Skip to content
1887

Microbial Genomics logo Microbial Genomics

Volume 9, Issue 9

Host interactions of novel species belonging to multiple families infecting bacterial host, WH2 Open Access

Abstract

Bacteroides, the prominent bacteria in the human gut, play a crucial role in degrading complex polysaccharides. Their abundance is influenced by phages belonging to the order. Despite identifying over 600 genomes computationally, only few have been successfully isolated. Continued efforts in isolation of more genomes can provide insights into phage-host-evolution and infection mechanisms. We focused on wastewater samples, as potential sources of phages infecting various hosts. Sequencing, assembly, and characterization of isolated phages revealed 14 complete genomes belonging to three novel species infecting WH2. These species, sp. ‘tikkala’ strain Bc01, sp. ‘frurule’ strain Bc03, and ‘Rudgehvirus jaberico’ strain Bc11, spanned two families, and three genera, displaying a broad range of virion productions. Upon testing all successfully cultured species and their respective bacterial hosts, we discovered that they do not exhibit co-evolutionary patterns with their bacterial hosts. Furthermore, we observed variations in gene similarity, with greater shared similarity observed within genera. However, despite belonging to different genera, the three novel species shared a unique structural gene that encodes the tail spike protein. When investigating the relationship between this gene and host interaction, we discovered evidence of purifying selection, indicating its functional importance. Moreover, our analysis demonstrated that this tail spike protein binds to the TonB-dependent receptors present on the bacterial host surface. Combining these observations, our findings provide insights into phage-host interactions and present three species as an ideal system for controlled infectivity experiments on one of the most dominant members of the human enteric virome.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): co-evolution , Crassvirales , phage-host-interaction , purifying selection , tail spike protein , TonB-depdenent receptors and wastewater
Funding
This study was supported by the:
  • Narodowa Agencja Wymiany Akademickiej (Award BPN/BEK/2021/1/00416)
    • Principal Award Recipient: PrzemysławDecewicz
  • Division of Diabetes, Endocrinology, and Metabolic Diseases (Award RC2DK116713)
    • Principal Award Recipient: WangDavidLuqueAntoni
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001100
2023-09-04
2026-01-18

Metrics

Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/9/mgen001100.html?itemId=/content/journal/mgen/10.1099/mgen.0.001100&mimeType=html&fmt=ahah

