Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Phages with a broad host range are common across ecosystems

Nature Microbiology volume 10, pages 2537–2549 (2025)Cite this article

Subjects

Abstract

Phages are diverse and abundant within microbial communities, where they play major roles in their evolution and adaptation. Phage replication, and multiplication, is generally thought to be restricted within a single or narrow host range. Here we use published and newly generated proximity-ligation-based metagenomic Hi-C (metaHiC) data from various environments to explore virus–host interactions. We reconstructed 4,975 microbial and 6,572 phage genomes of medium quality or higher. MetaHiC yielded a contact network between genomes and enabled assignment of approximately half of phage genomes to their hosts, revealing that a substantial proportion of these phages interact with multiple species in environments as diverse as the oceanic water column or the human gut. This observation challenges the traditional view of a narrow host spectrum of phages by unveiling that multihost associations are common across ecosystems, with implications for how they might impact ecology and evolution and phage therapy approaches.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Principles of MGE binning and host association.
Fig. 2: MetaTOR MGE output from metagenomic datasets.
Fig. 3: Host attribution to the vMAGs.
Fig. 4: Proteomic tree of the characterized vMAGs.

Similar content being viewed by others

Data availability

Sequence data as well as raw assemblies generated in this study have been deposited in the NCBI under the BioProject number PRJNA1169672 (mock community) and PRJNA1169674 (metagenomic datasets). Publicly available datasets as well as newly produced data used in the present study are all listed in Supplementary Table 2 with their associated BioProject ID. All MAG and MGEMAG data are provided as supplementary datasets and are available on Zenodo at https://doi.org/10.5281/zenodo.14851637 (ref. 63).

Code availability

Open-access versions of the programmes and pipelines used (Hicstuff, MetaTOR, HiContacts) are available online on GitHub: Hicstuff v.3.1.2 (https://github.com/koszullab/hicstuff), MetaTOR v.1.3.2 (https://github.com/koszullab/metaTOR) and HiContacts v.1.7.1 (https://github.com/js2264/HiContacts). Other mandatory programmes are also available online: Bowtie2 v.2.4.5 (http://bowtie-bio.sourceforge.net/bowtie2/), SAMtools v.1.9 (http://www.htslib.org/) and Cooler v.0.8.7–0.8.11 (https://cooler.readthedocs.io/en/latest/). The pipeline used in the present study to generate the data is available on GitHub at https://github.com/mmarbout/MetaHiC_pipeline (ref. 64).

References

  1. Salmond, G. P. C. & Fineran, P. C. A century of the phage: past, present and future. Nat. Rev. Microbiol. 13, 777–786 (2015).

    PubMed  CAS  Google Scholar 

  2. Paez-Espino, D. et al. Uncovering Earth’s virome. Nature 536, 425–430 (2016).

    PubMed  CAS  Google Scholar 

  3. Nayfach, S. et al. Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome. Nat. Microbiol. 6, 960–970 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  4. Modi, S. R., Lee, H. H., Spina, C. S. & Collins, J. J. Antibiotic treatment expands the resistance reservoir and ecological network of the phage metagenome. Nature 499, 219–222 (2013).

    PubMed  PubMed Central  CAS  Google Scholar 

  5. Shousha, A. et al. Bacteriophages isolated from chicken meat and the horizontal transfer of antimicrobial resistance genes. Appl. Environ. Microbiol. 81, 4600–4606 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  6. Edwards, R. A., McNair, K., Faust, K., Raes, J. & Dutilh, B. E. Computational approaches to predict bacteriophage–host relationships. FEMS Microbiol. Rev. https://doi.org/10.1093/femsre/fuv048 (2015).

  7. Hwang, Y., Roux, S., Coclet, C., Krause, S. J. E. & Girguis, P. R. Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats. Nat. Microbiol. 8, 946–957 (2023).

    PubMed  PubMed Central  CAS  Google Scholar 

  8. Hedžet, S., Rupnik, M. & Accetto, T. Broad host range may be a key to long-term persistence of bacteriophages infecting intestinal Bacteroidaceae species. Sci. Rep. 12, 21098 (2022).

    PubMed  PubMed Central  Google Scholar 

  9. Göller, P. C. et al. Multi-species host range of staphylococcal phages isolated from wastewater. Nat. Commun. 12, 6965 (2021).

    PubMed  PubMed Central  Google Scholar 

  10. Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J. & Segata, N. Shotgun metagenomics, from sampling to analysis. Nat. Biotechnol. 35, 833–844 (2017).

