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AsALG-6 is eliminated during Ascaris programmed DNA elimination [66-68]. The 26G-RNA Argonaute, AsALG-4, is highly and predominantly expressed in the male germline and highest during meiosis. AsALG-5 and AsALG-7 expression is in general low in the male and female germlines and early embryos through the comma stage, except for AsALG-7 in early spermatogenesis. The phylogenetic analysis in Figure 1A suggests they may be potential 26G-like Argonautes (Figure 1A). In some phylogenetic analyses (data not shown), AsALG-5 and AsALG- 7 cluster with C. elegans ERGO-1 or RDE-1. However, C. elegans ERGO-1 binds 26G-RNAs that are 2’- O-methylated by HENN-1 but Ascaris lacks HENN-1 [51]. Ascaris Argonaute antibodies To identify small RNAs associated with the Ascaris Argonautes, we generated polyclonal antibodies (see Material and Methods) to AsALG-1 (miRNA), AsALG-4 (26G-RNA), and all five WAGO Argonautes (AsCSR-1, AsNRDE-3, AsWAGO-1, AsWAGO-2, and AsWAGO-3). These Argonautes were chosen as they represent the diversity of small RNA pathways in Ascaris, are the most highly expressed, and appeared orthologous to major C. elegans Argonautes. Western blot analyses show these antibodies specifically recognize the corresponding Argonaute proteins (Figure S2A). In addition, RNA and Northern blot analyses of the AsALG-1 and AsWAGO-1 IP indicate significant enrichment for miRNAs and 22G- RNAs supporting the specificity of these antibodies (Figure S2B). Immunoprecipitation and proteomic analysis of several of the Argonautes further demonstrated the specificity of the antibodies for their respective Argonaute, including known associated proteins in C. elegans (data not shown). Additional IP and small RNA sequencing data (see below) support the specificity of the antibodies. Localization of Ascaris Argonautes in early embryos and the germline Early embryo immunohistochemistry using the antibodies to Ascaris Argonautes indicates that AsCSR-1, AsWAGO-1, AsWAGO-2, AsWAGO-3, AsNRDE-3, AsALG-4, and AsALG-1 are present in both the 7 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . cytoplasm and nucleus in early embryos (Figure 1C). AsWAGO-2 and AsWAGO-3 localize to condensed mitotic chromosomes during anaphase of a programmed DNA elimination mitosis and are described in a separate manuscript [69]. AsCSR-1 does not localize to condensed mitotic chromosomes [69]. We further examined the nuclear and cytoplasmic localization of several Argonautes in early embryos using Western Blots (Figure S2A). AsWAGO-3, AsCSR-1, and AsNRDE-3 are present in both the cytoplasm and nuclei, but significantly greater in the cytoplasm. Notably, AsALG-1 is also present in nuclei and is associated with miRNAs. However, AsWAGO-2 is equally present in the cytoplasm and nucleus whereas AsWAGO-1 is around two-fold higher in the cytoplasm compared to the nucleus.
C. elegans Argonautes localize to a variety of germ granules (P granules, Mutator foci, Z granules, and SIMR foci) in the germline and early embryo [70]. We carried out Ascaris Argonaute antibody histochemistry on the male and female germlines and early embryo. Using a variety of conditions, we have not been able to observe germ granules in the germline or early embryo. Similarly, other antibodies to Ascaris proteins known to localize in germ granules in the early C. elegans embryo (Dcp1, Dcp2, DcpS, Cgh-1, eIF4E, and others) also do not identify discrete granules in Ascaris early embryos. While it is possible that optimal fixation and other conditions may not have been identified for Ascaris germ granules, we have carried out extensive and successful immunohistochemistry in Ascaris embryos [71]. It is possible that such granules and functional complexes are present, but do not form large enough complexes to be visualized. Interestingly, CSR-1 antibodies did not identify P-granules in early embryos of C. briggsae [65] and P-granules have not been examined in other nematodes. Ascaris Argonaute antibodies IP specific small RNAs Ascaris Argonaute IP and small RNA sequencing demonstrate that the Argonautes associate with distinct small RNA classes that are complementary to different elements in the genome (Figure 2A). For all IP and small RNA sequencing experiments, we carried out two or more biological replicates. The Argonaute IPs and small RNAs obtained are highly reproducible and the small RNA sequencing per sample was over 30 million reads on average and often over 50 million (Table S2). In previous work we used a variety of approaches including preparing small RNA libraries that were both 5’-dependent and 5’-independent to determine if Ascaris small RNAs had 5’-monophosphate or 5’ triphosphate termini [51]. In this study, most small RNA libraries were 5’-independent capturing all small RNAs regardless of their 5’ phosphates (see Materials and Methods). However, AsALG-1 and AsALG-4 associated small RNA libraries were also constructed using 5’-dependent libraries to enrich for 5’-monophospahte RNAs (see Figure S3). Ascaris AsALG-1 specifically binds 5’-monophosphate miRNAs (many previously identified in [51]), AsALG-4 binds 5’-monophosphate 26G-RNAs, and the WAGOs typically bind 5’-triphosphate 22G-RNAs (22-24G-RNAs). Neither Ascaris miRNAs nor 26G-RNAs are represented at high abundance compared to the predominant 22G-RNAs (22-24G-RNAs) present in the total small RNA population (see Figure 2A, input). However, 8 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . these small RNA are highly enriched in AsALG-1 or AsALG-4 antibody IPs, respectively, demonstrating specificity and enrichment of the Argonaute IPs (Figure 2A).
The majority of small RNAs in all Ascaris tissues and stages examined are the secondary, 5-triphosphate 22G-RNAs and they are primarily associated with AsWAGO-1. Much lower abundance 5-monophosphate 22G-RNAs are also present. Their relationship to the triphosphate 22G-RNAs could be as primary siRNAs or dephosphorylated triphosphate 22G-RNAs [72]. Argonaute IP from tissues where an Argonaute is expressed at low levels generates small RNA profiles reflecting the input or are random as seen in the ovary, and 4-cell IP of AsALG-4 (Figure 2A) or WAGO-2 and WAGO-3 in the testis (Figure 4, M6-M7), suggesting non-specific background for these IPs. Overall, the data indicate that the Ascaris antibodies are specific reagents for analysis of Ascaris Argonautes. Ascaris chromosomes exhibit a relatively uniform distribution of genes [67] (Figure S4). However, repetitive sequences and mobile elements are biased toward DNA that is eliminated during programmed DNA elimination [66-68]. These eliminated sequences are at the ends of all germline chromosome (including 50–100 kb of subtelomeric repeat sequence that precedes the telomeres) and in the middle of a few chromosomes. The eliminated sequences include 30 Mb of a 120 bp tandem repeat that is present in internal and terminal regions of chromosomes. Based on a liberal prediction, we estimate that repetitive and mobile sequences constitute ~41% or 126 Mb of the Ascaris germline genome (see Materials and Methods). The majority of the Ascaris small RNAs are complementary to repetitive sequences and/or mobile elements in the genome (Fig. 2A, input and Figure S4). However, simple and satellite repeats such as the 120 bp tandem repeats are typically not targeted by small RNAs. Small RNAs to telomeric sequences have been observed in C. elegans [73], but no Ascaris small RNAs to telomeric sequences were observed in our in- depth and comprehensive sequencing (Table S2). AsWAGO-1, AsWAGO-2 and AsNRDE-3 associated 22G-RNAs target the repetitive regions of the genome (5,243 repeats high-confident targets; see Materials and Methods and Table S3). We hereafter refer to this targeted repetitive sequence set as WAGO-repeats as they are targeted by Ascaris WAGO Argonautes. These WAGO-repeat regions are enriched with > 10- fold small RNA reads (relative to mean coverage) and cover ~9.5 Mb or 3.4% of the genome (Table S3 and see also Figure 5A-B). The majority (60-80%) of the AsWAGO-1, AsWAGO-2, and AsNRDE-3 associated small RNAs sequenced map to these WAGO-repeats (Figure 2A, bottom horizontal percentage bar). AsWAGO-1 and AsWAGO-2 small RNA targets largely overlap, with AsWAGO-1 and its small RNAs being expressed at much higher levels. AsNRDE-3 small RNAs and their targets show greater diversity compared to AsWAGO-1 and AsWAGO-2, particularly in the male germline during later meiotic stages where AsNRDE-3 associated small RNAs also target mRNAs (see below). 9 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . To identify Ascaris genes that are potentially targeted by small RNAs, we normalized the small RNA reads to mRNAs based on reads-per-kb-per-million (rpkm). We considered mRNAs with antisense small RNAs over 10 rpkm in a stage as high-confidence targets (Table S4). Small RNAs that target mRNAs are generally antisense and fully complementary to mature mRNAs and associated with AsCSR-1, AsWAGO- 3, AsNRDE-3 (in the testis), and AsALG-4. The distribution of these small RNAs across mRNAs is typically uniform across transcripts or with a 5’ bias (Figure S5). These mRNA targeting Argonautes bind distinct sizes of small RNAs, with AsNRDE-3, AsWAGO-3, AsCSR-1 and AsALG-4 associated small RNAs 22G-, 23G-, 24G-, and 26G-RNAs, respectively (Figure S6). AsCSR-1 small RNAs appear to target most expressed mRNAs and the levels are often proportional to mRNA target expression in most stages (see Figure S7 and Table S4). These data are consistent with observations in C. elegans suggesting that AsCSR-1 likely functions to “license” gene expression [24, 26, 27, 63]. AsWAGO-3 appears orthologous to C. elegans C04F12.1 based on the phylogenetic analysis (Figure 1A). The targets of AsCSR-1 and AsWAGO-3 small RNAs are highly overlapping in many stages, particularly the 4-cell embryo (Figure 2B and Table S4). However, AsWAGO-3 is expressed at much lower levels compared to AsCSR-1 in germline and early embryos (Figure 1B). Notably, Ascaris small RNAs corresponding to genes in general do not target pre-mRNA introns. To further examine the diversity and complexity of small RNAs associated with different Ascaris Argonautes in the testis, ovary, and early embryo (4-cell), we compared the levels of small RNAs in these IPs matching mRNAs and repeats using principal component analysis (PCA) (Figure 2B-C). Small RNAs to mRNAs are similar in the ovary, more divergent in the embryo, and highly divergent in the testes (Figure 2B). Small RNAs to repetitive sequences associated with Argonautes show a similar relationship (Figure 2C). These data indicate that small RNAs associated with Ascaris Argonautes are most diverse in the testes targeting both mRNAs and repeats. While AsCSR-1, AsWAGO-3, AsNRDE-3, and AsALG-4 small RNAs target different numbers of mRNAs in the testis (ALG-4 targets a much smaller number of mRNAs), many of these targeted mRNAs overlap (Figure 2D and Table S4). Repetitive sequences targeted by AsWAGO-1, AsWAGO-2, and AsNRDE-3 small RNAs also largely overlap, particularly in the testis (Figure 2E and Table S3). Dynamics of Ascaris Argonautes and their associated small RNAs during spermatogenesis Small RNAs and pathways have been extensively analyzed in the C. elegans female germline. In contrast, analysis of C. elegans small RNAs and pathways are more limited in the male germline [30-32, 74-76].
21U-RNAs, 26G-RNAs, and 22G-RNAs are all known to play an important role in the C. elegans male germline. Our initial PCA analysis of small RNAs suggested a greater diversity of small RNAs in the testis (Figure 2B-C). Ascaris is sexually dimorphic and the extended male germline is ~1 meter in length. This 10 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . afforded us a unique opportunity to dissect and obtain large amounts of material from distinct regions of the testes, an attribute not available in C. elegans. We analyzed Argonautes, small RNAs, and target mRNA expression throughout Ascaris spermatogenesis to provide a comprehensive and in-depth analysis of small RNA pathways during nematode spermatogenesis. We defined five regions of the Ascaris male germline based on nuclear morphology and comparison with C. elegans (see Materials and Methods) [77, 78]. These regions include the mitotic region, transition zone, early meiosis (pachytene), late meiosis I and II, and spermatids (Figure 3). We dissected and collected seven samples of the male germline (M1-M7) that cover both mitotic and meiotic regions and carried out Argonaute IPs and small RNA sequencing as well as RNA-seq. Total small RNA and RNA-seq profiles were also generated for spermatids (M8) (Figure 4C and Table S4). The RNA-seq expression data indicates that most Ascaris Argonaute RNAs are significantly expressed during spermatogenesis (Figure 4B) (except AsALG-5, see Figure 1B). Overall, expression is highest during early stages of spermatogenesis with expression decreasing during diplotene and diakinesis. The exception, however, is AsALG-4 with very low expression during early spermatogenesis and much higher expression during late meiosis (M6-M7). The IP and small RNA sequencing data further illustrate the specificity of our Argonaute antibodies and reveals the types and targets of the small RNAs associated with each Argonaute during spermatogenesis (Figure 4D). The size distribution of the small RNAs also reveals distinct features of many AsWAGO associated siRNAs in the testis (Figure S6). This suggests flexibility in the biogenesis and processing of these small RNAs or changes in loading or binding properties [79, 80]. Notably, about 20-25% of all the AsCSR-1 small RNAs also begin with an adenine nucleotide. The low levels of AsWAGO-2 and AsWAGO- 3 in M6-M7 result in poor IP and small RNA data. Similarly, the low levels of ALG-4 in early spermatogenesis result in small RNA IPs that look like input without distinct 26G-RNAs, whereas in M6- M7 where AsALG-4 is expressed, 26G-RNAs are clearly dominant in the IPs. The targets of small RNAs associated with some Argonautes also change dramatically during spermatogenesis (Figure 4).
For example, AsNRDE-3 targets mainly WAGO-repeats in early stages (M1- M5) but then targets mRNAs in late meiosis (M6-M7). AsALG-4 associated 26G-RNAs only appear in late meiosis (M6-M7) targeting male, meiosis-specific mRNAs. AsWAGO-2 and AsWAGO-3 do not IP any specific small RNAs in the M6-M7. Interestingly, two RdRPs are also upregulated in the pachytene stage (M5, Figure 4B). Overall, the data illustrate major Argonaute and small RNA changes during meiosis (later pachytene) and are consistent with a role for siRNAs in clearing most mRNAs prior to final sperm maturation (see below) as very few mRNAs are present in Ascaris spermatids [51, 61]. 11 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Repeat targets of small RNAs during spermatogenesis Ascaris WAGO-1, WAGO-2, and NRDE-3 associated small RNAs extensively target repetitive sequences including mobile elements (defined as WAGO-repeats) during spermatogenesis. Many of these targets overlap with enriched H3K9me2/3 histone marks (Figure 5A-B). However, not all repetitive or mobile elements, H3K9me2/3 regions, and WAGO small RNA targets of the genome overlap. AsWAGO-2 and AsNRDE-3 associated repeat small RNAs decrease as spermatogenesis progresses, particularly in M6- M7 (Figure 5). In the testes, WAGOs target a subset of repetitive sequences at high levels in the mitotic germline. Most of these repetitive sequences are not expressed and thus appear silenced (Figure 5A and Tables S3). However, some WAGO-repeat regions are expressed, particular during pachytene (M4-M7, see Figure 5C and Table S3). Overall, small RNAs target many repetitive sequences or mobile elements during spermatogenesis. Several previous studies defined Ascaris sequences with characteristics of mobile elements [81-84]. We observed significant RNA expression (based on RNA-seq and PRO-seq) in the male and female germline (but not the early embryo) for one of these, a non-LTR R4 retrotransposon that inserts into the ribosomal locus. R4 was previously described as mobile based on its presence in different genomic locations among individuals [82, 84]. In contrast to the expression of R4, our RNA-seq analyses suggest that most other predicted mobile elements (previous work and current predictions) are not highly expressed. However, PRO-seq suggests many of these mobile element loci are bi-directionally transcribed at low levels. This bi-directional transcription could lead to dsRNA substrates for Dicer to generate primary siRNAs, leading to subsequent secondary siRNA generation to further silence the loci. Consistent with this, high levels of AsWAGO-1, AsWAGO-2 and AsNRDE-3 associated 22G-RNAs are observed to target many of these elements.
mRNA targets of small RNAs during spermatogenesis To define the timing and expression of Argonaute associated small RNAs and their mRNA targets during spermatogenesis, we first identified 5,526 genes targeted by at least one Argonaute (AsCSR-1, AsALG-4, AsNRDE-3, and AsWAGO-3) with antisense small RNAs over 10 rpkm in one or more of the spermatogenesis stages (see Table S4). These genes can be categorized into two broad groups based on their expression profiles. One group includes genes expressed throughout male germline development (M1-M7; 4,363 genes) whereas the other group are genes specifically expressed during meiosis (M5-M7; 1,163 genes, of which 232 are eliminated by programmed DNA elimination in early development [66-68]). Figure 6A shows an example of these two groups as neighboring genes on chromosome 1. The gene on the left (ag_00250, a chloride intracellular channel exc-4) is expressed throughout the male germline whereas the gene on the right (ag_00251, a gene encoding a hypothetical protein) is only expressed during meiosis. Both genes are targeted by AsCSR-1, and their mRNA levels are correlated with CSR-1 siRNA 12 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . levels across spermatogenesis. In contrast, the meiosis-specific gene ag_00251 is expressed during pachytene (M5-M7) and targeted by AsNRDE-3 in M5-M7 and AsALG-4 associated 26G-RNAs in M6-M7. Notably, 26G-RNAs are not detected during most of early pachytene (M5, see Figure 4D). Genome-wide analysis reveals AsCSR-1 small RNAs target a large, comprehensive set of genes, and the number of genes targeted varies across developmental stages. In contrast, AsALG-4 is expressed and targets a much smaller number of genes that are specifically expressed primarily during testis meiosis (Figure 6B). While AsNRDE-3 does not target many mRNAs during early spermatogenesis (M1-M4), the number of mRNA targeted rises to a level similar to AsCSR-1 in late spermatogenesis (M5-M7) (Figure 6B). In late meiosis (M6), the mRNA targets largely overlap between AsCSR-1 and AsNRDE-3 (Figure 6C and S7). While most AsALG-4 mRNA targets are also targeted by AsCSR-1 and AsNRDE-3, AsCSR-1 and AsNRDE-3 target many mRNAs not targeted by AsALG-4 (Figure 6C). The expression changes of Argonaute siRNAs and their targeted mRNAs identified two large groups mRNAs that are differentially regulated by these siRNAs (Figure 6D). Many of these AsCSR-1-only targets are differentially expressed during spermatogenesis including in the mitotic region and transition zone (Figure 6D). In contrast, AsALG-4 and its small RNAs are specific to mRNAs expressed during meiosis (M5-M7) and notably levels of these mRNA targets decrease when the AsALG-4 associated 26G-RNAs are expressed (Figure 6D).
26G-RNAs appear specific to mRNAs expressed during meiosis (~72%, 833 out of 1,163 meiosis-specific genes) (Table S4). In comparison, AsCSR-1 small RNAs target most of the expressed mRNAs throughout spermatogenesis (~89%, 4,910 out of 5,526 expressed mRNAs) (Table S4), but both the levels of AsCSR-1 and its small RNAs decrease significantly following M5. Notably, most AsALG-4 targeted mRNAs are expressed and also targeted by AsCSR-1 during pachytene (M5), but the corresponding 26G-RNAs are only expressed during later pachytene and meiosis (M6-7) (Figure 6D). Overall, our data suggests a model where AsCSR-1 likely licenses, fine-tunes and represses the levels of all expressed mRNAs during early spermatogenesis and perhaps throughout spermatogenesis, while AsALG-4 targets and likely represses meiosis-specific mRNAs. AsNRDE-3 small RNAs also target mRNAs later in meiosis, preferably at the 5’ end of the mRNAs (Figure 6E). Very low levels of mRNA are present in spermatids [51, 61]. The decrease in AsCSR-1 levels during the later stages of spermatogenesis could result in a reduction in licensing or protection from repression facilitating a decrease in AsCSR-1 target mRNAs. Prior to the formation of spermatids, AsCSR-1 in concert with AsALG-4 and AsNRDE-3 small RNAs may also repress and facilitate the turnover of all mRNAs (Figure 6D). AsALG-4 targeted genes are predominantly male meiosis-specific genes. Many of these genes, including major sperm protein genes, sperm motility genes, sperm specific family genes, class P genes, and pp1 phosphatases are also targeted by C. elegans ALG-3/4 [31, 74] indicating conservation of 26G-RNA 13 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . targets. However, many of the Ascaris 26G-RNA targets are unknown hypothetical genes and generally not conserved in other nematodes. New and novel genes have been shown to evolve at high levels in the testis [85-87]. The expression of these genes may require concerted control. AsALG-4 and its associated 26G-RNAs likely play a major role in clearing late meiosis mRNAs during spermatid formation, as the timing of these 26G-RNAs expression (M6-7) is in general later than their targeted mRNAs (M5-7), including AsALG-4 mRNA itself (Figure S8). Plasticity of small RNA pathways during spermatogenesis AsNRDE-3 largely targets repetitive sequences in the female germline, early embryo, and early stages of spermatogenesis. However, during the later stages of spermatogenesis, AsNRDE-3 small RNAs largely switch their targeting to mRNAs (Figure 7A). The percentage of mRNAs targeted by NRDE-3 increases from ~10% in the mitotic regions of the male germline to 50% in late pachytene (M6, Figure 4D and Figure 6B).
Over 2,600 mRNAs are targeted by AsNRDE-3 during spermatogenesis, with 2,050 mRNAs targeted alone in M6 (Figure 6D). Most of these AsNRDE-3 targets overlap with AsCSR-1 targets (Figure 6C-D, S7 and Table S4). These data indicate a plasticity in Ascaris NRDE-3 targets (repetitive sequences vs mRNAs) during spermatogenesis and suggest an important role for AsNRDE-3 during the later stages of spermatogenesis. This plasticity of small RNA targets is also observed in AsWAGO-3 (Figure 7B). Although AsWAGO-3 expression is in general low, in germline tissues AsWAGO-3 targets WAGO-repeats while in early embryos it targets mostly mRNAs (Figure 7B). Overall, these data indicate that plasticity in Ascaris Argonautes targets (Figure 7C), with respect to the class of genomic elements, occurs in different developmental stages and tissues. These observations raise questions regarding the biogenesis of the small RNAs, their loading into the Argonautes, and how these processes change. 14 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Discussion Our understanding of nematode small RNA pathways comes from detailed studies in C. elegans [8-12, 70, 88]. However, nematodes represent a very diverse phylum adapted to a wide variety of lifestyles with species present in almost all ecosystems including many parasitic species [37]. Little is known regarding the conservation and functional role of small RNA pathways (other than miRNAs) in these divergent nematodes [51, 89, 90]. Here, we characterize Argonautes and their small RNAs in the parasitic nematode Ascaris. Ascaris is a Clade III nematode that diverged from C. elegans (Clade V) ~365-400 million years ago [49, 50]. Ascaris has a reduced set of expressed Argonautes compared to C. elegans (10 vs.19) including 5 AGO-clade and 5 WAGO-clade Argonautes (Figure 1A). Ascaris (as well as most non-Clade V nematodes) lacks piRNAs (21U-RNAs) and PIWI Argonautes [51, 90]. We generated specific polyclonal antibodies to seven Ascaris Argonautes and analyzed small RNAs associated with AsALG-1, AsALG-4, AsWAGO-1, AsWAGO-2, AsWAGO-3, AsCSR-1, and AsNRDE-3 in early embryos, the female germline, and throughout the male germline. Overall, several small RNA pathways and their functions appear conserved between Ascaris and C. elegans while others have diverged in function and targets or been lost. The most abundant small RNAs in Ascaris are 22G-RNA secondary siRNAs. The majority are complementary to repetitive sequences and are associated with Ascaris WAGOs. However, other Ascaris WAGOs, including CSR-1, WAGO-3, and NRDE-3, also associate with 22G-24G RNAs that are complementary to mature mRNAs. Detailed analysis of AsCSR-1 and AsWAGO-3 small RNAs indicates they are primarily 24G-RNAs and 23G-RNAs, respectively (Figure S6), illustrating additional flexibility in average small RNAs sizes for their respective Argonautes.
AsNRDE-3 and AsWAGO-3 small RNAs target mRNAs and/or repetitive sequences depending on the developmental stage. AsALG-1 binds miRNAs. AsALG-4 binds 26G-RNAs (like C. elegans testis ALG-3/4) that target mRNAs expressed primarily in the male germline during meiosis. AsALG-4 function may differ in Ascaris compared to C. elegans, whereas the AsCSR-1 pathways appears to function similarly as in C. elegans [24-27, 63, 91, 92] even in the absence of an Ascaris piRNA pathway. A licensing CSR-1 pathway in Ascaris in the absence of a piRNA pathway. It has been suggested that a central role of piRNAs in C. elegans is to define “self” vs “non-self” (C. elegans genes vs foreign elements) [56]. C. elegans piRNAs have limited, miRNA-like complementarity to their targets (seed sequences, nucleotides 2-8, and additional 3’ sequences, nucleotides 14-19), thus providing the potential for targeting a vast array of sequences [53, 93, 94]. It has been proposed that a role of the C. elegans CSR-1 pathway is for “licensing” gene expression, thus enabling expression of genes, to counteract promiscuous piRNA silencing of germline transcripts [24, 26, 58]. Given the absence of piRNAs and PIWI in Ascaris, we sought to determine the targets of AsCSR-1 small RNAs and thus the potential function of 15 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . the Ascaris CSR-1 pathway. AsCSR-1 represents the most abundant Argonaute mRNA in the Ascaris germline and early embryos. Its associated 24G-RNAs are complementary to almost all transcribed mature mRNAs. This suggests the AsCSR-1 pathway may also function in “licensing” gene expression in Ascaris. C. elegans CSR-1 has also been proposed to “fine tune” gene expression of mRNAs loaded into oocytes [91], clear maternal mRNAs [25], and degrade mRNAs with non-optimal codons [95]. AsCSR-1 is present in oocytes and at its highest level during the maternal to zygotic transition which initiates at the one-cell stage in Ascaris prior to pronuclear fusion [61]. AsCSR-1 disappears early in Ascaris development at the 32-64 cell stage. These data are consistent with AsCSR-1 also playing a similar role as observed in C. elegans in fine tuning oocyte transcripts and clearing mRNAs during the maternal to zygotic transition. The balance among these functions of AsCSR-1 (licensing, fine tuning, and repressive) may be developmental stage and/or mRNA dependent and remains to be determined even in C. elegans. Ascaris Argonautes and small RNAs in spermatogenesis. Small RNA pathways and targets throughout the developmental stages of nematode spermatogenesis have not been analyzed. Ascaris is sexually dimorphic. We used the ~1 meter length of the male Ascaris germline to comprehensively examine mRNA, Argonautes and their associated small RNAs, and the small RNA targets throughout nematode spermatogenesis.
