A global virome of methanogenic archaea highlights novel diversity and adaptations to the gut environment

doi:10.21203/rs.3.rs-2539466/v1

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A global virome of methanogenic archaea highlights novel diversity and adaptations to the gut environment

https://doi.org/10.21203/rs.3.rs-2539466/v1

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published 25 Sep, 2023

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Mobile genetic elements (MGEs), especially viruses, have a major impact on microbial communities. Methanogenic archaea play key environmental and economical roles, being the main producers of methane -a potent greenhouse gas and an energy source. They are widespread in diverse anoxic artificial and natural environments, including animal gut microbiomes. However, their viruses remain vastly unknown. Here, we carried out a global investigation of MGEs in 3436 genomes and metagenome-assembled genomes covering all known diversity of methanogens and using a newly assembled CRISPR database consisting of 60,000 spacers of methanogens, the most extensive collection to date. We obtained 248 high-quality (pro)viral and 63 plasmid sequences assigned to hosts belonging to nine main orders of methanogenic archaea, including the first MGEs of Methanonatronarchaeales, Methanocellales and Methanoliparales archaea. We found novel CRISPR arrays in ‘Ca. Methanomassiliicoccus intestinalis’ and ‘Ca. Methanomethylophilus’ genomes with spacers targeting small ssDNA viruses of the Smacoviridae, supporting and extending the hypothesis of an interaction between smacoviruses and gut associated Methanomassiliicoccales. Gene network analysis shows that methanogens encompass a unique and interconnected MGE repertoire, including novel viral families belonging to head-tailed Caudoviricetes, but also icosahedral and archaeal-specific pleomorphic, spherical, and spindle (pro)viruses. We reveal well-delineated modules for virus-host interaction, genome replication and virion assembly, and a rich repertoire of defense and counter-defense systems suggesting a highly dynamic and complex network of interactions between methanogens and their MGEs. We also identify potential conjugation systems composed of VirB4, VirB5 and VirB6 proteins encoded on plasmids and (pro)viruses of Methanosarcinales, the first report in Euryarchaeota. We identified 15 new families of viruses infecting Methanobacteriales, the most prominent archaea in the gut microbiome. These encode a large repertoire of protein domains for recognizing and cleaving pseudomurein for viral entry and egress, suggesting convergent adaptation of bacterial and archaeal viruses to the presence of a cell wall. Finally, we highlight an enrichment of glycan-binding domains (immunoglobulin-like (Ig-like)/Flg_new) and diversity-generating retroelements (DGRs) in viruses from gut-associated methanogens, suggesting a role in adaptation to host environments and remarkable convergence with phages infecting gut-associated bacteria. Our work represents an important step toward the characterization of the vast repertoire of MGEs associated with methanogens, including a better understanding of their role in regulating their communities globally and the development of much-needed genetic tools.

Biological sciences/Microbiology/Archaea/Archaeal genomics

Biological sciences/Microbiology/Virology

Mobile genetic elements (MGE), including viruses and plasmids, play a major role in structuring and controlling microbial communities across ecosystems^1–3. While the ecological significance of bacterial viruses (bacteriophages) and plasmids has been extensively investigated, the role of archaeal MGEs remains poorly understood. Archaeal viruses are notorious for their unique virion morphologies and genomic diversity^4,5. In addition, several archaeal plasmids have been described, including conjugative plasmids⁶, non-conjugative cryptic plasmids⁷, virus satellites⁸, and diverse linear and circular megaplasmids, including the recently discovered Borgs^9–11. However, knowledge on archaeal MGEs is biased toward hosts belonging to a few taxonomic groups, predominantly Crenarchaea hyperthermophiles and members of the halophilic Haloarchaea¹².

Methanogens (methanogenic archaea) are phylogenetically diverse archaea that produce methane as a by-product of their energy metabolism¹³. Traditionally, methanogenic archaea have been classified into two groups: class I methanogens (Methanobacteriales, Methanococcales and Methanopyrales) and class II methanogens (Methanosarcinales, Methanomicrobiales and Methanocellales). Recently, the potential for methanogenesis was discovered in many additional lineages throughout the tree of Archaea: in the TACK superphylum (Methanomethyliales¹⁴ and Methanohydrogenales¹⁵, in a Korarchaeota genus called Methanodesulfokores^16,17 and in the Thaumarchaeota lineage Ca. Methylarchaeales ^18,19), in the Methanotecta (Methanonatronarchaeia²⁰, Archaeoglobales²¹, Methanoliparales¹⁶, Methenoflorentales²²), in the Diaforarchaea (Methanomassiliicoccales²³) and in the Acherontia (Nuwarchaeales_NM3¹⁶, Methanofastidiosa²⁴).

Methanogenic archaea thrive in diverse artificial and natural anoxic environments covering an extensive range of salinity and temperatures: freshwater and saline sediments^20,25,26, peatlands²⁷, terrestrial aquifers²⁸, hydrothermal vents^29,30, biogas reactors^31,32, digesters^33–37, wastewater treatment plants^38–42, oil facilities⁴³ and coal seam⁴⁴. Methanogens contribute to climate change through the production of a powerful greenhouse gas, participate in the complete degradation of organic matter in many anoxic environments through their interaction with fermentative bacteria, and are used in industry to transform biowaste into biogas. Moreover, five lineages of methanogens are commonly present in the animal gut: Methanobrevibacter and Methanosphaera (Methanobacteriales), Methanomethylophilaceae (Methanomassiliicoccales), Methanocorpusculum (Methanomicrobiales), and Methanimicrococcus (Methanosarcinales)^45–47. Three of them (Methanobrevibacter, Methanosphaera, Methanomethylophilaceae) are specifically associated with the human gut⁴⁸. The impact of methanogens on health and disease is far from being understood, but some species have been suggested to have a protective role, while others were linked with disease sites where they may favor the development of bacterial pathogens^49–51. Given the key environmental and economical roles of methanogens, a better understanding of the factors controlling the composition and dynamics of their populations in diverse environments is crucial.

