as previously described by Yan et al. [57], and connected to the pBWA(V)HS vector (Supplementary File S1). The pBI121-miR164a overexpression vector was created using the method described by Zhao et al. [58] (Supplementary File S2). The vector was transformed into the Agrobacterium tumefaciens strain GV3101 for tomato transformation after being sequence verified. For this experiment, Zhiqiang Wang kindly provided T3 homozygous transgenic seeds of miR164a#STTM and miR164a#OE and WT seeds [59] (miR164a#STTM-2 represents STTM-miR164a#2-18-4; miR164a#STTM-3 represents STTM-miR164a#5-20-11; miR164a#STTM-4 represents STTM-miR164a#7-21-14; miR164a#OE-1 represents OE-miR164a#13-11-1; miR164a#OE-2 represents OE-miR164a#15-12-15; miR164a#OE-4 represents OE-miR164a#16-13-19). Surface sterilization with 3% sodium hypochlorite was performed on the seeds of miR164a#STTM, miR164a#OE and WT for 5 min. The seeds were sterilized before being placed on a ½ × MS agar medium containing a 50 mM NaCl concentration and cultivated vertically for 14 days. The root lengths were measured using a centimeter ruler after 14 days of vertical culture, and all seedlings were weighed on an analytical balance to assess their growth status. At least 10 seeds were analyzed at a time and the experiment was repeated three times. The WT and miR164a#STTM and miR164a#OE transgenic lines seeds were planted in opaque pots with a soil mix of peat soil, laterite and vermiculite (2.2:1:0.8), and the plants were grown in a greenhouse at 25 °C, 16 h of light, and 8 h of dark light. Three-week-old (tomato seedlings with 4 to 5 true leaves are fully unfolded) WT, miR164a#STTM and miR164a#OE tomato seedlings were treated with salt stress by irrigating them with 100 mM NaCl every 4 days; the control group was irrigated with water. The plant height and stem diameter were measured and photographed to record the phenotype at 4, 8, 12, 16, 20, and 24 days after treatment initiation. A ruler was used to measure the height of the plant from its base to its highest point. The stem diameter of the tomato was measured using a vernier caliper scale at a height of 2 cm from the ground. After being exposed to salt stress for 0, 7 and 14 days, all the roots from five WT and miR164a#STTM and miR164a#OE transgenic lines were cleaned with sterile water after being removed from the soil, then frozen in the liquid nitrogen, and kept at −80 °C. For RNA analysis, the roots that had been exposed to 100 mM NaCl were taken at 0, 3, 6, 9, and 12 h. Each treatment contained 5 seedlings and three replicates were performed per experiment. The control fruits were harvested from tomato plants that had not been treated with water for 60 days, and the salt-stress fruits were harvested from tomato plants that had been treated with salt stress for 60 days. At least 18 ripening stage (BR) tomato fruits were selected from 6 different WT and miR164a#OE and miR164a#STTM transgenic lines, with 6 healthy and uniform tomato fruits selected from each plant. In transgenic miR164a#OE and miR164a#STTM and WT lines, 18 fruits at the breaking (Br) stage were similarly picked and kept at room temperature until Br + 7 days. Tomato fruits of preharvest and postharvest were photographed from the day of color break (BR days) to the 8th (Br + 7 days) and color changes were recorded. For the samples of preharvest fruits and postharvest fruits at the ripening stage (Br + 7 days), seeds were removed and fruit peel tissue were retained, ground to a powder with liquid nitrogen and stored at −80 °C and physiological data were collected. The first leaf of the third branch of three-week-old seedlings was stained with NBT solution (1 mg mL−1 in 10 mM phosphate buffer; pH 7.8) overnight in the dark after they had been exposed to salt (100 mM NaCl) for 14 days. The leaf was left to soak in a 1 mg mL−1 solution of DAB (pH 3.8) in the dark overnight. To remove chlorophyll, the discolored leaves were boiled in 95% ethanol for 10 min. Following staining, the color shades of the miR164a#STTM, WT, and miR164a#OE leaves’ NBT and DAB staining were assessed through visual inspection. Three-week-old tomato seedlings of WT, miR164a#STTM and miR164a#OE were cultivated in plates containing 100 mM NaCl solution for 14 days, while control tomato seedlings were placed in plates containing water. Tomato seedling roots were taken at 0, 7 and 14 days and stored at −80 °C. The content of H2O2 and O2•– was measured according to the method of the Assay Kit (Solarbio Inc., Beijing, China). The H2O2 and O2•– content both were expressed as μmol g−1 FW. The method of Wang et al. [60] was used to determine the MDA content. The approach of Ge et al. [61] was used to identify the proline content. Three fruits at the ripening stage (BR) were selected in each transgenic miR164a#OE and miR164a#STTM and WT lines and stored at room temperature until Br + 7 days. The color of tomato peel was measured at three positions in the middle of the fruit using the color difference meter (CR-400, Konica Minolta Camera Co., Ltd., Osaka, Japan) from the day of color breakage (BR day) to the 8th (BR + 7 days), and L*, a* and b* values were recorded. The content of soluble solids in tomato fruit was determined by saccharometer (H1987, Deke Machinery Technology Co., Ltd., Xingtai, China) according to the method Duan et al. [62]. The lycopene content was determined according to the method described by Fish et al. [63], with slight modifications. Briefly, ground tomato peel tissue (0.1 g) was weighed and homogenized in hexane-acetone-ethanol (ratio 2:1:1, v/v/v). After homogenization, 0.3 mL of distilled water was added and the mixture was immediately placed on ice for 5 min for better phase separation. After separation, the absorbance of the supernatant containing lycopene (hexane) was measured at 503 nm. The concentration of lycopene was estimated by the following equation: The content of ASA was determined by the method of Zhang et al. [64] with some modification, and expressed as mg Kg−1 FW. Briefly, tomato peel tissues (0.2 g) were homogenized in 2 mL of 5% trichloroacetic acid (TCA). The homogenate was then centrifuged at 12,000× g and 4 °C for 15 min. The 1.0 mL extracted supernatant was mixed with 1.0 mL of 50 g L−1 TCA solution, 1.0 mL of absolute ethyl alcohol, 0.5 mL of 0.4% phosphoric acid-ethyl alcohol, 1.0 mL of 5 g L−1 red phenanthroline-ethyl alcohol and 0.5 mL of 0.3 g L−1 ferric chloride-ethyl alcohol. The absorbance of the supernatant was measured at 534 nm using a microplate reader (SpectraMax190; Molecular Devices, Sunnyvale, CA, USA). The content of carotenoids was determined by the method of Zhu et al. [65], and expressed as mg mL−1 FW. The ELISA Kit (enzyme label Biotechnology Co., Ltd., Yancheng, China) was used to measure the content of ABA in the sample. At 450 nm, the content of ABA in the root tissue was measured. The content of ABA was given as mg L−1. RNA was extracted from root tissues with the Fast Pure Plant Total RNA Kit (Tiangen Biotechnology Co., Ltd., Ltd., Nanjing, China). The samples’ RNA integrity was examined using agarose gel electrophoresis. The relative expression of Sly-miR164a, NAC1, NAC100 and GOB was determined by qRT-PCR. The miR164a and target genes (NAC1, NAC100 and GOB) quantifications were performed with the U6 and Actin as the internal reference gene, respectively. The relative expression levels were calculated using the equation 2-ΔΔCT. Primer sequences used for qRT-PCR are listed in Supplementary Table S1. The experimental results were analyzed using a one-way ANOVA (p < 0.05) in IBM SPSS Statistics 23.0 (SPSS, Chicago, IL, USA), and different letters indicated significant difference between WT and transgenic tomatoes. The results are presented as the mean and standard deviation of three replications. Overexpression of Sly-miR164a increased the sensitivity of tomato plants to salt. Knockdown of the Sly-miR164 in tomato plants played a positive regulatory role in response to salt stress, which enhanced the expression of NAC and decreased ROS and MDA accumulation levels in transgenic plants, and improved the preharvest and postharvest fruit nutritional value of tomato.