A striking feature of Ascaris small RNA pathways is the unique expression of AsALG-4 and associated 26G-RNAs during the later stages of spermatogenesis (M6-M7). This is followed by a significant decrease in the mRNAs targeted by the 26G-RNAs (Figure 6). AsALG-4 and 26G-RNAs may be similar in function to pachytene piRNAs in mice that facilitate mRNA clearance in spermatids [96-99]. This function may be enhanced with AsCSR-1 and AsNRDE-3 that also appear to repress mRNAs during pachytene and later meiosis (see below). Thus, independently evolved small RNA pathways may have convergent functions and play key roles during pachytene of spermatogenesis. In C. elegans, it has been proposed that 26G-RNAs likely identify spermatogenesis mRNA targets for generation of secondary 22G-RNAs [29-32, 74]. This does not appear to be the case in Ascaris as our current data further refine our previous finding [51] and indicate that AsALG-4 and 26G-RNA expression does not precede the appearance of secondary 22G-RNAs to the same mRNA targets. In contrast, our data suggests that 26G-RNAs appear much later than most of the small RNAs targeting mRNAs during spermatogenesis and 26G-RNAs are associated with the loss of mRNAs in late spermatogenesis and the formation of spermatids (Figure 6). The current Ascaris data are consistent with a model where AsCSR-1 small RNAs likely license gene expression during early stages of spermatogenesis, the female germline, and early embryo similar to the licensing role of CSR-1 in C. elegans [24, 26, 27, 63]. We show that AsALG-4 26G-RNAs appear during 16 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . late stages of spermatogenesis commensurate with when their target mRNAs disappear. AsALG-4 26G- RNAs are uniformly distributed across their target transcripts (current data and [51]). This contrasts with the 5’ and 3’ end targeting of transcripts of C. elegans ALG-3/4 26G-RNAs during spermatogenesis [74]. Thus, AsALG-4 transcript targeting differs from C. elegans ALG-3/4 indicating flexibility and differences in targeting between nematodes. The AsALG-4 transcript targeting appears more similar to C. elegans ERGO-1 26G-RNAs that uniformly target across transcripts [74]. Strikingly, AsNRDE-3 22G-RNA targets are largely repetitive sequences during early spermatogenesis but during the later stages (M6-M7) their targets are predominantly mRNAs. C. elegans NRDE-3 is involved in the nuclear RNAi pathway and contributes to co-transcriptional repression (inhibiting elongation) [60, 100]. AsNRDE-3 small RNAs target the 5’ ends of transcript in M6-M7. This may be associated with co- transcriptional repression of targets. The decrease in AsCSR-1 levels during the later stages of spermatogenesis may lead to loss of licensing or protection from repression also resulting in a decrease in AsCSR-1 target RNAs.
AsCSR-1 could also play a repressive role as recently described [25, 95]. Notably, targets of AsCSR-1, AsALG-4, and AsNRDE-3 in M6-M7 largely overlap. Ascaris spermatids exhibit very low levels of mRNAs and small RNAs. We suggest that during the later stages of Ascaris meiosis these Argonautes, their changes in expression, and small RNAs act in concert to clear mRNAs in the formation of spermatids. Overall, complex and diverse small RNA pathways contribute to key patterns of gene regulation likely involving licensing during early spermatogenesis and transcriptional and post- transcriptional repression during the later stages of Ascaris spermatogenesis. Plasticity of Ascaris WAGO-3 and NRDE-3 targets. Ascaris WAGO-1 and WAGO-2 associated small RNAs only target repetitive sequences. However, AsWAGO-3 and AsNRDE-3 small RNAs, depending on the stage and tissue, can target either repetitive sequences or mature mRNAs. AsWAGO-3 small RNAs in early embryos predominantly target mature mRNAs that overlap with AsCSR-1 (AsWAGO-3 RNA is expressed at much lower levels than AsCSR-1) whereas in the male gonad they largely target repetitive sequences. Sequence alignment and phylogenetic analyses suggests AsWAGO-3 appears similar to C. elegans C04F12.1 and clusters with CSR-1. C. elegans NRDE-3 IP and 22G-RNA analysis indicates the small RNAs target intergenic repetitive loci [101]. In Ascaris, NRDE-3 also targets primarily repetitive sequences during early spermatogenesis, the female germline, and in 4-cell embryos. However, during the later stages of spermatogenesis, a large percentage of NRDE-3 small RNAs target mRNAs. Secondary 22G-siRNAs in C. elegans are generated by RNA-dependent RNA polymerase following identification of target RNAs by primary siRNAs. The change in small RNA targets in AsWAGO-3 and AsNRDE-3 raises questions regarding how distinct types of targets are identified as substrates for the biogenesis of small RNAs, the RdRPs used to generate the 22G-RNAs, and the loading of these RNAs into distinct Argonautes in different stages [79, 80]. 17 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Ascaris primary siRNAs. Several studies suggest that introduction of dsRNA leads to RNA interference in Ascaris embryos (Davis, R.E., unpublished), larvae [102, 103], the isolated and perfused adult intestine [104], and muscle [105] through injection of dsRNA into the pseudocoelom of adults. The key C. elegans RDE-1 Argonaute binds exogenous siRNAs derived from dsRNA. Ascaris appears to lack an RDE-1 Argonaute. What Ascaris Argonaute then acts on introduced dsRNA or endogenous dsRNA to generate primary siRNAs that induce the generation of secondary siRNAs? Most of our phylogenetic analyses suggest that AsALG-5 and AsALG-7 appear related C. elegans ALG-3/4, while in a few cases, they cluster with either RDE-1 or ERGO-1.
AsALG-7 expression is highest in early stages of spermatogenesis. However, we observe very low levels of 26G-RNAs in early spermatogenesis suggesting AsALG-7 may not bind 26G-RNAs. The lack of HENN-1 and 26G-RNAs in other stages suggests that AsALG-5 and AsALG-7 are not likely orthologs of ERGO-1. It is possible that the widely expressed AsALG-7 might serve functions similar to C. elegans RDE-1. Overall, with no Ascaris piRNAs and 26G-RNAs not likely serving as primary siRNAs to initiate secondary siRNA generation, the origin of endogenous primary siRNAs in Ascaris that lead to the abundant 22G-RNAs is unclear. Recent data suggest that in some C. elegans stages or compartments the CSR-1 slicer activity [22] may initially function to target and cleave mRNAs thereby serving to identify RNAs for RdRPs to initiate the generation of secondary siRNAs for CSR-1 [95]. A similar mechanism may occur in Ascaris. Evolutionary comparison of Argonautes and small RNA pathways in nematodes A diverse array of repetitive sequences are targeted by 22G-RNAs in Ascaris and these are the most abundant small RNAs. Notably, Ascaris Argonautes that associate with small RNAs targeting repetitive sequences (AsWAGO-1, AsWAGO-2, and AsNRDE-3) do not have the catalytic tetrad for slicing activity. Many mobile elements in Ascaris are transcribed bidirectionally at low levels and may generate dsRNAs for primary siRNA generation that may then lead to secondary, amplified 22G-RNAs and suppression of mobile element expression. High levels of these 22G-RNAs target mobile elements in most developmental stages. Many, but not all of these loci exhibit repressive histone marks including H3K9me2/3 (Figure 5). The Ascaris genome lacks de novo DNA methyltransferases and cytosine DNA methylation appears absent in many nematodes [106, 107]. Thus, a key role of Ascaris small RNAs and their pathways is likely to silence mobile elements and other repetitive sequences through repressive histone chromatin marks. Other Clade III-IV nematodes also target mobile elements in the absence of piRNAs. Although 22G-RNAs appear absent in Clades I & II [90], other types of small RNAs are generated to mobile elements in these clades. These small RNAs are likely derived from RdRPs generating dsRNA that are cleaved by Dicer similar to plant and fungal systems that generate monophosphate siRNAs [2]. Cytosine DNA methylation is present in some Clade I nematodes [107-109] and siRNAs may lead to DNA methylation and 18 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . transcriptional repression of mobile elements. Taken together, different nematodes appear to use diverse mechanisms to repress mobile elements [90]. Previous analysis of the evolutionary conservation of Argonautes and different types of small RNAs in nematodes suggest that the complexity of Argonautes and small RNA pathways in Caenorhabditids is not conserved throughout nematodes [8, 40, 41, 51, 89, 90, 106, 110-112].
The piRNA pathway is present only in Clade V nematodes; C. elegans CSR-1 and/or C04F12.1 orthologs are present in some Clade III, V and IV nematodes, but appear absent in Clade I and II nematodes; and nuclear Argonautes (HRDE-1 or NRDE-3) are present in many Caenorhabditids and some Clade III nematodes, but they appear absent in other Clades. Here, we have shown general conservation of Caenorhabditid CSR-1, ALG-3/4, and WAGO associated small RNAs and their targeting in Ascaris (Clade III). Secondary siRNAs (22G-RNAs or longer) are present in Clades III-V, but they are absent in Clades I-II. Strongyloididae (Clade IV) appear to have 27GA-RNAs instead of 22G-RNAs and the secondary siRNAs of Globodera pallida (Clade IV) are 22-26 nt in length. Differences in the sizes of small RNAs is also observed in Ascaris with discrete small RNAs (22-24G) associated with different WAGOs. Although orthologs of ALG-3/4 appear present in most nematodes, 26G-RNAs appear generally absent; Ascaris appears to be an exception with abundant 26G- RNAs during spermatogenesis meiosis. If 26G-RNAs in other nematodes are restricted to meiotic regions of the male germline as seen in Ascaris, they may not have been enriched in samples used in previous analyses of those nematodes. 22G-RNAs and transgenerational inheritance Transgenerational inheritance in C. elegans is associated with piRNAs, 22G-RNAs, and histone H3K9me3 and H3K27me3 marks [11, 35, 88, 113]. C. elegans HRDE-1 is important for maintenance of inheritance over several generations whereas NRDE-3 appears limited to one generation. An interesting question is whether Argonautes and small RNA pathways are associated with transgenerational inheritance in Ascaris and other nematodes. Transgenerational inheritance in C. elegans has been associated with environmental information (odors, temperature, food, other stress, etc. ), behavior, lifespan, and viral and bacterial pathogens [35, 88, 114-119]. In parasitic nematodes, transgenerational inheritance of information like these and particularly host immune responses would be clearly beneficial. For example, exosomes from the parasitic nematode, Heligmosomoides polygyrus (bakeri), contain 22G-RNAs and a WAGO Argonaute, and can suppresses Type 2 innate responses and eosinophilia [111, 120]. Nematode Argonautes and small RNA pathways may play key roles in host-parasite interactions and communication among nematodes. As many of these nematode Argonautes and small RNA pathways are worm-specific and thus differ from their hosts, they could be potential targets for new therapies against parasitic nematodes. 19 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Summary Nematoda is a diverse phylum including free-living and parasitic species.
Ascaris lacks piRNAs but maintains a CSR-1 pathway with small RNAs that target most expressed mRNAs. Thus, AsCSR-1 appears to act in a “licensing” pathway as observed in C. elegans in the absence of a piRNA pathway as well as serving other tuning or repressive functions. Ascaris ALG-4 associated 26G-RNAs target male meiosis- specific genes commensurate with their mRNA degradation and do not appear to act as primary siRNAs for targeting and generating secondary 22G-RNAs during spermatogenesis. Several Ascaris Argonautes, including AsNRDE-3 and AsWAGO-3 targets are stage dependent altering their targets between mRNAs and repeats during spermatogenesis and development. Our data significantly expand our understanding of the conservation, divergence, and flexibility of nematode Argonautes and small RNA pathways. Nematode Argonautes and small RNA pathways may have initially evolved for specific types of gene regulation leading to better fitness, but over time may have been co-opted for other functions in diverse nematodes. 20 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Materials and Methods Ascaris Collection of Ascaris tissues, sperm, and embryonation were as previously described [51, 61]. Male and female germline tissues were washed in PBS, frozen whole or following dissection in liquid nitrogen, and stored at -80°C (see Figure S9, male germline). Lysates from frozen total germline tissue or dissected male germline were prepared by first grinding the frozen samples in a mortar and pestle in liquid nitrogen followed by homogenization in a metal dounce at 4°C in 20 mM Tris–HCl pH 7.9, 75 mM NaCl, 0.5 mM EDTA, 0.85 mM DTT. Nuclei were lysed by addition of 20 volumes of 20 mM HEPES pH 7.6, 300 mM NaCl, 0.2 mM EDTA, 1 mM DTT, 7.5 mM MgCl2, 1M urea, 1% NP-40(v/v), 200 U of NxGen RNase Inhibitor (Lucigen), and protease inhibitor cocktail (Roche) [121]. Fresh Ascaris 4-cell embryos were decoated and directly homogenized in a metal dounce and nuclei lysed as described above. Lysates were then used for total RNA isolation or immunoprecipitation. Antibodies We generated polyclonal antibodies to Ascaris fusion proteins for AsALG-1, AsALG-4, AsCSR-1, AsWAGO-1, AsWAGO-2, AsWAGO-3, and AsNRDE-3 and also to peptides for AsWAGO-2 and AsWAGO- 3. AsALG-1 amino acids 1-165 (HQ611964), AsALG-4 amino acids 1-75 (HQ611965), AsCSR-1 amino acids 1-162 (HQ611969), AsWAGO-1 amino acids 1-113 (HQ611970) AsWAGO-2 amino acids 1-141 (HQ611971), AsWAGO-3 amino acids 49-202 (HQ611972), and AsNRDE-3 amino acids 45-246 (HQ611973) were fused in frame with GST using the Bam H1 site of pGEX-6P-1 (GE Healthcare), the proteins were expressed in E. coli, purified using Glutathione Sepharose 4B columns, and used as the immunogens for the initial boost to generate polyclonal rabbit antibodies (Covance).
For additional boosts, we used the Ascaris proteins cleaved from GST-fusions bound to Glutathione Sepharose 4B by treatment with PreScission protease (GE Healthcare). AsWAGO-2 peptides (YASRRMFELTKQSRDDYRA and RNGGQETSSSSSGEAGHLDI) and AsWAGO-3 peptides (VISYGRGKARRKEFPKQAGT and RENDLPRNGESVDWNRITD) were fused to KLH and used as immunogens to generate polyclonal rabbit antibodies (Pocono Rabbit Farm & Laboratory, Inc.). Antibodies were affinity purified using either the peptides linked to SulfoLink beads (Pierce) or the Ascaris proteins (without GST) linked to a mix of Affigel-10/15 (BioRad). Embryo Immunohistochemistry Ascaris embryo immunohistochemistry was carried as described [61] using a modified freeze-crack method to permeabilize and fix embryos. Briefly, decoated embryos were suspended in 50% methanol and 2% formaldehyde solution and were frozen and thawed 3 times using a dry ice/ethanol bath. The embryos were re-hydrated with 25% methanol in PBS pH 7.4 for 1 min. After washing twice with PBS pH 7.4, the embryos were incubated in signal enhancer solution (Invitrogen I36933) for 30 min at RT. The embryos 21 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . were then re-suspended in blocking solution (0.5% BSA in PBS pH7.4) for 30 min at RT, followed by overnight incubation in primary antibodies at 4°C, and then a 2 hr incubation in secondary antibodies (Invitrogen) at room temperature. Nuclei were stained with DAPI. Cytological analysis of the Ascaris male germline Regions of 1-5 cm were collected from 1% formaldehyde-fixed dissected gonads at defined distances from the distal tip. Germline fragments were placed on a glass slide with PBS pH 7.4 and gently rolled over with a glass rod to release germline tissue from the outer somatic sheath. Samples were next stained with DAPI and the slides mounted in Prolong anti-fade medium (Invitrogen). Regions were characterized and defined based on nuclear morphology and presence or absence of mitotic/meiotic structures as follows: 1. Mitotic: round-shape interphase nuclei with evenly distributed chromatin and defined nucleolus and the presence of mitotic metaphases and anaphases. 2. Transition zone: more compact chromatin with punctate aspects and irregular shape, no mitoses observed. 3. Meiosis I – Pachytene: Chromatin aspects similar to a “bowl of spaghetti”, increasing nuclear size from early (closer to TZ) to late (closer to meiotic progression). 4. Meiosis 1 & 2: increased chromatin compaction (diplotene), visualization of individual bivalents (diakinesis), further localization to the metaphase plate (metaphase I) and segregation to opposite poles with lagging material in the middle corresponding to sex chromosomes (anaphase I).
While no clear observations of meiosis II prophase to anaphase were obtained, groups of 4 nuclei in very close proximity to each other indicated completion of the second meiotic division and formation of haploid nuclei. 5. Spermatids: dispersed, very small and compact nuclei. Immunohistochemistry of the Ascaris germline was carried out on the same samples as described above. Tissue fragments were kept on the slide throughout the whole immunohistochemistry procedure, with careful pipetting of the solutions to avoid sample loss. Samples were first permeabilized in 0.2% Triton X- 100/PBS for 15 min at room temperature, followed by 2 washes in PBS. Next, samples were suspended in blocking solution (1% BSA in PBS pH 7.4), covered with parafilm and incubated for 1 hr at room temperature in a wet chamber. Primary and secondary antibody (Invitrogen) incubations were performed overnight at 4 C and for 2 hr at RT, respectively, with slides covered with parafilm and placed in wet chamber. After staining of nuclei with DAPI, slides were mounted in anti-fade medium (Invitrogen) and kept in the dark at room temperature for 24 h before imaging. Image Acquisition Ascaris germline immunohistochemistry and DAPI-stained preparations were imaged on an Applied Precision DeltaVision microscope, using a 60X immersion objective and FITC/DAPI excitation filter set. Images were deconvolved with Applied Precision’s Softworx software and analyzed using Fiji software. Ascaris embryos immunohistochemistry images were captured on a Leica DM6B fluorescence 22 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . microscope, equipped with a Leica DFC 7000 T camera, using a 40X objective, FITC/DAPI excitation filter set and LASX software. Argonaute Immunoprecipitation Argonaute IPs were carried out using affinity purified rabbit antibodies pre-bound to Protein A Dynabeads (Fisher Scientific) (5-10 ug of antibody per 100 ul of beads) [122]. Germline or embryo whole cell lysates were mixed with Protein A Dynabeads and rotated overnight at 4°C. Protein A Dynabeads were recovered and washed with high-salt buffer (50 mM Tris–HCl, pH 7.4, 1M NaCl, 1mM EDTA, 1% Igepal CA-630, 0.1% SDS, 0.5% sodium deoxycholate) three times. The beads were resuspended in 250 ul of Proteinase K buffer containing 200 µg/ml Proteinase K and incubated for 1 hr at 37°C. RNA was extracted using Trizol LS (Invitrogen) adapted for small RNA recovery by precipitation using 2 volumes of isopropanol, 15 µg of GlycoBlue (Invitrogen), and 30 minutes incubation at -80°C followed by centrifugation at 18,500 x g for 35 minutes at 4°C. The RNA was treated with RppH (25 units, New England Biolabs) in Thermopol buffer for 5’ independent cloning [123].
Both untreated and RppH-treated samples were done for AsALG-1 and AsALG-4 samples. Following RppH treatment, samples were repurified with Trizol LS (Invitrogen) (adopted for small RNAs extraction) and stored at -80°C. RNA, small RNA libraries and sequencing RNA was isolated using Trizol or LS Trizol (Invitrogen). Total RNA samples were fractionated into small RNA (< 200 nt) and long RNA (>200nt) using the Monarch RNA cleaner (New England Biolabs). Small RNA libraries were prepared using the Small RNA-Seq Library Prep Kit (Lexogen). Both 5’-phosphate and 5’-phosphate independent libraries (RppH-treated) [123] were prepared. Libraries from 4-cell embryos were also prepared using 18-30 nt gel purified RNA using the SMARTer smRNA-Seq Kit (Clontech) and NEXTflex-Small-RNA-Seq (New England Biolabs) with similar results. RNA >200 nt was treated with TURBO DNase (Ambion) and rRNA depletion carried out using RiboCop rRNA Depletion Kit for Human/Mouse/Rat (Lexogen). Long RNA (>200 nt) libraries were made using CORALL Total RNA-Seq Library Prep Kit (Lexogen). Both small and long RNA libraries were sequenced 150 nt from both ends using the Illumina NovaSeq 6000 System. Small RNA data analysis Bioinformatic processing of small RNA sequencing data was carried out as previously described [51]. Briefly, adaptor sequences were trimmed and then the reads collapsed to non-redundant datasets. The reads were then mapped to the Ascaris genome and other various datasets [124] to determine targets and their expression levels. To define complementary regions in the genome corresponding to AsWAGO-1 and AsWAGO-2 small RNAs, we first mapped reads from each Argonaute IP-small RNA library to the genome using bowtie [125]. We normalized the coverage for each library to 30 million reads, a number close to the 23 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . average number of raw input reads for the libraries. With an average length of ~22 nt for the small RNAs, this corresponds to ~2.5x coverage of the 280-Mb genome. As AsWAGO-1 and AsWAGO-2 small RNA targets are very similar, we merged genomic regions in close proximity (within 2,000 bp) if they have >= 20 fold average coverage (50 x) from any of the 20 AsWAGO-1 and AsWAGO-2 libraries (using mergeBed d 2000). This merge is necessary as a locus is often not fully covered with high-levels of siRNAs. This approach defined an initial set of enriched loci (9,164 with length >= 50 bp). We then used the normalized reads (rpkm) mapped to these loci and a 10-fold enrichment in at least one library to define these genome regions as enriched for AsWAGO-1 and AsWAGO-2 small RNAs. These regions were further filtered to remove loci related to rRNA, tRNAs, miRNAs or mitochondrial DNA.
Overall, we defined 3,948 AsWAGO- 1 and AsWAGO-22 targeted (10x enriched) genomic regions that constitutes 8.1 Mb of sequence and named them WAGO-repeats. Using the same approach, we defined 2,912 (6.2 Mb) AsNRDE3 targets. The majority (~77%) of the sequences defined as AsNRDE-3 targets overlap with AsWAGO-1/2 targets. See Table S3 and S4 for the defined WAGO-repeats and mRNAs and their WAGO-associated small RNAs. PCA analysis on the small RNA libraries was done using DESeq2 plotPCA [126]. Heatmaps were generated using Treeview 3 [127]. Repetitive sequence identification. Repetitive sequences were identified using a combination of homology-based and de novo approaches, including RepeatMasker [128], LTRharvest [129], RepeatScout [130], RepeatExplorer [131], dnaPipeTE [132], MGEScan-nonLTR [133], Helsearch [134], MITE-Hunter [135], SINEfinder [136], TEdenovo [137], and RepARK [138]. The final collection of repetitive sequences was filtered for redundancy with CD-hit and are available in within the repeat track at http://genome.ucsc.edu/s/jianbinwang/Ascaris_small_RNAs. Data access. The small RNA and RNA sequencing data is deposited to NCBI GEO database (accession number pending). The data is also available in UCSC Genome Browser track data hubs [139] that can be access with this link: http://genome.ucsc.edu/s/jianbinwang/Ascaris_small_RNAs. 24 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Acknowledgements We thank Richard Komuniecki, Bruce Bamber, Jeff Myers, and Routh Packing Co. for their support and hospitality in collecting Ascaris material. We thank Adam Wallace and Stella Kratzer for initial work on the purification, evaluation, and western blot analysis of the Ascaris Argonaute antibodies. We thank Diane Shakes and Diana Chu for advice and suggestions for the analysis of Ascaris spermatogenesis and members of the C. elegans small RNA research community for comments and feedback on the manuscript. This work was supported by NIH grants to R.E.D. (AI049558 and AI114054) and J.W. (AI155588) and startup funds from the University of Tennessee at Knoxville to J.W. 25 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . References 1. 2. 3. 4. 5. 6. 7. 8. 9. Bartel, D.P. (2018). Metazoan MicroRNAs. Cell 173, 20-51. Gutbrod, M.J., and Martienssen, R.A. (2020). Conserved chromosomal functions of RNA interference. Nat Rev Genet. Houri-Zeevi, L., and Rechavi, O. (2017). A Matter of Time: Small RNAs Regulate the Duration of Epigenetic Inheritance.