MGEs, and especially viruses, have a major impact on microbial communities through the lysis of susceptible hosts, horizontal gene transfer, and by modulating the host metabolism by auxiliary metabolic genes (AMGs). However, current knowledge on the virosphere of methanogens is limited to a few viral isolates. Eight viruses of the class Caudoviricetes (head-tailed viral morphology) have been described for Methanobacteriales (Anaerodiviridae³³, Leisingerviridae⁵², and Speroviridae⁵³ families), Methanomicrobiales (family Pungoviridae³¹) and Methanococcales (family Fervensviridae²⁹) hosts, and an unclassified spherical virus was isolated on a Methanosarcinales host^43,54. In addition, a dozen of proviruses has been found in Methanobacteriales, Methanococcales, Methanosarcinales and Methanonatronarchaeales genomes^48,55,56. Moreover, a recent study revealed a diversity of head-tailed viruses infecting Methanobrevibacter in human metagenomes⁵⁷. Finally, genomes of Methanomassiliicoccales from the human gut have been found to harbor CRISPR spacer targeting small ssDNA viruses of the Smacoviridae family^58–60. This is intriguing, as smacoviruses are phylogenetically related to viruses infecting eukaryotes^59,6162.

Limited knowledge on methanogen MGEs may be related to difficulties in the cultivation of these anaerobic hosts. Culture-independent methods applied to metagenome and virome data can circumvent this limitation⁶⁰. Here, we explored the repertoire of MGEs in 3436 genomes covering all known lineages of methanogens. We identify 248 high-quality (pro)viral and 63 plasmid sequences and assign them to hosts belonging to nine main orders of methanogenic archaea. Their analysis reveals a unique and diverse repertoire of MGEs including novel viral families and highlights specific evolutionary patterns including adaptation to the host environment.

Identification of mobile genetic elements of methanogenic archaea

To identify MGEs associated with archaeal methanogens, we assembled a database (“methanogen genome database”) consisting of 3436 genomes and metagenome-assembled genomes (MAGs) from Genbank⁶³, the Unified Human Gastrointestinal Genome catalog (UHGG) database⁶⁴, the IMG database⁶⁵, and MAGs reconstructed from animal gut samples available in our group (Supplementary Table S1). Complete genomes and MAGs are a rich source of proviral sequences and occasional extrachromosomal elements - circular or linear contigs with terminal repeats, included in the genome assembly during the process of binning⁶⁶. Our pipeline for the identification of MGEs of methanogens consisted of four steps: CRISPR prediction, MGE prediction, host assignment and vOTU definition (Fig. 1). First, we identified all CRISPR spacers and CRISPR repeats in the “methanogens genome database” using the CRISPR-Cas-Finder program⁶⁷ (Step 1 in Fig. 1). The resulting data were assembled into a “methanogens CRISPR database”, which includes ~ 60000 spacer sequences, the most extensive collection to date (Supplementary Table S2, Supplementary Data). Next, we predicted MGE sequences in the “methanogens genome database” using a decision-tree approach (Step 2 in Fig. 1). The “methanogens genome database” was first screened for the presence of major capsid proteins (MCPs), a hallmark of viruses, using sensitive homology searches based on profiles obtained from the PFAM and phrogs databases⁶⁸. Based on the presence and type of the MCPs identified, potential MGEs were classified into three groups: i) putative head-tailed (pro)viruses with the HK97-fold MCP (1404 sequences), ii) (pro)viruses with other MCP types (271 sequences), iii) extrachromosomal elements without known MCP (1661 sequences).

The HK97 fold is a conserved structural fold found in capsids of head-tailed (pro)viruses (class Caudoviricetes)⁶⁹ and in capsid-like nanocompartments of archaea and bacteria called encapsulins⁷⁰. To distinguish (pro)viruses from encapsulins, we specified that potential head-tailed (pro)virus sequences should contain at least one of two other hallmark genes of head-tailed viruses¹², namely the portal protein or the terminase large subunit (TerL) (Fig. 1). To remove low-quality contigs with incomplete (pro)viruses, we overlapped the ends of the contigs to predict complete sequences of viruses in the extrachromosomal form – circular or linear contigs with direct or inverted terminal repeats (TR), respectively. Then, we applied CheckV⁷¹ to estimate the completeness of the remaining sequences and to extract proviruses from the surrounding host sequences. The CheckV estimation of viral completeness is based on a similarity between query viral sequence and the “CheckV complete viral genome database”, which consists mostly of viruses of bacteria. As a result, CheckV underestimates the completeness of archaeal head-tailed (pro)viruses (Supplementary Table S3). Therefore, we selected CheckV contigs with > 90% completeness and refined the integration sites for the rest of the contigs manually. Among the 1404 sequences with an HK97-fold MCP, 370 fulfilled all the above-mentioned conditions and were thus classified as complete head-tailed (pro)viruses.