PMC10003228

Nathalia Caroline de Oliveira Melo,Amanda Cuevas-Sierra,Edwin Fernández-Cruz,Victor de la O,José Alfredo Martínez

Fecal Microbiota Composition as a Metagenomic Biomarker of Dietary Intake

03-03-2023

biomarker,dietary patterns,fidelity measures,food intake,gut microbiota,precision nutrition

Gut microbiota encompasses the set of microorganisms that colonize the gastrointestinal tract with mutual relationships that are key for host homeostasis. Increasing evidence supports cross intercommunication between the intestinal microbiome and the eubiosis–dysbiosis binomial, indicating a networking role of gut bacteria as potential metabolic health surrogate markers. The abundance and diversity of the fecal microbial community are already recognized to be associated with several disorders, such as obesity, cardiometabolic events, gastrointestinal alterations, and mental diseases, which suggests that intestinal microbes may be a valuable tool as causal or as consequence biomarkers. In this context, the fecal microbiota could also be used as an adequate and informative proxy of the nutritional composition of the food intake and about the adherence to dietary patterns, such as the Mediterranean or Western diets, by displaying specific fecal microbiome signatures. The aim of this review was to discuss the potential use of gut microbial composition as a putative biomarker of food intake and to screen the sensitivity value of fecal microbiota in the evaluation of dietary interventions as a reliable and precise alternative to subjective questionnaires.

Fecal Microbiota Composition as a Metagenomic Biomarker of Dietary Intake Gut microbiota encompasses the set of microorganisms that colonize the gastrointestinal tract with mutual relationships that are key for host homeostasis. Increasing evidence supports cross intercommunication between the intestinal microbiome and the eubiosis–dysbiosis binomial, indicating a networking role of gut bacteria as potential metabolic health surrogate markers. The abundance and diversity of the fecal microbial community are already recognized to be associated with several disorders, such as obesity, cardiometabolic events, gastrointestinal alterations, and mental diseases, which suggests that intestinal microbes may be a valuable tool as causal or as consequence biomarkers. In this context, the fecal microbiota could also be used as an adequate and informative proxy of the nutritional composition of the food intake and about the adherence to dietary patterns, such as the Mediterranean or Western diets, by displaying specific fecal microbiome signatures. The aim of this review was to discuss the potential use of gut microbial composition as a putative biomarker of food intake and to screen the sensitivity value of fecal microbiota in the evaluation of dietary interventions as a reliable and precise alternative to subjective questionnaires. Investigations about the influence of nutrition on human health are crucial to understand the pivotal involvement of food intake consumption on the prevention, development, and management of chronic diseases, such as obesity or type 2 diabetes [1,2,3]. In this context, dietary intervention often needs to measure nutrient intake as well as to monitor the adherence of patients to nutritional prescriptions, whose assessment or control may provide reliability and precision in metabolic management. In nutritional practice, dietary evaluation is usually performed via traditional methods: diet recall, diet diaries, or food frequency questionnaires; these supply information about nutrient consumption [4]. Available methods about food intake measurements are frequently implemented in dietetic applications, whose advantages include the relatively easy data collection and the possibility of rapid verification of the adherence to nutritional interventions at low cost. However, these methods present limitations related to the ability to accurately assess food intake. Complementarily, in the last few years, there has been an increasing interest in the use of blood and urinary determinations as food intake biomarkers [5], while fecal microbiota is envisaged to have a role based on metagenomic approaches [6]. Indeed, modern dietary biomarkers involve measurable and quantifiable metabolic determinations, which can be evaluated in different biological samples that also potentially identify physiological processes related to food intake of a nutrient or dietary pattern, reflecting a more precise dietetic assessment [7]. Additionally, multiple factors need to be necessarily considered to establish an ideal biomarker of food intake, as concerns specificity, sensibility, and plausibility. Furthermore, a characteristic response over time and dose after food intake is expected, as well as being reproducible with a specific food group. Chemically, the biomarker should be stable in the selected matrix, during sample analysis and along storage, and the analytical technique to identify must be inexpensive, as far as possible. Moreover, factors related with the biomarker and analytical methods, such a robustness and reliability, should be addressed during method validation, followed by analytical performance parameters, such as limits of detection and quantification, precision, and accuracy [8]. Although defining all factors related to an ideal biomarker is difficult, it is highly recommended to fulfill as many viable conditions as possible before selecting a potential candidate as a food intake biomarker. Noteworthily, in the era of ‘omics’ technology, biomarkers that suitably estimate intake foods or dietary patterns are scarce. The lack of effective and accurate biomarkers makes it difficult to perform studies requiring this information and make it necessary to rely on participant subjective recall, which often produces biases. Diet is an important driver—over genetics and other environmental factors—shaping the human gut microbiota (GM). The GM refers to the ecosystem of microorganisms (viruses, fungi, protozoa, archaea, and, in greater proportion, the bacteria) that reside in symbiosis, both in the small intestine and in the host colon [9]. Growing evidence in the scientific literature is employing GM baseline information in integrative models to follow dietary interventions since some types of foods serve as substrates for microbial growth, which modulates not only fecal composition but reflects host homeostasis and indicates the early emergence of metabolic disruptions, such as cardiovascular diseases [10] and liver steatosis and obesity [11], as well modulating the immune system [12]. Considering that fecal samples are easy to collect and being a non-invasive method, there is an important gap in the knowledge about the usefulness of the fecal microbiota to generate nutritional biomarkers. Although there are pioneer findings highlighting the role of the gut microbiome as a predictor of dietary response, there are few controlled studies that specifically evaluate the potential use of GM composition as a biomarker of food consumption. Furthermore, analysis of the GM has been focused on dysbiosis, which corresponds to adverse qualitative and/or quantitative changes in intestinal microorganisms, closely