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Bioinformatics 30, 1003-1005. 33 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Figure Legends Figure 1. Ascaris has 10 Argonautes. A. Argonaute protein phylogenetic tree showing the relationship of Ascaris and C. elegans Argonautes. Ascaris Argonautes are in purple boxes. Labels indicate the type of Argonaute or its associated small RNA. GenBank accession numbers for these Argonaute protein sequences are available in Table S1. Argonautes highlighted in green represent a canonical fly PIWI and Arabidopsis AGO Argonaute. The Argonautes were aligned using Muscle and the tree generated using Neighbor Joining and Maximum Likelihood (1,000 bootstraps) with the bootstrap values illustrated. Ascaris proteins for which antibodies were generated are marked with Ab. B. RNA expression of Ascaris Argonautes and RNA-dependent RNA polymerases (RdRPs). The levels of expression (numbers are in rpkm) are shown in a heatmap with higher expression in red. Note that we view an rpkm value that is less than 5 as a background level of expression. The developmental stages are as follows: M1 to M8 are regions of the male germline, with M1 = early mitotic region, M2 = late mitotic region, M3 = transition zone, M4 = transition zone to early pachytene, M5 = pachytene, M6 = late pachytene, M7 = meiosis diplotene to diakinesis, and M8 = spermatids (see Figure 3, text, add Materials and Methods for a detailed description of the male germline stages); F1 to F5 are regions of the female germline, with F1 = mitotic region, F2 = early pachytene, F3 = late pachytene, F4 = diplotene, F5 = oocyte; zygote maturation stages prior to pronuclear fusion isolated from the uterus (E1-4; E4 is the stage passed from Ascaris and the host to the environment) [61]; embryo development (at 30° C) stages, with E5 = 24hr (1-cell), E6 = 46hr (2-cell), E7 = 64hr (4-cell), E8 = 96hr (16-cell), E9 = 116hr (32-64-cell), E10 = 7day (256-cell), larvae L1 (10-day) and L2 (21-day) [61]; and adult somatic tissues, with Mu = Muscle, In = intestine and Ca = carcass, which includes the cuticle, hypodermis, muscle, nervous system, and pharynx. C. Ascaris Argonaute immunohistochemistry in early embryos. DAPI (blue) in left panel and immunohistochemistry (green) in right panel. Figure 2. Ascaris Argonautes bind specific sets of small RNAs. A. Size distribution, frequency, and targets of small RNAs associated with specific Argonautes. Small RNAs (18-30 nt) from input and Argonaute immunoprecipitation (IP) were plotted for the whole testis (male germline), whole ovary (female germline), and 4-cell embryo (60 hr). In these and all subsequent small RNA size distribution figures, small RNAs starting with A, C, G, and U of different sizes (x-axis) were plotted against their read frequencies (y- axis; raw reads in millions).
Data are derived from two or more biological replicates combined. The small RNAs were categorized by their type (miRNA) or complementarity to different targets as shown in percentage bars below each size distribution plot. The target categories are sequences matching: 1) rRNAs or 2) tRNAs; 3) miRNAs; 4) repetitive sequences and mobile elements that are targets of AsWAGO- 1, AsWAGO-2 and AsNRDE-3 (WAGO-repeats); 5) siRNAs antisense to mRNAs; siRNAs matching 6) introns or 7) intergenic regions; 8) small RNAs that have no full-length match to the genome (no match); 9) and sense small RNAs that correspond to mRNAs. B and C. Principal component analysis (PCA) of small RNAs associated with Argonautes in different stages showing the overall relationship among these small RNA libraries. B is PCA analysis of small RNAs that target mRNAs and C is small RNAs that target the WAGO-repeats. D and E. Venn diagram showing the Argonaute small RNA overlapping targets in the testis for mRNAs (D) and WAGO-repeats (E). Figure 3. Ascaris male gonad regions and nuclear morphology. A. Schematic representation of regions of Ascaris male germline illustrated that correspond to C. elegans male germline and nuclear morphology. Corresponding regions between C. elegans and Ascaris are kept to scale; however, the length of the Ascaris male gonad is ~1 meter. Regions labeled are: 1) mitotic (pink), 2) transition zone (orange), 3) meiosis 1 – pachytene, 4) meiosis 1 & 2 (green), and 5) spermatids (blue). Regions of the Ascaris male germline collected for Argonaute IP and RNA-seq are labeled M1-M8, separated by blue vertical lines. B. Nuclear morphology of DAPI-stained regions of the Ascaris male gonad. (a-d) Overview of the mitotic region illustrating the progressive increase in gonad thickness. Mitotic stages are observed (metaphase, anaphase; arrows), confirmed by staining with CENP-A and the mitosis marker H3S10P (data not shown), as well as apoptotic nuclei (*). Larger and less condensed nuclei are also detected, scattered through the mid-plane (dotted circles). (e) The transition zone exhibits more condensed and punctate nuclear morphology. (f-h) “Spaghetti bowl”-like nuclei characteristic of early (f), middle (g) and late pachytene (h). 34 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . (i-m) Stages of meiotic progression: diplotene (i); diakinesis, with distinguishable individual bivalents (j); metaphase I (k); anaphase I (l), note lagging sex chromosomes (inset, arrowhead); and second meiotic division resulting in 4 haploid nuclei (m, contour). (n) spermatids. Figure 4. Small RNAs associated with Ascaris Argonautes during spermatogenesis. A. Illustration of Ascaris stages of spermatogenesis from Figure 3.
B. RNA expression profiles of Ascaris Argonautes and RdRPs throughout spermatogenesis. The Argonautes are plotted in two groups based on their expression pattern or their targets. C. Small RNAs from mature spermatids (M8). The random size distribution pattern illustrates the low levels of bona fide small RNAs. D. Small RNAs during spermatogenesis (M1-M7). In C and D, the size distribution, frequency, and classification of small RNAs are as described as in Figure 2A. Figure 5. AsWAGO-1, AsWAGO-2 and AsNRDE-3 associated small RNAs target repeats during spermatogenesis. A. Genome browser view of a region of chromosome 1 illustrating Argonaute associated small RNAs, RNA expression (RNA-seq), and H3K9me3 levels. Only spermatogenesis stages that exhibit changes in expression or changes in Argonaute small RNA or mRNA expression are illustrated. Note NRDE-3 associated small RNAs change their targets from repeats to mRNAs during pachytene and late meiosis (M5-M7). B. Ascaris WAGO repeat targets largely overlap with genomic H3K9me3 levels and/or the presence of transposable elements. C. siRNA levels to the top targets (top 1,776 WAGO repeat loci; see Table S3) for each WAGO during spermatogenesis. Heatmaps illustrate the standard Z-score (converted from rpkm) showing changes in expression of siRNAs associated with AsWAGO-1, AsWAGO- 2 and AsNRDE-3. The RNA expression (rpkm) of the targets is also illustrated (right). Targeted loci were sorted based on the same order in the four heatmaps. Figure 6. AsCSR-1 and AsNRDE-3 license and fine-tune mRNA expression during early spermatogenesis whereas AsCSR-1, AsNRDE-3, and AsALG-4 facilitate the clearance of mRNAs during late spermatogenesis. A. Genome browser view of a region of chromosome 1 illustrating AsCSR- 1, AsNRDE-3 and AsALG-4 associated small RNAs and their mRNA target expression during spermatogenesis. B. AsCSR-1, AsNRDE-3 and AsALG-4 mRNA targets during spermatogenesis. AsCSR- 1 small RNAs targets are pervasive in different stages and correlate with RNA expression, AsNRDE-3 small RNA targets switch from repeats to mRNAs in pachytene and late meiosis (M5-M7), whereas AsALG- 4 is expressed and its associated 26G-RNAs target mRNAs that are primarily restricted to meiosis (M6- M7) in the male gonad. Shown are the number of mRNAs targeted by different Argonautes. The color indicates where these mRNA targets are most highly expressed in developmental stages using the same color scheme as Figure 1B. Note AsCSR-1 and AsNRDE-3 target a broad group of mRNAs, while AsALG- 4 targets mostly testis-specific genes. C. AsCSR-1, AsNRDE-3 and AsALG-4 targeted mRNAs largely overlap during late meiosis. Venn diagrams showing the relationship between these targets in the M6 stage where all three Argonautes have a large number of targets. D. siRNA and targeted mRNA levels in M6 (Figure 6C) during spermatogenesis. Very low levels of small RNAs are in mature spermatids (Figure 4C); thus, a 0 value is used in M8 for the AGO IPs.
Heatmaps illustrate the standard Z-score (converted from rpkm) showing changes in siRNA and mRNA expression. Targeted genes were sorted based on the same order in the heatmap pairs. E. AsNRDE-3 siRNAs are enriched for sequence at the 5’ ends of mRNAs. siRNA distribution on mRNAs changes in AsNRDE-3, AsCSR-1 and AsALG-4 during spermatogenesis (see also Figure S5). Figure 7. Plasticity of Ascaris small RNA pathways. A. AsNRDE-3 bound small RNAs change their targets from genomic repetitive sequence to mRNAs during spermatogenesis (M5-M7). B. WAGO-3 bound small RNAs change their targets from genomic repetitive sequence in male mitotic germline to mRNAs in 4-cell embryos. C. Model for Ascaris small RNA pathways (see text) (Bolder lines indicate predicted stronger affects and the proportion of small RNAs and their repetitive or mRNA targets are shown as a percentage of all small RNAs below the horizontal lines). 35 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A PIWI Ab CSR-1 WAGO C (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) Ab ERGO-1 & RDE-1 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:21) Ab ? Ab (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22) WAGO Ab (cid:38)(cid:54)(cid:53)(cid:16)(cid:20) 26G (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) WAGO (cid:36)(cid:47)(cid:42)(cid:16)(cid:20) Ab Ab miRNA Canonical Agos (cid:36)(cid:47)(cid:42)(cid:16)(cid:23) WAGO Ascaris Agos B RNA-seq rpkm spermatogenesis to sperm oogenesis to oocyte zygote early embryo late embryo larvae soma Developmental stage M1 M2 M3 M4 M5 M6 M7 M8 F1 F2 F3 F4 F5 E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 L1 L2 Mu In Ca ALG-1 21 23 31 28 12 1 1 5 93 54 56 12 3 10 13 18 28 26 39 42 42 58 78 40 8 0 3 2 s O G A ALG-4 ALG-5 ALG-6 3 2 1 3 34 63 40 4 8 5 6 4 2 0 0 24 28 29 21 12 2 1 1 1 1 1 10 4 5 5 30 16 17 5 1 1 1 2 2 4 3 3 3 3 0 0 2 3 3 3 6 8 13 7 13 13 8 5 23 22 26 34 21 25 18 5 2 1 1 0 4 2 0 1 0 0 1 1 0 0 0 0 1 1 ALG-7 40 44 25 17 20 6 3 2 10 8 8 4 3 9 8 9 15 14 14 10 17 15 10 9 2 2 1 3 CSR-1 109 132 105 122 141 70 35 18 180 96 104 12 29 127 206 241 336 193 131 52 8 3 4 5 1 2 5 3 s O G A W WAGO-1 80 81 47 92 65 8 WAGO-2 25 26 23 23 10 1 WAGO-3 15 16 15 15 9 2 4 11 17 12 13 6 9 88 89 80 125 106 74 51 23 10 6 5 1 5 33 31 33 11 10 49 47 42 37 26 31 17 8 6 5 4 1 3 9 5 5 2 1 2 2 3 3 11 10 10 21 21 19 15 3 1 1 8 28 65 1 10 4 3 30 27 NRDE-3 19 22 15 13 38 19 6 3 33 19 20 5 6 25 28 34 33 52 50 31 25 24 12 9 1 3 3 3 s P R d R RdRP-1 RdRP-2 RdRP-3 13 14 12 20 37 7 6 6 4 4 3 11 10 7 16 58 4 0 3 0 2 2 9 6 1 3 3 1 14 7 6 2 8 2 2 6 1 4 3 2 4 3 2 0 1 1 1 3 2 2 2 12 12 15 20 11 11 7 1 2 2 4 9 2 4 6 3 4 8 3 3 3 1 0 1 0 0 2 2 1 1 1 0 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:44)(cid:49)(cid:51)(cid:56)(cid:55)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:36)(cid:47)(cid:42)(cid:16)(cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3) (cid:36)(cid:47)(cid:42)(cid:16)(cid:23)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3) (cid:38)(cid:54)(cid:53)(cid:16)(cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:21)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3) U G C A 6 0 1 8 U G C A 0 2 6 1 U G C A 4 2 0 2 U G C A 5 4 4 1 2 1 2 1 6 1 5 3 0 1 (cid:87)(cid:72)(cid:86)(cid:87)(cid:76)(cid:86) 8 6 2 1 8 5 2 5 1 6 4 4 2 5 0 0 0 0 0 0 0 0 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 0 2 2 1 U G C A U G C A 8 U G C A 6 1 U G C A 0 3 5 2 0 1 4 (cid:82)(cid:89)(cid:68)(cid:85)(cid:92) 2 2 1 8 0 2 5 1 6 2 2 6 0 1 4 4 2 2 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 4 1 (cid:25)(cid:19)(cid:75)(cid:85) (cid:11)(cid:23)(cid:16)(cid:70)(cid:72)(cid:79)(cid:79)(cid:12) 2 1 0 1 8 6 4 U G C A 2 2 U G C A 0 2 6 1 2 1 8 U G C A 8 6 4 2 U G C A 5 1 0 1 8 6 4 2 2 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 rRNAs tRNAs miRNAs WAGO−repeats mRNA−antisense introns intergenic no match mRNA−sense B D 40 C(cid:54)(cid:53)(cid:16)1 (cid:80)(cid:53)(cid:49)(cid:36)(cid:3)(cid:87)(cid:68)(cid:85)(cid:74)(cid:72)(cid:87)(cid:86) (cid:38)(cid:54)(cid:53)(cid:16)(cid:20) (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22) e c n a i r a v % 0 1 : 2 C P 30 W(cid:36)(cid:42)(cid:50)(cid:16)3 20 10 N(cid:53)(cid:39)(cid:40)(cid:16)3 0 W(cid:36)(cid:42)(cid:50)(cid:16)(cid:21) W(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) -10 A(cid:47)(cid:42)(cid:16)4 W(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) W(cid:36)(cid:42)(cid:50)(cid:16)2 N(cid:53)(cid:39)(cid:40)(cid:16)3 W(cid:36)(cid:42)(cid:50)(cid:16)3 C(cid:54)(cid:53)(cid:16)1 A(cid:47)(cid:42)(cid:16)4 group a ovary a 60hr a testis (cid:20)(cid:28)(cid:25) (cid:25)(cid:19) (cid:23)(cid:25)(cid:28) (cid:20)(cid:21)(cid:26) (cid:20)(cid:28) (cid:20)(cid:15)(cid:22)(cid:19)(cid:26) (cid:27)(cid:28)(cid:23) (cid:28)(cid:21)(cid:19) (cid:24)(cid:24) (cid:25)(cid:28) (cid:21)(cid:23) (cid:20)(cid:25)(cid:20) C 0 40 PC1: 82% variance 80 120 (cid:36)(cid:47)(cid:42)(cid:16)(cid:23) (cid:24) (cid:20)(cid:24) 43 (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) 60 (cid:58)(cid:36)(cid:42)(cid:50)(cid:3)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:3)(cid:87)(cid:68)(cid:85)(cid:74)(cid:72)(cid:87)(cid:86) e c n a i r a v % 5 : 2 C P 40 20 0 W(cid:36)(cid:42)(cid:50)(cid:16)3 C(cid:54)(cid:53)(cid:16)1 W(cid:36)(cid:42)(cid:50)(cid:16)2 (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) W(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) C(cid:54)(cid:53)(cid:16)1 A(cid:47)(cid:42)(cid:16)4 A(cid:47)(cid:42)(cid:16)4 W(cid:36)(cid:42)(cid:50)(cid:16)2 C(cid:54)(cid:53)(cid:16)1 A(cid:47)(cid:42)(cid:16)4 group a ovary a 60hr a testis E (cid:20)(cid:22)(cid:26) (cid:21)(cid:28)(cid:26) WAGO−1 (cid:20)(cid:21)(cid:22) (cid:26)(cid:22)(cid:24) (cid:25)(cid:28)(cid:25) 20 N(cid:53)(cid:39)(cid:40)(cid:16)3 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) W(cid:36)(cid:42)(cid:50)(cid:16)2 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22) W(cid:36)(cid:42)(cid:50)(cid:16)1 W(cid:36)(cid:42)(cid:50)(cid:16)3 N(cid:53)(cid:39)(cid:40)(cid:16)3 (cid:23)(cid:23) (cid:21)(cid:20)(cid:23) 50 0 50 PC1: 82% variance 100 150 WAGO−2 NRDE−3 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:86) (cid:81) (cid:68) (cid:74) (cid:3)(cid:72)(cid:79)(cid:72) (cid:17) (cid:38) (cid:75) (cid:87) (cid:74) (cid:81) (cid:72) (cid:79) (cid:3) (cid:80) (cid:88) (cid:3) (cid:19) (cid:19) (cid:24) (cid:97) (cid:20) (cid:21) (cid:22) (cid:23) (cid:24) (cid:71) (cid:68) (cid:81) (cid:82) (cid:74) (cid:3) (cid:72) (cid:68) (cid:48) (cid:79) (cid:81) (cid:82) (cid:74) (cid:72) (cid:85) (cid:3) (cid:70) (cid:76) (cid:87) (cid:82) (cid:87) (cid:76) (cid:76) (cid:48) (cid:17) (cid:20) (cid:72) (cid:81) (cid:82) (cid:93) (cid:3) (cid:81) (cid:82) (cid:76) (cid:87) (cid:76) (cid:86) (cid:81) (cid:68) (cid:85) (cid:55) (cid:17) (cid:21) (cid:72) (cid:81) (cid:72) (cid:87) (cid:92) (cid:75) (cid:70) (cid:68) (cid:51) (cid:3) (cid:16) (cid:3) (cid:44) (cid:3) (cid:86) (cid:86) (cid:82) (cid:72) (cid:48) (cid:76) (cid:76) ... (cid:44) (cid:44) (cid:3) (cid:71) (cid:81) (cid:68) (cid:3) (cid:44) (cid:3) (cid:86) (cid:86) (cid:82) (cid:72) (cid:48) (cid:76) (cid:76) (cid:17) (cid:23) (cid:86) (cid:71) (cid:76) (cid:87) (cid:68) (cid:80) (cid:85) (cid:72) (cid:83) (cid:54) (cid:17) (cid:24) (cid:17) (cid:22) (cid:40)(cid:68)(cid:85)(cid:79)(cid:92) (cid:47)(cid:68)(cid:87)(cid:72) (cid:39)(cid:76)(cid:83)(cid:79)(cid:82)(cid:87)(cid:72)(cid:81)(cid:72) (cid:80) (cid:88) (cid:88) (cid:3)(cid:86) (cid:3) (cid:17) (cid:36) (cid:75) (cid:87) (cid:74) (cid:81) (cid:72) (cid:79) (cid:3) (cid:80) (cid:3) (cid:20) (cid:97) (cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:21) (cid:22) (cid:39)(cid:76)(cid:68)(cid:78)(cid:76)(cid:81)(cid:72)(cid:86)(cid:76)(cid:86) (cid:23)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:24) B (cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94) (cid:48)(cid:20)(cid:3)(cid:3)(cid:48)(cid:21)(cid:3)(cid:3)(cid:3)(cid:48)(cid:22)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:23) (cid:2)(cid:2)(cid:2) (cid:48)(cid:24) (cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94) (cid:48)(cid:25)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:26) (cid:48)(cid:27) (cid:54)(cid:72)(cid:80)(cid:76)(cid:81)(cid:68)(cid:79) (cid:89)(cid:72)(cid:86)(cid:76)(cid:70)(cid:79)(cid:72) bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:80)(cid:76)(cid:87)(cid:82)(cid:87)(cid:76)(cid:70)(cid:3)(cid:87)(cid:85)(cid:68)(cid:81)(cid:86)(cid:76)(cid:87)(cid:76)(cid:82)(cid:81) (cid:83)(cid:68)(cid:70)(cid:75)(cid:92)(cid:87)(cid:72)(cid:81)(cid:72) (cid:80)(cid:72)(cid:76)(cid:82)(cid:86)(cid:76)(cid:86)(cid:3)(cid:44)(cid:18)(cid:44)(cid:44)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:86)(cid:83)(cid:72)(cid:85)(cid:80)(cid:68)(cid:87)(cid:76)(cid:71)(cid:86)(cid:3) (cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94) (cid:48)(cid:20)(cid:3)(cid:3)(cid:48)(cid:21)(cid:3)(cid:3)(cid:3)(cid:48)(cid:22)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:23) (cid:2)(cid:2)(cid:2) (cid:48)(cid:24) (cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:2)(cid:94)(cid:48)(cid:27)(cid:3) (cid:48)(cid:25)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:26) B m k p r 0 5 1 0 0 1 0 5 WAGO−1 WAGO−2 WAGO−3 ALG−1 CSR−1 ALG−4 NRDE−3 (cid:53)(cid:71)(cid:53)(cid:51)−1 R(cid:71)(cid:53)(cid:51)−(cid:21) R(cid:71)(cid:53)(cid:51)−3 C 1 (cid:48)(cid:27) U G C A 0 0 18 20 22 24 26 28 30 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 0 20 40 60 80 100 D (cid:48)(cid:20)(cid:3) (cid:48)(cid:21)(cid:3) (cid:48)(cid:22)(cid:3) (cid:48)(cid:23)(cid:3) (cid:48)(cid:24)(cid:3) (cid:48)(cid:25)(cid:3) (cid:48)(cid:26)(cid:3) U G C A 2 U G C A U G C A 1 U G C A 5 . 0 (cid:44)(cid:49)(cid:51)(cid:56)(cid:55) 4 2 5 . 0 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 U G C A U G C A 1 U G C A 6 1 2 1 U G C A 2 (cid:36)(cid:47)(cid:42)(cid:16)(cid:23) 5 . 0 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 0 1 5 . 1 8 U G C A 2 8 8 6 U G C A 0 1 8 U G C A U G C A 2 (cid:38)(cid:54)(cid:53)(cid:16)(cid:20) 4 4 5 . 0 2 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 6 U G C A 2 2 U G C A 4 U G C A 1 U G C A 5 . 0 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22) 5 .