References

  1. Hou K, Wu Z-X, Chen X-Y, Wang J-Q, Zhang D et al. Microbiota in health and diseases. Signal Transduct Target Ther 2022; 7:135 [View Article] [PubMed]
     [Google Scholar]
  2. Integrative HMP (iHMP) Research Network Consortium The integrative human microbiome project. Nature 2019; 569:641–648 [View Article] [PubMed]
     [Google Scholar]
  3. Shamash M, Maurice CF. Phages in the infant gut: a framework for virome development during early life. ISME J 2022; 16:323–330 [View Article] [PubMed]
     [Google Scholar]
  4. Hugenholtz P, Goebel BM, Pace NR. Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J Bacteriol 1998; 180:6793 [View Article]
     [Google Scholar]
  5. Pace NR, Stahl DA, Lane DJ, Olsen GJ. The analysis of natural microbial populations by ribosomal RNA sequences. In Marshall KC. eds Advances in Microbial Ecology [Internet] Boston, MA: Springer US; 1986 pp 1–55 [View Article]
     [Google Scholar]
  6. Inglis LK, Edwards RA. How metagenomics has transformed our understanding of bacteriophages in microbiome research. Microorganisms 2022; 10:1671 [View Article] [PubMed]
     [Google Scholar]
  7. Roach MJ, Beecroft SJ, Mihindukulasuriya KA, Wang L, Paredes A et al. Hecatomb: an end-to-end research platform for viral metagenomics. bioRxiv 20222022 [View Article]
     [Google Scholar]
  8. Hesse RD, Roach M, Kerr EN, Papudeshi B, Lima LFO et al. Phage diving: an exploration of the carcharhinid shark epidermal virome. Viruses 2022; 14:1969 [View Article] [PubMed]
     [Google Scholar]
  9. Anthenelli M, Jasien E, Edwards R, Bailey B, Felts B et al. Phage and bacteria diversification through a prophage acquisition ratchet. bioRxiv 2020 [View Article]
     [Google Scholar]
  10. Knowles B, Silveira CB, Bailey BA, Barott K, Cantu VA et al. Lytic to temperate switching of viral communities. Nature 2016; 531:466–470 [View Article]
     [Google Scholar]
  11. Chevallereau A, Pons BJ, van Houte S, Westra ER. Interactions between bacterial and phage communities in natural environments. Nat Rev Microbiol 2022; 20:49–62 [View Article] [PubMed]
     [Google Scholar]
  12. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010; 464:59–65 [View Article] [PubMed]
     [Google Scholar]
  13. HMP Consortium Structure, function and diversity of the healthy human microbiome. Nature 2012; 486:207–214 [View Article] [PubMed]
     [Google Scholar]
  14. Pargin E, Roach MJ, Skye A, Papudeshi B, Inglis LK et al. The human gut virome: composition, colonization, interactions, and impacts on human health. Front Microbiol 2023; 14963173 [View Article] [PubMed]
     [Google Scholar]
  15. Yutin N, Benler S, Shmakov SA, Wolf YI, Tolstoy I et al. Analysis of metagenome-assembled viral genomes from the human gut reveals diverse putative CrAss-like phages with unique genomic features. Nat Commun 2021; 12:1044 [View Article] [PubMed]
     [Google Scholar]
  16. Edwards RA, Vega AA, Norman HM, Ohaeri M, Levi K et al. Global phylogeography and ancient evolution of the widespread human gut virus crAssphage. Nat Microbiol 2019; 4:1727–1736 [View Article] [PubMed]
     [Google Scholar]
  17. Rossi A, Treu L, Toppo S, Zschach H, Campanaro S et al. Evolutionary study of the crassphage virus at gene level. Viruses 2020; 12:1035 [View Article] [PubMed]
     [Google Scholar]
  18. Norman JM, Handley SA, Baldridge MT, Droit L, Liu CY et al. Disease-specific alterations in the enteric virome in inflammatory bowel disease. Cell 2015; 160:447–460 [View Article] [PubMed]
     [Google Scholar]
  19. Dutilh BE, Cassman N, McNair K, Sanchez SE, Silva GGZ et al. A highly abundant bacteriophage discovered in the unknown sequences of human faecal metagenomes. Nat Commun 2014; 5:4498 [View Article] [PubMed]
     [Google Scholar]