associated with pathological processes, or, less frequently, on eubiosis, related to the balance between beneficed and pathogenic populations affecting intestinal health [13], but not examining the role of fecal bacteria as a possible biomarker of food intake. Currently, for fecal samples, composition of GM can be found out using novel techniques, such as analysis of the length of the terminal restriction fragment directed to 16S rRNA (gene) [14] and nanopore; although pyrosequencing and next-generation sequencing are the preferred analytical methods, their analyses are challenging for routine clinical practice [15]. In this regard, the aim of this review was to summarize the available scientific evidence concerning gut bacteria associations with dietary intake and analyze the potential of GM composition as a sensitive marker of food/nutrient consumption and dietary adherence assessment. Evaluating and monitoring food intake in individuals or populations is habitually achieved by non-invasive practical methods involving diverse food registration tools from face-to-face consultation or through digital instruments [4]. Food intake computing and applicability cover both individual patient care as well as public health research, facilitating an understanding of the nutritional effects in health–disease mechanisms [16] and contributing to design nutritional strategies to combat diseases associated with unhealthy food intake and nutrition [17]. These methods usually require self-report, good recent memory, and available time for data recording [4]. In addition, the interpersonal understanding variations on the requested information, the motivation of the participants, and individual’s inherent culture and data misinterpretation result in a challenge by exposing the methods to measurement errors, reducing their reliability and reflection of reality [18]. Some traditional methods of assessing food consumption are food recall for the last 24 h, food frequency questionnaires, and food diary stand out [4]. The food recall of the last 24 h usually considers what the individual ingested the day before or in the 24 h of non-consecutive and random days, but it is not feasible for all populations because it is subjective and depends on recent memory. In addition, they generally require the assessment of food preparation, amounts ingested, and time between determinate meals, for example, which leads to a great intra- and interpersonal variability on dietary intake [19]. On the other hand, food frequency questionnaires evaluate habitual intake over a longer period (weeks, months) and deal with the frequency that a person consumes food items (1–3×/week, for example), classifying them into categories, associated with nutritional compounds. This tool can be qualitative, quantitative, or semi-quantitative, but, as disadvantages, relies on personal cooperation, is extensive, and does not assess the exact amount of nutrients ingested in a consistent manner [4]. In this context, the food diary comprises a gentle method, which depends on the participant’s motivation, covers the registration of all foods, beverages, and dietary supplements that an individual consumes within an established period, and can vary between days and months. Preferably, data should be recorded based on measurement in grams or milliliters of food portions, which leads to the need for prior training of the participants [17]. Together, the current methods of estimating food consumption, despite some benefits, such as low cost, practicality, and being non-invasive, have biases that compromise results’ value and suitability, emphasizing the need for complementary methods that accurately estimate nutrient intake, which can be detailed approaches using specific and validated metabolomic or metagenomic strategies. The human gut harbors communities of microorganisms, which play a crucial role in physiological and metabolic functions [9]. These microbes form a very complex ecological entity that interplay in many aspects with nutrition and health, such as transformation and production of metabolites, enzymes and vitamins, and extraction of nutrients from food [20]. The balance between beneficial versus pathogenic microorganisms, within intestinal and immunological homeostasis, is known as eubiosis. In contrast, qualitative and/or quantitative changes in microbial populations associated with loss of intestinal epithelium integrity and local and systemic inflammatory process are considered as dysbiosis [13]. Dysbiosis can alter the normal beneficial contribution by the microbiota to the host, as well as make the intestinal epithelium susceptible to pathogenic agents and molecules, leading to the fragility of the intestinal epithelial barrier, which is associated with systemic chronic inflammatory processes that favors the appearance of chronic non-communicable diseases (Figure 1) [20]. The microbiome is sensitive to many factors that can disturb balance (including infections, change in diet, and long-term use of antibiotics, stress, sleep disturbances, etc.), making an individual predisposed to disease, and can influence metabolic health through several interactions between the host and microbes [21], either mediated indirectly (through the availability of diet-dependent metabolites) or directly (through modulation of microbiome composition and post-biotic products) by diet [22]. However, the standard definition of a basal or healthy level for bacterial taxa, as well as general microbiota markers, is still evaluated based on abundance and richness (which are related to the total number of bacterial species and their characteristics in a sample), alpha diversity (related to the distribution of species abundances in a sample), and beta (which assesses the similarity between microbial communities) where Chao and Shannon indices are widely used for these purposes [23]. Overweight is a growing global health problem associated with several clinical comorbidities and impaired quality of life, whose etiology is multifactorial [24], being characterized by an excessive accumulation of white adipose tissue and accompanied by endocrine and inflammatory disturbances [25]. In recent years, GM has been associated with obesity installation, not only in adults but also in children [26]. Some investigations have reported the association of certain bacteria with obesity. In short, although some results show the highest proportion of Firmicutes in relation to Bacteroidetes in obese individuals, these findings are still controversial [27,28,29]. Similarly, there is a higher concentration of Lactobacillus spp. and a low proportion of Bacteroides vulgatus, in addition to an association between Staphylococcus spp. with the largest energy stock [30]. In contrast, Akkermansia muciniphila is reduced in the microbiota of obese individuals [31], stressing that some of the causal relationships or related consequences between obesity and fecal microbiota need to be verified. The association between GM and host metabolic health is close, where changes in body weight have been shown to be accompanied by shifts in gut microorganism diversity in adults [32] and adolescents [33]. As an example, the genus Akkermansia has been widely associated with lean