0 2 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 0 1 0 1 U G C A 8 U G C A 6 U G C A U G C A 6 (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) 6 4 2 5 . 0 4 2 4 2 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 0 2 5 1 5 1 5 2 0 2 U G C A 0 1 0 3 0 2 5 1 U G C A 5 1 U G C A 0 1 U G C A 0 1 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) 5 1 0 1 5 0 2 0 1 0 1 0 1 5 5 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 4 U G C A U G C A U G C A U G C A 2 (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:21) 5 . 0 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 18 20 22 24 26 28 30 20 40 60 80 100 20 40 60 80 100 0 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 (cid:85)(cid:53)(cid:49)(cid:36)(cid:86) (cid:87)(cid:53)(cid:49)(cid:36)(cid:86) (cid:80)(cid:76)(cid:53)(cid:49)(cid:36)(cid:86) (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:86) (cid:80)(cid:53)(cid:49)(cid:36)(cid:16)(cid:68)(cid:81)(cid:87)(cid:76)(cid:86)(cid:72)(cid:81)(cid:86)(cid:72)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:76)(cid:81)(cid:87)(cid:85)(cid:82)(cid:81)(cid:86) (cid:76)(cid:81)(cid:87)(cid:72)(cid:85)(cid:74)(cid:72)(cid:81)(cid:76)(cid:70) (cid:81)(cid:82)(cid:3)(cid:80)(cid:68)(cid:87)(cid:70)(cid:75) (cid:80)(cid:53)(cid:49)(cid:36)(cid:16)(cid:86)(cid:72)(cid:81)(cid:86)(cid:72) bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:42)(cid:72)(cid:81)(cid:72) (cid:48)(cid:82)(cid:71)(cid:72)(cid:79)(cid:86) chr1: (cid:25)(cid:17)(cid:26)(cid:20) (cid:25)(cid:17)(cid:26)(cid:24) (cid:25)(cid:17)(cid:26)(cid:28)(cid:3)(cid:48)(cid:69)(cid:3)(cid:3)(cid:3)(cid:3) B (cid:58)(cid:36)(cid:42)(cid:50)(cid:3)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:86)(cid:3)(cid:11)(cid:28)(cid:17)(cid:24)(cid:21)(cid:3)(cid:48)(cid:69)(cid:12) (cid:51)(cid:85)(cid:72)(cid:71)(cid:76)(cid:70)(cid:87)(cid:72)(cid:71)(cid:3)(cid:55)(cid:40)(cid:86)(cid:3) (cid:58)(cid:36)(cid:42)(cid:50)(cid:3)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:86)(cid:3) (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22)(cid:3)(cid:80)(cid:53)(cid:49)(cid:36)(cid:86)(cid:3) (cid:43)(cid:22)(cid:46)(cid:28)(cid:80)(cid:72)(cid:22)(cid:3)(cid:85)(cid:72)(cid:74)(cid:76)(cid:82)(cid:81)(cid:86) (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:20) (cid:48)(cid:20) 400 _ 0 _ 400 _ (cid:21)(cid:17)(cid:21)(cid:26) (cid:20)(cid:17)(cid:19)(cid:24)(cid:3) (cid:19)(cid:17)(cid:22)(cid:23) (cid:24)(cid:17)(cid:27)(cid:25) (cid:48)(cid:24) 0 _ 400 _ (cid:23)(cid:27)(cid:17)(cid:21)(cid:27) (cid:21)(cid:26)(cid:17)(cid:24)(cid:25) (cid:22)(cid:20)(cid:17)(cid:20)(cid:28) (cid:48)(cid:25) 0 _ 400 _ (cid:48)(cid:26) 0 _ 400 _ (cid:50)(cid:89)(cid:68)(cid:85)(cid:92) 0 _ 400 _ (cid:25)(cid:19)(cid:75)(cid:85) 0 _ 400 _ (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:21) (cid:48)(cid:20) (cid:48)(cid:24) 0 _ 400 _ 0 _ 400 _ (cid:43)(cid:22)(cid:46)(cid:28)(cid:80)(cid:72)(cid:22)(cid:3) (cid:85)(cid:72)(cid:74)(cid:76)(cid:82)(cid:81)(cid:86)(cid:3) (cid:11)(cid:27)(cid:22)(cid:17)(cid:28)(cid:26)(cid:3)(cid:48)(cid:69)(cid:12) (cid:55)(cid:85)(cid:68)(cid:81)(cid:86)(cid:83)(cid:82)(cid:86)(cid:68)(cid:69)(cid:79)(cid:72)(cid:3) (cid:72)(cid:79)(cid:72)(cid:80)(cid:72)(cid:81)(cid:87)(cid:86) (cid:11)(cid:25)(cid:23)(cid:17)(cid:28)(cid:24)(cid:3)(cid:48)(cid:69)(cid:12) (cid:48)(cid:25) 0 _ 400 _ (cid:48)(cid:26) (cid:50)(cid:89)(cid:68)(cid:85)(cid:92) 0 _ 400 _ 0 _ 400 _ C WAGO-1 WAGO-2 NRDE-3 RNA-seq M1 M2 M3 M4 M5 M6 M7 M1 M2 M3 M4 M5 M6 M7 M1 M2 M3 M4 M5 M6 M7 M1 M2 M3 M4 M5 M6 M7 M8 (cid:25)(cid:19)(cid:75)(cid:85) (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) 0 _ 400 _ (cid:48)(cid:20) 0 _ 400 _ (cid:48)(cid:21) 0 _ 400 _ (cid:48)(cid:22) 0 _ 400 _ (cid:48)(cid:23) 0 _ 400 _ (cid:48)(cid:24) 0 _ 400 _ (cid:48)(cid:25) 0 _ 400 _ (cid:48)(cid:26) 0 _ 400 _ (cid:50)(cid:89)(cid:68)(cid:85)(cid:92) 0 _ 400 _ (cid:25)(cid:19)(cid:75)(cid:85) (cid:38)(cid:54)(cid:53)(cid:16)(cid:20) 0 _ 400 _ (cid:36)(cid:47)(cid:42)(cid:16)(cid:23) (cid:48)(cid:25) 0 _ 400 _ (cid:48)(cid:25) (cid:43)(cid:22)(cid:46)(cid:28)(cid:80)(cid:72)(cid:22) 0 _ 100 _ (cid:55)(cid:72)(cid:86)(cid:87)(cid:76)(cid:86) 0 _ 100 _ (cid:50)(cid:89)(cid:68)(cid:85)(cid:92) 0 _ 100 _ (cid:25)(cid:19)(cid:75)(cid:85) 0 _ 200 _ (cid:53)(cid:49)(cid:36)(cid:16)(cid:86)(cid:72)(cid:84) (cid:48)(cid:20) 0 _ 200 _ (cid:48)(cid:21) 0 _ 200 _ (cid:48)(cid:22) 0 _ 200 _ (cid:48)(cid:23) 0 _ 200 _ (cid:48)(cid:24) 0 _ 200 _ (cid:48)(cid:25) 0 _ 200 _ (cid:48)(cid:26) 0 _ 200 _ (cid:48)(cid:27) 0 _ 200 _ (cid:50)(cid:89)(cid:68)(cid:85)(cid:92) 0 _ 200 _ (cid:25)(cid:19)(cid:75)(cid:85) 0 _ Z-score: -2.5 0 2.5 RPKM: 0 100 10000 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:42)(cid:72)(cid:81)(cid:72) (cid:38)(cid:54)(cid:53)(cid:16)(cid:20) (cid:48)(cid:20) (cid:48)(cid:21) chr1:(cid:3)(cid:3)(cid:23)(cid:17)(cid:27)(cid:28)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:23)(cid:17)(cid:27)(cid:28)(cid:24)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:23)(cid:17)(cid:28)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:23)(cid:17)(cid:28)(cid:19)(cid:24)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:69) 400 _ 0 _ 400 _ 0 _ 400 _ B r e b m u N e n e G (cid:3) (cid:71) (cid:72) (cid:87) (cid:72) (cid:74) (cid:85) (cid:68) (cid:55) 0 0 0 4 0 0 0 3 0 0 0 2 0 0 0 1 , (cid:87)(cid:72)(cid:86)(cid:87)(cid:76)(cid:86)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:82)(cid:89)(cid:68)(cid:85)(cid:92)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:93)(cid:92)(cid:74)(cid:82)(cid:87)(cid:72)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:72)(cid:68)(cid:85)(cid:79)(cid:92)(cid:3)(cid:72)(cid:80)(cid:69)(cid:85)(cid:92)(cid:82) (cid:79)(cid:68)(cid:87)(cid:72)(cid:3)(cid:72)(cid:80)(cid:69)(cid:85)(cid:92)(cid:82)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:79)(cid:68)(cid:85)(cid:89)(cid:68)(cid:72)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:86)(cid:82)(cid:80)(cid:68)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:79)(cid:82)(cid:90)(cid:3)(cid:72)(cid:91)(cid:83)(cid:85)(cid:72)(cid:86)(cid:86)(cid:76)(cid:82)(cid:81) C (cid:27)(cid:21)(cid:25) (cid:21)(cid:23)(cid:23) (cid:28)(cid:21)(cid:23) (cid:49)(cid:53)(cid:39)(cid:40)(cid:239)(cid:22) (cid:36)(cid:47)(cid:42)(cid:239)(cid:23) (cid:24)(cid:25) (cid:20)(cid:22)(cid:24) (cid:28)(cid:20) (cid:48)(cid:22) 0 _ 400 _ 0 M1 M2 M3 M4 M5 M6 M7 M1 M2 M3 M4 M5 M6 M7 M6 M7 (cid:21)(cid:22)(cid:24) (cid:38)(cid:54)(cid:53)(cid:239)(cid:20) (cid:48)(cid:23) (cid:31)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:3)(cid:38)(cid:54)(cid:53)(cid:16)(cid:20)(cid:3)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:33)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:31)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:3)(cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22)(cid:3)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:16)(cid:33)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:31)(cid:16)(cid:36)(cid:47)(cid:42)(cid:16)(cid:23)(cid:16)(cid:33) 0 _ 400 _ (cid:48)(cid:24) 0 _ 400 _ D CSR-1 targets 24G-RNAs mRNAs NRDE-3 targets 22G-RNAs mRNAs ALG-4 targets 26G-RNAs mRNAs (cid:48)(cid:25) M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 M1 M2 M3 M4 M5 M6 M7 M8 0 _ 400 _ (cid:48)(cid:26) (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) 0 _ 400 _ (cid:48)(cid:20) 0 _ 400 _ (cid:48)(cid:21) 0 _ 400 _ (cid:48)(cid:22) 0 _ 400 _ (cid:48)(cid:23) 0 _ 400 _ (cid:48)(cid:24) 0 _ 400 _ (cid:48)(cid:25) 0 _ 400 _ n = 1,206 (cid:48)(cid:26) 0 _ (cid:36)(cid:47)(cid:42)(cid:16)(cid:23)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3) 400 _ (cid:48)(cid:25) 0 _ 400 _ 2.5 Z-score 0 2.5 (cid:48)(cid:26) (cid:53)(cid:49)(cid:36)(cid:16)(cid:86)(cid:72)(cid:84)(cid:3)200 _ 0 _ (cid:48)(cid:20) 0 _ 200 _ (cid:48)(cid:21) 0 _ 200 _ n = 2,076 n = 2,050 (cid:48)(cid:22) (cid:48)(cid:23) (cid:48)(cid:24) (cid:48)(cid:25) 0 _ 200 _ 0 _ 200 _ 0 _ 200 _ E l e v e l A N R s i d e z 5 4 3 2 1 (cid:48)(cid:21) Antisense CSR−1 NRDE−3 (cid:48)(cid:24) Antisense CSR−1 NRDE−3 (cid:48)(cid:25) Antisense CSR−1 ALG−4 NRDE−3 (cid:48)(cid:26) 0 _ 200 _ 0 _ 200 _ i l a m r o N 0 1 Sense Sense Sense (cid:48)(cid:27) 5'(cid:3)(cid:20)(cid:24)(cid:8) mRNAs 3' 5'(cid:3)(cid:20)(cid:24)(cid:8) mRNAs 3' 5'(cid:3)(cid:20)(cid:24)(cid:8) mRNAs 3' 0 _ bioRxiv preprint doi: https://doi.org/10.1101/2021.07.23.453445 ; this version posted July 23, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A (cid:49)(cid:53)(cid:39)(cid:40)(cid:16)(cid:22) (cid:48)(cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:21)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:22)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:23)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:24)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:25)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:48)(cid:26)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3) (cid:19) (cid:20) (cid:19) (cid:20) (cid:36)(cid:79)(cid:79)(cid:16)(cid:86)(cid:76)(cid:53)(cid:49)(cid:36)(cid:86) (cid:27) (cid:25) (cid:23) (cid:56) (cid:42) (cid:38) (cid:36) (cid:24) (cid:17) (cid:19) (cid:27) (cid:25) (cid:23) (cid:56) (cid:42) (cid:38) (cid:36) (cid:21) (cid:56) (cid:42) (cid:38) (cid:36) (cid:21) (cid:19) (cid:19) (cid:19) (cid:19) (cid:19) (cid:19) (cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:19) (cid:20) (cid:19) (cid:20) (cid:27) (cid:56) (cid:42) (cid:38) (cid:36) (cid:56) (cid:42) (cid:38) (cid:36) (cid:56) (cid:42) (cid:38) (cid:36) (cid:56) (cid:42) (cid:38) (cid:36) (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:86) (cid:23) (cid:25) (cid:23) (cid:24) (cid:17) (cid:19) (cid:23) (cid:21) (cid:25) (cid:23) (cid:21) (cid:21) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:19) (cid:20) (cid:19) (cid:20) (cid:80)(cid:53)(cid:49)(cid:36)(cid:86)(cid:3) (cid:11)(cid:68)(cid:81)(cid:87)(cid:76)(cid:86)(cid:72)(cid:81)(cid:86)(cid:72)(cid:12) (cid:25) (cid:19) (cid:27) (cid:25) (cid:23) (cid:21) (cid:19) (cid:21) (cid:19) (cid:56) (cid:42) (cid:38) (cid:36) (cid:24) (cid:17) (cid:19) (cid:19) (cid:56) (cid:42) (cid:38) (cid:36) (cid:25) (cid:19) (cid:27) (cid:21) (cid:19) (cid:56) (cid:42) (cid:38) (cid:36) (cid:21) (cid:19) (cid:56) (cid:42) (cid:38) (cid:36) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) B C mRNAs ALG-1 miRNAs (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:22) (cid:48)(cid:20)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:82)(cid:89)(cid:68)(cid:85)(cid:92)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:3)(cid:23)(cid:16)(cid:70)(cid:72)(cid:79)(cid:79) 1-5% repeats (cid:36)(cid:79)(cid:79)(cid:16)(cid:86)(cid:76)(cid:53)(cid:49)(cid:36)(cid:86) (cid:25) (cid:21) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:21) (cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:56) (cid:42) (cid:38) (cid:36) (cid:22)(cid:19) (cid:27) (cid:25) (cid:23) (cid:21) (cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:56) (cid:42) (cid:38) (cid:36) (cid:22)(cid:19) ALG-5 ALG-6 ALG-7 ?
?? (cid:27) (cid:56) (cid:42) (cid:38) (cid:36) (cid:27) (cid:25) (cid:58)(cid:36)(cid:42)(cid:50)(cid:16)(cid:85)(cid:72)(cid:83)(cid:72)(cid:68)(cid:87)(cid:86) (cid:23) (cid:21) (cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:80)(cid:53)(cid:49)(cid:36)(cid:86)(cid:3) (cid:11)(cid:68)(cid:81)(cid:87)(cid:76)(cid:86)(cid:72)(cid:81)(cid:86)(cid:72)(cid:12) (cid:27) (cid:23) (cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:56) (cid:42) (cid:38) (cid:36) (cid:22)(cid:19) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) (cid:27) (cid:25) (cid:20)(cid:27) (cid:21)(cid:19) (cid:21)(cid:21) (cid:21)(cid:23) (cid:21)(cid:25) (cid:21)(cid:27) (cid:22)(cid:19) ALG-4 CSR-1 WAGO-3 NRDE-3 WAGO-1 WAGO-2 26G 24G 23G 22G 22G 22G 10-20% 80-90%
bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Genomic differentiation within East Asian Helicobacter pylori 1, § § 2, 3, , Lihua He 8 , Yukako Katsura #1 Yuanhai You , Kaisa Thorell 6 Cha 7 , Kazunari Murakami #15 1 , Koji Yahara 4 5 , Yoshio Yamaoka , Jeong-Heon , TEAMHp 9 , Ichizo Kobayashi #10, 11, 12, 13, 14 , Daniel Falush , Jianzhong Zhang . 1 State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China 2 Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Sweden 3 Department of Clinical Microbiology, Sahlgrenska University Hospital, Västra Götaland Region, Gothenburg, Sweden 4 Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo 5 Department of Environmental and Preventive Medicine, Oita University Faculty of Medicine, Oita, Japan 6 Department of Oral Biology, BK21 Plus Project, Yonsei University College of Dentistry, Seoul, Korea 7 Department of Gastroenterology, Faculty of Medicine, Oita University, Oita, Japan Primate Research Institute, Kyoto University, Inuyama, Japan 8 9 TEAMHp (Team for East Asian Genomics of Helicobacter pylori)* 10 I2BC, University of Paris-Saclay, Gif-sur-Yvette, France 11 Department of Infectious Diseases, Kyorin University School of Medicine, Mitaka-shi, Tokyo, Japan 12 Department of Computational Biology and Medical Sciences (formerly Department of Medical Genome Sciences), Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan 13 Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan 14 Research Center for Micro-Nano Technology, Hosei University, Koganei-shi, Tokyo, Japan The Center for Microbes, Development and Health, Key Laboratory of Molecular Virology 15 and Immunology, Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China. § Equal first authors. #Address correspondence to: Jianzhong Zhang (zhangjianzhong@icdc.cn), Daniel Falush (danielfalush@googlemail.com) and Ichizo Kobayashi (ikobaya@k.u-tokyo.ac.jp) Author contributions: YouY, DF and JZ designed the project; YouY, LH and JZ prepared Chinese H. pylori strains; YouY, KY, KT, YK, and IK performed data analysis; IK, YouY, KM and TEAMHp provided newly sequenced Japanese H. pylori genomes. JHC provided 1 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license .
Korean genomes. YouY, KT, IK, and DF wrote the manuscript. All authors read and approved the manuscript. 2 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . ABSTRACT The East Asian region, including China, Japan and Korea, accounts for half of gastric cancer deaths. However, different areas have contrasting gastric cancer incidence and the population structure of Helicobacter pylori in this ethnically diverse region is yet unknown. We aimed to investigate genomic differences in H. pylori between these areas to identify sequence polymorphisms associated with increased cancer risk. We analysed 381 H. pylori genomes collected from different areas of the three countries using phylogenetic and population genetic tools to characterize population differentiation. The functional consequences of Single Nucleotide Polymorphisms (SNPs) with a highest fixation index (Fst) between subpopulations were examined by mapping amino-acid changes on 3D protein structure, solved or modelled. 329/381 genomes belonged to the previously identified hspEAsia population indicating that import of bacteria from other regions of the world has been uncommon. Seven sub-regional clusters were found within hspEAsia, related to sub-populations with various ethnicities, geographies and gastric cancer risks. Sub-population-specific amino-acid changes were found in multi-drug exporters (hefC), transporters (frpB-4), outer membrane proteins (hopI), and several genes involved in host interaction, such as catalase, involved in H2O2 entrance, and a flagellin site mimicking host glycosylation. Several of the top hits including frpB-4, hefC, alpB/hopB, and hofC. were also differentiated within the Americas, indicating that a handful of genes may be key to local geographic adaptation. H. pylori within East Asia are not homogeneous but have become differentiated geographically at multiple loci that have facilitated adaptation to local conditions and hosts. This has important implications for further evaluation of these changes in relation to the varying gastric cancer incidence between geographical areas in this region. Keywords: population genomics; Fst; multidrug efflux pump; outer membrane protein; flagellin glycosylation; bacterial pathogenesis; gastric cancer. 3 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Introduction Helicobacter pylori has co-evolved with human beings for at least 100,000 years and has strong association with the occurrence of gastric (stomach) cancer 1.
H. pylori are transmitted most effectively within households and have therefore experienced low migration rates compared to many other members of the human microbial flora. As a result, we can expect the pattern of differentiation to reflect historical human migration patterns. The population structure of H. pylori worldwide has been classified into seven major groups that indeed correlate with ancient human migrations 2, of which the hpEastAsia includes at least three subgroups: hspEAsia, hspAmerind and hspMaori. The hspEAsia subgroup is thought to be ubiquitous within East Asian countries with high gastric cancer incidence, including China, Japan and Korea. These countries together make up 1/5 of the world population but account for half the global mortality from the disease 3, 4. The hspEAsia strains have documented higher virulence than other subpopulations and have diverged from the Western strains in several proteins including virulence factors 5, 6. Many genes have also diverged within this region 5. The prevalence of gastric cancer show geographic and ethnic variations also within East Asia. Some north and southeast areas of China such as Fujian have higher incidence 7, whereas some west regions, such as Yunnan, have low incidence (Figure 1) 8, 9. China also shows diverse distribution of population ethnicities; in southwest Yunnan province more than twenty ethnicities exist. South Korea has been reported with the highest incidence in the world 10, 11 and similar is true for the Japanese main islands (including Hokkaido) 12, while in Okinawa, where the ethnic composition is different, the incidence is low 13. Previous studies on the high- risk regions have suggested that diet, lifestyle and H. pylori properties may contribute to the high risk. However, despite the complex human migrations and evolutionary history in these areas, variation of H. pylori within the hspEAsia subpopulation has been poorly explored. In the present work, we analysed a collection of genomes of H. pylori strains from various places in these three countries. Our phylogenetic and population genetic analysis revealed presence of pronounced regional and ethnical population structure within hspEAsia, and specific sequence differences differentiating these subpopulations. Most of these highly region-specific variants were found on proteins involved in host interaction. Furthermore, placement of the variants on protein structure provided insight into molecular mechanisms underlying regional adaptation. Methods Strain collection across East Asia We collected 357 H. pylori isolates from China, Japan and South Korea, isolated between 1999 and 2018, including 11 provinces of China and 6 regions of Japan (Supplementary Tables S1- S2, Figure 1). We use data from 2014 to show regional risk levels in China and compared it with data from Japan and Korea 7, 8, 10-13. Our sample of 77 Yunnan isolates includes strains from 4 ethnic minorities and the Han majority individuals. 4 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Figure.1. Geographic distribution of the East Asian H. pylori strain dataset of this study. Shade of the circle fill indicates gastric cancer incidence. Grey fill indicates missing incidence data. Genome sequencing Genomic DNA was extracted using the Qiagen DNeasy Mini Kit and genomes were sequenced using Illumina or PacBio sequencers. Quality assessment of genomic DNA, SMRTbell library preparation, and data evaluation were performed for PacBio RS II sequencing. Sequences were deposited into GenBank with BioProject number PRJNA482300. Combining publicly available genomes with these newly sequenced genomes, we collected a dataset consisting of 381 H. pylori genomes for further analysis (Supplementary Table S2). Genomic comparison We used Snippy 14 to perform a whole genome alignment with XZ274 as reference genome and extracted 225 942 variable core genome sites. For the phylogenetic analysis, the dataset of 381 strains were combined with 1-3 reference sequences for each of the major H. pylori populations (Supplementary Table 3). Population structure and phylogenetic analysis 5 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . The concatenated whole genome SNPs dataset was also used to prepare the haplotype data for ChromoPainter and fineSTRUCTURE analyses 15, 16. 13 highly clonal sequences were removed prior to the analysis, resulting in a comparison of 368 genomes. The recombination rate was set to 0.000001 per site/base according to previous studies 16. Using each genome as both donor and recipient haplotypes, we used ChromoPainter to calculate the number of genetic chunks exported from a donor to a recipient and generated a co-ancestry matrix. Then fineSTRUCTURE was run by setting the burn-in and Markov chain Monte Carlo (MCMC) chain of 100,000 iterations to generate clusters for all the individual strains. We also generated a phylogenetic tree using FastTree 17, which was labelled using iTol 18. Definition of subgroups and calculation of Fst between subgroups Subgroups were defined according to the population structure analysed by fineSTRUCTURE. We named the subgroups assigned by fineSTRUCTURE as “Sg” (Supplementary Table S2). To identify the SNPs attributed to the divergence of subgroups more accurately, we used a more stringent definition of the subgroups. Only those isolates assigned into a singular cluster in the fineSTRUCTURE tree were defined to form a subgroup. For example, for China southwest isolates, only those from Yunnan Mosuo and Pumi ethnicities, which clustered into a singular clade, were defined as a subgroup, “YunnanMP”.
For China southeast, only those from Fujian Changle that clustered into a singular clade were defined as a subgroup, “Fuijan”. For each SNP site, we calculated a fixation index (Fst) for each subgroup such that Fst (sg1) = pairwise calculation of Fst of sg1 versus all other subgroups. We also compared isolates from China with those from Japan and South Korea and the two lower-incidence regions, Yunnan and Okinawa, versus high incidence regions (the remainder of hspEAsia strains). Mapping high-Fst SNPs on protein structure We located each of the SNPs with the highest Fst values on the reference genome of XZ274, a Tibetan strain, to identify its gene and effect on amino-acid sequence. If the gene was missing or atypical in this strain, we used strain F57, a Japanese strain, or 26695, a European strain, instead as shown in Table S4. We mapped the amino acids on solved H. pylori protein structure or on protein structure homology-modelled by SwissModel and its repository for 26695 (https://swissmodel.expasy.org/repository?start=0&rows=50&query=Helicobacter+pylori+26 695). We analysed and presented them by PyMOL 19. Results East Asian H. pylori population structure is associated with geography and host ethnicity To analyse the genetic structure of H. pylori in China, Japan and South Korea, we constructed a phylogenetic tree (Figure 2A) and clustered the strains using fineSTRUCTURE15, 16 (Figure 2B), and constructed a phylogenetic tree (Figure 2A). The two methods gave broadly concordant clustering and indicated differentiation at multiple scales. By including reference genomes from the other main H. pylori populations, we found that the 52 most differentiated 6 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . strains do not belong to hspEAsia and have had distinct evolutionary histories. One main cluster of these comprised isolates from individuals of Mongolian ethnicity (Sg4, Figure 2B), which in the tree grouped between the references of hspIndigenousAmerica (previously called hspAmerind) and hpAsia2 populations. We also identified a cluster of Okinawan strains diverging after hpEurope, and before hpAsia2 and hpEastAsia (Figure 2A), also shown in the lowest line of the co-ancestry matrix (Figure 2B). This likely corresponds to Group C in MLST and STRUCTURE analysis of Okinawan strains 20. Because these populations are best analyzed in the context of broader regional variation, we focused our remaining analysis on variation within the 329 hspEAsia isolates in our sample. A B Figure 2. Phylogenetic and population genetic analysis of East Asia H. pylori strains . A) Phylogenetic tree of East Asia genomes combined with reference sequences from global H. pylori populations.
B) Co-ancestry analysis of East Asia isolates after removing highly clonal isolates HspEAsia isolates are relatively homogeneous but show fine-scale differentiation that is strongly correlated with geography. The majority of Japanese isolates clustered together (Sg7), with Okinawan hspEAsia strains forming a distinct subpopulation (Sg6). The latter likely corresponds to Group A in MLST 20. Two strains from Hokkaido cluster with the Sg6 Okinawan strains. This is likely related to the evolutionary structure of Japanese people and of the Okinawa people 21. The native ethnicity remains in Hokkaido (as Ainu ethnicity) and in Okinawa. 7 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . South Korean isolates also form a distinct subpopulation, which cluster together with isolates from the Northeast of China, concordant with its geographic location. A few Japanese strains are in the Korean cluster while a few Korean strains are in the main Japanese cluster and branching around the same time as the Okinawa cluster (Figure 2AB). This may reflect immigration from Korea to Northern Kyushu and Okinawa. Within China, there is clear differentiation between the Northeast, Southeast and Southwest areas. Within the Southwest, a subpopulation containing strains from Yunnan Mosuo and Pumi ethnicities could also be observed. A Tibetan isolate clustered with the Pumi population, consistent with their migration and mixture history. Within the Southeast, there was also a sub-population (Sg2), specific to Fujian Changle, a region of high gastric cancer incidence (Figure 2, Supplementary table S1). The Southeast cluster also includes multiple clusters of Japanese/Okinawa strains (Figure 2AB) likely reflecting the immigration to Japan/Okinawa especially frequent since the advent of rice-paddy cultivation. Many genetic variants show strong differentiation by subpopulations In order to explore the genetic basis of local differentiation, we calculated fixation index, Fst, between the hspEAsia subpopulations identified by fineSTRUCTURE. To obtain more reliable SNPs associated with subgroup separation, we used the YunnanMP sub-cluster of Sg1 and Fujian sub-cluster of Sg2, along with the remaining 5 subgroups defined by the fineSTRUCTURE analysis. For most of the subpopulations, more than 99% of SNPs were weakly differentiated, with Fst less than 0.3 (Supplementary Figure S1). The Korean subpopulation had a smaller sample size and showed the weakest Fst values. Both single nucleotide polymorphisms (SNPs) and clustered nucleotide polymorphisms (CNPs), likely resulting from recombination between diverged sequence groups, were found. To functionally interpret differentiation between the populations, we focused on the SNPs with the top 20 Fst values in each subgroup and then removed SNPs with Fst < 0.5.
This resulted in a list of 56 genes, several of which occurred more than once (Supplementary Table 4, bold). In the main text, we focus on the genes with the strongest evidence for differentiation. Six of these had one SNP with Fst>0.6 and appeared in at least two top 20 lists. Another 6 had at least 2 SNPs with Fst>0.6. Of these HofC has multiple non-synonymous SNPs with Fst up to 0.86, marking it out as also being a particularly strong candidate for being differentiated by natural selection. To predict the effect of differentiated variants on H. pylori biology and pathogenesis, we functionally annotated the genes and interpreted the impact of differentiated amino acids on the protein structures, solved or based on homology modelling. The majority of genes containing the most differentiated SNPs could be grouped into four major categories; (i) transporters, (ii) outer membrane proteins, (iii) metabolism and (iv) host interaction. (i) Transporters: 8 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . The hef multidrug efflux pump H. pylori carries 4 gene clusters that each encodes for a set of RND superfamily of multidrug efflux pump corresponding to TolC-AcrA-AcrB of E. coli (Figure 3). They pump out endogenous bile salts and ceragenins as well as various antibiotics 22-24. The single most differentiated SNP in our analysis is in hefC (HP0607) in the YunnanMP subpopulation, with an Fst=0.89. This N86S is also the most differentiated between the lower cancer incidence regions (Yunnan and Okinawa) and the remainder. This residue corresponds to the gate to channel III for planar aromatic cations in E. coli homolog 25 and the regional adaptation may therefore remodel this gate to export chemicals of this type at different ratios. Also, the outer component of the efflux pump, HefD, showed YunnanMP specific residues in the equatorial domain that may be involved in the interaction with the inner component to open the aperture. A. pump B. (i) C. HefD C. (i) (I) equatorial domain D228N (Yunnan) (ii) (iii) (ii) Vertical line Figure 3. Inferred structure and differentiated amino acid sites of Multidrug efflux pump related proteins. A) TolC-AcrA-AcrB of E. coli and its H. pylori homologs. B) HefC (MWE_0907), modelled on PDB 3W9I (MexB of Pseudomonas aeruginosa). (iii) HefC modelled on PDB 3AOD (AcrB of E. coli). Yunnan-specific N86S is at the entrance of channel III. C) HefD (MWE_1139), modelled on PDB 5BUN (ST50 from Salmonella enterica subsp. enterica serovar Typhi). Yellow spheres indicate Mongol-differentiated E219D. The TonB-dependent nickel importer frpB-4 A gene containing multiple highly differentiated SNPs, especially in North Eastern China, is frpB-4 (HP1512), encoding for an outer membrane transporter of nickel of some form 26.