We then proceeded to analyze the second group of potential (pro)viruses with other types of MCPs (Fig. 1). Nine contigs appeared to be complete virus genomes in extrachromosomal form and we identified several additional potential proviruses. Given the genetic diversity of these (pro)viruses from other reference viruses present in the CheckV database, we did not rely on automatic tools to predict their completeness but rather manually identified the provirus integration sites. After manual completeness filtering, we obtained 48 sequences of complete proviruses that encode MCPs unrelated to the HK97-fold family, leading to a total of 57 potential non-head-tailed (pro)viruses.

Finally, we moved on to analyze the rest of the contigs lacking known MCPs (Fig. 1). From this group, we identified 1661 sequences that appeared in circular form. To confirm the plasmid or viral nature of these sequences, we identified 36 that matched spacers from the “methanogens CRISPR database” with > 90% identity. For the remaining contigs, protein annotation using the MGE-specific database of hmm profiles⁶⁸ revealed 260 contigs with MGE-specific genes. Together, this step led to a classification of 296 sequences as potential extrachromosomal MGEs of methanogens.

The final dataset of 723 MGEs predicted from the “methanogens genomes database” was supplemented with 73 putative viral sequences from the human gut previously identified through metaviromic studies ^72–76 (“gut virome database”, Fig. 1). Finally, we added 44 MGE sequences assigned to methanogenic hosts in the IMG/VR database ⁶⁵ and 38 MGEs of methanogenic archaea from the NCBI database identified in previous studies^{29,31,33,37,43,54, 77–79} (“known MGEs of methanogens”, Fig. 1).

We then proceeded to infer the hosts for the 723 predicted MGEs (Step 3 in Fig. 1). An MGE was assigned to a methanogenic host if: (i) it is a provirus integrated into the genome of a methanogenic archaeon, (ii) it is matched by a CRISPR spacer from the “methanogens CRISPR database” with > 90% identity or (iii) the best Blastp hit of one of its proteins with > 70% identity corresponds to a protein of a methanogenic archaeon from the RefSeq database. Based on these criteria, 421 MGEs (58%) could be assigned to methanogenic hosts. To assign hosts to the remaining MGEs, we clustered them based on their encoded proteins using vContact2⁸⁰ and transferred the host assignment to closely related MGEs (MGEs that shared at least three protein clusters). Collectively, this allowed assigning methanogenic hosts to additional 196 MGEs (27%), leading to a total of 617 assigned MGEs (85%). Finally (Step 4 in Fig. 1), we proceeded to the vOTU definition for each predicted MGE by calculating their average nucleotide identities (ANI), which yielded 248 (pro)viral and 63 plasmid OTUs with a threshold of 95% ANI (the list of all MGEs is presented in Supplementary Table S4).

A rich repertoire of MGEs associated with all major lineages of methanogenic archaea

The 248 identified (pro)-viruses infect hosts belonging to the main known lineages of methanogenic archaea (Fig. 2A; Supplementary Table S4). The vast majority (79%) belongs to Caudoviricetes (pro)viruses and are associated with Methanobacteriales (n = 92), Methanosarcinales (50), Methanomicrobiales (25), Methanomassiliicoccales (23), Methanococcales (4) and Methanoliparales (1) hosts. Seventeen viruses were predicted to infect acetoclastic Methanotrix/Methanosaeta, among the main methane producers on Earth⁸¹. We also identified seven viruses associated with methanotrophic archaea belonging to the Methanosarcinales (ANME-2, ANME-3). Phylogenetic analysis of the portal protein (Supplementary Figure S1) shows that these head-tailed viruses are very diverse, forming multiple families encompassing the few currently characterized viruses. For example, head-tailed viruses of Methanosarcinales fall into six independent clades: three include the previously described (pro)viruses MetMV, ANMV-1 and Mace-Pro1, while the rest represent totally novel viral families (Supplementary Figure S1).

For the remaining (pro)viruses, we identified icosahedral tailless (pro)viruses with the double jelly-roll (DJR) associated with Methanococcales (3), Methanosarcinales (1), and Methanomicrobiales (13). We also found archaea-specific viral morphologies⁸². These are represented by pleomorphic proviruses associated to Methanonatronarchaeales (6), but also for the first time in gut-associated Methanomassiliicoccales (27), extending the distribution of pleolipo-like viruses beyond saline environments. We also identified already described spherical virus MetSV of Methanosarcina mazei⁵⁴ (1) and the nearly-complete spindle-shaped virus previously predicted to infect Methanosarcina³⁷ (1) (Fig. 2A).

The 63 plasmids of methanogenic archaea (of which 39 are newly predicted ones) are circular and have an average size of 28 kbp. They are associated to eight orders of methanogens: Methanosarcinales (n = 34), Methanobacteriales (11), Methanococcales (10), Methanomicrobiales (4), Methanomassiliicoccales (1), Methanoliparales (1), Korarchaeota (1), Methanocellales (1). Finally, we could not identify any MGEs in Methanopyrales, Methanofastidiosales, NM3, Methanoflorentales, Methanohydrogenales and Methanomethyliales, probably due to scarcity of available genomic data for these lineages (Fig. 2A).