    PubMed  CAS  Google Scholar 

  11. Gounot, J.-S. et al. Genome-centric analysis of short and long read metagenomes reveals uncharacterized microbiome diversity in Southeast Asians. Nat. Commun. 13, 6044 (2022).

    PubMed  PubMed Central  CAS  Google Scholar 

  12. Nayfach, S. et al. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 39, 578–585 (2021).

    PubMed  CAS  Google Scholar 

  13. Arisdakessian, C. G., Nigro, O. D., Steward, G. F., Poisson, G. & Belcaid, M. CoCoNet: an efficient deep learning tool for viral metagenome binning. Bioinformatics 37, 2803–2810 (2021).

    PubMed  CAS  Google Scholar 

  14. Johansen, J. et al. Genome binning of viral entities from bulk metagenomics data. Nat. Commun. 13, 965 (2022).

    PubMed  PubMed Central  CAS  Google Scholar 

  15. Camargo, A. P. et al. Identification of mobile genetic elements with geNomad. Nat. Biotechnol. https://doi.org/10.1038/s41587-023-01953-y (2023).

  16. Roux, S. et al. iPHoP: an integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria. PLoS Biol. 21, e3002083 (2023).

    PubMed  PubMed Central  CAS  Google Scholar 

  17. Marbouty, M. et al. Metagenomic chromosome conformation capture (meta3C) unveils the diversity of chromosome organization in microorganisms. eLife 3, e03318 (2014).

    PubMed  PubMed Central  Google Scholar 

  18. Beitel, C. W. et al. Strain- and plasmid-level deconvolution of a synthetic metagenome by sequencing proximity ligation products. PeerJ 2, e415 (2014).

    PubMed  PubMed Central  Google Scholar 

  19. Burton, J. N., Liachko, I., Dunham, M. J. & Shendure, J. Species-level deconvolution of metagenome assemblies with Hi-C-based contact probability maps. G3 4, 1339–1346 (2014).

    PubMed  PubMed Central  Google Scholar 

  20. Marbouty, M. & Koszul, R. Metagenome analysis exploiting high-throughput chromosome conformation capture (3C) data. Trends Genet. 31, 673–682 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  21. Stalder, T., Press, M. O., Sullivan, S., Liachko, I. & Top, E. M. Linking the resistome and plasmidome to the microbiome. ISME J. https://doi.org/10.1038/s41396-019-0446-4 (2019).

  22. Marbouty, M., Thierry, A., Millot, G. A. & Koszul, R. MetaHiC phage–bacteria infection network reveals active cycling phages of the healthy human gut. eLife 10, e60608 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  23. Marbouty, M., Baudry, L., Cournac, A. & Koszul, R. Scaffolding bacterial genomes and probing host–virus interactions in gut microbiome by proximity ligation (chromosome capture) assay. Sci. Adv. 3, e1602105 (2017).

    PubMed  PubMed Central  Google Scholar 

  24. Chen, Y., Wang, Y., Paez-Espino, D., Polz, M. F. & Zhang, T. Prokaryotic viruses impact functional microorganisms in nutrient removal and carbon cycle in wastewater treatment plants. Nat. Commun. 12, 5398 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  25. Chevallereau, A. et al. Next-generation ‘-omics’ approaches reveal a massive alteration of host RNA metabolism during bacteriophage infection of Pseudomonas aeruginosa. PLoS Genet. 12, e1006134 (2016).

    PubMed  PubMed Central  Google Scholar 

  26. Baudry, L., Foutel-Rodier, T., Thierry, A., Koszul, R. & Marbouty, M. MetaTOR: a computational pipeline to recover high-quality metagenomic bins from mammalian gut proximity-ligation (meta3C) libraries. Front. Genet. 10, 753 (2019).

    PubMed  PubMed Central  CAS  Google Scholar 

  27. Pan, S., Zhu, C., Zhao, X.-M. & Coelho, L. P. A deep Siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat. Commun. 13, 2326 (2022).

    PubMed  PubMed Central  CAS  Google Scholar 

  28. Du, Y., Fuhrman, J. A. & Sun, F. ViralCC retrieves complete viral genomes and virus–host pairs from metagenomic Hi-C data. Nat. Commun. 14, 502 (2023).