It is a member of TonB-dependent transporter family, which forms a trimer of 22-stranded beta barrels each filled with a ‘plug’ (Figure 4A,B). H. pylori reference strain 26695 carries four frpB homologs: frpB-1 (HP0876), frpB-2/3 (HP0916/5), and frpB-4 (HP1512). 9 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Ligand binding lets TonB change the conformation of the plug, which opens a channel, a process energized by the ExbBD proton-driven motor 27 (Figure 4B). Four China North East- specific Fst sites cluster (Fig. 4D), with three sites (739, 740, 742) presumably representing a CNP (clustered nucleotide polymorphisms). The next residue (743) distinguishes between Japan (K) and China (J). Northeast China-differentiated F759Y (F for the remainder and Y for Northeast China) and YunnanMP-differentiated K774R are situated above the barrel in the model and may interact with the ligand. Various regions of the Americas show region-specific amino-acid changes in other areas of the protein 28, out of which three are predicted to be in the decoy loop. Taken together, these changes may affect nickel transport and, consequently, urease activity, since the urease enzyme requires nickel for acid acclimation 29. The changes could be related to regional differences in host nickel metabolism and stomach acidity. A. FrpB-4 B. TonB-dependent import system K774R (Yunnan) Ni binding transporter ligand outer membrane F759Y (NE) Y739 (NE) 248 250 398 395 TonB plug C peptidoglycan 244 361 N ExbD N740D (NE) 743 K (Japan) R (China-all) Q697R (NE) H742R (NE) 309 307 242 (Americas) H+ ExbB inner membrane Figure 4. (A) FrpB-4 (MWE_1700) modelled on PDB 4AIQ (FrpB of N. meningitidis) including Americas-specific sites. (B) TonB-dependent transport system. When the transporter in the outer membrane catches a ligand, it pushes out its plug for TonB to pull and open the channel. This movement of TonB is energized by ExbBD motor in the inner membrane driven by H+ flow. Other transporters: Hof proteins (Helicobacter-specific outer membrane protein family 30) are 18-stranded β- barrels homologous to Occ family of Pseudomonas and Campylobacter jejuni MOMP (major outer membrane protein) involved in passive diffusion of cations including antibiotics and in adhesion 31-33. HofC (HP0486), required for H. pylori colonization in mice 34, contains the most differentiated SNPs in Fujian, a region of high cancer incidence with Fst=0.86. The gene is highly variable in global strains and shows many America-differentiated SNPs and region- differentiated SNPs within the Americas 29, within one narrow region. Fujian-differentiated D186S in HP0486 (166 in MWE_0556) lies at a distance from them. Fujian-differentiated V9A is in its signal peptide.
OppD (HP0250), the cytoplasmic subunit of the oligopeptide ABC transporter, has YunnanMP-differentiated KG306R within the ATP binding Walker motif A (Figure 5A). 10 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . A. OppD B. GltA (iv) 6-mer (i) (ii) 2-mer A124 S127T S127T A124 S127T (Yunnan) 127 127 127 (v) (iii) Figure 5. A) OppD (MWE_0327), ATP binding subunit of an oligopeptide ABC transporter as modelled on PDB 4FWI (Thermoanaerobacter tengcongensis). B) Citrate synthase, GltA (i) (ii) (iii) MWE_1570 modelled on PDB 3MSU (Francisella tularensis homolog). (iv) (v) On PDB 2h12 (Acetobacter aceti). (ii) Outer membrane proteins HopB/ AlpB/ Omp21 (HP0913), an adhesin of the Hop family required for colonization, carries Fujian-differentiated N289D and N286H. According to a previous study, 24 polymorphic sites within 49 bp in AlpB are enriched for Asian ancestry in hspEuropeColombia and 32 polymorphic sites within 65 bp were enriched for Asian ancestry in hspAfrica1Nicaragua populations 29. Another member of the Hop family of outer membrane proteins, HopI (HP1156), has a site (467) that distinguishes between Japan (H) and China-all (D) and YunnanMP-differentiated V633L. (iii) Central Metabolism The region-differentiated amino-acid changes involve a handful of key metabolic enzymes. Citrate synthase GltA (HP0026, MWE_1570), is the first enzyme in the TCA cycle catalysing the conversion of acetyl-CoA and oxaloacetate to citrate. Yunnan-differentiated S127T is located between the two identical monomers and is likely involved in their association as well as in dimer-dimer association to form a 6-mer (Figure 5B). The differentiated SNP might change the quaternary structure. Mutation of A124 in this interface was found in experimental evolution in E. coli 35. In addition to GltA, two other key metabolic enzymes, PorB (HP1111), a subunit of pyruvate:ferredoxin oxidoreductase, and FixP (HP0147, MWE_0216), a subunit of cytochrome c oxidase had high Fst values in YunnanMP. PorB, a key enzyme in the microaerophilic metabolism of H. pylori, converts pyruvate to acetyl-CoA, the substrate of 11 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . GltA, and FixP is a component in aerobic respiration. The Yunnan-differentiated residue is at the proton entrance (Supplementary Figure 4C). Together, these changes might affect the metabolic capacity of this regional H. pylori subpopulation. (iv) Host interaction In addition to the genes listed above, region-specific non-synonymous variants are present in several genes that are annotated as known virulence or host interaction factors.
Catalase KatA (HP0875) (Figure 6A) detoxifies H2O2 generated by host immune cells. It also binds host vitronectin, thereby protecting against complement-mediated killing 36. The preferred route for H2O2 is the channel S451-D109-H56-heme (Fig. 6A (ii)) 37. YunnanMP- differentiated P160H by the entrance S451 drastically changes local conformation and surface electric charge. Fujian-differentiated N248D with -1 change in the electric charge takes place near the dimer- dimer interface (Figure 6A (i)) likely changing their interaction. A. Catalase, KatA B. FlaA, flagellin (i) I206V C. TlpD (i) N248D (Fujian) H2O2 T364R E227R I426V A375S (Yunnan) H315 H56 D109 S451 (ii) D0 core D1 variable D4 HOCl C340 H372 H368 S Zn H2O2 H2O2 (iii) TLR5 D2 D3 W345 host glycosylation mimicry (ii) H2O2 H160P (Yunnan) H56 heme b another subunit R, L switch (chemotaxis) I426V (Fujian) A430 T364R (Fujian) pse HP0559/ 3t9o S451 D109 IN221-222 E227R (Yunnan) I206V (Yunnan) MWE_0565/ HP0875 (iv) (v) R227 E227 + 2 R227 (Yunnan) Q293 Figure 6. A) Catalase KatA (HP0875, PDB 2A9E). (i) Dimer of dimer. (ii) Channel for H2O2.Yunnan-specific P160H by its entrance S451 drastically changes local conformation and surface electric charge (mutagenesis in PyMOL). B) Flagellin, FlaA. (i) A view from the distal end of the 22-mer model of FlaA (MWE_0913) on G508A mutant of Campylobacter jejuni homolog (PDB 6x80) with 4 population-specific amino-acid changes in two interacting monomers. (ii) Monomer with 5 domains. (iii) Population-specific amino-acid changes. pse = pseudaminic acid. (iv) Surface electric charge change by E227R. (v) R227 interaction with a neighboring monomer. C) TlpD, chemotaxis receptor for HOCl. HP0559 modeled on PDB 3T9O, the regulatory CZB domain of DgcZ (E. coli). 12 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . The flagellar filament made of flagellin FlaA (HP0601) (Figure 6B, is involved in motility, cell adherence and immune modulation. We have modelled it using the similar Campylobacter jejuni homolog 38. The flagellin has rod-shaped domains forming a hydrophobic core, and the other domains decorating the surface of the filament are hypervariable. The flagellin is glycosylated by pseudaminic acid at several residues to stabilize the flagellum and to mimic host cell surface, a way for the bacterium to modulate the immune response 39, but Fujian-differentiated T364R eliminates one of these sites (Figure 6B (iii)). E227R drastically changes the surface electric charge and likely affects its interaction with a neighboring monomer (Figure 6B (iv)(v)). Another Fujian-differentiated residue 426 in the conservative core is next to residue 427, which is involved in evasion from TLR5- mediated innate immunity through subunit interaction 38.
Furthermore, residue 430 adjacent to 426 in the 3-D structure is somehow involved in switching between R and L conformations for swimming/tumbling in chemotaxis in Campylobacter 40. TlpD (HP0599, MWE_0916) (Figure 6C), is a cytosolic chemotaxis sensor required for colonization. TlpD senses HOCl, an antimicrobial produced by neutrophils during inflammation 41. HOCl oxidizes a conserved cysteine (C340) within a 3His/1Cys Zn-binding motif to inactivate chemo-transduction signalling. YunnanMP-differentiated A375S is right by this motif. Additional proteins in Table 1 are described in Supplementary Text and Supplementary figures. Discussion Analyses of H. pylori in East Asia have tended to emphasize their homogeneity and uniformly high virulence potential. A single subpopulation of the bacteria, hspEAsia, is prevalent in the region. The hspEAsia strains have been found to be invariably CagPAI positive, with the cagA gene containing the ABD EPIYA motif which is thought to promote strong binding of the protein to SHP-2 42. HspEAsia strains also characteristically have a particular variant of vacA. Our large collection of genomes of H. pylori from multiple regions in China, Japan and Korea confirm these observations. Only a small number of these isolates, of which a majority of are from Mongolia and Okinawa, belonged to other H. pylori populations. For the scope of this study, these were excluded from subsequent analyses. All but 13 of the total 381 isolates were cagA positive and 355 have the characteristic ABD EPIYA type, including 316 out of 329 hpEAsia isolates. Our results add a layer of complexity to the picture of uniformity by demonstrating that there is differentiation of H. pylori strains of the hspEAsia subpopulation between regions in East Asia. Despite a large burden of gastric disease in the region, most H. pylori infections by hspEAsia are asymptomatic, and the gastric cancer incidence varies widely across the region, especially in China. A large part of these differences might be attributable to diet and environment. However, our results imply that there are also bacterial factors differentiating these regions, which may be significant for disease development, especially because the bacteria themselves can adapt to environmental conditions 5. 13 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Geographic differentiation between populations accumulates progressively when migration rates between them are low. Further, adaptation of bacteria to differences in environmental conditions can greatly accelerate the process of differentiation in specific regions of the genome. Our results, in combination with a previous study of genetic variation within the Americas 29 suggest that there are a handful of loci that have undergone rapid differentiation in several regions, and therfore may be considered keys for host adaptation.
These include the genes frpB-4, hefC, alpB/hopB, and hofC. Our strategy to identify geographically differentiated SNPs by dividing one population (hspEAsia) into minimal subpopulations, i.e. strains with consistent population and strain labels, and comparing fixation index (Fst) site-by-site between these populations reveal numerous loci of differentiation (Suppl. table S4). Of these we discuss the 12 with the strongest evidence for being involved in local adaptation in more detail in the main text in this paper. Some of the region-specific SNPs are in genes encoding for proteins that have been implicated host interaction and virulence in the narrow sense: attack by immune system (catalase, TlpD), host adhesion (HopB/AlpB and several outer membrane proteins), and host surface mimicry (the flagellin FlaA). Several of the other genes are transporters that may have implications for antimicrobial resistance, or are involved in nutrient acquisition. These results suggest that various host-adaptive changes in many host-interaction proteins lead to population differentiation. A similar gene set was found when rapid genome changes were investigated in shorter-term, intra-body micro-evolution 43. Epidemiological and experimental evidence suggests that iron-deficiency increases H. pylori virulence and risk of gastric cancer 44. In our analyses we could see both in iron and nickel metabolism highlighted by regional changes. Apart from the above-mentioned frpB-4, genes encoding for the TonB motor proteins ExbB-2 and ExbD-2, heme transporter frpB-1 45 appear in the list of the 34 genes with Fst >0.5 and the central transcription factor ferric uptake regulator, fur had regional variants (Supplementary text). The causal mechanism underlying this association is not clear but it plausibly reflects bacterial response to nutrient limitation. Simply put, it is possible that bacteria adopt more aggressive strategies in interacting with the host and its microbiome when iron and other metals such as nickel, which is necessary for urease function, is in short supply. In other organisms, linkage means that high Fst regions often occur in large blocks, making it difficult to infer which sites are involved in local adaptation. However, H. pylori lineages recombine with each other, exchanging substantial fraction of their DNA in individual mixed infections 46. The size of replacement in one event can be as short as 40 bp47, with the result that linkage is broken down rapidly. This means that individual nucleotides can rise to high frequencies in specific populations, meaning that local adaptation can potentially occur on a very exquisite scale. Many of the highly differentiated amino-acid changes are close to critical residues of the protein and are plausible candidates to cause important functional changes, based on 3-D modelling and previous functional analyses. We have suggested possible functional 14 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . consequences but validation by targeted experiments and clinical observations is necessary. Although the functional consequences of genomic differentiation of H. pylori within different parts of the world remain to be elucidated, the presence of this differentiation already has potential clinical utility. All else being equal, individuals who are infected by H. pylori that are characteristically found in high gastric cancer incidence regions are likely to be at higher risk than those associated with lower incidence regions, firstly because the bacteria may be more virulent but secondly because infection to the bacteria might also be a marker for exposure to environmental factors that underlie the high disease risk. Acknowledgements We thank Jonas Korlach and Primo Baybayan for help in SMRT sequencing. We would like to thank and the staff of Comparative Genomics Laboratory at National Institute for Genetics, Mishima, Japan for supporting genome sequencing. We thank Dr Chao Yang, Professor Yujun Cui and Ruifu Yang for the discussions about H. pylori population genetics of H. pylori, and M. Zwama for discussion on HefC, Mizuki Ohno and Yosuke Kawai for discussion on human genetics. This work was supported by a grant from the State Key Laboratory of Infectious Disease Prevention and Control (SKLID) (2014SKLID102) of the Chinese Center for Disease Control and Prevention. Supported by National Science and Technology Major Project (2018ZX10712-001) and a joint project 'Isolation and sequence analysis of Helicobacter pylori strains collected from investigations on carriage rate '. KT was supported by Swedish Society for Medical research (SSMF). Parts of the bioinformatic analyses were performed on resources provided by Swedish National Infrastructure for Computing (SNIC) through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under projects snic2018-8-24/uppstore2017270, partially funded by the Swedish Research Council through grant agreement no. 2018-05973. This work was also supported in part by MEXT KAKENHI (19K22543, 17H04666, 26113704, 25291080, 221S0002 to IK, 18K14766 to YK) and by Shanghai Municipal Science and Technology Major Project (No. 2019SHZDZX02 to DF). ___________________________________________________________________________ Note to the cover page TEAMHp (Team for East Asian Genomics of Helicobacter pylori) represents the following people. Takahiro Bino NIBB Core Research Facilities, National Institute for Basic Biology, Okazaki, Aichi, Japan Data Analysis 15 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license .
Masaki Fukuyo Department of Molecular Oncology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan, Kazusa DNA Research Institute Chiba 292-0818, Japan Rumiko Suzuki Department of Environmental and Preventive Medicine, Oita University Faculty of Medicine Provide strains John Harting Pacific Biosciences, Menlo Park, CA 94025, USA Data Analysis Mototsugu Kato1,2 1 Division of Endoscopy, Hokkaido University Hospital, Sapporo, Hokkaido 060- 8468, Japan. 2 Department of Gastroenterology, National Hospital Organization Hakodate Hospital, Hakodate, Hokkaido, Japan. Provided strains Mutsuko Konno Department of Pediatrics, Sapporo Kosei General Hospital, Sapporo, Hokkaido, Japan Provided strains Yuji Kohara Advanced Genomics Center, National Institute of Genetics, Shizuoka 411-8540, Japan Carried out Pacbio sequencing Christine Lambert Pacific Biosciences, Menlo Park, CA 94025, USA Carried out experiments Yohei Minakuchi Comparative Genomics Laboratory, National Institute of Genetics, Shizuoka 411- 8540, Japan Carried out experiments. Shin Nishiumi Department of Gastroenterology, Graduate School of Medicine, Kobe University, Chuou-ku, Kobe, Hyogo, 650-0017, Japan. Provided strains Shuji Shigenobu (NIBB Core Research Facilities, National Institute for Basic Biology, Okazaki, Aichi, Japan) Data Analysis Noriko Takahashi Department of Computational Biology and Medical Sciences (formerly Department of 16 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . Medical Genome Sciences Graduate School of Frontier Sciences, University of Tokyo, Tokyo 108-8639, Japan, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo 108-8639, Japan, Kyorin University School of Medicine, Mitaka, Tokyo 181-8611, Japan, Atsushi Toyoda Comparative Genomics Laboratory and Advanced Genomics Center, National Institute of Genetics, Shizuoka 411-8540, Japan Carried out Pacbio sequencing Ikuo Uchiyama Laboratory of Genome Informatics, National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Aichi, Japan Data Analysis Hirokazu Yano Department of Computational Biology and Medical Sciences (formerly Department of Medical Genome Sciences), Graduate School of Frontier Sciences, University of Tokyo, Tokyo 108-8639, Japan, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo 108-8639, Japan, Graduate School of Life Sciences, Tohoku University, Sendai 980-8577, Japan Carried out experiments Masaru Yoshida Department of Gastroenterology, Graduate School of Medicine, Kobe University, Chuou-ku, Kobe, Hyogo, 650-0017, Japan. Provided strains Conflict of interest: Christine Lambert and John Harting are full-time employees at Pacific Biosciences of California, a company developing single-molecule sequencing technologies.
The other authors declare that they have no conflict of interest. 17 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . References: 1. Moodley Y, Linz B, Bond RP, et al. Age of the association between Helicobacter pylori and man. PLoS Pathog 2012;8:e1002693. Falush D, Wirth T, Linz B, et al. Traces of human migrations in Helicobacter pylori populations. Science 2003;299:1582-5. Collaborators GBDSC. The global, regional, and national burden of stomach cancer in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease study 2017. Lancet Gastroenterol Hepatol 2020;5:42-54. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. Kawai M, Furuta Y, Yahara K, et al. Evolution in an oncogenic bacterial species with extreme genome plasticity: Helicobacter pylori East Asian genomes. BMC Microbiol 2011;11:104. Furuta Y, Yahara K, Hatakeyama M, et al. Evolution of cagA Oncogene of Helicobacter pylori through Recombination. Plos One 2011;6. Wong BC, Lam SK, Wong WM, et al. Helicobacter pylori eradication to prevent gastric cancer in a high-risk region of China: a randomized controlled trial. JAMA 2004;291:187-94. Chen W, Sun K, Zheng R, et al. Cancer incidence and mortality in China, 2014. Chin J Cancer Res 2018;30:1-12. He J, Chen W. Annual Report of Cancer Registration in China: National Cancer Center, China, 2017. Jung KW, Won YJ, Kong HJ, et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2011. Cancer Res Treat 2014;46:109-23. Eom BW, Jung KW, Won YJ, et al. Trends in Gastric Cancer Incidence According to the Clinicopathological Characteristics in Korea, 1999-2014. Cancer Res Treat 2018;50:1343-1350. Bray F CM, Mery L, Piñeros M, Znaor A, Zanetti R, and Ferlay J. CI5PLUS: Cancer Incidence in Five Continents Time Trends. Volume 2019, 2017. Ganjoho.jp Graph Database. Volume 2020: Center for Cancer Control and Information Services, National Cancer Center Japan. Seemann T. snippy: fast bacterial variant calling from NGS reads. GitHub, 2015. Lawson DJ, Hellenthal G, Myers S, et al. Inference of population structure using dense haplotype data. PLoS Genet 2012;8:e1002453. Yahara K, Furuta Y, Oshima K, et al. Chromosome painting in silico in a bacterial species reveals fine population structure. Mol Biol Evol 2013;30:1454-64. Price MN, Dehal PS, Arkin AP. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 2009;26:1641-50. Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation.
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Identification and characterization of Helicobacter pylori genes essential for gastric colonization. J Exp Med 2003;197:813- 22. Quandt EM, Gollihar J, Blount ZD, et al. Fine-tuning citrate synthase flux potentiates and refines metabolic innovation in the Lenski evolution experiment. Elife 2015;4 :e09696. Richter C, Mukherjee O, Ermert D, et al. Moonlighting of Helicobacter pylori catalase protects against complement-mediated killing by utilising the host molecule vitronectin. Sci Rep 2016;6:24391. Jha V, Chelikani P, Carpena X, et al. Influence of main channel structure on H2O2 access to the heme cavity of catalase KatE of Escherichia coli. Arch Biochem Biophys 2012;526:54-9. Kreutzberger MAB, Ewing C, Poly F, et al. Atomic structure of the Campylobacter jejuni flagellar filament reveals how epsilon Proteobacteria escaped Toll-like receptor 5 surveillance. Proc Natl Acad Sci U S A 2020;117:16985-16991. 27. Maki-Yonekura S, Matsuoka R, Yamashita Y, et al. Hexameric and pentameric complexes of the ExbBD energizer in the Ton system. Elife 2018;7:e35419. Hawtin PR, Delves HT, Newell DG. The demonstration of nickel in the urease of Helicobacter pylori by atomic absorption spectroscopy. FEMS Microbiol Lett 1991;61:51-4. Thorell K, Yahara K, Berthenet E, et al. Rapid evolution of distinct Helicobacter pylori subpopulations in the Americas. PLoS Genet 2017;13:e1006546. Alm RA, Bina J, Andrews BM, et al. Comparative genomics of Helicobacter pylori: analysis of the outer membrane protein families. Infect Immun 2000;68:4155-68. Page WJ, Huyer G, Huyer M, et al. Characterization of the porins of Campylobacter jejuni and Campylobacter coli and implications for antibiotic susceptibility. Antimicrob Agents Chemother 1989;33:297-303. Bauwens E, Joosten M, Taganna J, et al. In silico proteomic and phylogenetic analysis of the outer membrane protein repertoire of gastric Helicobacter species. Sci Rep 2018;8:15453. De E, Jullien M, Labesse G, et al. MOMP (major outer membrane protein) of Campylobacter jejuni; a versatile pore-forming protein. FEBS Lett 2000;469:93-7. Kavermann H, Burns BP, Angermuller K, et al. Identification and characterization of Helicobacter pylori genes essential for gastric colonization. J Exp Med 2003;197:813- 22. Quandt EM, Gollihar J, Blount ZD, et al. Fine-tuning citrate synthase flux potentiates and refines metabolic innovation in the Lenski evolution experiment. Elife 2015;4 :e09696. Richter C, Mukherjee O, Ermert D, et al. Moonlighting of Helicobacter pylori catalase protects against complement-mediated killing by utilising the host molecule vitronectin. Sci Rep 2016;6:24391. Jha V, Chelikani P, Carpena X, et al. Influence of main channel structure on H2O2 access to the heme cavity of catalase KatE of Escherichia coli. Arch Biochem Biophys 2012;526:54-9. Kreutzberger MAB, Ewing C, Poly F, et al. Atomic structure of the Campylobacter jejuni flagellar filament reveals how epsilon Proteobacteria escaped Toll-like receptor 5 surveillance.
Proc Natl Acad Sci U S A 2020;117:16985-16991. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 19 bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. made available under a CC-BY 4.0 International license . 39. Schirm M, Soo EC, Aubry AJ, et al. Structural, genetic and functional characterization of the flagellin glycosylation process in Helicobacter pylori. Mol Microbiol 2003;48:1579-92. 40. Wang F, Burrage AM, Postel S, et al. A structural model of flagellar filament switching across multiple bacterial species. Nat Commun 2017;8:960. Perkins A, Tudorica DA, Amieva MR, et al. Helicobacter pylori senses bleach (HOCl) as a chemoattractant using a cytosolic chemoreceptor. PLoS Biol 2019;17:e3000395. Higashi H, Tsutsumi R, Fujita A, et al. Biological activity of the Helicobacter pylori virulence factor CagA is determined by variation in the tyrosine phosphorylation sites. Proc Natl Acad Sci U S A 2002;99:14428-33. Ailloud F, Didelot X, Woltemate S, et al. Within-host evolution of Helicobacter pylori shaped by niche-specific adaptation, intragastric migrations and selective sweeps. Nat Commun 2019;10:2273. Noto JM, Lee JY, Gaddy JA, et al. Regulation of Helicobacter pylori Virulence Within the Context of Iron Deficiency. J Infect Dis 2015;211:1790-4. Carrizo-Chavez MA, Cruz-Castaneda A, Olivares-Trejo Jde J. The frpB1 gene of Helicobacter pylori is regulated by iron and encodes a membrane protein capable of binding haem and haemoglobin. FEBS Lett 2012;586:875-9. Cao Q, Didelot X, Wu Z, et al. Progressive genomic convergence of two Helicobacter pylori strains during mixed infection of a patient with chronic gastritis. Gut 2015;64:554-61. Bubendorfer S, Krebes J, Yang I, et al. Genome-wide analysis of chromosomal import patterns after natural transformation of Helicobacter pylori. Nat Commun 2016;7:11995. 40. Wang F, Burrage AM, Postel S, et al. A structural model of flagellar filament switching across multiple bacterial species. Nat Commun 2017;8:960. Perkins A, Tudorica DA, Amieva MR, et al. Helicobacter pylori senses bleach (HOCl) as a chemoattractant using a cytosolic chemoreceptor. PLoS Biol 2019;17:e3000395. Higashi H, Tsutsumi R, Fujita A, et al. Biological activity of the Helicobacter pylori virulence factor CagA is determined by variation in the tyrosine phosphorylation sites. Proc Natl Acad Sci U S A 2002;99:14428-33. Ailloud F, Didelot X, Woltemate S, et al. Within-host evolution of Helicobacter pylori shaped by niche-specific adaptation, intragastric migrations and selective sweeps. Nat Commun 2019;10:2273. Noto JM, Lee JY, Gaddy JA, et al. Regulation of Helicobacter pylori Virulence Within the Context of Iron Deficiency. J Infect Dis 2015;211:1790-4. Carrizo-Chavez MA, Cruz-Castaneda A, Olivares-Trejo Jde J. The frpB1 gene of Helicobacter pylori is regulated by iron and encodes a membrane protein capable of binding haem and haemoglobin.