To study the relationships between the newly identified MGEs of methanogenic archaea and to assess their connections to MGEs of other archaea and bacteria, we used network analysis by vConTACT2⁸⁰ and the NCBI Bacterial and Archaeal Viral RefSeq V85 database. We constructed a gene-sharing network where each node represents an MGE, and two nodes are connected if the respective MGEs share more than three protein clusters (Fig. 2B). MGEs are largely clustered by host taxonomy, suggesting that this is the first factor underlying gene content similarity. Plasmids and viruses of the same host share proteins involved in replication, integration, and host interactions. Head-tailed viruses associated with different orders of methanogenic archaea (Methanomicrobiales, Methanosarcinales, Methanoliparales, Methanobacteriales, and Methanomassiliicoccales) form an interconnected component in the network by sharing similar sets of structural proteins (Fig. 2B). Interestingly, the head-tailed virus component is also connected to the bacterial part of the network through the head-tailed virus vir120 of Methanoculleus (Methanomicrobiales). Structural proteins of this virus are in fact ~ 30–40% identical to those of a tailed bacteriophage from Geobacillus (Firmicutes) (Supplementary Figure S2), suggesting the possibility of past coinfection and/or extensive gene exchange between these archaeal and bacterial head-tailed viruses. In contrast, head-tailed viruses of Halobacteria, Methanococcales, and most of the Methanomassiliicoccales form discrete components (Fig. 3A), likely reflecting high sequence divergence of their structural proteins.

It has been recently proposed that small ssDNA viruses of the Smacoviridae family⁵⁹ infect Methanomassiliicoccales archaea, based on eight spacers from the type I-B CRISPR array of Methanomassiliicoccus intestinalis Issoire-Mx1 targeting smacovirus genomes with 90–100% identity⁸³. Using the same identity threshold, we could match 16 additional spacers from M. intestinalis type I-B CRISPR arrays and 10 spacers from Methanomethylophilus CRISPR arrays of types I-B and V-A. Notably, in addition to smacoviruses from the human gut, these new spacers matched chicken, porcine and lynx-associated smacoviruses (Supplementary Table S5). These results further extend and support a possible interaction between smacoviruses and gut associated Methanomassiliicoccales. Interestingly, no spacers targeting smacoviruses were found in other gut methanogens, highlighting a specific interaction between these viruses and Methanomassiliicoccales. However, this conclusion should be treated with caution. In fact, we note that smacoviruses are phylogenetically nested among viruses with experimentally confirmed eukaryotic hosts^62,84 and do not show affinity to prokaryotic plasmids encoding the same type of replication proteins⁸⁵. If smacoviruses indeed infect Methanomassiliicoccales, this relationship could represent a rare case of inter-domain virus transfer from eukaryotes to archaea. Alternatively, we cannot exclude the possibility that exogenous smacovirus DNA is non-specifically internalized into Methanomassiliicoccales cells and occasionally gets incorporated into the CRISPR arrays.

Together, these results uncover a rich mobilome including viruses and plasmids associated with all major lineages of methanogenic archaea. This atlas of MGEs derived from diverse environments and methanogen lineages enables to glean into factors underlying niche adaptation and evolutionary patterns in the global archaeal mobilome.

Functional annotation of methanogens MGEs

To characterize the functional potential of the identified MGEs and their interactions with methanogenic hosts, we proceeded with their annotation. Proteins encoded in MGEs were clustered using vContact2⁸⁰ and annotated using the arCOGs database⁸⁶, the NCBI conserved domains database⁸⁷ and the phrogs database⁶⁸. Overall, most proteins from (pro)viruses and plasmids were assigned to the “function unknown” and “mobilome” arCOG categories (Supplementary Figure S3). We found a significant difference in arCOG classification between the two types of MGEs, with plasmids encoding a larger fraction of proteins involved in replication, cell wall biogenesis, and protein modification and turnover than (pro)viruses (p-value < 0.001, chi-square test). Also, when compared to the recently identified Borgs, the gene content of the newly predicted plasmids is less enriched in metabolism-related proteins and contains more mobilome-specific arCOGs (Supplementary Figure S3), suggesting fundamentally different modes of propagation for Borgs as compared to plasmids with much smaller genomes. Notably, differently from Borgs, we could not identify any genes related to methanogenesis in the predicted MGEs, indicating that manipulation of host metabolism is not a general strategy of these elements.

Fifty-four viruses were found as circular contigs with sequence lengths ranging from 10 kbp (spherical virus of Methanosarcina, MetSV)⁵⁴ to 228 kbp (head-tailed virus of Methanobrevibacter) (Supplementary Table S4). Ninety vOTUs were found in the integrated form, as proviruses, with sequence length in the range of 6–10 kbp (Pleolipoviridae-like integrated elements of Methanonatronarchaeales and Methanomassiliicoccales) to 82 kbp (head-tailed provirus of Methanobrevibacter) (Supplementary Table S4).

Identified (pro)viruses of methanogens display a vast diversity in terms of gene content (Fig. 3, Supplementary Data, Supplementary Table S6). The majority of head-tailed vOTUs display modular genomic organization similar to that of other bacterial and archaeal Caudoviricetes viruses, with evidently delineated modules for virus-host interaction, genome replication and virion assembly (Fig. 3). Proteins potentially involved in viral genome replication were identified in 40% of the vOTUs and include primases of the AEP superfamily ⁸⁸, B-family DNA polymerases, clamp loaders and PCNA-like processivity factors as well as minichromosome maintenance (MCM)-like replicative DNA helicases, DNA ligases and ssDNA-binding proteins. Like haloarchaeal head-tailed viruses¹², viruses of methanogens encode components of purine and pyrimidine synthesis pathways and biosynthesis of nucleotide sugars pathway used to accelerate viral genome replication. This is the case of thymidylate synthase (ThyA), which is found in 22 vOTUs infecting members of Methanobacteriales, Methanosarcinales and Methanoliparales (Supplementary Table S6).