  20. Shkoporov AN. Create one new order (Crassvirales) including four new families, ten new subfamilies, 42 new genera and 73 new species (Caudoviricetes) 2021 https://ictv.global/ictv/proposals/2021.022B.R.Crassvirales.zip
     [Google Scholar]
  21. Dutilh BE, Varsani A, Tong Y, Simmonds P, Sabanadzovic S et al. Perspective on taxonomic classification of uncultivated viruses. Curr Opin Virol 2021; 51:207–215 [View Article] [PubMed]
     [Google Scholar]
  22. Walker PJ, Siddell SG, Lefkowitz EJ, Mushegian AR, Adriaenssens EM et al. Recent changes to virus taxonomy ratified by the International Committee on Taxonomy of Viruses (2022). Arch Virol 2022; 167:2429–2440 [View Article]
     [Google Scholar]
  23. Borges AL, Lou YC, Sachdeva R, Al-Shayeb B, Penev PI et al. Widespread stop-codon recoding in bacteriophages may regulate translation of lytic genes. Nat Microbiol 2022; 7918–927 [View Article] [PubMed]
     [Google Scholar]
  24. Ivanova NN, Schwientek P, Tripp HJ, Rinke C, Pati A et al. Stop codon reassignments in the wild. Science 2014; 344:909–913 [View Article]
     [Google Scholar]
  25. Crisci MA, Chen L-X, Devoto AE, Borges AL, Bordin N et al. Closely related Lak megaphages replicate in the microbiomes of diverse animals. iScience 2021; 24:102875 [View Article]
     [Google Scholar]
  26. Peters SL, Borges AL, Giannone RJ, Morowitz MJ, Banfield JF et al. Experimental validation that human microbiome phages use alternative genetic coding. Nat Commun 2022; 13:5710 [View Article] [PubMed]
     [Google Scholar]
  27. Shkoporov AN, Khokhlova EV, Fitzgerald CB, Stockdale SR, Draper LA et al. ΦCrAss001 represents the most abundant bacteriophage family in the human gut and infects bacteroides intestinalis. Nat Commun 2018; 9:4781 [View Article] [PubMed]
     [Google Scholar]
  28. Hryckowian AJ, Merrill BD, Porter NT, Van Treuren W, Nelson EJ et al. Bacteroides thetaiotaomicron-infecting bacteriophage isolates inform sequence-based host range predictions. Cell Host Microbe 2020; 28:371–379 [View Article] [PubMed]
     [Google Scholar]
  29. Guerin E, Shkoporov AN, Stockdale SR, Comas JC, Khokhlova EV et al. Isolation and characterisation of ΦcrAss002, a crAss-like phage from the human gut that infects bacteroides xylanisolvens. Microbiome 2021; 9:89 [View Article] [PubMed]
     [Google Scholar]
  30. Shkoporov AN, Khokhlova EV, Stephens N, Hueston C, Seymour S et al. Long-term persistence of crAss-like phage crAss001 is associated with phase variation in bacteroides intestinalis. BMC Biol 2021; 19:163 [View Article] [PubMed]
     [Google Scholar]
  31. Porter NT, Hryckowian AJ, Merrill BD, Fuentes JJ, Gardner JO et al. Phase-variable capsular polysaccharides and lipoproteins modify bacteriophage susceptibility in bacteroides thetaiotaomicron. Nat Microbiol 2020; 5:1170–1181 [View Article] [PubMed]
     [Google Scholar]
  32. Bayfield OW, Shkoporov AN, Yutin N, Khokhlova EV, Smith JLR et al. Structural atlas of a human gut crassvirus. Nature 2023; 617:409–416 [View Article] [PubMed]
     [Google Scholar]
  33. McNulty NP, Wu M, Erickson AR, Pan C, Erickson BK et al. Effects of diet on resource utilization by a model human gut microbiota containing bacteroides cellulosilyticus WH2, a symbiont with an extensive glycobiome. PLoS Biol 2013; 11:e1001637 [View Article] [PubMed]
     [Google Scholar]
  34. Summer EJ. Preparation of a phage DNA fragment library for whole genome shotgun sequencing. Methods Mol Biol 2009; 502:27–46 [View Article] [PubMed]
     [Google Scholar]
  35. Kim AH, Armah G, Dennis F, Wang L, Rodgers R et al. Enteric virome negatively affects seroconversion following oral rotavirus vaccination in a longitudinally sampled cohort of Ghanaian infants. Cell Host & Microbe 2022; 30:110–123 [View Article]
     [Google Scholar]
  36. Wick RR. Filtlong: Tool for filtering long reads by quality 2018 https://github.com/rrwick/Filtlong/
     [Google Scholar]