FEBS Lett 2012;586:875-9. Cao Q, Didelot X, Wu Z, et al. Progressive genomic convergence of two Helicobacter pylori strains during mixed infection of a patient with chronic gastritis. Gut 2015;64:554-61. Bubendorfer S, Krebes J, Yang I, et al. Genome-wide analysis of chromosomal import patterns after natural transformation of Helicobacter pylori. Nat Commun 2016;7:11995. 41. 42. 43. 44. 45. 46. 20 bioRxiv preprint doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Table 1. Genes with a SNP with Fst > 0.5 in the top 20 lists Criterion Gene Locus tag HP0607 HP1512 HP0601 Figure Category Annotation Residue function Channel entrance Ligand binding Glycosylation for host mimicry and more Channel Dimer-dimer interface 3B 4A 6B Efflux pump TonB-dependent importer Motility Inner membrane component of the multidrug HefABC efflux pump Outer membrane nickel importer Flagellin of flagella, involved in immune system evasion Fst > 0.6 + top 20 in different pairwise comparisons hefC frpB-4 flaA HP0875 6A Sensor Catalase sensing and destroying H2O2 entrance; katA HP1156 HP0913 HP0599 HP1339 Outer membrane protein Outer membrane protein Sensor TonB-dependent importer Outer membrane protein HopI Hop family adhesin HopB/AlpB/Omp21. Chemotaxis sensor sensing and destroying HOCl hopI hopB/alpB tlpD exbB-2 Active site Channel entrance 6C S3C Energizer/motor in the inner membrane driven by proton HP0486 HP1111 Outer membrane protein Energy metabolism Hof family protein implicated in adhesion and antibiotics diffusion Fst > 0.6 2 or more SNPs hofC porB Subunit interaction Subunit of pyruvate:ferredoxin oxidoreductase, part of the microaerophilic metabolic pathway leading to acetyl~CoA Citrate synthase, the first enzyme in TCA cycle incorporating acetyl~CoA Subunit interaction Oligopeptide ABC transporter, ATPase subunit HP0026 HP0250 5B 5A Energy metabolism Importer gltA oppD Cofactor binding Outer membrane protein Energy metabolism OmpA family peptidoglycan-associated lipoprotein Subunit of cytochrome c oxidase in aerobic respiration Ligand binding Channel entrance None (syn) Protein binding Protein stability in Scaffolding periplasm Ligand binding Ligand binding Ligand Channel (plug) Channel entrance Subunit interaction HP1125 HP0147 HP0899 HP0971 HP1503 HP0284 Fst > 0.5 omp18 fixP hypC hefD copA mscS-1 S4C Hydrogenase expression/formation protein 3C S2E Efflux pump Exporter Sensor Outer membrane component of the HefABC multidrug efflux pump Copper(I) exporter Mechano-sensor sensing tension in the membrane the HP1564 HP0876 HP0686 S2D S3A S3B Importer TonB-dependent importer TonB-dependent importer D-methionine ABC transporter, methionine-binding subunit metQ frpB-1 fecA-1 Outer membrane heme importer Outer membrane iron(III) dicitrate importer binding; HP1340 HP0797 HP0358 HP0034 S3C S3F TonB-dependent importer Outer membrane protein Outer membrane protein Micronutrient synthesis Inner membrane energizer/motor driven by proton exbD-2 hpaA omp panD Neuraminyllactose-binding hemagglutinin Putative outer membrane protein S4A (i) Vitamin B5 synthesis Interaction between cleaved peptides HP0029 Micronutrient synthesis Vitamin B7 synthesis bioD bioRxiv preprint doi: https://doi.org/10.1101/2021.06.05.447026 ; this version posted June 5, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . HP0281 HP1223 HP0218 S4A (iii) Micronutrient synthesis S4B S2B Active site Q-base synthesis; Q-base on tRNA affects translation accuracy tgt rhoD rkiP Detox Oncoprotein? Rhodanese detoxifying cyanide generated in microbiome Mimic of human RKIP tumor suppressor Interaction signal peptide Human binding Active site Cofactor binding Substrate Active site Substrate binding Cofactor binding with S2A Effector SLR family with repeated alpha-helix pairs protein hcpX HP0595 HP1451 HP0021 S3D Secretion Secretion Membrane lipid modifier S-S formation dsbI jag lpxE Regulator of VirB11/Cag-alpha gate of Cag secretion system S2C Lipid A 1-phosphatase to hide it from the innate immune response binding; HP0416 HP1027 S3E S4D Membrane lipid modifier Cyclopropane-fatty-acyl-phospholipid synthase for acid protection cfaS fur Regulator of Fe/Ni import, redox balance and acid response
bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The BNT162b2 mRNA vaccine induces polyfunctional T cell responses with features of longevity. Gisella Guerrera1†, Mario Picozza1†, Silvia D’Orso1, Roberta Placido1, Marta Pirronello1, Alice Verdiani1, Andrea Termine2, Carlo Fabrizio2, Flavia Giannessi1, Manolo Sambucci1, Maria Pia Balice3, Carlo Caltagirone4, Antonino Salvia5, Angelo Rossini5, Luca Battistini1, and Giovanna Borsellino1. Affiliations: 1Neuroimmunology Unit, Santa Lucia Foundation IRCCS; Rome, Italy. 2Data Science Unit, Santa Lucia Foundation IRCCS; Rome, Italy 3Clinical Microbiology Laboratory, Santa Lucia Foundation IRCCS; Rome, Italy. 4Department of Clinical and Behavioral Neurology, Santa Lucia Foundation IRCCS; Rome, Italy. 5Medical Services, Santa Lucia Foundation IRCCS; Rome, Italy. Co-corresponding authors: g.borsellino@hsantalucia.it, l.battistini@hsantalucia.it †These authors contributed equally to this work Abstract Vaccination against SARS-CoV-2 infection has shown to be effective in preventing hospitalization for severe COVID-19. However, multiple reports of break-through infections and of waning antibody titers have raised concerns on the durability of the vaccine, and current discussions on vaccination strategies are centered on evaluating the opportunity of a third dose administration. Here, we monitored T cell responses to the Spike protein of SARS-CoV-2 in 71 healthy donors vaccinated with the Pfizer–BioNTech mRNA vaccine (BNT162b2) for up to 6 months after vaccination. We find that vaccination induces the development of a sustained anti-viral memory T cell response which includes both the CD4+ and the CD8+ lymphocyte subsets. These lymphocytes display markers of polyfunctionality, are fit for interaction with cognate cells, show features of memory stemness, and survive in significant numbers the physiological contraction of the immune response. Collectively, this data shows that vaccination with BNT162b2 elicits an immunologically competent and potentially long-lived SARS-CoV-2-specific T cell population. Understanding the immune responses to BNT162b2 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. provides insights on the immunological basis of the clinical efficacy of the current vaccination campaign and may instruct future vaccination strategies. Introduction Mass-vaccination against COVID-19 has quickly shown to be effective and to confer high levels of protection against COVID-19 in real-world settings (1). However, one notion that all immunologists learned during the pandemic was that natural infection with coronaviruses induces short-lived immunity (2), with reinfections occurring frequently.
This notion was quickly revised by subsequent studies showing that T cell immunity to SARS is actually long lived (3, 4). The study of immune responses in COVID-19 patients with various degrees of disease severity have revealed that indeed infection with SARS-CoV-2 elicits a robust immune response, involving both the innate and the adaptive arms of the immune system and theoretically effective in protecting from reinfections (5, 6). However, this protection is not absolute and impeccable, and cases of reinfection do occur (7). Humoral immunity provides a shield against reinfection through the generation of neutralizing antibodies, which are easily measurable and are widely used as indicators of protective immunity (8, 9). Notably, subjects with undetectable or impaired humoral responses can nonetheless clear the infection, suggesting that antigen-specific T cells are themselves effective at containing the virus (10– 12). Evidence of T cell involvement in the immune response to SARS-CoV-2 came from reports showing that the emergence of activated T cells precedes recovery from COVID-19 (13–16), and was later confirmed in in vitro studies which characterized antigen-specific CD4+ and CD8+ lymphocytes reactive with overlapping peptide pools from the SARS-CoV-2 Spike protein (15, 17–19). These cells persist in COVID-19 convalescents (4, 20–23), and have been shown to reduce viral loads in non-human primate models of infection; crucially, they arise also following vaccination both with mRNA- and adenoviral-vaccines (24–27). It is necessary and urgent to identify the cellular immune components induced by vaccination and to measure their persistence, also in the view of reports of waning immunity over time and in recent updates in vaccination strategies which now propose administration of a third dose. Here, we show the results of a longitudinal study on T cell responses in 71 health-care workers and scientists vaccinated with the BNT162b2 vaccine following the European Medicines Agency (EMA)-approved vaccination schedule, up to 6 months after the first dose. We find robust induction of neutralizing antibodies and of Spike-specific CD4+ and CD8+ lymphocytes which persist in the periphery after the physiological contraction of the initial response. These cells are detectable in most individuals also before vaccination, denoting the presence of a pre- 2 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. existing pool of cross-reactive cells, and they are expanded significantly after the boost. We show that vaccine-induced T cells are mostly central and effector memory cells, and that they are equipped with overlapping sets of molecules which enable them to perform multiple immune functions: facilitation of B cell differentiation and antibody production, direct cytotoxic activity, and cytokine production, and that they are equally represented in both sexes.
Importantly, we show that vaccination also induces the generation of potentially long-lived memory stem cells, pilasters of durable immunity. Results Induction and persistence of neutralizing antibodies The antibody response to vaccination with BNT162b2 was measured in serum samples obtained at the day of the boost (T1), 14 days later (T2), and 6 months after the first dose (T3). As expected from previous studies, all individuals in our cohort were devoid of neutralizing antibodies (nAbs) at baseline, and significant levels of nAbs were obtained in 100% of individuals only after the second dose (Fig.1A), (T1: median 28; T2, median 1786; T3: median 517). Age and gender are key variables in immunity induced by vaccination, whose effectiveness decreases with age and is usually lower in males (28). Thus, we analyzed the differences in antibody levels in male and female donors and also correlated them with age. We find that antibody titers correlate negatively with age at all time points, confirming previous results (29, 30) (Fig. 1C). In our cohort antibody levels induced by BNT162b2 are comparable between males and females, as shown also in other studies (30)(Fig. 1B), although females seem to retain lower levels of nAbs 6 months after vaccination. Thus, this data shows that BNT162b2 aptly induces the production of nAbs which decrease over time but are however maintained at high levels for at least 6 months. Induction and durability of the Spike-specific T cell response To investigate the cellular immune response induced by vaccination, we exposed freshly obtained peripheral blood mononuclear cells (PBMC) to peptide pools spanning the entire sequence of the Spike (S) protein. Blood collection was performed at baseline (T0), on the day of the boost (day 21, T1), 14 days later (T2), and after 6 months (T3). Several effector functions of CD4+ cells consist in the upregulation of surface molecules for intercellular communication, and these may remain trapped inside the cells if the secretion inhibitors required for intracellular cytokine detection 3 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. are present during antigenic stimulation. Thus, to fully capture the T cell antigen-specific response and to maximize sensitivity, two separate assays for the detection of the expression of surface Activation-Induced Markers (AIM) and for Intracellular Cytokine Staining (ICS) were set up (Fig. S1 for gating strategy). Moreover, all assays were performed on freshly isolated PBMCs in order to avoid the inevitable cell loss during the freezing/thawing procedure, and to obtain accurate absolute cell counts. AIM+ CD4+ T cells were defined by upregulation of CD40L and CD69, while CD137 and CD69 expression identified the AIM+ CD8+ subset (Fig. 2A). After paired background subtraction from parallel unstimulated cultures, 99% of donors (66/67) had detectable numbers of AIM+ CD4+ cells at baseline (median 349 cells/ml, range 63-4639); 21 days after the first dose of vaccine these cells were identified in all donors, and at higher levels (median 2218 cells/ml, range 319-110394, p <0.0001), and further still at 14 days after the boost (median 3608 cells/ml, range 566-101864); 6 months after the first dose AIM+ CD4+ cell numbers were still increased 5-fold compared to baseline (median 1660, range 349-74859).
AIM+ CD8+ T lymphocytes were present at baseline in only 63% of the donors (42/67, median 209 cells/ml, range 18-2695), and increased following vaccination (59/71, median 900 cells/ml, range 54- 21142, p<0,0001), with further expansion after the second dose (64/69, median 1539 cells/ml, range 46-18,638), and persisted after 6 months in all donors (median 706 cell/ml, range 78- 27593) (Fig. 2B,C).The total magnitude of the T cell response (that is, including both CD4+ and CD8+ cells) increased significantly following priming (T1) and rechallenge (T2), and decreased 6 months after the first dose (T3) (Fig. 2D). Importantly, the Stimulation Index (SI, the ratio of AIM+ T cells in stimulated over unstimulated samples) of AIM+ CD4+ cells increased dramatically after the first dose, remained at high levels after boosting (Fig. 2E), and increased further after 6 months, reaching a median of 25,7. The SI of AIM+ CD8+ T cells peaked 14 days after the boost, and declined by 1/3 at the latest time-point. Moreover, the fraction of individuals showing CD4+ with SI >3 increased at all time points, denoting the establishment of an antigen-specific T cell population (Fig. 2F). The frequency of S-specific CD4+ (and not CD8+) T cells induced by vaccination correlated inversely with age only 21 days after the first dose (T1), although a tendency towards reduced numbers of activated T cells with increasing age was observed at all time points (Fig. S2A), again with no significant differences between males and females (Fig. S2B). The numbers of AIM+ cells correlated with antibody levels only after priming and not at subsequent time points (Fig. S2C), suggesting that humoral and cellular immune responses follow different kinetics. However, machine learning indicated that the number of AIM+ CD4+ 4 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. cells 21 days after priming is the best predictor of nAbs levels after 6 months, as expected from a T cell-dependent B cell response (Fig. S2D). Thus, vaccination induces clearly detectable and robust antigen-specific T cells in both sexes, arising before the development of high antibody titres, with a major expansion occurring after the first dose of vaccination followed by consolidation of the response after the boost, and persistence for up to 6 months. Cytokine production by S-specific T cells. Cytokine production was assessed by intracellular flow cytometry following stimulation o.n. with the peptide pools in the presence of monensin and brefeldin (Fig. 3A). Measurement of cytokine production showed that at baseline 62% and 50% of the tested donors showed IFNg+ CD4+ and CD8+ cells, respectively (CD4: median 90 cells/ml, range 1-1536; CD8: median 116 cells/ml, range 9-592) (Fig. 3B,C). Three weeks after the first dose, 90% of individuals showed IFNg+ CD4+ T cells (median 275 cells/ml, range 5- 5799), while CD8+IFNg+ (median 446 cell/ml, range 2-6606) were found in 77% of individuals.
Two weeks after the boost, 97% and 69% of individuals showed IFNg+ CD4+ (median 17111 cell/ml, range 200-19595) and CD8+ T cells (median 592 cells/ml,, range 1- 36917), respectively; these cells were maintained for 6 months (CD4: median 360 cell/ml, range 51-13028; CD8: median 315, range 13-4586). 53% of donors at baseline showed IL-2+ CD4+ T cells (median 13 cells/ml, range 2-171); this fraction increased to 84% after the first dose (median 139 cells/ml, range 4-2595) then reached 94% after the boost (median 1838 cells/ml, range 140-17302), and remained detectable after 6 months (median 446 cells/ml, range 20-5678). Polyfunctional IFN-g+IL-2+ CD4+ T cells were induced in 99% of the individuals only following the booster dose (median 825 cells/ml, range 43-7088), and persisted for at least 6 months after the first dose (median 169 cells/ml, range 9-1533) (Fig. 3D). Polyfunctional CD8+ T cells co-expressing IFNg+ and lysosomal associated membrane glycoprotein (LAMP-1, CD107a) increased significantly after the boost (T0: median 33 cells/ml, range 1-1528; T1: median 54 cells/ml, range 2-694; T2: median 108 cells/ml, range 11-11965; T3: median 106 cells/ml, range 1-1854) (Fig. 3D). Induction of these cytokine- secreting S-specific T cells was equivalent in both sexes at all time points (Fig. S3A). The number of TNF-a-secreting CD4+ and CD8+ cells was highest at the peak of the secondary response, 14 days after the second dose (Fig. S3B); at the same time point polyfunctional TNFa+IFNg+ cells decreased significantly, and after 6 months they were found to be at pre- vaccination levels. Further analysis of CD107a, TNFa and Granzyme B co-expression among 5 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. CD4+ and CD8+ T cells producing IFNg+ revealed changing patterns between time points (p<0.001 for all comparisons except for IFNg+ CD4+ T cells between T1 and T2, Figure 3E), with the fraction of polyfunctional CD4+ cells increasing at each time point, and a predominance of CD8+ cells with 2 functions at the latest time point, indicating a dynamic refolding of functional programs in antigen-specific T cells following boost and and contraction. Cytokine secretion was also measured, at the peak of the response (T2), in the supernatants of cultures stimulated with the peptide pools. Production of high levels of IFNg and IL-2 was confirmed, whereas IL-17 and IL-4 were barely detectable (<5 pg/ml), confirming the Th1 differentiation profile of S-specific cells (Fig. S3B). Thus, vaccination induces the emergence in both males and females of a robust CD4+ and CD8+ cytokine response by T cells already after priming, while full effector functions marked by polyfunctionality are acquired only following the boost, and then maintained for at least 6 months.
Features of Spike-specific T cells. We then characterized the antigen-specific T cells induced by vaccination through the definition of their differentiation status (Fig.4). The study of the composition of naïve, memory, and effector cell fractions within AIM+ cells in the peripheral blood shows a high frequency of cells with a naïve phenotype at baseline which drops after vaccination, matched by a striking increase in the fraction of effector and central memory cells in both CD4+ and CD8+ subsets, suggesting differentiation from a pool of S-specific cell precursors after antigen exposure and successful induction of a memory cell pool (Fig. 4A and B). The fraction of terminally differentiated CD45RA+CCR7- in both CD4+ and CD8+ subsets drastically decreases following vaccination, suggesting the establishment of a lively and non- terminal immune response. Six months after the first dose, S-specific cells which have survived the physiological contraction of the immune response are mostly central- and effector memory cells, and in the CD8+ subset these cells also include a significant fraction of terminally differentiated effectors. It should be noted that the fraction of AIM+ T cells at baseline necessarily includes also non Spike-specific CD4+ and CD8+ lymphocytes, (as suggested by the low stimulation index and by the similar distribution of the differentiation subsets in AIM+ and in total CD4+ or CD8+ T cells, respectively), and these cannot be excluded from the analysis. After priming and boosting, however, the very high stimulation indices indicate that AIM+ cells are completely represented by S-specific T lymphocytes. For this reason, we 6 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. limited further and deeper phenotypic analysis of Spike-specific cells to the time points after vaccination. Thus, although the absolute number of antigen-specific T cells does not significantly increase following the second dose, the composition of this subset differs significantly between priming and recall responses, and indicates the establishment of an efficient population of S-specific cells comprising a significant fraction of non-terminally differentiated and potentially long- lived memory cells. Effector features of Spike-Specific CD4+ and CD8+ cells. We then explored by unbiased analysis the changes in time in the expression of immunologically relevant markers occurring in antigen-specific T cells. We used FlowSOM clustering to identify 4 CD4+ T cell clusters segregated by the expression pattern of CD137, CD39, ICOS, PD-1, HLA-DR, CD25, CXCR5, CD95, CCR7, CD45RA, CD38, and CD127 and superimposed those clusters in a UMAP plot generated by embedding the same set of markers (Fig. 5A). Since Ki67, a marker of cell proliferation, was never expressed on AIM+ cells (not shown), we excluded it from analysis.
AIM+ CD4+ T cells distribute differently in the UMAP plot at the three different time points (Fig. 5B), highlighting an overall phenotypic shift. Among these cell clusters, cluster 3 and 4 result unchanged in frequency, while clusters 1 and 2 show significant changes over time (Fig. 5C). Cluster 2, which increases in frequency at each time point, is characterized by high expression of activation markers (CD25, CD38, CD39, HLA-DR, CD137) and displays features typical of T follicular helper (Tfh) cells (i.e. expression of ICOS-L, PD-1, and CXCR5) while cluster 1 is composed by cells which show a non-activated profile, and decreases with time (Fig. 5A and C). This data indicates that the antigen-specific CD4+ T cell phenotype is shaped and “perfectioned” by the second encounter with the antigen, and the acquired phenotype persists in the peripheral blood for at least 6 months. Data analysis through manual gating and measurement of single marker expression on the antigen-specific T cells, revealed the emergence and persistence in time, albeit at lower levels after 6 months, of CD4+ subsets displaying high levels of PD-1, ICOS, and CXCR5 (Fig. S4), denoting their ability to interact with B cells in lymphoid follicles. At the 6-month time point expression of activation markers such as CD25, CD39, CD38, and HLA-DR is greatly reduced, in line with what expected after the physiological contraction of the immune response. Also S-specific CD8+ lymphocytes are remodeled by vaccine doses, as shown by the distinct distribution with time along the UMAP axes (Fig. 5E). Two clusters, comprising highly (Cluster 4) and slightly less (Cluster 3) activated AIM+ CD8+ T cells, show transient expansion 7 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. after the booster dose (Fig. 5 D and F). This is in contrast to Cluster 1 (Naïve-like cells) which remains stable after a first decrease in frequency at T2, and to Cluster 2 (CCR7+ CD127+ CD45RA- central memory CD8+ T cells) which is not significantly reduced at T2 but increases in size at 6-months. Manual analysis of AIM+ CD8+ T cells confirmed the transient increase at T2 of CD38+, HLA-DR+ and CD25+ cell frequencies, whereas CD39+ and PD-1+ cells steadily decrease or increase, respectively, at T2 and T3 compared to T1 (Fig. S4). Thus, antigen-specific T cells acquire phenotypic features of activation and functional capability early after the booster, and most of these attributes are less evident and partially replaced, in the long run, by characteristics distinctive of more quiescent memory cells. Generation of TSCM cells. Among the desirable outcomes of vaccination lies the generation of a pool of stem memory cells, which can rapidly and efficiently differentiate in an army of highly effective and polyfunctional lymphocytes in case of re-encounter with their nominal antigen (31).
Stemness includes long-term persistence, a key aspect in this age of pandemics and uncertainties on the durability of the novel vaccines. Thus, we searched for these cells within the antigen-responsive CD4+ and CD8+ subsets. After the first dose, CD4+AIM+CD45RA+CD27+CCR7highCD95+ cells, representing CD4+TSCM (T Stem cell memory) cells, were detectable in 88% of individuals (Fig. S5); 2 weeks after the second dose, this fraction was still 88%; after 6 months, 91% of individuals showed these cells (Fig.6A). The number of circulating CD4+ TSCM rose from a median of 0,01 cells/ml at baseline to 14,7 cells/ml on the day of the boost, and further to 15,28 cell/ml two weeks after the second dose; after 6 months these cells were slightly increased in number (median 23,9 cells/ml). CD8+ TSCM followed similar kinetics, with 94%, 87%, and 96% of individuals showing these cells (0.05, 6, 8, and 8 cells/ml at baseline, T1, T2, and T3 respectively). To investigate the possible impact of TSCM on future immune responses, we applied a machine learning approach to test if the number of TSCM induced by vaccination significantly predicts immunological outcomes at distant time points. We find that indeed the number of TSCM induced after priming is a significant predictor of the number of both CD4+ and CD8+ activated T cells at the latest time point (Fig. 6B). These findings show that vaccination with BNT162b2 induces the emergence of a population of cells with features of longevity, which remain numerically stable in the peripheral blood for at least 6 months, and which predict the persistence of T cell responses. 8 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. DISCUSSION Mass vaccinations are underway to control the continued dissemination of SARS-CoV-2. Specific viral control is achieved through the action of effector cells of the adaptive immune system: the antibody-producing progeny of B cells, and the functionally diverse population of T cells derived from a small pool of naïve progenitors which expand and differentiate to achieve the ability to provide B cell help, to directly kill virally infected cells, and to sustain the immune response through the production of cytokines, all while maintaining a source of non-terminally differentiated but antigen-experienced cells which can rapidly expand upon antigen re-encounter. In all of this, T cells are indispensable: an optimal antibody response is the consequence of a competent underlying T cell response, and T cell responses alone can successfully clear infection with SARS-CoV-2, as shown in COVID-19 patients lacking B cells (10, 12), and in seronegative COVID-19-recovered individuals (32–34). Here, we investigate the immune response occurring after vaccination with BNT162b2 to understand how the vaccine animates T cells specific for the S-protein, in order to predict whether this response will be durable and if it is similar in individuals of both sexes and at different ages.