Viruses of methanogens encode diverse DNA modification systems for protection against restriction-modification-like systems of their hosts (Fig. 3 and Supplementary Table S6). The most prevalent ones include adenine- and cytosine-specific methyltransferases, which are found in 54% of the vOTUs associated with all major lineages of methanogenic archaea. In 32 MGEs, we found methyltransferases encoded next to predicted restriction endonucleases, representing full restriction-modification systems. In addition, we identified systems involved in DNA sulfur modification and several queuosine synthases and FolE GTP cyclohydrolase potentially involved in DNA modification with queuosine⁸⁹, as previously reported in haloarchaeal viruses and bacteriophages¹².

Some viral genomes encode proteins involved in the shutdown of host translation and transcription and in countering the host defense systems (Fig. 3 and Supplementary Table S6). For instance, multiple viruses harbor Lar-like⁹⁰ or ArdC-like anti-restriction proteins⁹¹, involved in the alleviation of the host restriction-modification systems. Additionally, we identified several peptidyl-tRNA hydrolases, which potentially participate in the inhibition of translation of the host proteins.

Interference modules of the type IV-B CRISPR-Cas system were found in six viruses associated with Methanobacteriales and Methanosarcinales archaea (Supplementary Table S7). Other potential defense systems include viperin⁹² (plasmid pMETHO01 of Methanomethylovorans), BREX⁹³ and AVAST⁹⁴ systems in plasmids of Methanobrevibacter, a PD-Lambda-1⁹⁵ protein in four viruses of Methanobacteriales, an hma system⁹⁶ encoded in a virus of Methanoperedens, and the serine/threonine kinase system stk2⁹⁷ in a provirus of Methanobacterium (Supplementary Table S7). This rich repertoire of defense and counter-defense systems suggests a highly dynamic and complex network of interactions between methanogens and their MGEs, likely extending beyond the classical predator-prey relationships⁹⁸.

In Crenarchaeota⁶ and Thaumarchaeota⁹⁹, type IV secretion system proteins constitute the conjugation machinery involved in DNA transfer, but no such system has been reported thus far in Euryarchaeota. Interestingly, we found potential conjugation systems including virB4, virB5 and virB6 genes, encoded not only by plasmids but also by head-tailed (pro)viruses associated with methanotrophic archaea of the ANME-3 lineage (Methanosarcinales, Supplementary Figure S4). These head-tailed viruses might thus be potentially transmitted between host cells both through infection and conjugation. Experimental validation of these conjugation systems may open new possibilities for genetic manipulation in methanotrophic archaea.

Viruses of Methanobacteriales contain proteins to cross the pseudo-peptidoglycan cell wall

Methanobacteriales are widespread in the environment and represent the main archaeal component of the animal and human gut microbiomes^45,48,100. All five previously characterized viruses of Methanobacteriales (phiF1, phiF3³⁴, psiM2¹⁰¹, psiM100⁷⁷, Drs3³³ and C158³⁷) infect environmental hosts, while viruses associated with Methanobacteriales from the gut environment have been reported but not comprehensively described^37,48,55. Our analysis shows that head-tailed viruses of Methanobacteriales are very diverse and can be divided into 18 families, including the 3 previously known Speroviridae⁹², Leisingerviridae ⁵², and Anaeroviridae³³, as well as 15 new ones. These include all complete (pro)viral sequences, corresponding to 7 vOTUs recently identified in human metagenomes by Li et al.⁵⁷ (Fig. 4, marked with asterisks). Many of these new families are currently represented by a single virus genome, underscoring a considerable and still largely uncovered genetic diversity. We provide detailed characterization for the four most abundant viral families (provisionally denoted as ‘Families 1-2-3-4’) associated with both isolated and uncultured Methanobrevibacter species found in intestinal ecosystems (Fig. 4, Supplementary Table S4). Family 1 viruses (~ 53–63 kbp) are predicted to have siphovirus-like morphology and are targeted by CRISPR spacers from up to 156 different M. smithii and M. intestini genomes⁴⁸. Family 2 viruses (~ 50–76 kbp) are predicted to have myovirus-like morphology and to infect Methanobrevibacter members from bovine and goat intestinal metagenomes. Family 3 viruses (~ 42–228 kbp) are also predicted to have myovirus-like morphology and include proviruses from M. oralis and from multiple human and animal gut metagenome-assembled genomes of Methanobrevibacter. Family 4 is the most widespread in human gut metagenomes and metaviromes; it is predicted to have sipho-like morphology and contains the previously described sipho-like provirus from M. smithii ATCC 35061 strain (Msmi-Pro1^55,102). For a more detailed description of these families, see the Supplementary text.

The Methanobacteriales represent one of the two orders of archaea with pseudo-peptidoglycan (pPG) cell walls, an evolutionary convergence with bacterial PG¹⁰³. Like head-tailed viruses of bacteria, the head-tailed viruses of Methanobacteriales must therefore overcome the pPG barrier of the host twice in their lifecycle: during virus entry upon delivery of genomic DNA into the host cytoplasm, and during virion egress through the lysis process¹⁰⁴. During the entry process, bacteriophages carry out local degradation of the cell wall by exolysins, which are PG-cleaving domains typically fused to the structural tail proteins that recognize and attach to the cell surface (fibers, spikes, baseplate, tail tape measure proteins). At the end of the infection cycle, the PG layer is destroyed by the endolysins, small soluble proteins with a PG-cleaving domain and optional PG-recognition domains. We found that an analogous paradigm applies to Methanobacteriales viruses, which display several cell wall degradation enzymes (exolysins and endolysins) (Fig. 4).