  37. Cantu VA, Sadural J, Edwards R. PRINSEQ++, a multi-threaded tool for fast and efficient quality control and preprocessing of sequencing datasets. PeerJ Preprints 2019 [View Article]
     [Google Scholar]
  38. Roach MJ, Pierce-Ward NT, Suchecki R, Mallawaarachchi V, Papudeshi B et al. Ten simple rules and a template for creating workflows-as-applications. PLoS Comput Biol 2022; 18:e1010705 [View Article] [PubMed]
     [Google Scholar]
  39. Kolmogorov M, Yuan J, Lin Y, Pevzner PA. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 2019; 37:540–546 [View Article] [PubMed]
     [Google Scholar]
  40. Li D, Luo R, Liu C-M, Leung C-M, Ting H-F et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 2016; 102:3–11 [View Article]
     [Google Scholar]
  41. Wick RR, Schultz MB, Zobel J, Holt KE. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 2015; 31:3350–3352 [View Article] [PubMed]
     [Google Scholar]
  42. Mallawaarachchi V, Wickramarachchi A, Lin Y. GraphBin: refined binning of metagenomic contigs using assembly graphs. Bioinformatics 2020; 36:3307–3313 [View Article] [PubMed]
     [Google Scholar]
  43. Mallawaarachchi VG, Lin Y. MetaCoAG: binning metagenomic contigs via composition, coverage and assembly graphs. Res Comput Mol Biol 2022 [View Article]
     [Google Scholar]
  44. Mallawaarachchi VG, Wickramarachchi AS, Lin Y. Improving metagenomic binning results with overlapped bins using assembly graphs. Algorithms Mol Biol 2021; 16:3 [View Article] [PubMed]
     [Google Scholar]
  45. Raiko M. viralVerify: viral contig verification tool 2021 https://github.com/ablab/viralVerify
     [Google Scholar]
  46. Woodcroft BJ. CoverM:DNA read coverage and relative abundance calculator 2021 https://github.com/wwood/CoverM
     [Google Scholar]
  47. Zimin AV, Salzberg SL, Ouzounis CA. The genome polishing tool POLCA makes fast and accurate corrections in genome assemblies. PLoS Comput Biol 2020; 16:e1007981 [View Article] [PubMed]
     [Google Scholar]
  48. Carrillo D. CrassUS - Crassvirales Uncovering Software 2022 https://github.com/dcarrillox/CrassUS
     [Google Scholar]
  49. Nakamura T, Yamada KD, Tomii K, Katoh K, Hancock J. Parallelization of MAFFT for large-scale multiple sequence alignments. Bioinformatics 2018; 34:2490–2492 [View Article]
     [Google Scholar]
  50. Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One 2010; 5:e9490 [View Article] [PubMed]
     [Google Scholar]
  51. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res 2019; 47:W256–W259 [View Article] [PubMed]
     [Google Scholar]
  52. Gilchrist CLM, Chooi Y-H. clinker & clustermap.js: automatic generation of gene cluster comparison figures. Bioinformatics 2021; 37:2473–2475 [View Article] [PubMed]
     [Google Scholar]
  53. Chan PP, Lowe TM. tRNAscan-SE: searching for tRNA genes in genomic sequences. Methods Mol Biol 2019; 1962:1–14 [View Article] [PubMed]
     [Google Scholar]
  54. Legendre P, Desdevises Y, Bazin E, Page RDM. A statistical test for host-parasite coevolution. Syst Biol 2002; 51:217–234 [View Article] [PubMed]
     [Google Scholar]
  55. Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods 2012; 9:671–675 [View Article]
     [Google Scholar]
  56. The GIMP Development Team GIMP 2019 https://www.gimp.org
     [Google Scholar]
  57. Luque A, Benler S, Lee DY, Brown C, White S. The missing tailed phages: prediction of small capsid candidates. Microorganisms 2020; 8:1944 [View Article] [PubMed]
     [Google Scholar]
  58. Lee DY, Bartels C, McNair K, Edwards RA, Swairjo MA et al. Predicting the capsid architecture of phages from metagenomic data. Comput Struct Biotechnol J 2022; 20:721–732 [View Article] [PubMed]
     [Google Scholar]
  59. Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 2019; 20:238 [View Article] [PubMed]
     [Google Scholar]