The timing of our glimpses into the immune system’s antigen-specific dynamics was such that we could observe the emergence and the evolution of the effector functions of vaccine-induced T cells, and then record the physiological contraction of the immune response and study the features of the surviving antigen-specific cells. The use of freshly obtained blood cells permitted the detection of fragile markers, avoided the bias introduced by freezing/thawing procedures, and provided the possibility to precisely calculate absolute cell counts, a measure routinely used to guide clinical decisions in infectious diseases, such as HIV infection (35). The simultaneous measurement of serum levels of neutralizing antibodies provided insights on the effective induction of the humoral arm of the adaptive response. NAbs were induced by vaccination in all individuals in our cohort. Although titers did decline with time, they were maintained at high levels for the entire period of our observation (6 months), in agreement with previous studies (27, 36). Importantly, the efficacy of the vaccine in inducing antibodies was equivalent in both sexes, and correlated inversely with age, as expected. We find that most individuals harbour Spike-specific T cells already at baseline, likely due to the presence of a pool of naïve progenitors and of memory clones which are cross-reactive with other coronaviruses (3, 15–17, 37, 38). These cells are highly responsive to antigen encounter, and their SI increases with time. CD8+ cells show a less vigorous response compared to the 9 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. CD4+ subset possibly due to the sub-optimal stimulation of CD8+ cells by 15-mers, as those used in our assays (39). High antibody titers induced by influenza vaccination have been shown to correlate positively with the frequency of T cells expressing follicular helper molecules, including CXCR5 and ICOS (40, 41). Relevant to infection with SARS-CoV-2, an interesting study has shown the absence of germinal centers and a block in the differentiation of Tfh cells in post-mortem tissues from COVID-19 patients (42), with loss of both transitional and follicular B cells in severe disease. Here, we find a consistent population of T cells equipped with the molecules needed for interaction with B cells, which survives the contraction of the immune response and is clearly detectable 6 months after vaccination albeit with a measurable (but not statistically significant) decrease in magnitude. The number of antigen-specific cells expressing CXCR5, crucial for positioning T cells in the germinal center within lymph nodes, was increased 5-fold at the latest time point compared to the initial measurement on the emerging population of antigen-specific cells, three weeks after the first dose.
Similarly, T cells expressing ICOS and PD-1 composed a significant fraction of the antigen-specific subset, and were numerically maintained for at least 6 months. These findings show that vaccination with BNT162b2 appropriately induces the differentiation of the T cell subset specialized in providing B cell help and thus in sustaining the generation of high-affinity antibodies in germinal centers, and that these cells persist in the periphery for at least 6 months. Importantly, AIM+ T cell numbers correlate with serum antibody levels only in the primary response, measured 3 weeks after the first dose, while subsequent measurements indicated that T cell responses and antibody levels follow different kinetics: thus, the sole measurement of nAbs does not inform on the whole immunological ensemble induced by vaccination, although high antibody levels seem to correlate with protection from infection both in animal models and in humans (43–46). Moreover, CD4+ T cells have also other abilities, such as those related to cytokine production and to direct cytotoxic function. In agreement with previous results, we find that antigen- specific CD4+ T cells induced by vaccination with BNT162b2 produce cytokines typical of the Th1 profile (IFNg, TNFa), and minimal levels of IL-4 and IL-17. In infants the presence in the peripheral blood of ³100 influenza-specific IFNg-producing cells/ml confers protection against clinical influenza (47), and a correlation between both magnitude and polyfunctionality of T cell responses and resistance to infection has been described in other vaccine settings (48– 54). In this study, we show that 6 months after vaccination with BNT162b2 over 300 CD4+ and CD8+ Spike-specific IFNg-producing T cells/ml are clearly detected in the periphery, with 10 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. diverse functionalities. CD4+ cells acquire both helper and cytotoxic functions which are particularly evident at the peak of the antigen-specific response, 14 days after the boost. At this time point we detect the highest frequencies of cells with a polyfunctional phenotype, in both CD4+ and CD8+ S-specific T cells. Interestingly, the CD4+ subset is more spared from the physiological contraction of the immune response, 6 months after receiving the first dose of BNT162b2, and it shows polyfunctional features of both cytotoxicity and ability to provide B- cell help. At the same time point, the antigen-specific CD8+ T cell subset seems to drop at lower levels, although these cells are still clearly detectable and are significantly expanded compared to the baseline. This data is consistent with studies which have investigated cellular immune responses in individuals recovering from COVID-19 (16, 20, 55–58), and with other studies on mRNA vaccination (59, 60), and suggest that vaccine-induced T cells have the prerequisites to confer protection from subsequent infections.
Moreover, the persistence of a numerically consistent pool of antigen-specific T cell, which we find to be still increased 6- fold from baseline after 6 months, may be the source for of effector cells which can promptly expand in case of antigen re-encounter (61). The finding that CD4+ and CD8+ TSCM are present throughout the 6-month period of this study suggests that immunity offered by vaccination should be long-lived, since it induces a reservoir of cells with multipotent capacity which likely are the very cells that provide long-lasting protection, and whose generation is a target of vaccination (62–64). Importantly, the number of TSCM was stable during the period of our study, and crucially those induced after priming are highly significant predictors of future T cell responses. This knowledge may inform current vaccination strategies and decisions on third dose vaccine administration, which may be spared for the fragile or immunologically impaired and re-directed to the unvaccinated, globally. This study has the inevitable limits of human studies, and was performed on circulating lymphocytes, which may be different from those who reside at mucosal barriers and which confer immediate protection against infection. Also, we did not investigate Spike-specific B lymphocytes, and dosage of antibody titers was the only read-out of successful induction of humoral immunity. Similarly, the innate arm of the immune response, which has intriguingly been shown to be activated by vaccination(65), was not included in this study; both of these elements are currently under active investigation the world over. Further time points will also be necessary to measure effective durability of anti-SARS-CoV-2 immune responses. Moreover, although donors were equally distributed for age and sex, our sample was limited in size. 11 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. This notwithstanding, some considerations may be made. On the whole, the results of this study can be visualized as the dynamic and integrated emergence of a theoretically effective Spike- specific adaptive immune response, characterized by a T cell response which precedes in time the development of high levels of anti-Spike neutralizing antibodies (Fig.7). T cells induced after the first encounter with the Spike protein are mostly effector cells, which secrete intermediate levels of cytokines, express the highest levels of Granzyme B, have not acquired polyfunctionality, and a fraction is also competent for the interaction with B cells; notably, also cells with features of stemness and longevity appear. After the boost, the peak of the response shows a fully activated, cytotoxically empowered, multifunctional, and B cell “friendly” T cell population, and this also corresponds to the highest levels of neutralizing antibodies in the serum.
What remains after 6 months is a population of T cells with features of polyfunctionality and ability to provide B cell help; at this time point, Spike-specific T cells which have survived the immunological contraction are highly specific and prone to give rise to effective and rapid antiviral responses, both by sustaining the production of neutralizing antibodies and by exerting direct cytotoxicity towards already infected cells. Concomitantly, the pool of TSCM is stably maintained. In our cohort we did not find differences between males and females in any of the investigated immunological measurements. This model provides the immunological basis of the current clinical data showing the effectiveness of the vaccine in preventing severe disease, of the low frequency of breakthrough infections, and of the reduced time-window of contagiousness of re-infected individuals, all signs of effective immunity. Previous literature on T cell responses following vaccination shows similar immunological patterns in previously validated and approved anti-viral vaccines with outcomes of pluri-decennial immunity. This also suggests that a third booster dose may not be needed in most individuals, since over 90% of vaccinees develop T cells with features of longevity and show high numbers of circulating and appropriately modeled antigen-specific memory cells, ready to effectively and rapidly engage in a possible re-encounter with the virus. Immunologically fragile individuals, however, or those who are unavoidably exposed to high titers of virus may be better protected by a third dose of vaccination which has been shown to increase antibody levels, thus providing an immediate albeit temporary shield against viral entry in the host cell. In an equitable world, and based on the current data on vaccine effectiveness in preventing severe disease, after having secured the fragile from infection the absolute precedence should be given to unvaccinated individuals globally, in the unified endeavor to curb viral circulation and to prevent disease. 12 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. MATERIALS AND METHODS Study Design This work started to prospectively define cellular immune responses against the SARS-CoV-2 Spike-protein induced by mRNA vaccine administration. To this aim, we enrolled 71 individuals from the sanitary personnel and from scientists operating at the Santa Lucia Foundation which were scheduled for vaccination with Pfizer-BioNTech BNT162b2 between 12 January and 2 February 2021 (Table S1). All donors signed informed consent forms approved by the Ethical Committee of the Santa Lucia Foundation. Venous blood was obtained immediately before the first dose (T0), 21 days thereafter, at the time of boosting (T1), and two weeks after the second dose (T2), and 6 months after the first dose (T3).
To avoid gender and age biases, an equal number of female and male volunteers, as well as an equal number of subjects 22-45 and 45-66 years old, was included. Not all subjects were analyzed at each time point due to precautionary quarantine of some individuals during the study. All data is presented in table 3. Evaluation of anti SARS-CoV-2 Antibodies The measurement of anti SARS-CoV-2 neutralizing Abs was performed by electrochemiluminescence sandwich immunoassay (ECLIA) through Roche Elecsys Anti-SARS-CoV-2 S (Roche diagnostics, Switzerland). The neutralizing Ab were measured on a Cobas 601 modular analyzer (Roche diagnostics, Switzerland), using a cut-off of 0.8 U/ml to determine Ab levels. In particular, Elecsys Anti- SARS-CoV-2 S U/mL measurements are equivalent to WHO International Standard Binding Arbitrary Units per mL (BAU/mL), according to which higher values than 0.8 BAU/mL are considered positive. AIM assay In vitro stimulation of freshly obtained PBMC was performed as described (66). In brief, 200 ml of cell suspensions (10 x 106 cells/ml) were seeded in U-bottom 96-well plates at a density of (0,2 ml/well) and stimulated for 18 hours with or without PepTivator SARS- CoV-2 protein S, S1 and S+ peptide pools (1 mg/ml each, Miltenyi Biotec). Purified aCD40 (0,5 μg/µl, Miltenyi Biotech) was added at culture start to enhance endpoint CD40L staining by inhibiting its recycling. Supernatants and cells from these culture wells were collected for cytokine measurement and flow cytometry, respectively. Intracellular Cytokine Staining PBMC were incubated with the addition of BV421- conjugated antiCD107a (1/200 dilution, BD Biosciences), Monensin and Brefeldin A (5μM and 10 μg/ml, respectively, both from Sigma-Aldrich) after the first hour of incubation to allow 13 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. accumulation of cytokines into the cytoplasm and avoid endo-lysosome acidification which can quench fluorescence from the aCD107a reinternalized during degranulation. At the end of the culture, cells were harvested and directly stained for flow cytometry. Flow cytometry staining and acquisition Post-culture cells were pelleted in V-bottom 96- well plates and resuspended in 30 μl of antibodies at pre-optimized concentrations and diluted in Brilliant Stain Buffer (BD Biosciences), then incubated for 15’ at RT. After a washing step, cell pellets were fixed either in FoxP3 fixation/permeabilization Buffer (ThermoFisher) for 20’ at RT (AIM Assay) or in Formaldehyde 4% in PBS (ICS Assay). ICS was performed by incubating cells in 30 μl of antibodies against cytokines and Granzyme B diluted in a Saponin (Sigma-Aldrich) 0.5% W/V solution. The complete list of antibodies used for surface staining and ICS is shown in Table S2. Samples were acquired on a fully equipped Cytoflex LX within 6 hours from staining and fixation.
Quality Control beads (Beckman Coulter) were used daily to check and standardize instrument performances. Data was analyzed with FlowJo v. 10.7 Cytokine measurements IL4, IL17, TNFa and IFNg were measured in frozen culture supernatants from the AIM assays described above by a bead-based sandwich ELISA (MACSPlex Cytokine Kit, Miltenyi Biotech) according to manufacturer instructions. Statistical analysis Statistical analysis was performed with GraphPad Prism 9. Details of the statistical tests applied for each experiment are illustrated in the respective figure legends. 14 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Supplementary Materials Fig. S1 Identification of AIM+ and IFNg+ T cell subpopulations by flow cytometry. Fig. S2 Correlation of T cell responses with age and sex. Fig. S3 Cytokine production by Spike-specific T cells. Fig. S4 Phenotype of AIM+ CD4+ and CD8+ AIM+ T cells Fig. S5 Vaccination with BNT162b2 induces T cells with features of TSCM. Table S1 Donors Table S2 Flow Cytometry Reagents Acknowledgments: We thank the volunteers for donating their blood and time, and the nurses for their assistance. We are grateful to Daniela F. Angelini for critically reading the manuscript. Funding: This work was partially supported by the Italian Ministry of Health to L.B. (COVID-2020-12371735). Author contributions: GB, LB, and AR conceptualized the study. AR, AS and CC performed vaccination supervision and donor enrollment. GG and MP set up and supervised all experimental procedures. GG, RP, SD, AV, MPirr, MS, FG performed cell stimulations, stainings, flow cytometry experiments, and cytokine measurements. MPB performed antibody dosage. GB prepared the dataset for analysis. GB and MP performed descriptive statistics. AT and CF did the statistical analysis. Funding acquisition: LB. Writing – original draft: GB. Writing – review & editing: GB, MP, LB, with input from all authors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data is included in Table S3. 15 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. REFERENCES 1. N. Dagan, N. Barda, E. Kepten, O. Miron, S. Perchik, M. A. Katz, M. A. Hernán, M. Lipsitch, B. Reis, R. D. Balicer, BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Mass Vaccination Setting, New Engl J Med (2021), doi:10.1056/nejmoa2101765. 2. A. W. D. Edridge, J. Kaczorowska, A. C. R. Hoste, M. Bakker, M. Klein, K. Loens, M. F. Jebbink, A. Matser, C. M. Kinsella, P. Rueda, M. Ieven, H. Goossens, M. Prins, P. Sastre, M. Deijs, L. van der Hoek, Seasonal coronavirus protective immunity is short-lasting, Nat Med 26, 1691–1693 (2020).
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63. P. C. del Amo, J. L. Beneytez, L. Boelen, R. Ahmed, K. L. Miners, Y. Zhang, L. Roger, R. E. Jones, S. A. F. Marraco, D. E. Speiser, D. M. Baird, D. A. Price, K. Ladell, D. Macallan, B. Asquith, Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness, Plos Biol 16, e2005523 (2018). 24 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 64. R. S. Akondy, M. Fitch, S. Edupuganti, S. Yang, H. T. Kissick, K. W. Li, B. A. Youngblood, H. A. Abdelsamed, D. J. McGuire, K. W. Cohen, G. Alexe, S. Nagar, M. M. McCausland, S. Gupta, P. Tata, W. N. Haining, M. J. McElrath, D. Zhang, B. Hu, W. J. Greenleaf, J. J. Goronzy, M. J. Mulligan, M. Hellerstein, R. Ahmed, Origin and differentiation of human memory CD8 T cells after vaccination, Nature 552, 362–367 (2017). 65. P. S. Arunachalam, M. K. D. Scott, T. Hagan, C. Li, Y. Feng, F. Wimmers, L. Grigoryan, M. Trisal, V. V. Edara, L. Lai, S. E. Chang, A. Feng, S. Dhingra, M. Shah, A. S. Lee, S. Chinthrajah, S. B. Sindher, V. Mallajosyula, F. Gao, N. Sigal, S. Kowli, S. Gupta, K. Pellegrini, G. Tharp, S. Maysel-Auslender, S. Hamilton, H. Aoued, K. Hrusovsky, M. Roskey, S. E. Bosinger, H. T. Maecker, S. D. Boyd, M. M. Davis, P. J. Utz, M. S. Suthar, P. Khatri, K. C. Nadeau, B. Pulendran, Systems vaccinology of the BNT162b2 mRNA vaccine in humans, Nature 596, 410–416 (2021). 66. C. Strafella, V. Caputo, G. Guerrera, A. Termine, C. Fabrizio, R. Cascella, M. Picozza, C. Caltagirone, A. Rossini, M. P. Balice, A. Salvia, L. Battistini, G. Borsellino, E. Giardina, Case Report: Sars-CoV-2 Infection in a Vaccinated Individual: Evaluation of the Immunological Profile and Virus Transmission Risk, Front Immunol 12, 708820 (2021). 25 bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Anticorpi T0 T1 T2 T3 A ✱✱✱✱ B ✱✱✱✱ Anticorpi F/M ✱✱✱✱ ✱✱✱✱ ns ns ns 104 104 G G g g I g I n g n z z a r a t u r t e u N e n U U A A i i i l i l 102 100 G G g g I I g g n n i i z z i i l l a a r r t t u u e e N n U U A A 102 100 10-2 T0 T1 T2 T3 F M F M F M T1 T2 T3 C T1 T2 T3 * * * G g I g n i z i l G g I g n i z i l G g I g n i z i l a r t u e n U A a r t u e n U A a r t u e n U A Fig. 1 Antibody response following vaccination with BNT162b2. A) Concentration of neutralizing anti-Spike IgG at baseline (T0), 21 days after the first dose (T1), 14 days after the second dose (T2), and 6 months after the first dose (T3). p values were determined using the Friedman test with Dunn correction for multiple comparisons; p < 0.001. *** p < 0.0001; no simbols: not significant. B) antibody levels at the different time points in females (F) and males (M).
Statistical analysis between time points was performed using Kruskall-Wallis test. ns= not significant C) Spearman’s rank correlation test was applied to test for correlation between AU neutralizing IgG and age at each time point (T). Significance levels, Spearman’s rank correlation coefficient (ρ) and Confidence Intervals for each plot are reported in figure (* = p < 0.05; = p < 0.01; * = p < 0.001; **** = p < 0.0001). bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A B C T0 T1 T2 T3 AIM+ CD4 CD4 att senza zeri ✱✱✱✱ AIM+ CD8 CD8 att senza zeri 100 ✱✱✱✱ CD4 ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ s l l e c 80 CD8 9 6 D C CD40L CD137 m / s l l e c 4 D C + M A I f o # 105 103 101 T0 T1 T2 T3 m / s l l e c 8 D C + M A I f o # 105 103 101 ✱✱✱✱ T0 T1 T2 ✱ T3 T + M A h t i I w s l a u d i v i d n f o % 60 40 20 0 CD4 CD8 D l m / s l l 35000 T0 T1 T2 T3 e c + M A I 8 D C d n a 4 D C f o # 0 CD4 att SI T3 CD8 att SI senza zeri CD4 CD8 E ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ F I S + M A 4 D C I 102 100 ✱✱✱✱ ✱✱✱ ✱✱✱✱ I S + M A 8 D C I 102 101 100 ✱✱✱✱ 3 > I S + M A h t i I w s l a u d i v i d n 100 80 60 40 20 10-2 10-1 f o % 0 T0 T1 T2 T3 CD4 T0 T2 T1 CD8 T3 CD4 CD8 Fig.2 Spike-specific T cell responses induced by vaccination with BNTb16b2. A) Representative flow cytometry plots gated on CD4+ or CD8+ T cells showing upregulation of activation markers (CD69 and CD40L for CD4 cells and CD69 and CD137 for CD8 cells) following o.n. stimulation with a pool of overlapping peptides covering the wt Spike protein at baseline (T0), 21 days after the first dose (T1), 14 days after the second dose (T2), and 6 months after initial vaccination (T3). Numbers in gates represent percentages of positive cells. B) Longitudinal analysis of spike-specific CD4+ and CD8+ absolute cell counts, following background subtraction, in paired samples. Time points were compared by non parametric Kruskall Wallis repeated measures Friedman test; lines represent median with interquartile range. p < 0.05; p < 0.01; p < 0.001; *p < 0.0001; no symbol, not significant. C) Fraction of individuals showing spike-specific AIM+ CD4+ and CD8+ cells at each time point. D) Magnitude of T cell responses. AIM+ CD4+ and CD8+ absolute cell counts were aggregated for each donor and displayed in the bar charts at the different time points. E) Stimulation indeces (ratio of stimulated and paired unstimulated samples) of CD4 and CD8 cells in the different time points; time points were compared by non parametric Kruskall-Wallis test; bars represent median with interquartile range. p < 0.05; p < 0.01; * p < 0.001; ****p < 0.0001; no symbol, not significant. F) Fraction of individuals showing S.I. >3 in CD4 and CD8 cells at the different time points. G) bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A B CD4 IFNg+ ✱✱✱ CD8 IFNg+ CD8 IFNg+ T3 solo pos C T0 T1 T2 T3 ✱✱✱✱ ✱✱✱✱ ✱ ✱✱ 100 ✱✱✱✱ s l l CD4 CD8 g N F I IL2 l m / s l l e c + γ N F I 4 D C # 104 102 l m / s l l e c + γ N F I 8 D C f o # 104 102 ✱ e c T + g N F I h t i w s l a u d i v i d n i 80 60 40 20 CD107a 100 T0 T1 T2 T3 100 T0 T1 T2 T3 f o % 0 CD4 CD8 D CD4 IL-2 T3 solo pos kruskall ✱✱✱✱ 106 ✱✱✱✱ m / s ✱✱ ✱✱✱✱ l l e c + 2 L 104 4 D C o # 102 m / s l l e c + 2 L I + γ N F + 4 D C I f o # CD4 IFNg+IL-2+ T3 solo pos ✱✱✱✱ 106 ✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ 104 102 CD8 CD107 IFNg counts solo pos ✱ ✱✱✱✱ m / s ✱✱ l l e c + γ N F 104 I / a 7 0 1 D C 8 D C 102 f o # E CD4 Gated on CD8+ IFNg+ IFNg+ CD8 Gated on CD8+ IFNg+ IFNg+ T1 ** T2 ** T3 Number of Functions 4 3 2 1(IFNg) 100 100 100 T0 T1 T2 T3 T0 T1 T2 T3 T0 T1 T2 T3 Fig. 3 Spike-specific T cell responses are characterized by cytokine production and by markers of cytotoxicity. A) Representative flow cytometry plots gated on CD4+ or CD8+ T cells showing production of IFNg and IL2 by CD4+ cells (top) and both IFNg production and upregulation of CD107a (LAMP-1) by CD8 cells (bottom) following stimulation with a pool of overlapping peptides covering the wt Spike protein, at baseline (T0), 21 days after the first dose (T1), 14 days after the second dose (T2), and 6 months after initial vaccination (T3). Numbers in gates indicate percentages of positive cells. B) Longitudinal analysis of absolute cell counts of spike-specific IFNg-producing CD4+ and CD8+, following unstimulated control background subtraction, in paired samples. Time points were compared by non parametric repeated measures Friedman test; lines represent median with interquartile range. p < 0.05; p < 0.01; p < 0.001; p < 0.0001; no symbol, not significant. C) Fraction of individuals showing spike-specific IFNg+ CD4+ and CD8+ cells at each time point. D) Longitudinal analysis of Spike-specific CD4+ cells producing IL2 or both IL2 and IFNg (left and center panels) and of CD8+ cells expressing both CD107a and IFNg (left panel). p values were determined as in Fig 3B. E) Coexpression of functional markers (CD107a, Granzyme B and TNFa) in IFNg-producing S- specific CD4+ and CD8+ T cells. The percentage of T cells positive for the specified number of functions is indicated by the pie slices for each timepoint, with functions=0 indicating the fraction of cells that produce only **: p < 0.001 by a partial permutation test (10000 iterations, Monte Carlo IFNg (gating parameter). simulation) on distributions into combinatorial gates. bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A Naive CD4 att naive T3 ✱✱✱✱ ✱✱✱✱ CM CD4 att CM T3 ✱✱✱✱ ✱✱ EM CD4 att EM T3 ✱✱✱ ✱✱✱✱ EMRA CD4 EMRA T3 B 100% AIM+ 100% Total Naive 80 ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ 80 ✱✱✱✱ ✱ ✱✱✱ 100 ✱✱✱✱ ✱✱ 100 50 ✱✱ ✱✱✱✱ ✱✱ 75% 75% EM CM CD4 4 D C + M A I 60 40 4 D C + M A I 60 40 4 D C + M A I 80 60 4 D C + M A I 15 10 50% 50% EMRA f o % f o % f o % 40 f o % 25% 25% 20 20 20 5 0 0 0 0 0% 0% T0 T1 T2 T3 T0 T1 T2 T3 T0 T1 T2 T3 T0 T1 T2 T3 T0 T1 T2 T3 T0 T1 T2 T3 CD8 att EM T3 CD8 att EMRA T3 ✱✱✱ ✱✱✱✱ CD8 att naive T3 ✱✱✱ ✱✱✱ 100% 100% 80 ✱✱✱✱ ✱✱✱✱ 40 CD8 att CM T3 ✱✱✱✱ 100 ✱✱✱✱ 100 ✱✱✱✱ ✱✱✱✱ 75% 75% ✱✱✱✱ ✱ 80 CD8 8 D C + M A I o % 60 40 20 8 D C + M A I f o % 30 20 10 ✱✱✱✱ ✱✱✱✱ ✱✱✱ 8 D C + M A I f o % 50 8 D C + M A I f o % 60 40 50% 25% 50% 25% 20 0 T0 T1 T2 T3 0 T0 T1 T2 T3 0 T0 T1 T2 T3 0 T0 T1 T2 T3 0% T0 T1 T2 T3 0% T0 T1 T2 T3 Fig.4 Differentiation status of Spike-specific CD4+ and CD8+ T cells.