Exolysins and endolysins of Methanobacteriales viruses include different types of enzymatic domains: peptidase_C71 (PeiW-like)¹⁰⁵, peptidase_C39^106,107 (PeiR-like), and glycosyl hydrolase (Fig. 4, Supplementary Table 8). Identified exolysins mostly contain one or two peptidase-C71 domains. For myoviruses with predicted contractile tails, the peptidase_C71 domain is typically fused to baseplate wedge proteins. Viruses with sipho-like morphology (i.e., long, non-contractile tails) instead encode the peptidase_C71 domain fused to a tail tape measure protein (TMP) and/or a spike protein. The spike protein carries an additional Ig-like domain with a potential pPG-binding function. Interestingly, Leisingerviridae viruses do not encode any identifiable exolysins (Fig. 4), suggesting they are either able to pierce the cell wall of the host without degrading the pPG-layer during viral entry or, more likely, encode novel pPG-degrading enzymes.

While exolysins contain the peptidase_C71 domain, the predicted endolysins of viruses of Methanobacteriales exhibit higher diversity (Fig. 4). In addition to the previously characterized pPG-cleaving peptidase_C71 (PeiW-like)⁷⁷ and peptidase_C39 (PeiR-like)¹⁰⁷, viruses of Methanobacteriales also encode glycosyl hydrolases and transpeptidases. The pPG-cleaving domains are encoded in different combinations with putative pPG-recognition modules (PMBR - pseudomurein binding repeat, PGRP - peptidoglycan recognition protein, Ig-like - immunoglobulin-like domains) (Supplementary Figure S5). Notably, the distribution of pPG-cleaving and pPG-recognition domains in viruses of gut-associated Methanobacteriales are different from those of environmental Methanobacteriales (Supplementary Figure S5), suggesting that the diversification of these domains might be linked to adaptation to the gut environment.

Our results show that Methanobacteriales viruses encode a diverse repertoire of pPG-cleaving and pPG-recognition domains, indicating that bacterial and archaeal viruses have converged independently on similar solutions to cross the cell wall.

Enrichment in Ig-like domains and diversity-generating retroelements (DGR) is an adaptation of methanogen viruses to the gut environment

Ig-like domains (belonging to the beta-sandwich domain family) encoded by phages infecting human gut bacteria are thought to be involved in attachment to the surface of the host or to the mucosal layer of the gut epithelial cells, thereby providing immunity by controlling bacteria through predation^108–111. To explore whether Ig-like domains are also involved in the adaptation of methanogen viruses to the gut environment, we screened the viral genomes using Pfam profiles of beta-sandwich domains.

We found 289 proteins with Ig-like domains encoded by viruses of Methanobacteriales, Methanosarcinales, Methanomicrobiales, Methanomassiliicoccales and Methanococcales (Supplementary Table S9). In addition to the exolysins and endolysins described above, Ig-like domains were also found in the major capsid proteins (MCPs), major tail proteins (MTPs), tail and head fibers, and spikes. Notably, some Ig-like domains associated with MCP or MTP are presumably translated through a programmed − 1 frameshift mechanism, as previously shown for Ig-like domains in some bacteriophages¹¹². The frameshift mechanism is thought to produce a limited number (3–5%) of MCP or MTP molecules with Ig-like domains, which minimizes the negative impact of the additional domain on virion assembly. Ig-like domains were found in both gut-associated and environmental methanogens and are likely primarily involved in interaction with the carbohydrate moieties present on the surface of the archaeal hosts. However, we observed that gut-specific Methanobacteriales viruses (Families 1,2,3) encode significantly more Ig-like domains than environmental viruses (p-value 0.003, t-test) (Fig. 4, Fig. 5A).

The Flg_new (/List_Bact; PF09479) domain is a potential adhesin domain structurally akin (beta-sandwich) to the Ig-like domain and has been shown to be specifically enriched in some host-associated bacteria¹¹³ as well as gut-associated Methanomassiliicoccales¹¹³ and Methanosarcinales¹¹⁴. Four Flg_new repeats are present in the Pil3A protein of Streptococcus gallolyticus, playing an essential role in the adhesion of this bacterial pathogen to human gut mucosa¹¹⁵. We found 85 viral proteins which contain the Flg_new domain (Supplementary Table S10). Interestingly, the large majority (83) belong to head-tailed and pleolipo-like viruses of gut-associated Methanomassiliicoccales (Supplementary Table S10) and are therefore also enriched with respect to environmental viruses (Fig. 5B). The majority of the viral Flg_new-containing proteins have a transmembrane domain (86%) and a signal peptide (73%). This domain organization (signal peptide - Flg_new repeats - transmembrane domain) is similar to previously described adhesins of Methanomassiliicoccales hosts¹¹³. Altogether, our result suggests that both Ig-like and Flg_new domains play a role in the adaptation of Methanobacteriales and Methanomassiliicoccales viruses to the gut environment.