individuals and appears to be significantly more prevalent after weight reduction [34]. A study by Korpela et al. [35], applying regression models, successfully predicted host and microbiota responses to a weight control diet in obese patients, using the pretreatment abundance of fecal microbiota (mainly Firmicutes) as predictors. Another study showed that baseline GM was an important factor in determining diet-induced individual weight loss, where the abundance of Blautia wexlerae and Bacteroides dorei were the strongest predictors for weight loss [36]. Interestingly, a study by Christensen et al. [37] suggested that adults following the same diet, depending on baseline abundance levels of the Prevotella species in their gut, may lose more or less weight. In fact, these authors showed that adding more daily dietary fiber, without any caloric restriction, can lead to more weight lowering in individuals with a high abundance of Prevotella. In this line, similar results were obtained in other publications from the same group, where individuals with a high abundance of Prevotella lost more body fat after a new Nordic diet (rich in grains/fiber) than the standard Danish diet. Furthermore, fat loss was not observed in those with a low basal abundance of Prevotella species following the new Nordic diet [38]. Indeed, different nutritional strategies are used to promote weight and body fat reduction. However, the repercussions of the nutritional strategy can modify and benefit the host microbiota in different ways, depending on whether the person is male or female. This finding was observed in the study of Cuevas-Sierra et al. [39], which found, by offering a calorie-restricted diet, moderately rich in proteins for 4 months to overweight men and women, different responses concerning microbial abundance observed through metabolomic evaluations, with a significant decrease in class Negativicutes and species Dielma fastidiosa in men, while an increase was found in the species Phascolarctobacterium succinatutens and Ruthenibacterium lactatiformans in women. These investigations show the role of GM as a biomarker of weight loss and suggest the evaluation of fecal composition and metabolites as potential predictors of metabolic responses and weight-lowering success, highlighting the need to establish models to individualize slimming diets prescription based on the composition of basal GM. Excess weight and dysbiosis are closely associated with the chronic low-degree inflammatory process, which affects the production of inflammatory cytokines (IL-6 and TNF-α) and compromises the sensitivity and actions of hormones, such as insulin, contributing to insulin resistance and the onset of Type 2 Diabetes Mellitus (T2DM) in the longer term [40]. Among the findings reported after the analysis of the microbiota of subjects with T2DM, the genera Bifidobacterium, Bacteroides, Faecalibacterium, Akkermansia, and Roseburia are in smaller proportions, while the genera Ruminococcus, Fusobacterium, and Blautia are positively associated with the disease [41]. Microbial metabolism of the intestine relates to cardiometabolic homeostasis in different ways, where exacerbated production of metabolites, such as trimethylamine N-oxide or short-chain fatty acids, and changes in bile acid metabolism pathways seem to contribute negatively to cardiovascular health [42]. In this context, the abundant presence of Porphyromonas gingivalis, Helicobacter pylori, and Chlamydia pneumoniae is associated with atherosclerosis [43]. Likewise, this diseased population has an increased concentration of the genera Collinsella, Roseburia, and Eubacterium and butyrate-producing bacteria [44]. In addition, patients with atherosclerotic plaque have typical microbiome patterns with high levels of Proteobacteria and low levels of Firmicutes [42]. The etiology of IBD (intestinal bowel disease) is partly attributed to a dysregulated immune response involving gut microbiome dysbiosis [45]. Multiple studies have documented differences in the composition of GM between patients with IBD and healthy individuals, particularly regarding microbial diversity and relative abundance of specific bacteria. Some of these bacteria are Ruminococcus gnavus (enriched), Faecalibacterium prausnitzii, and Prevotella copri (depleted) [46]. Additionally, the relative abundance of some taxa appears to correlate with established markers of this disease. In this sense, specific bacterial species, such as F. prausnitzii and Clostridium difficile (strongly accompanying dysbiosis, colitis, and severe diarrhea in humans), have been closely associated with IBD and proinflammatory responses, reinforcing their clinical value as a potential bacterial biomarker of this disease, as assessed by the presence of F. prausnitzii and Escherichia coli in 28 healthy controls, 45 patients with CD, 28 patients with UC, and 10 patients with IBS [47]. Additional findings from these patients confirmed that F. prausnitzii was a specific indicator of IBD and was significantly lower [48]. Some further evidence indicates that GM plays a vital role in the initiation, progression, and metastasis of colorectal cancer [49]. In the same way, the scientific literature has been expanding the knowledge about bacterial populations that, when in excess, are associated with their development, highlighting the presence of Streptococcus bovis, Bacteroides fragilis enterotoxigénicos, Fusobacterium nucleatum, Enterococcus faecalis, E. coli, and Peptostreptococcus anaerobius as main pathogens [50]. In the last few years, growing evidence has pointed towards the bidirectional gut microbiota–brain axis playing a role in mental health [51,52,53]. The current scientific data support an altered gut microbiome in subjects with mental disorders, such as depression and anxiety, and point to some bacterial components as potential biomarkers related with these diseases. Thus, in the Flemish Gut Flora Project, fecal Dialister and Coprococcus spp. were markers of good mental health [54]. On the other hand, Heym et al. studied 40 participants from the general population in the UK and found that the fecal abundance of Lactobacillus spp. was directly related to positive self-judgment but only indirectly to cognitive depression and lower affective empathy [55]. Other studies have revealed the role of genera, such as Coprococcus, Bifidobacterium, Lactobacillus, Roseburia, and Faecalibacterium, with lower levels of anxiety and depression [56]. In fact, Bacteroides, Escherichia, Shigella, and Streptococcus are associated with higher levels of stress [57]. In addition, the genus Eggerthella (and, in general, the depletion of certain anti-inflammatory butyrate-producing bacteria) appeared to be shared between major depressive patients [58]. The study of Lucidi et al. [59] showed the potential role of Pseudomonas aeruginosa as a possible biomarker for discriminating patients with affective disorders from control individuals. Further, these authors found that the Lachnospiraceae family might play a role in the onset of depression via affecting the inflammation levels in the host. Dietary patterns are recognized to be involved in disease and health [50,51,52,53,54,55,56,57,58,59,60,61,62]. However, the