    PubMed  PubMed Central  CAS  Google Scholar 

  29. Marie-Nelly, H. et al. High-quality genome (re)assembly using chromosomal contact data. Nat. Commun. 5, 5695 (2014).

    PubMed  CAS  Google Scholar 

  30. Bickhart, D. M. et al. Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation. Genome Biol. 20, 153 (2019).

    PubMed  PubMed Central  Google Scholar 

  31. Yaffe, E. & Relman, D. A. Tracking microbial evolution in the human gut using Hi-C reveals extensive horizontal gene transfer, persistence and adaptation. Nat. Microbiol. https://doi.org/10.1038/s41564-019-0625-0 (2019).

  32. Press, M. O. et al. Hi-C deconvolution of a human gut microbiome yields high-quality draft genomes and reveals plasmid-genome interactions. Preprint at bioRxiv https://doi.org/10.1101/198713 (2017).

  33. Kalmar, L. et al. HAM-ART: an optimised culture-free Hi-C metagenomics pipeline for tracking antimicrobial resistance genes in complex microbial communities. PLoS Genet. 18, e1009776 (2022).

    PubMed  PubMed Central  CAS  Google Scholar 

  34. Varona, N. S. et al. Host-specific viral predation network on coral reefs. ISME J. 18, wrae240 (2024).

    PubMed  PubMed Central  CAS  Google Scholar 

  35. DeMaere, M. Z. et al. Metagenomic Hi-C of a healthy human fecal microbiome transplant donor. Microbiol. Resour. Announc. 9, e01523-19 (2020).

    PubMed  PubMed Central  Google Scholar 

  36. Rojas, C. A., Gardy, J., Eisen, J. A. & Ganz, H. H. Recovery of 52 bacterial genomes from the fecal microbiome of the domestic cat (Felis catus) using Hi-C proximity ligation and shotgun metagenomics. Microbiol. Resour. Announc. 12, e0060123 (2023).

    PubMed  Google Scholar 

  37. Kent, A. G., Vill, A. C., Shi, Q., Satlin, M. J. & Brito, I. L. Widespread transfer of mobile antibiotic resistance genes within individual gut microbiomes revealed through bacterial Hi-C. Nat. Commun. 11, 4379 (2020).

    PubMed  PubMed Central  CAS  Google Scholar 

  38. Ivanova, V. et al. Hi-C metagenomics in the ICU: exploring clinically relevant features of gut microbiome in chronically critically ill patients. Front. Microbiol. 12, 770323 (2022).

    PubMed  PubMed Central  Google Scholar 

  39. Bickhart, D. M. et al. Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities. Nat. Biotechnol. 40, 711–719 (2022).

    PubMed  CAS  Google Scholar 

  40. Piligrimova, E. G. et al. Putative plasmid prophages of Bacillus cereus sensu lato may hold the key to undiscovered phage diversity. Sci. Rep. 11, 7611 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  41. Pfeifer, E., Moura de Sousa, J. A., Touchon, M. & Rocha, E. P. C. Bacteria have numerous distinctive groups of phage-plasmids with conserved phage and variable plasmid gene repertoires. Nucleic Acids Res. 49, 2655–2673 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  42. Bouras, G. et al. Pharokka: a fast scalable bacteriophage annotation tool. Bioinformatics 39, btac776 (2022).

    PubMed Central  Google Scholar 

  43. Al-Shayeb, B. et al. Clades of huge phages from across Earth’s ecosystems. Nature 578, 425–431 (2020).

    PubMed  PubMed Central  CAS  Google Scholar 

  44. Du, Y. & Sun, F. HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps. Genome Biol. 23, 63 (2022).

    PubMed  PubMed Central  CAS  Google Scholar 

  45. Nishimura, Y. et al. ViPTree: the viral proteomic tree server. Bioinformatics 33, 2379–2380 (2017).

    PubMed  CAS  Google Scholar 

  46. Shkoporov, A. N. et al. Long-term persistence of crAss-like phage crAss001 is associated with phase variation in Bacteroides intestinalis. BMC Biol. 19, 163 (2021).

    PubMed  PubMed Central  CAS  Google Scholar 

  47. Guerin, E. et al. Biology and taxonomy of crAss-like bacteriophages, the most abundant virus in the human gut. Cell Host Microbe 24, 653–664.e6 (2018).

  48. Schmidtke, D. T. et al. The prototypic crAssphage is a linear phage-plasmid. Cell Host Microbe 33, 1347–1362.e5 (2025).