Genes at the interface of virus-host interactions are among the fastest evolving components of both cellular and viral genomes^116–118. A prime example is represented by genes encoding cellular receptors and viral receptor-binding proteins. One of the dedicated mechanisms ensuring a fast mutational pace involves diversity-generating retroelements (DGRs)^119–123, a group of genetic elements that utilize error-prone reverse transcription to introduce variations in the target gene (and the corresponding protein) sequence. Remarkably, DGRs have been coopted by both prokaryotic viruses and their hosts to quickly diversify the receptor-binding proteins and receptors, respectively^118,124. In the case of head-tailed viruses, the target sequences are usually located in genes encoding tail proteins, specifically within receptor-binding domains ^119,120. Using the MyDGR server¹²⁵, we predicted 25 DGRs in tailed, tailless icosahedral, and pleolipo-like viruses of Methanosarcinales, Methanomicrobiales, and Methanomassiliicoccales (Supplementary Table S4). The DGR system of viruses of methanogens has a similar configuration to DGRs described in bacteriophages (Fig. 5C): it consists of a reverse transcriptase (RT) gene and two imperfect repeat sequences: a template repeat (TR) used for cDNA synthesis and a variable repeat (VR) in the target gene, which is replaced by a TR-cDNA during the retrohoming process. All target proteins have the same domain architecture: 1 to 5 beta-sandwich Ig-like domains or Flg_new domains followed by a C-type lectin fold (CLec-fold) ligand-binding domain. Depending on the DGR, 11–20 diversified amino acids are located on the surface of the CLec-fold domain, accommodating up to ~ 10¹⁶ protein sequence variants, consistent with previous estimates for archaeal viruses (10¹⁸)⁷⁸. According to the domain architecture and genomic location, we annotated the target proteins of these DGRs as tail fibers for head-tailed viruses, and capsid spike proteins for icosahedral tailless viruses (Fig. 5C). Again, we found that DGRs are more prevalent in viruses of gut-associated methanogens than in viruses of environmental methanogenic archaea (Fig. 5D). Interestingly, clustering of the RT proteins based on sequence similarity using the CLANS program¹²⁶ shows that DGR systems of viruses of methanogenic archaea are not related to the previously reported archaeal viral DGR systems¹²⁷. Notably, the DGR of head-tailed and tailless viruses of Methanomicrobiales are closely related (40–60% identical), suggesting horizontal gene transfer between the two groups of viruses.

These results suggest that enrichment in Ig-like and Flg_new domains is a potential strategy involved in the adaptation of methanogen viruses to the gut environment, similar to bacteriophages of the human gut^108–111. They also extend recent studies of DGRs in genomic and metagenomic sequences, demonstrating that DGRs are particularly abundant in gut microbiomes^121,120.

This study uncovered a rich mobilome including viruses and plasmids associated with nine major lineages of methanogenic archaea - residents of animal gut microbiomes, natural environments, and industrial sites. We report several novel viruses and plasmids associated with methanogens for which a few viruses were previously known (e.g., Methanobacteriales, Methanosarcinales, Methanomicrobiales), and the first MGEs of Methanonatronarchaeales, Methanocellales and Methanoliparales archaea. The diversity of viruses and plasmids of methanogens is far from saturation, as exemplified by the single-species families of Methanobacteriales viruses and prompts for further investigation by new sequencing data and characterizations.

The MGEs of methanogens are dominated by head-tailed and icosahedral tailless viruses, which share gene contents across different methanogenic hosts and ecological niches but show limited genomic similarity to viruses of other archaea and bacteria. Despite the environmental and phylogenetic diversity of methanogenic archaea, their viruses are connected into a global virome, potentially through switching hosts and exchanging genomic sequences.

Our results reveal common adaptation mechanisms, including modular genomic organization of tailed viruses, opposing host defense systems with DNA modifications, and optimizing viral replication using virus-encoded nucleotide synthesis proteins. Moreover, viruses of Methanobacteriales encompass a variety of pPG-cleaving enzymes suggesting convergent adaptation of bacterial and archaeal viruses to the presence of a cell wall.

Another example of convergent adaptation concerns proteins involved in attaching virions to the host cells or carbohydrates of the mucosal layer. Ligand-binding structures such as Ig-like/Flg_New domains and receptor-binding proteins diversified by DGR systems are overrepresented in viruses of methanogenic archaea from the gut, suggesting a role in adaptation to the intestinal environment. The role of glycan binding domains in the interactions between the host-mucosa, microorganisms and their viruses is still weakly explored¹²⁸. In addition to previously reported glycan binding domains (e.g, Ig-like, CBDP35, BACON)¹²⁸, the Flg_New domain may also help viruses to maintain in the gut environment together with their host. The specificity of the viral Flg_new proteins for binding mammalian mucosa and/or the microbial host remains to be determined.

Due in part to the lack of reference viral genomes, archaeal MGEs are generally not considered in large-scale metagenomic studies, dominated by bacteria and bacteriophages. Our analysis represents therefore an important step towards recognizing this minor but relevant part of viral communities that infect archaeal hosts. Identifying common evolutionary patterns between archaeal and bacterial viruses from similar environments will bring new key information on the mobilomes of both prokaryotic domains.

Assembly of databases

To assemble the “methanogens genome database”, we retrieved all genomes and MAGs of methanogenic lineages of archaea (see list in Supplementary Table S1) from the Genbank database as of January 2022.

CRISPR-Cas arrays were identified by the CRISPR-Cas-Finder program with default parameters¹³⁰. CRISPR arrays with evidence level > 4 were retained in the “methanogens CRISPR database”. To avoid redundancy, spacer sequences were clustered with 90% of identity over the full length of the spacer using the VSEARCH program¹³¹. Viral contigs from previous metaviromic studies^72–76 of human gut were combined into the “gut virome database”.