impact of different foods and dietary patterns on the modulation of the microbiota is not yet clearly elucidated but is known to drive changes in GM [62], intestinal barrier functions, and immune system competence [63,64]. The scientific literature shows that not only sex, age, physical activity, and other lifestyle factors influence GM but that 3 days of dietary interventions (composition and mealtime) are already able to induce changes in bacterial composition and even alter the set of postbiotic molecules that microbes produce [65,66,67]. Thus, the diet is recognized as a key modifiable factor in the manipulation of the microbial community, with a direct impact on the composition and maintenance of beneficial bacterial populations through the continuous supply of dietary substrates [62]. In this context, recent research found a microbiota pattern or signature associated with different dietary patterns, and these results drive a new possibility to use GM not only as associated to diseases [68,69] but also as a biomarker of dietary intake (Figure 2). Recently, PREDICT 1 (Personalized Responses to Dietary Composition Trial 1) [70] was able to study the gut microbiome on a scale and complexity never seen before. Through metagenomic sequencing (average of 8.8 ± 2.2 gigabases/sample), along with long-term dietary data and hundreds of measurements of participants’ fasting and postprandial blood markers, it was possible to identify a set of microbial species that are strongly and consistently linked to cardiometabolic biomarkers and related to obesity and postprandial responses, as well as to dietary patterns, approximating the analysis of the GM for precision clinical practice [70] and consistent use as food intake as a biomarker. Indeed, dietary patterns may display characteristic microbiome signatures depending on the composition and nutrient distribution (Table 1). The Mediterranean diet (MD) is characterized by daily consumption of whole grains/pulses and cereals (fiber and carbohydrates), legumes, vegetables, and fruits; mono- and polyunsaturated fatty acids (extra virgin olive oil and oilseeds); bioactive and antioxidant compounds, as flavonoids, phytosterols, terpenes, and polyphenols [85], in addition to discouraging the consumption of excessive red meat and saturated fat and moderating the consumption of dairy products [71], whose nutritional composition pattern partly mimics the Dietary Approaches to Stopping Hypertension (DASH diet), which produces positive effects in the prevention and control of cardiovascular and other metabolic diseases [72,86,87]. MD positively modulates the host microbiota, leading to different local and systemic responses, correlating with the re-establishment of eubiosis [88] concerning the Bacteroidetes and beneficial groups of Clostridium, with a detriment on the Proteobacteria phylum and Bacillaceae family levels [89]. In 2018, Garcia-Mantrana [71] observed, in adults with a high adherence to MD, that GM was composed of 77.31% ± 2.88 of Firmicutes, 15.86% ± 0.28 of Bacteroidetes, 3.13% ± 0.65 of Actinobacterias, 1.78% ± 1.22 of Verrucomicrobia, and slightly less than 1% of Proteobacterias. In investigations conducted through the PREDIMED program (Prevención con Dieta Mediterránea) [87], it was found that adherence to MD had a lower consumption of animal-protein-associated higher concentration of Bacteroidetes. At the same time, participants who consumed more complex carbohydrates and plant proteins produced higher amounts of volatile short-chain fatty acids [87]. The intake of oleic acid derived from extra virgin olive oil when consumed in excess may have an unfavorable effect on the bacterial diversity of GM [73]. However, MD daily consumption, in adequate amounts for each individual, is associated with an increase in lactic-acid-producing bacteria, mainly Bifidobacterium and Lactobacillus, leading to reductions in inflammatory cytokine secretion (IL-6, IL-17A, TNF-α, IL-1β, COX-2, LDC-LDC) [90] and the stimulation of butyrate production, with anti-inflammatory and atheroprotective actions, defending colonocytes against oxidative stress [91]. The GM is favored by the consumption of another typical MD component, such as omega-3 fatty acids, which has a repercussion in the balance of the proportion of Firmicutes:Bacteroidetes and increased bacteria of the family Lachnospiraceae and genus Bifidobacterium, while controlling the presence of lipopolysaccharides and Enterobacteriaceae family, with potential anti-inflammatory effects [92]. In another way, the high availability of polyunsaturated fatty acids acquired by the diet seems to inhibit some bacterial populations, reducing the risk of obesity and inflammation [74]. The Roseburia spp. is an important member of the microbiota that metabolizes omega-6 fatty acid and converts it into conjugated linoleic acid, which is recognized by immune cells, enhancing the function of regulatory T cells [93]. Likewise, Lactiplantibacillus plantarum is known for producing conjugated linolenic acid, eliciting an important impact on the composition of the microbiota by stimulating the trophic presence of Ruminococcus and Prevotella, leading to a reduced level of pro-inflammatory cytokines and increased IL-10 (anti-inflammatory) and nuclear peroxisome proliferator-activated receptor-γ (PPAR-γ) [93]. Plant-based diets include vegetarian and vegan patterns involving a low consumption of animal proteins (from fish, eggs, and dairy products) or no animal food consumption, respectively [83]. The abundant supply of fruits, vegetables, whole grains, pulses, seeds, oils, and vegetable fats constitutes an important source of dietary fiber and bioactive compounds [94]. The composition of GM among vegans and vegetarians may not differ, and both include a higher composition of beneficial fecal bacteria when compared to omnivores [95]. Thus, research data show that plant-based diets are associated with high fecal levels of species of genus Prevotella [41,96], which has anti-inflammatory properties [87]. In a study by Filippo et al. [97], it was possible to verify that the GM of children from Burkina Faso (Africa), who had a diet based on vegetables (rich in fiber and resistant starch), when compared to children from Italy, who had a diet like the Western (low in fiber), elicited relevant differences in bacterial phylum count: Actinobacteria and Bacteroidetes were more represented in Africa than in Italian children (10.1% versus 6.7% and 57.7% versus 22.4%, respectively), whereas Firmicutes and Proteobacteria were more abundant in Italian than in African children (63.7% versus 27.3% and 6.7% versus 0.8%, respectively). Moreover, in an experimental study with rodents, some effects of the plant-based diet on GM were tested, where there was a significant increase in genus Bacteroides and Alloprevotella, and a reduction in genus Porphyromonas and Erysipelothrix [76]. Similarly, diets rich in complex carbohydrates, whole grains and wheat bran were associated with increased Bifidobacterium spp. and Lactobacillus spp., which play a protective role in the intestinal barrier by inhibiting the invasion and growth of pathogens [98]. Likewise, resistant starch and whole barley can also increase lactic acid bacteria (Ruminococcus spp., Eubacterium rectale, Roseburia spp.), apparently benefiting the systemic health of the host [77]. Thus, plant-based diets and associated main food components affect the bacterial composition and metabolic pathways of the GM positively, increasing symbiotic microorganisms and favoring global health [99]. However, more studies are needed to determine the impact of these diets on intestinal microbes since, nowadays, the use of chemicals to favor the growth, maturation, and conservation of food can compromise putative benefits on GM. Western diet (WD) consumption represents a global health concern because it is related to increasing rates of obesity and chronic non-communicable diseases, characterized by high caloric density associated with frequent consumption of unhealthy fats (saturated and trans), refined sugars, salt, alcohol, and other elements, such as dyes, preservatives, and antimicrobials, and also with reduced consumption of fruits, vegetables, and legumes, among other foods [78]. The adoption of this dietary pattern seems to have distinct repercussions on the microbiota of men and women [42], although it is already associated with dysbiosis, enterocytic dysfunctions, and increased intestinal permeability, in addition to the leakage of toxic bacterial metabolites into the circulation, contributing to the development of low-grade systemic inflammation [79]. When evaluating GM in consumers of WD, there is a reduced overall count of microorganisms and a change in the abundance of bacterial species. In general, the study of the Firmicutes to Bacteroidetes ratio has been linked to Western diet consumption and obesity, which seems to be accompanied by an increased abundance of class Erysipelotrichales and Bacilli [67]. In a meta-analysis performed by Jiao et al. [100], it was found that the relative abundance of Actinobacteria is reduced and that there is an increase in Proteobacteria. Additionally, the dominance of four bacterial classes (Bacteroidia, Clostridia, Bacilli, and Erysipelotrichi) was observed, corresponding to 90% GM composition for a high-fat diet (HFD). Likewise, a HFD is associated with reductions in some fecal populations, such as Prevotellaceae, Rikenellaceae, and Bifidobacterium spp., which is negatively correlated with the function of the intestinal barrier [101]. Interestingly, when assessing the fecal sample of men and women in the Spanish population, with a high frequency of consumption of ultra-processed foods (>5 servings/day), it was possible to demonstrate associations between increases in Bifidobacterium and Actinobacteria with the consumption of pizza and Actinobacteria with industrialized dairy in women. For men, it was reported that an increase in Bacteroidetes correlated positively with processed meat [102]. Despite the findings that support the negative impact of the WD on GM, the cause for which these changes occur is still inconclusive, since studies are conducted with different types, amounts, and proportions of fats, sugars, calories, and dietary fiber, impacting microbial health. Carbohydrates are a main group of macronutrients which yield energy, being chemically categorized into non-fibrous polysaccharides, lignin, resistant starch, and non-digestible oligosaccharides/dietary fibers (DFs) [103]. DFs are assigned according to insoluble and soluble properties and are often abundant nutrients in both plant-based and omnivorous diets, by consuming foods, such as cereals, roots and tubers, legumes, fruits, and vegetables [104]. Soluble fibers elicit a prebiotic effect, being rapidly metabolized and fermented by intestinal bacteria, significantly influencing the abundance and diversity of GM [105]. At the same time, the undigestible oligosaccharides are resistant to digestion in the small intestine and pass to the colon, where they are exposed to bacterial utilization being affected by the type, number, and colonization of intestinal bacteria, with beneficial effects already reported on Bifidobacterium and Lactobacillus levels, favoring the production of short-chain fatty acids (acetate, butyrate, and propionate) [106] and inhibiting the growth of some intestinal pathogens of the Enterobacteriaceae family (Salmonella spp., adherent-invasive Escherichia coli), as reported [76]. Moreover, modern dietary patterns are associated with a high intake of refined carbohydrates, such as fructose, mainly found in the form of corn syrup in beverages and ultra- and processed foods, with a reduced consumption of dietary fiber. Together, these changes negatively impact bacterial diversity and survival, leading to dysbiosis [80] and non-alcoholic fatty liver disease [11]. In insufficient fiber consumption, intestinal bacteria resort to glycoproteins of the mucus layer. However, only a few species can use this source of nutrient (such as the species Bacteroides thetaiotaomicron), which reduces bacterial diversity and associated potential benefits [81,107]. Additionally, there are some practices based on nutritional strategies, such as a low-carbohydrate diet (low-carb diet), ketogenic, and low FODMAPS (fermentable oligo-, di-, monosaccharides, and polyols), which are designed to reduce dietary sources of carbohydrate and dietary fiber [82,83,84]. In general, low-carb diet adherence leads to a reduction in the abundance and diversity of beneficial bacteria, with a fall in Firmicutes (mean abundance: 5.53), Verrucomicrobia (mean abundance: 0.51), Eubacterium rectale, Dialister, Ruminococcus gnavus, and Clostridium accompanying an increase in E. coli, Desulfovibrio spp., Parabacteroides, and Bacteroidetes (mean abundance: 5.29) [63]. Dietary fats are macronutrients that, in addition to providing energy, are essential for some metabolic pathways, such as the transport of fat-soluble vitamins, cell membrane composition, and hormonal synthesis [108]. Lipids can be found in the form of unsaturated fat (mainly mono- and polyunsaturated), saturated, and produced by the food industry in the form of trans fatty acids [109]. The high intake of saturated fats and omega-6 polyunsaturated fatty acids or small amounts of omega-3 and an omega-6/omega-3 ratio of 20:1 has been related not only with adverse metabolic consequences but also with changes in the GM [91]. Dysbiosis linked to excess dietary fats is commonly associated with weight gain and has repercussions, such as reduced total count of intestinal microorganisms, change in the abundance of bacterial species, and progression of intestinal permeability [110]. Changes in GM depend on the type of fatty acids ingested, where the intake of omega-3 is directly associated with an increase in the abundance of Lactobacillus, while monounsaturated fatty acid and omega-6 consumptions are inversely related to Bifidobacterium content [111]. In addition, changes in microbiota composition induced by a high-fat diet in animal and human models mainly favor an increase in the proportion of Firmicutes to Bacteroidetes (73% and 21%, respectively) [79]. On the other hand, another study noted an increase in dietary fat in the short term produced increases in Alistipes and Bacteroides [67]. Likewise, a rise in the abundance of Proteobacteria phylum and a fall in the levels of Prevotellaceae