  60. Edgar RC. High-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny. Bioinformatics2021 [View Article]
     [Google Scholar]
  61. Stecher G, Tamura K, Kumar S. Molecular Evolutionary Genetics Analysis (MEGA) for macOS. Mol Biol Evol 2020; 37:1237–1239 [View Article] [PubMed]
     [Google Scholar]
  62. Tamura K, Stecher G, Kumar S, Battistuzzi FU. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 2021; 38:3022–3027 [View Article] [PubMed]
     [Google Scholar]
  63. Li WH, Wu CI, Luo CC. A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes. Mol Biol Evol 1985; 2:150–174 [View Article] [PubMed]
     [Google Scholar]
  64. Kosakovsky Pond SL, Posada D, Gravenor MB, Woelk CH, Frost SDW. GARD: a genetic algorithm for recombination detection. Bioinformatics 2006; 22:3096–3098 [View Article] [PubMed]
     [Google Scholar]
  65. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S et al. ColabFold: making protein folding accessible to all. Nat Methods 2022; 19:679–682 [View Article] [PubMed]
     [Google Scholar]
  66. Li Z, Jaroszewski L, Iyer M, Sedova M, Godzik A. FATCAT 2.0: towards a better understanding of the structural diversity of proteins. Nucleic Acids Res 2020; 48:W60–W64 [View Article] [PubMed]
     [Google Scholar]
  67. Ye Y, Godzik A. Flexible structure alignment by chaining aligned fragment pairs allowing twists. Bioinformatics 2003; 19:ii246–ii255 [View Article]
     [Google Scholar]
  68. Varadi M, Anyango S, Deshpande M, Nair S, Natassia C et al. AlphaFold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res 2022; 50:D439–D444 [View Article] [PubMed]
     [Google Scholar]
  69. Yan Y, Tao H, He J, Huang S-Y. The HDOCK server for integrated protein-protein docking. Nat Protoc 2020; 15: [View Article]
     [Google Scholar]
  70. Nanoporetech Consortium. medaka: Sequence correction provided by ONT Research 2022 https://github.com/nanoporetech/medaka/releases
     [Google Scholar]
  71. Arumugam K, Bağcı C, Bessarab I, Beier S, Buchfink B et al. Annotated bacterial chromosomes from frame-shift-corrected long-read metagenomic data. Microbiome 2019; 7: [View Article]
     [Google Scholar]
  72. Cook R, Brown N, Rihtman B, Michniewski S, Redgwell T et al. The long and short of it: benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies. bioRxiv 2023 [View Article]
     [Google Scholar]
  73. Delesalle VA, Tanke NT, Vill AC, Krukonis GP. Testing hypotheses for the presence of tRNA genes in mycobacteriophage genomes. Bacteriophage 2016; 6:e1219441 [View Article] [PubMed]
     [Google Scholar]
  74. Papudeshi B, Rusch DB, VanInsberghe D, Lively CM, Edwards RA et al. Host association and spatial proximity shape but do not constrain population structure in the mutualistic symbiont Xenorhabdus bovienii. mBio 2023; 14:e0043423 [View Article] [PubMed]
     [Google Scholar]
  75. Nobrega FL, Vlot M, de Jonge PA, Dreesens LL, Beaumont HJE et al. Targeting mechanisms of tailed bacteriophages. Nat Rev Microbiol 2018; 16:760–773 [View Article]
     [Google Scholar]
  76. Pollet RM, Martin LM, Koropatkin NM. TonB-dependent transporters in the bacteroidetes: unique domain structures and potential functions. Mol Microbiol 2021; 115:490–501 [View Article] [PubMed]
     [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001100
Loading
Host interactions of novel Crassvirales species belonging to multiple families infecting bacterial host, Bacteroides cellulosilyticus WH2
M Gen 9, 001100 (2023); https://doi.org/10.1099/mgen.0.001100
/content/journal/mgen/10.1099/mgen.0.001100
/content/journal/mgen/10.1099/mgen.0.001100
Loading

Data & Media loading...

Supplements

Supplementary material 1

EXCEL

Supplementary material 2

EXCEL

Supplementary material 3

EXCEL

Supplementary material 4

EXCEL

Supplementary material 5

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error