Identification of MGEs

All contigs from the “methanogens genome database” were screened for hallmark viral genes with hmmsearch¹³² using the phrog⁶⁸ database of hmm profiles and several custom-made profiles of major capsid proteins. If the HK97-like major capsid protein was found in a contig, the 150 kbp region around the MCP was scanned with hmmsearch for the terminase large subunit and portal proteins. The completeness of contigs with HK97-like MCPs was defined by three methods: by CheckV⁷¹ with standard parameters, by selecting circular contigs (at least 50 nt overlap of sequence termini) and by manual curation of integrated sites for proviruses using UGENE software¹³³.

Host assignment

(Pro)viruses could be assigned to corresponding hosts if the length of host DNA in the (pro)virus-containing contig exceeded 10 kbp. Spacers from the “methanogens CRISPR database” were compared to the “gut virome database” and with the viral sequences identified in this study with blastn (word size 7, e-value 0.001, identity > 90%). The taxonomy of the genome from which the spacer with the best identity originated was then used to assign a host for an MGE targeted by CRISPR spacers. For the MGEs that remained unassigned, protein sequences (predicted by Prodigal¹³⁴ with the “meta” option) were compared to the Refseq protein database and an MGE was assigned to a host if the best hit was found in its genome with a blastp e-value < 0.001 and id > 70%. Finally, the gene-sharing network of all potential MGEs of methanogens (assigned and unassigned to hosts) was constructed by VContact2⁸⁰ with default parameters. The host annotation of MGEs at the order level (e.g., Methanobacteriales) was distributed to the first neighbors in the network, and conflicting host annotations were resolved manually.

Phylogenetic tree of head-tailed viruses

Protein sequences of portal proteins of archaeal tailed viruses were identified using Pfam hmm profiles search¹³⁵. The protein sequences were clustered with MMseq2¹³⁶ using the following parameters: minimum sequence identity 0.8 and minimum alignment coverage 0.7. A representative set of proteins (167 sequences) was aligned with Promals3D¹³⁷ and trimmed with trimal¹³⁸ using the -gappyout option, leading to 351 amino acid positions. The phylogenetic tree was constructed by IQTree¹³⁹ with –auto and fast bootstrap options (VT + F + R5 model was selected). The tree was visualized in itol¹⁴⁰, and branches with support values < 0.8 were collapsed.

Identification of pPG-cleaving, pPG-recognition modules, Ig-like domains and DGRs

We demarcated viral families of Methanobacteriales according to the proteome-based tree generated by the VIPTree program¹⁴¹ and the percentage of shared protein clusters (viruses within one family share > 30% of genes). We then annotated all pPG-cleaving domains using the hhpred server¹³⁵ .

To identify Ig-like domains including domains translated by a programmed frameshift, nucleotide sequences of viruses were translated into six frames, and ORFs longer than 30 amino acids were selected using the seqinr R package¹⁴². Translated ORFs were searched against the Pfam database (release 35) with hhscan (-E 0.01). We selected only hits to beta-sandwich domains (Pfam clans CL0159, CL0011, CL0287, CL0202). Overlapping Pfam hits were merged with the “reduce” function in the Granges package¹⁴³, and resulting regions were filtered by the length of the aligned viral sequence (> 30 aa). Identified Ig-like domains in six frame translations were mapped back to viral proteins with blastp (-evalue 1e-20) and to viral genomes with tblastn (-evalue 1e-20). DGRs were predicted using the myDGR server¹⁴⁴.

Gene-sharing network

The gene-sharing network was built by Vcontact⁸⁰ with default parameters and analyzed in Cytoscape¹⁴⁵. Briefly, the protein sequences of all MGEs were identified by Prokka¹⁴⁶ and combined with protein sequences of viruses from the Refseq database. The total collection of protein sequences was then classified into clusters by the MCL algorithm. The similarity measure for each pair of MGEs was calculated by Vcontact¹⁴⁷ based on the number of shared protein clusters and the total amount of clusters in the NCBI Bacterial and Archaeal Viral Refseq V85 database. Host assignment was added before the visualization of the gene-sharing network in Cytoscape. During the visualization step, viruses of bacteria not related to archaeal MGEs were discarded to achieve better clarity of the resulting network. In the gene-sharing network, each node represents an MGE, and two nodes are connected if the respective MGEs share more than three protein clusters. The positioning of nodes was optimized by the “Organic algorithm”, which reunites nodes with the same neighbors¹⁴⁸.

Data availability

All nucleotide and protein sequences of identified (pro)viruses and plasmids as well as the CRISPR database are provided in Supplementary Data.

Contributions

S.M. carried out all analysis. G.B., M.K. and S.G. conceived and supervised the study. All authors wrote the paper.

Acknowledgements

This work was supported by the French National Agency for Research Grants Viromet (ANR-20-CE20-009-01) and Methevol (ANR-19-CE02-0005-01), and by the French Government's Investissement d'Avenir program, Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" (grant n°ANR-10-LABX-62-IBEID). We thank the computational and storage services (Maestro cluster) provided by the IT department at Institut Pasteur, Paris.

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A global virome of methanogenic archaea highlights novel diversity and adaptations to the gut environment

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Abstract

Figures

Introduction

Results And Discussion

Identification of mobile genetic elements of methanogenic archaea

A rich repertoire of MGEs associated with all major lineages of methanogenic archaea

Functional annotation of methanogens MGEs

Viruses of Methanobacteriales contain proteins to cross the pseudo-peptidoglycan cell wall

Concluding Remarks

Methods

Assembly of databases

Identification of MGEs

Host assignment

Phylogenetic tree of head-tailed viruses

Identification of pPG-cleaving, pPG-recognition modules, Ig-like domains and DGRs

Gene-sharing network

Declarations

References

Additional Declarations

Supplementary Files

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