and Rikenellaceae family were also found, as well as a reduction in Bifidobacterium spp. after high fat intake [100]. Indeed, the amount of fat in the diet is an important driver of microbial fecal oscillation, with direct relationships with the metabolic homeostasis of the host, thanks to the unregulated modulation that fat exerts on the Reg3γ (regenerating islet-derived protein III gamma), which consequently and negatively influences the abundance and endogenous variation in bacterial species, leading to dysbiosis [112]. Intriguingly, some results are inconsistent in relating different proportions and types of fat sources with changes in the microbiota, which seems to be justified by the different amounts of dietary fiber offered in the diets, a putative conflicting factor in the evaluation of the cause–effect relationship between dietary fat and GM [113]. Proteins are a macronutrient that supply important substrates, such as amino acids, and often play a precursor role in the synthesis of enzymes, antibodies, and muscle deposit. Animal or vegetable protein sources vary according to the composition of the peptide chain and supply of amino acids (essential and non-essential). In this context, GM plays an essential role in amino acid metabolism, both in the small intestine and in the gut [114], where proteins are hydrolyzed by proteases and peptidases secreted by gut bacteria in the intestinal lumen, which may be absorbed by enterocytes or fermented by bacterial species in short-chain fatty acids, hydrogen sulfate, and ammonia [115]. Vegetable proteins often have low digestibility [116], while animal protein is more easily degraded by aerobic microorganisms in the large intestine, with a lower incidence of gastrointestinal effects [117]. In the small intestine, bacterial populations, such as Klebsiella spp., Escherichia coli, Streptococcus spp. Succinivibrio dextrinosolvens, Mitsuokella spp., and Anaerovibrio lipolytica, directly metabolize amino acids and can secrete various proteases and peptidases [116,117]. Protein molecules and undigested peptides are fermented, resulting in the production of microbial metabolites, such as short-chain fatty acids, ammonia, polyamines, hydrogen sulfide, phenolic, and indolic compounds, which can be transported to colonocytes and elicit beneficial or deleterious effects on epithelial cells, depending on their concentrations in the lumen [118]. In the colon, bacterial genera Bacteroides and Clostridium, and phylum Proteobacteria, which are potentially pathogenic, are related to protein substrates from animal sources, particularly from red meat and dairy products [79], and produce toxic substrates, such as ammonia and polyamines, which include nitrosamines and trimethylamine N-oxide [119], implicated in cardiovascular disorders [120]. Thus, when the consumption of this type of protein becomes excessive, it is necessary to reduce these potential pathogens and consequently restore the microbial ecosystem through the change in dietary composition [121]. In contrast, plant proteins, especially from soybeans and peanuts, may play a positive role in modulating beneficial bacterial composition in the intestine, increasing communities of Bifidobacterium and reducing Enterobacteriaceae family and Clostridium perfringens in rats after nitrogenous enrichment of the diet with 20% peanut protein [122]. Studies relating GM to a single micronutrient are rare, since the food itself is composed of a set of nutrients [123]. However, experimental studies using the daily supplementation of isolated micronutrients demonstrated a crucial role in the regulation of energy metabolism, growth, cell differentiation, and immune functions, including possible methods of interaction with fecal microbiota composition [124,125]. Interestingly, some vitamins are synthesized by GM (thiamine, riboflavin, niacin, biotin, pantothenic acid, folate, or vitamin K) through the mediation of various intestinal bacteria, such as the phyla Bacteroidetes, Fusobacteria, and Proteobacteria [126]. On another side, sun exposure and vitamin D supplementation were associated with increased Lachnobacterium and reduced Lactococcus in children aged 3 to 6 months [127]. Vitamin K can be acquired through dietary sources and through bacterial fermentation, with the consequent production of menaquinone [128]. Recently, it was observed, in a study with rodents, that low intake of this vitamin is associated with changes in the microbial composition of the intestine and that dietary supplementation of vitamin K leads to an increase in the family Lachnospiraceae FCS020 and Ruminococcaceae UCG-009 in females and increase in the genus Ruminococcus_1 in males, favoring bacterial diversity [129]. Furthermore, upon reaching the colon, some vitamins positively modulate GM. In 2019, Choi et al. [130] analyzed the impact of different dosages of vitamin E on the composition of GM and found that its deficiency is related to a proportion of 61% of Firmicutes, 36% of Bacteroidetes, 0,5% of Verrucomicrobia, and 1.3% of Proteobacterias. Vitamins A, B2, D, and beta-carotene lead to increased abundance of bacterial species; vitamins A, B2, B3, C, and K maintain microbial diversity; vitamin D favors the richness and diversity of microorganisms and vitamin C leads to increased production of short-chain fatty acids. Additionally, the impact of vitamins A and D is also reported on the modulation of the intestinal immune response, with secondary repercussions on gastrointestinal health and microbiome [131,132]. Regarding minerals, it has been evidenced that iron is a key element involved as a cofactor in redox reactions, diverse metabolic pathways, and electron transport chain mechanisms but also to influence the composition of the microbiota [132]. Thus, Constante et al. [133] demonstrated, in mice, that a diet rich in heme iron favored the abundance of Proteobacteria and reduced the abundance of Firmicutes. Another trial with rodents reported that excessive sodium intake is associated with reduced abundance of Lactobacillus spp. and the genera Oscillibacter, Pseudoflavonifractor, Clostridium clusters XIVa, Johnsonella, and Rothia, while greater abundance of Parasutterella spp. and Erwinia species, and the families Christensenellaceae, Corynebacteriaceae [134], Lachnospiraceae, and Ruminococcus [79]. In particular, a reduction in Lactobacillus spp. associated with excess sodium consumption increased Th17 cells and favored the expression of pro-inflammatory processes by altering intestinal homeostasis and reflecting increased vulnerability to inflammatory insults [135]. Bioactive compounds (BCs) are characterized as chemical molecules acquired through dietary or external supplements where, although not essential for survival or produced by the human body, their intake confers benefits [136]. These compounds, with wide structural diversity, are widely found in food sources in the plant kingdom [137]. BCs consist of flavonoids, phenolic acids, stilbenes, lignans, and many others and, when ingested, a low proportion is absorbed in the small intestine, while habitually, the largest amount remains in the colon and is metabolized by gut bacteria [137]. The interaction between the consumption of BCs and GM