    PubMed  PubMed Central  CAS  Google Scholar 

  49. Beaulaurier, J. et al. Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation. Nat. Biotechnol. 36, 61–69 (2018).

    PubMed  CAS  Google Scholar 

  50. Ravi, A., Valdés-Varela, L., Gueimonde, M. & Rudi, K. Transmission and persistence of IncF conjugative plasmids in the gut microbiota of full-term infants. FEMS Microbiol. Ecol. 94, fix158 (2018).

  51. Brödel, A. K. et al. In situ targeted base editing of bacteria in the mouse gut. Nature 632, 877–884 (2024).

    PubMed  PubMed Central  Google Scholar 

  52. Lamy-Besnier, Q. et al. Chromosome folding and prophage activation reveal specific genomic architecture for intestinal bacteria. Microbiome 11, 111 (2023).

    PubMed  PubMed Central  CAS  Google Scholar 

  53. Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).

    PubMed  CAS  Google Scholar 

  54. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    PubMed  PubMed Central  CAS  Google Scholar 

  55. Matthey-Doret, C. et al. koszullab/hicstuff: use miniconda layer for docker and improved P(s) normalisation. Zenodo https://doi.org/10.5281/zenodo.4066363 (2020).

  56. Cournac, A., Marie-Nelly, H., Marbouty, M., Koszul, R. & Mozziconacci, J. Normalization of a chromosomal contact map. BMC Genomics 13, 436 (2012).

    PubMed  PubMed Central  CAS  Google Scholar 

  57. Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  58. Bowers, R. M. et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).

    PubMed  PubMed Central  CAS  Google Scholar 

  59. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    PubMed  PubMed Central  CAS  Google Scholar 

  60. Abdennur, N. & Mirny, L. A. Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics 36, 311–316 (2019).

    PubMed Central  Google Scholar 

  61. Serizay, J., Matthey-Doret, C., Bignaud, A., Baudry, L. & Koszul, R. Orchestrating chromosome conformation capture analysis with Bioconductor. Nat. Commun. 15, 1072 (2024).

    PubMed  PubMed Central  CAS  Google Scholar 

  62. Letunic, I. & Bork, P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242–W245 (2016).

    PubMed  PubMed Central  CAS  Google Scholar 

  63. Marbouty, M. Phages with a broad host range are common across ecosystems. Zenodo https://doi.org/10.5281/zenodo.14851637 (2025).

  64. Bignaud, A., Serizay, J., Baudry, L., Matthey-Doret, C. & Marbouty, M. Metagenomic Tridimensional Organisation-based Reassembly. GitHub https://github.com/mmarbout/MetaHiC_pipeline (2024).

Download references

Acknowledgements

We thank P. Moreau for assistance during experimental work, the different teams of the Microbiology department from Institut Pasteur, and especially J. Czarnecki for providing bacterial pellets; D. d’Alelio from the Stazione Zoologica Anton Dohrm for help with the oceanic sample; and the hacienda Vergel de Gaudalupe for allowing us to sample their fermenter. This research was funded, in whole or in part, by Agence nationale pour la recherche ANR-20-CE92-0048 to M.M. and L.D. and ANR-16-JPEC-0003–05 to R.K. and by a grant from the French government, managed by the Agence Nationale de la Recherche under the France 2030 programme (ANR-23-CHBS-0002) to R.K. The Biomics Platform, C2RT, Institut Pasteur, Paris, France, is supported by France Génomique (ANR-10-INBS-09) and IBISA. A.B. was supported by an ENS fellowship from the French Ministry of Higher Education, Research and Innovation. D.E.C. is supported by a PhD grant from the PhastGut project. A.B. and D.E.C. belong to Ecole Doctorale Complexité du vivant ED515 of Sorbonne Université. L.M., M.G.-O. and M.C.-G. were supported by funding from Programa de Apoyo a Proyectos de Investigacion e Innovacion Technologica (DGAPA-UNAM – IN212524). Sequencing and library preparation was supported by Agencia Nacional de Investigación e Innovación (ANII-Uruguay) grant number FSGSK_1_2019_1_159735 and Fondo para la Convergencia Estructural del MERCOSUR (FOCEM). Illustrations used in the present publication (Figs. 1 and 3 and Extended Data Fig. 2) were obtained from the Internet under a Creative Commons CC0 license (https://svgsilh.com/fr/). A CC-BY public copyright license has been applied by the authors to the present document and on all subsequent versions up to the author-accepted manuscript version arising from this submission, in accordance with the grants’ open-access conditions.