A) Frequency of naïve, central memory (CM), effector memory (EM) and CD45RA+ effector memory (EMRA) within AIM+ CD4+ (top panels ) and CD8+ (bottom panels), at baseline (T0), after the first dose (T1), 14 days after the second dose (T2), and 6 months after initial vaccination (T3). Time points were compared by non parametric repeated measures Friedman test; lines represent median with interquartile range. p < 0.05; p < 0.01; p < 0.001; *p < 0.0001; no symbol, not significant. B) Fraction of AIM+ or total CD4+ (top panels) and CD8+ (bottom panels) that belong to the indicated subsets at each time point. bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A Y P A M U UMAP X Cluster # 1 23 4 Cluster# 4 3 2 1 B T1 T2 C 100 s l l e c T 4 D C + M A n h t i I i 50 * w Y P A M U T3 r e t s u C l f o % 0 T1 T2 T3 1 2 3 UMAP X Scaled marker intensity D Y P A M U UMAP X Cluster# 3 4 1 2 Cluster# 4 3 2 1 E T1 T2 F s l l e c T 8 D C + M A n h t i I i 100 50 * * w T3 r e t s u C l Y P A M U f o % 0 1 2 3 T1 T2 T3 UMAP X Scaled marker intensity Fig. 5 Phenotype shifts in AIM+ T cells over time. A) and D), top panels. UMAP embedding and FlowSOM clustering based on the expression of the indicated markers on AIM+ CD4 (A) and CD8 T cells (D). The cell clusters identified by FlowSOM are superimposed on the UMAP plots and manually contoured to highlight cluster boundaries. A and D) Bottom panels. Heatmaps with two-way hyerachical clustering of the scaled and centred median fluorescence intensity (MFI) values for the indicated markers expressed by the AIM+ CD4+ (A) and CD8+ (D) T cell clusters. B and E) UMAP plots with AIM+ CD4+ (B) and CD8+ (E) T cells selected from each time point. C and F) Bar plots showing relative frequency of cell clusters at indicated time points among AIM+ CD4+ (C) and CD8+ (F) T cells. Statistical significance was inferred by ANOVA (non parametric Friedman test) followed by a post hoc two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. p < 0.05; p < 0.01; p < 0.001. bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A CD4 TSCM complete senza zeri QUESTE CD8 TSCM complete senza zeri B ** ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ 103 l 103 m M C S T 4 D C + M A # / I 101 10-1 m M C S T 8 D C + M A # / I 101 10-1 10-3 10-3 T0 T1 T2 T3 T0 T1 T2 T3 Fig. 6 TSCM cells are induced after priming and remain in the periphery for at least 6 months. A) Absolute cell counts of CCR7+CD45RA+CD27+CD95+ AIM+ CD4 (left) and CD8 (right) cells at the different time points. Timepoints were compared by non parametric Kruskall- Wallis test; lines represent median with interquartile range.
**p < 0.0001; no symbol, not significant. B) The relevance of T1 CD4 TSCM cells/ml in predicting T3 AIM+ CD4 (top) and CD8 (bottom) cells/ml was tested with two General Linear Models with stepwise selection aiming to optimize Akaike Information Criterion (AIC) (Bozdogan, 1987). Model’s R2 were 0.21 and 0.16 for AIM+ CD4 and CD8 cells respectively. The number of CD4 TSCM in T1 cells/ml was deemed as significant in predicting both CD4+ and CD8+ AIM+ cell numbers in T3 (*p < 0.0001; p < 0.05). Lines represent linear regression. bioRxiv preprint doi: https://doi.org/10.1101/2021.09.27.462006 ; this version posted September 28, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 6000 5000 l m / s l l 4000 e c + M A # I 3000 2000 1000 CD4+ CD8+ CD4+/CD8+ 0 20 40 60 80 100 120 140 160 180 200 Days T0 T1 T2 T3 Fig.7 T cell responses to vaccination with BNTb16b2. T cell marker measurements from both CD4 and CD8 AIM+ cells are normalized across the 3 time points, and the relative positivity for each marker is displayed on the radar plots. Measurements from CD4+ T cells are shown in red, those from CD8+ cells are blue, and cumulative measurements from both subsets are purple. The resulting plots illustrate the main features of T cells responding to a pool of peptides derived from the Spike protein of SARS-CoV-2. Dashed circles indicate neutralizing anti-Spike antibody levels. Histograms represent CD4 (yellow) and CD8 (blue) cell counts along the timeline. Siringes indicate the time point of vaccine administration, and tubes correspond to the day of blood sampling. TSCM: T memory stem cells; CM: central memory; EM: effector memory; EMRA: CD45RA+ effector memory; Cyto+: aggregation of absolute numbers of CD4 and CD8 cell producing at least one cytokine among IFNg, IL2, and TNF-a; IFNg MFI: mean fluorescence intensity of the IFNg signal in IFNg+ CD8 (blue) or CD4 (red) cells.
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 1 Pseudomonas putida group species serve as reservoirs of conjugative plasmids disseminating 2 Tn402-like class 1 integrons carrying blaVIM-2 metallo-β-lactamase genes 3 4 Marco A. Brovedan,a Patricia M. Marchiaro,a María S. Díaz,a Diego Faccone,b Alejandra 5 Corso,b Fernando Pasteran,b Alejandro M. Viale,a# Adriana S. Limansky a# 6 7 aInstituto de Biología Molecular y Celular de Rosario (IBR, CONICET), Facultad de Ciencias 8 Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Rosario, Argentina 9 bServicio de Antimicrobianos, Instituto Nacional de Enfermedades Infecciosas-ANLIS Dr. 10 Carlos G. Malbrán, Ciudad Autónoma de Buenos Aires, Argentina 11 12 #Corresponding authors. Alejandro M. Viale and Adriana S. Limansky. viale@ibr- 13 conicet.gov.ar; limansky@ibr-conicet.gov.ar 14 15 Running Head: VIM-2-producing Pseudomonas putida group species 16 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 17 ABSTRACT 18 The Pseudomonas putida group (P. putida G) is composed of at least 21 species 19 associated to a wide range of environments, including the clinical setting. Here, we 20 characterized 13 carbapenem-resistant P. putida G clinical isolates carrying blaVIM-2 from 21 different hospitals of Argentina. Multilocus sequencing (MLSA) and phylogenetic analyses 22 based on the 16S rDNA, gyrB and rpoD sequences comparison allowed us to assign them to 7 23 well-differentiated species. Sequencing analysis revealed that blaVIM-2 genes were carried in 24 these isolates by three different class 1 integrons (In41, In899 and In528) embedded into 25 Tn402-like transposons. Those harboring In41 and In899 were designated Tn6335 and 26 Tn6336, respectively, with the former found among 10 isolates. Both encompassed complete 27 transposition modules and inverted repeats boundaries characteristic of the Tn5053/Tn402 28 family, whereas the third, bearing In528, exhibited a defective tni module. Tn6335 and 29 Tn6336 were located in conjugative pLD209-type plasmids in P. asiatica, P. juntendi, P. 30 putida G/II, and P. putida G/V isolates, and could be mobilized to Escherichia coli and P. 31 aeruginosa indicating a relevant mechanism of blaVIM-2 dissemination. In other P. asiatica 32 and P. putida G/II isolates, Tn6335 was found inserted into the Tn21 subgroup transposons- 33 res region, indicating capability for intragenomic mobilization and further dissemination 34 associated to Tn3 family transposons.
The Tn402-like defective element was also found 35 inserted into the res region of another Tn3 family transposon in a P. monteilii isolate, but in 36 an atypical orientation. Overall findings shed light on the mechanisms by which resistance 37 genes move through environmental and opportunist Pseudomonas species. 38 39 Keywords: Pseudomonas putida group, carbapenem resistance, Tn402-like class 1 integrons, 40 VIM-2 metallo-β-lactamase, conjugative pLD209-type resistance plasmids. 41 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 42 INTRODUCTION 43 The members of the genus Pseudomonas are ubiquitous in nature, and thrive in very 44 different ecological niches including soils, water, sediments, air, and human environments (1, 45 2, 3, 4, 5). Pseudomonas members are endowed with a wide metabolic versatility and a broad 46 potential for adaptation to challenging environmental conditions. The genus includes 47 pathogenic species such as P. aeruginosa, an important cause of healthcare associated 48 infections especially affecting immunocompromised patients (6). One main cause of the 49 success of P. aeruginosa in the nosocomial environment is represented by its ability to resist 50 the most classes of antimicrobial agents of clinical use (multidrug resistance, MDR), a 51 situation that nowadays includes last-resource therapeutic options such as the carbapenems. 52 Horizontal gene transfer (HGT) of genetic platforms carrying resistance genes from other 53 bacteria inhabiting the same ecological niche has certainly impacted the P. aeruginosa ability 54 to evolve MDR and to persist in human-associated environments (6). 55 Different phenotypic and chemotaxonomic features have been extensively used in 56 Pseudomonas classification, but much more reliable approaches are represented by genomic- 57 based procedures (1, 2, 3, 4; 5). In this context, while 16S rDNA sequence comparisons have 58 been pivotal to delineate the limits of the Pseudomonas genus, the discriminatory ability of 59 this approach at the intrageneric level is generally low (3). A more accurate definition at the 60 species level requires other approaches such as multilocus sequence analysis (MLSA) using a 61 number of selected core genes that include, besides 16S rDNA, other housekeeping genes 62 such as gyrB, rpoB and/or rpoD (1, 2, 3, 4, 5). This is the case of the P. putida group (P. 63 putida G), which is composed of at least 21 assigned species which share with P. aeruginosa 64 a wide range of environmental niches including soils, freshwater, and animals (1, 2, 3, 4, 5, 7, 65 8, 9; 10). Among this group, P. putida, P. monteilii, P. fulva, P. mosselii, and newly proposed 66 species such as P. asiatica and P. juntendi have been recently associated to infections 3 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 67 affecting human hosts (4, 5, 11, 12, 13, 14). Although most P. putida G isolates of human 68 origin have generally exhibited susceptibility to most clinically-employed antimicrobial 69 drugs, an emerging resistance to carbapenems among them has more recently been reported. 70 This, in turn, has been accompanied by the detection of metallo--lactamase (ML) genes of 71 the VIM, IMP, DIM, or NDM families, pointing to P. putida G members as possibly serving 72 as active reservoirs of such resistance genes (13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25). 73 The potential dissemination of these genes to co-existing human pathogens including P. 74 aeruginosa and members of the Enterobacteriaceae family poses a serious challenge to 75 successful antimicrobial therapy (6, 13, 17, 26). 76 Among MβL genes, blaVIM-2 is one of the most widely found among clinical strains of 77 P. aeruginosa worldwide (26, 27, 28). In MDR P. aeruginosa strains the blaVIM-2 gene is 78 usually carried by “mobile” class 1 Tn402-like integron, which are members of the 79 Tn5053/Tn402 family (29, 30, 31, 32, 33). The members of this transposon family are known 80 by characteristic 25-bp initial and terminal inverted repeats (IRi and IRt, respectively) 81 boundaries, a tni module composed of tniA, tniB, tniQ, and tniC (also designated tniR) genes 82 responsible for replicative transposition, and to generate a 5-bp direct repeat (DR) at the site 83 of insertion. Moreover, they show a notable selectivity for recombination (res) regions located 84 upstream of tnpR genes of Tn3 family members such as Tn21, or to the equivalent regions 85 associated to segregational mechanisms of particular plasmids (32, 33, 34, 35, 36, 37). In P. 86 aeruginosa, blaVIM-2-containing Tn402 transposons are located in the chromosome or, more 87 worryingly, associated to conjugative plasmids which may enormously facilitate the spread of 88 carbapenem resistance (6, 13, 18, 31). In contrast to the case of P. aeruginosa, however, 89 fewer data exist at present on the genetic platforms carrying blaVIM-2 genes among other 90 Pseudomonas species sharing similar niches, including P. putida G. A detailed 91 characterization of these platforms could then provide important insights into the role of P. 4 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 92 putida G members as reservoirs of blaVIM-2 genes, and on the mechanisms of spreading of 93 carbapenem and other resistance genes among clinically relevant bacterial species.
94 We have recently characterized by complete sequencing a self-transferable plasmid, 95 pLD209, housed by the carbapenem-resistant P. putida G clinical strain LD209 (13, 17). 96 pLD209 carries a Tn402 integron/transposon possessing blaVIM-2 and aacA4 gene cassettes 97 (13, 17). In this work, we characterized different genetic platforms carrying blaVIM-2 genes 98 present in a collection of carbapenem-resistant P. putida G clinical strains isolated in hospitals 99 of two major cities of Argentina. The observations reported here led us to propose intra- and 100 inter-genomic mechanisms of blaVIM-2 dissemination among environmental Pseudomonas and 101 Gram-negative pathogens co-existing in the clinical setting. 102 103 RESULTS 104 Bacterial isolates 105 A total of 13 carbapenem-resistant clinical isolates from hospitals of the Buenos Aires 106 City and Rosario City areas of Argentina, identified phenotypically as belonging to the P. 107 putida group by the VITEK 2C System, were included in this study (Table 1 and Table S1). 108 All of the P. putida G isolates analyzed here showed clinical resistance to imipenem and 109 meropenem, and to other -lactams such as ceftazidime and piperacillin-tazobactam. With the 110 exception of BA9115, all other isolates showed resistance to gentamicin. Ten isolates were 111 also resistant to ciprofloxacin (Table S1). Concerning carbapenem resistance, an EDTA- 112 imipenem microbiological assay in combination with an EDTA disk synergy test (38) 113 revealed the presence of MβL activity in all 13 isolates. The searching of different MβL genes 114 by PCR employing specific primers for blaIMP, blaVIM, blaSPM and blaNDM genes (Table S2), 115 followed by sequencing analysis of the obtained amplicons, found only blaVIM-2 in all 13 116 isolates. 5 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 117 118 Assignment of the analyzed isolates to the species level within the P. putida G 119 A more precise assignment of the 13 isolates was conducted by MLSA (2) employing 120 comparisons of the concatenated partial sequences of 16S rDNA (1,301 bp), gyrB (669 bp) 121 and rpoD (677 bp) genes. After obtaining the corresponding amplified sequences for each 122 isolate (Table S2), the derived concatenates were first aligned and compared to the equivalent 123 sequences extracted from reference strains representing the different species of the P. putida 124 G, including recently proposed species (1, 2, 4, 5). The threshold percentage of identity 125 between concatenate sequences used to discriminate between species within P. putida G was 126 set at ≥ 97.5 % (1, 2). In this study, we assigned each of the isolates described here to the 127 species to which the corresponding concatenates shared the higher percentage of sequence 128 identity (see summary in Table 1).
Thus, isolates BA7908 and BA9115 were assigned to P. 129 putida sensu stricto; HB157 and BA9713 to P. monteilii; BA7816, LD209, HB313 and 130 HP613 to P. asiatica; and LA111 to P. juntendi, as judged by percentages of identity that 131 ranged from 99.3% (LA111, P. juntendi) to 99.94% (BA9713, P. monteilii) to the 132 corresponding species (Table 1). In the case of 4 isolates (HP813, HE1012, LA1008, and 133 BA9605) the highest percentages of concatenate sequence identity to the corresponding 134 closest defined species were found to be lower than the 97.5% threshold value (Table 1). 135 However, as also seen in the Table, these isolates could be assigned to recently proposed P. 136 putida G novel species (1) as judged by percentages of concatenate sequence identity that 137 ranged from 98.03 to 99.81%. This included the assignment of LA1008 and HE1012 to P. 138 putida G/II, HP813 to P. putida G/I, and BA9605 to P. putida G/V (Table 1). Also, 139 intraspecies sequence similarity values of different isolates assigned to the same species (P. 140 putida, P. monteilii, and P. putida G/II, Table 1) were found to be higher than 98.8%. 6 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 141 Secondly, a maximum-likelihood (ML) phylogenetic analysis using the corresponding 142 concatenated sequences of 16S rDNA, gyrB and rpoD genes validated the species 143 assignations obtained above (Fig. 1). This analysis also included the corresponding 144 concatenates from additional type strains of species of the P. putida G (1, 2, 4, 5). P. 145 aeruginosa (ATCC 10145) and P. oryzihabitans (ATCC 43272) were used as outgroups (Fig. 146 1, see Table S3 for details). This analysis confirmed the assignation of isolates BA9115 and 147 BA7908 to P. putida; HB157 and BA9713 to P. monteilii; BA7816, LD209, HP613, and 148 HB313 (the latter three isolates displaying identical concatenate sequences, Table S3) to P. 149 asiatica; and LA111 to P. juntendi, as judged by the monophyletic groups formed in each 150 case with the corresponding defined species. The clinical strain LD209, previously 151 characterized as belonging to the P. putida G on the basis of phenotypic procedures (13), 152 could now be more confidentially assigned to P. asiatica on the basis of the analysis 153 described above. 154 Of note, some isolates clustered with newly proposed species, such as HP813 with P. 155 putida G/I KT2440; LA1008 and HE1012 with P. putida G/II ATCC 23483; and BA9605 156 with P. putida G/V W619 (Fig. 1). Thus, our local collection of clinical isolates was 157 composed of (at least) seven different species now assigned to the P. putida group. It is worth 158 noting that in the ML tree (Fig. 1) the RYU5 strain, recently proposed as representative of the 159 new species P. asiatica within the P. putida group (4), clustered with the CFBP4966 strain.
160 The latter was in turn proposed as a representative of a new P. putida group species 161 designated G/IV (1). Our observations, including the 98.1% nucleotide identity shown by the 162 corresponding concatenate sequences (Table 1), strongly point to these two strains as 163 belonging to a same species. 164 Further discriminatory fingerprinting analyses (39) showed that the four clinical 165 isolates assigned here to P. asiatica (see above) could be subdivided into two separate clonal 7 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 166 lineages: one constituted by LD209, HB313, and HP613, and the other by BA7816 (Fig. S1, 167 Table 1). Also, the two isolates assigned to P. putida sensu stricto (BA9115 and BA7908, 168 respectively) could also be ascribed to two separate clonal lineages, and the same situation 169 was found for the two isolates assigned to P. monteilii (HB157 and BA9713) and the two 170 assigned to P. putida G/II (LA1008 and HE1012) (Fig. S1, Table 1). These results indicated 171 the presence, among the 13 P. putida G isolates included in this study, of 11 still 172 distinguishable isolates by using more discriminatory genetic procedures (Fig. S1). This not 173 only exemplifies the difficulties in defining the limits between species in this phylogenetically 174 closely-related group (1, 2, 3, 4, 5), but also indicates that further delimitations of the 175 presently-accepted species may be necessary in the future. 176 In summary, the above results indicate the existence of (at least) seven distinguishable 177 species of the P. putida G carrying blaVIM-2 among our isolates, and reinforce the notion of 178 this group acting as a carbapenem resistance genes reservoir (13, 17). Moreover, they also 179 revealed the persistence and/or dissemination in our local nosocomial environment of a 180 specific clone of P. asiatica (designated PaA, Table 1 and Table S1). Similar results 181 concerning the nosocomial transmission of a single clone of P. putida have been reported in a 182 tertiary hospital of Pittsburgh, Pennsylvania, U.S.A. (40). A further characterization of the 183 blaVIM-2-carrying genetic platforms in the above-mentioned isolates could then shed light on 184 the mechanisms involved in their exchange among P. putida G species. 185 186 Characterization of genetic structures harboring blaVIM-2 genes in the P. putida G isolates 187 analyzed 188 The characterization of the near genomic context of blaVIM-2 using PCR primers 189 designed to hybridize in the 5’ and 3’ conserved segments of “typical” class 1 integrons 190 (Table S2) systematically failed to produce amplification bands in all of the 13 P. putida G 8 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020.
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 191 clinical isolates analyzed here. Conversely, the use of Int1-F and TniC-R2 primers, 192 hybridizing into the 5’-CS and the 5’ region of the tniC gene located in the tni module of 193 Tn402 transposons, respectively (Table S2) generated amplification bands in all of them. 194 These results indicated the presence of Tn402-like class 1 integrons carrying blaVIM-2 in all 13 195 P. putida G isolates. Subsequent sequencing analysis of the amplicons not only confirmed the 196 presence of blaVIM-2-containing gene cassettes and their association to a tniC gene of a 197 Tn5053/Tn402 transposon family in all cases, but also identified the presence of three 198 different blaVIM-2-containing unusual class 1 integrons among them (see below, Fig. 2). 199 We have previously reported that the P. asiatica LD209 strain carries a conjugative 200 plasmid of 38,403 bp, designated pLD209 (13, 17). The detailed analysis of the pLD209 201 sequence (13) indicated that it harbours a Tn402-like transposon of 7,633 bp endowed with a 202 complete tni module, and a class 1 integron (In41) possessing blaVIM-2 and aacA4 resistance 203 cassettes (Fig. 2A). This Tn402 element has been assigned the denomination Tn6335 by the 204 Tn Number Registry (41). The sequence characterization of the amplicons obtained from the 205 different P. putida G isolates described above indicated the presence of the In41 arrangement 206 in P. putida BA7908, P. monteilii BA7913, P. asiatica HP613, P. asiatica HB313, P. juntendi 207 LA111, P. putida G/I HP813, P. putida G/II HE1012, P. putida G/II LA1008, and P. putida 208 G/V BA9605 (Table 1). Further PCR amplification of the immediate genetic context of In41 209 (see Materials and Methods for details) followed by sequencing analysis confirmed the 210 presence of Tn6335 in all of these isolates. 211 Concerning the other isolates, similar procedures than those described above detected 212 only the blaVIM-2 gene cassette into the variable region of the class 1 integron carried by P. 213 putida BA9115 and P. asiatica BA7816 (Table 1). This single-cassette integron was 214 previously reported with the designation In899 (GenBank accession number KJ668595) in 215 Pseudomonas chlororaphis M11740 isolated in Argentina, where it was found in a 55-kbp 9 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 216 plasmid (42). Further sequencing analysis indicated that In899 was embedded in a complete 217 Tn402 transposon of 6,994 bp in our isolates (Fig.
2A). This novel Tn402 element was 218 assigned the denomination Tn6336 by the Tn Number Registry (Fig. 2A). 219 Finally, a similar analysis conducted in P. monteilii HB157 (Table 1) indicated a class 220 1 integron carrying dhfrB1, aacA4 and blaVIM-2 gene cassettes, accompanied by a defective tni 221 module containing only the tniC gene (Fig. 2B). Further completion of its downstream region 222 by an inverse PCR procedure (see Material and Methods for details) indicated that it formed 223 part of a Tn402-like element spanning a total of 5,239 bp (MT192132.1, Fig. 2B). This 224 methodology allowed to confirm a defective tni module composed only of a complete 225 resolvase tniC gene and an upstream 44 bp remnant of the intergenic tniC/tniQ region, 226 accompanied by a short fragment (11 bp) of the 5´ coding region of tniA gene (Fig. 2B). The 227 finding of an IS6100 element near this tniA remnant suggests that disruption occurred as the 228 consequence of this IS targeting tniA, followed by further deletions/rearrangements at the 229 vicinity of the insertion site. In support to this inference, a BLASTn search indicated that this 230 defective Tn402-like element shares almost full identity in the first 4,084 nucleotides 231 (spanning from the IRi at the left boundary to the short 44-bp intergenic fragment located at 232 the 5’ region of the tniC gene, and including the integron-associated dhfrB1-, aacA4- and 233 blaVIM-2 gene cassettes) with the equivalent region of a complete Tn402 family transposon 234 (8,041 bp) located in different P. aeruginosa strains including R22 (AM993098.1) and DZ-B1 235 (KY579949.1). A further stretch of homology spanning 150 nucleotides (81% nucleotide 236 identity) between these elements was found at the corresponding right boundaries, and 237 included the 25-bp inverted repeat IRt and associated sequences (Fig. 2B). Most intriguingly, 238 a second 25-bp inverted repeat identical to IRi was located upstream of the tniC gene 239 (designated IRi’ in Fig. 2B). Our database searching identified an identical Tn402(tniABQ) 240 element in the chromosome of P. putida PP112420, a clinical strain isolated in China 10 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 241 (GenBank accession CP017073.1; nucleotide positions 5,137,406 to 5,142,644). The 242 observation that this Tn402(tniABQ) element is bounded by both IRi and IRt and immediate 243 associated sequences characteristic of Tn5053/Tn402 transposons (30) opens the possibility 244 that it could be mobilized to other genomic locations in cells providing in trans the enzymes 245 required for transposition. Tn5053/Tn402 family transposons use a replicative mechanism of 246 transposition, in which resolution of cointegrates is mediated by the product of the tniC gene 247 acting at a res site located in the 61-bp tniC/tniQ intergenic region (30).
In this context, 248 comparative sequence analysis of the remnant 44 bp region upstream of tniC in 249 Tn402(tniABQ) indicated that the recombination site and immediate adjunt sequences were 250 preserved in this defective element. 251 252 Plasmid transfer of blaVIM-2-containing Tn402-like class 1 integrons from P. putida G 253 members to E. coli and P. aeruginosa 254 We next analyzed whether the Tn402 elements characterized above were carried by 255 plasmids endowed with transfer potentiality. For this purpose, conjugation experiments were 256 conducted using the corresponding P. putida G isolates as donors, and E. coli DH5α or P. 257 aeruginosa PAO1 as recipient cells (see Materials and Methods for details). We previously 258 reported that, in laboratory conjugation assays, plasmid pLD209 harbored by P. asiatica 259 LD209 could be transferred to E. coli DH5α and to P. aeruginosa PAO1 (17). By conducting 260 similar conjugation experiments, we could detect plasmid transfer to E. coli DH5α and also to 261 P. aeruginosa PAO1 when the donor was P. asiatica LD209 (used as control), P. asiatica 262 BA7816, P. asiatica HB313, P. putida G/II HE1012, P. putida G/V BA9605, or P. juntendi 263 LA111, as judged by the selection of imipenem-resistant transconjugants of the corresponding 264 recipients in all of the above cases and the subsequent detection of acquired ML activity in 265 all of them (Table S4 and data not shown). 11 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.23.424275 ; this version posted December 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 266 The antimicrobial susceptibility patterns of the corresponding E. coli DH5 267 transconjugants (designated Ect209, Ect7816, Ect313, Ect1012, Ect9605 and Ect111, 268 respectively) are shown in Table S4. All of them acquired resistance to imipenem and the 269 other -lactams tested, as judged by the increments observed in the corresponding MIC values 270 when compared to E. coli DH5α cells (Table S4). It is worth noting that, with the exception of 271 Ect7816, the MIC values to gentamicin also increased from 4- to 8-fold in all transconjugants 272 (Table S4). The overall observations are in agreement with the conjugative transfer, from the 273 indicated P. putida G isolates, of a plasmid containing Tn6335 carrying blaVIM-2- and aacA4- 274 resistance determinants in each Ect209, Ect313, Ect1012, Ect9605 and Ect111, and of a 275 plasmid housing Tn6336 carrying only a blaVIM-2 cassette in Ect7816 (Fig. 2A). 276 To further examine the self-transfer capability of the plasmids selected in each of these 277 Ect transconjugants, agar mating assays were done using each of them as donors, and 278 chloramphenicol-resistant E. coli MC4100 cells as recipients following previously described 279 procedures (17) (Table 1).