is bidirectional: in one strand, it was found that bacterial fermentation is an essential process that directly influences the bioavailability and bioactivity of the BCs and, on the other hand, BCs may modulate the composition of GM thanks to the action of their aromatic or other metabolites [138]. Dietary polyphenols are widely studied bioactive components that increase both Bifidobacterium spp. and Lactobacillus spp., providing cardiovascular protection, with antibacterial and anti-inflammatory effects [75]. Similarly, in the study of Molan, Liu, and Plimmer [139], humans that received carotenoids through the ingestion of blackcurrant (672 mg/day for 2 weeks) induced an increase in Bifidobacterium spp. and Lactobacillus spp. and a reduction in Bacteroides spp. and Clostridium spp. Further, in an experimental trial, rats receiving a high-fat diet and synthetic fructose were supplemented with pterostilbene (15 or 30 mg/kg), which showed increased abundance of Akkermansia and Erysipelatoclostridium at the same time as a decrease in Clostridium [140]. In studies with animals, there is a divergence of results due to methodological variability. Thus, the consumption of anthocyanin seems to reduce the phylum Verrucomicrobia [141] while the consumption of polyphenols increases the concentrations of Akkermansia muciniphila [142]. Furthermore, flavonoid consumption was associated with a reduction in Firmicutes [143], while saponin intake increased this microorganism in fecal samples [144]. Kefir is a fermented product produced by a culture of lactic acid bacteria (such as Lactobacillus harbinensis, Lactobacillus paracasei, and Lactiplantibacillus plantarum), acetic, and yeasts that exert probiotic activity [145], with an influence on tolerance to bile acids and salts on adhesion of the intestinal mucosa and antimicrobial resistance, providing health benefits [146]. However, when evaluating its impact on the composition of GM, there is only an increase in the relative abundance of Lachnospiraceae A2 (Linear Discriminant Analysis = 4.60) and reduced the relative abundance of the genus Clostridium and family Clostridiaceae (Linear Discriminant Analysis = 4.25), which suggests the need for further studies [147]. In summary, the intake of BC impacts GM diversity, with intestinal and systemic repercussions [10,70,96,148]. Currently, there is industrial manipulation of a multitude of probiotic strains, which colonize, survive, and differentiate in the gut environment according to the food stimuli. Thus, the intake of probiotic strains and their trophic action are directly related to the type of nutrient and diet ingested [149]. However, depending on the component, the dose consumed, and the method of preparation, the inhered repercussions on GM can be questionable and need further elucidation [150]. Interest in devising biomarkers of food and nutrient intake has been advancing rapidly in recent years, which has been driven by practical needs in proposing new methods for assessing and monitoring food intake. Understanding relationships will allow for the detection of dietary changes from their initial moment, which facilitates an early nutritional intervention, contributing to the prevention of chronic non-communicable diseases associated with food imbalances as well as the evaluation of dietary adherence during clinical treatments. Metagenomic studies are playing an important role in the identification of biomarkers of food intake and represent a precise approach that reflects the physiological function driven by food intake. Healthy eating is associated with body homeostasis in all systems, which is based on the complex interaction between biochemical and physiological pathways at different cellular levels that are responsible for maintaining health, including GM. Currently, robust nutritional intake biomarkers are scarce, impacting the delay concerning advances around nutritional and dietary assessment. However, it is already known that GM is directly modulated by the composition of the diet and that the isolated consumption of certain nutrients or food groups stimulates the growth of specific bacterial taxa, which, interestingly, suggests that the composition of intestinal bacteria is a potential mirror of food consumption. The gastrointestinal tract is extensive and has distinct bacterial populations throughout anatomize portions, where the collection of fecal samples is an eventually practical, fast, and non-invasive method for the evaluation of the composition of bacterial species and their metabolites. Therefore, GM seems to be a viable tool for dietary assessment (Table 2). Dietary patterns have an impact on GM (Table 1) and, among the different patterns, it is observed that those consisting of high dietary fiber and bioactive components intake are controlled in animal and dairy protein and reduced in ultra-processed consumption, such as the Mediterranean and vegetable diets, associated with greater abundance and diversity of bacterial groups, positively affecting lipid metabolism, inflammatory state, liver, intestinal function, and immune control through different metabolic pathways and epigenetic interactions. On the other hand, the scarcity of dietary fiber, micronutrient deficiency, and the exacerbated consumption of refined sugars, saturated fats, and sodium negatively modulate this ecosystem, reducing bacterial diversity and loss of epithelial integrity in the intestine, which is associated with dysregulation of inflammation, body adiposity, increased expression of inflammatory cytokines, and the emergence of chronic non-communicable diseases, such as obesity and metabolic syndrome [12]. In addition, species, such as Bifidobacterium spp., Lactobacillus spp., and Akkermancia muciniphila, are already associated with host health [21,28,31] and, conversely, Bacteroidetes and Ruminococcus spp. show the unfavorable conditions at the core of metabolism and inflammatory state [42,61], emphasizing the direct relationship between diet and the composition of GM. The heterogeneity between individuals/groups (sex, age, genetics, lifestyle, and others) and dietary variations among different populations, in addition to access to appropriate methodologies, constitutes a practical limitation in this area of study. However, as future perspectives, considering the number of data and valuable information that can be extracted from both GM and diet, the technological advancement, and the understanding of the cause/consequence relationships between gut bacterial species and diet should be considered. In this context, the relationship between food consumption and health status/ disease brings with it a new aspect of evaluation, where GM plays a central role. Thus, the study of bacterial composition (abundance/diversity), derived metabolites, and dynamics and their association with food intake emerges as a promising prediction tool of the “omics era” (Figure 3). This new view can facilitate the understanding of the repercussions of eating different dietary patterns and nutrients on metabolic health and inflammatory status and allows for the development of personalized and accurate nutritional strategies through GM modulation, with injected on personalized precision nutrition.