Author information

Author notes

  1. These authors contributed equally: Amaury Bignaud, Martial Marbouty.

Authors and Affiliations

  1. Spatial Regulation of Genomes Group, Institut Pasteur, CNRS UMR 3525, Université Paris Cité, Paris, France

    Amaury Bignaud, Devon E. Conti, Agnès Thierry, Jacques Serizay, Romain Koszul & Martial Marbouty

  2. Collège Doctoral, Sorbonne Université, Paris, France

    Amaury Bignaud & Devon E. Conti

  3. Bacteriophage Bacterium Host, Institut Pasteur, Université Paris Cité, CNRS UMR6047, Paris, France

    Devon E. Conti & Laurent Debarbieux

  4. Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France

    Karine Labadie

  5. Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France

    Julie Poulain

  6. Clinical Research Coordination Office, Institut Pasteur, Université Paris Cité, Paris, France

    Olivia Cheny

  7. Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Querétaro, Mexico

    Maritrini Colón-González, Marianna Guerrero-Osornio & Lucia Morales

  8. Department of Infectious Diseases, School of Immunology and Microbial Sciences, Guy’s Hospital , King’s College London, London, UK

    Sophie Helaine & Peter Hill

  9. Médecine petite enfance, Orsay, France

    Gwenaelle Le Tinier

  10. Bioinformatics and Biostatistics Hub, Institut Pasteur, Université Paris Cité, Paris, France

    Gael A. Millot

  11. Microbial Genomics Laboratory, Institut Pasteur de Montevideo, Montevideo, Uruguay

    Andrés Parada, Nadia Riera & Gregorio Iraola

  12. Departamento de Ecología y Evolución, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay

    Andrés Parada

Authors
  1. Amaury Bignaud
    View author publications

    Search author on:PubMed Google Scholar

  2. Devon E. Conti
    View author publications

    Search author on:PubMed Google Scholar

  3. Agnès Thierry
    View author publications

    Search author on:PubMed Google Scholar

  4. Jacques Serizay
    View author publications

    Search author on:PubMed Google Scholar

  5. Karine Labadie
    View author publications

    Search author on:PubMed Google Scholar

  6. Julie Poulain
    View author publications

    Search author on:PubMed Google Scholar

  7. Olivia Cheny
    View author publications

    Search author on:PubMed Google Scholar

  8. Maritrini Colón-González
    View author publications

    Search author on:PubMed Google Scholar

  9. Laurent Debarbieux
    View author publications

    Search author on:PubMed Google Scholar

  10. Marianna Guerrero-Osornio
    View author publications

    Search author on:PubMed Google Scholar

  11. Sophie Helaine
    View author publications

    Search author on:PubMed Google Scholar

  12. Peter Hill
    View author publications

    Search author on:PubMed Google Scholar

  13. Gwenaelle Le Tinier
    View author publications

    Search author on:PubMed Google Scholar

  14. Gael A. Millot
    View author publications

    Search author on:PubMed Google Scholar

  15. Lucia Morales
    View author publications

    Search author on:PubMed Google Scholar

  16. Andrés Parada
    View author publications

    Search author on:PubMed Google Scholar

  17. Nadia Riera
    View author publications

    Search author on:PubMed Google Scholar

  18. Gregorio Iraola
    View author publications

    Search author on:PubMed Google Scholar

  19. Romain Koszul
    View author publications

    Search author on:PubMed Google Scholar

  20. Martial Marbouty
    View author publications

    Search author on:PubMed Google Scholar

Contributions

A.B., R.K. and M.M. conceptualized the study. A.B., R.K. and M.M. designed the methodology. A.B. and M.M. designed software. M.M. performed validation. M.M. conducted investigations, with contributions from J.S., G.L.T., O.C., N.R., D.E.C., A.T., M.G.-O., M.C.-G., J.P. and K.L. A.B. and M.M. conducted formal analysis, with contributions from A.P., G.A.M. and J.S. M.M. and A.B. curated data. D.E.C., G.I., N.R., M.M., K.L., L.M., A.T., A.B., J.P., P.H., D.E.C., G.L.T., M.G.-O. and M.C.-G. procured resources. M.M. and R.K. performed visualization. M.M., R.K. and A.B. wrote the original draft. All authors edited the paper. M.M., R.K., S.H., L.M., G.I., L.D., G.L.T. and O.C. supervised the project. M.M., G.I., L.D. and R.K. acquired funding. M.M. and R.K. administered the project.

Corresponding authors

Correspondence to Romain Koszul or Martial Marbouty.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Microbiology thanks Louis-Patrick Haraoui and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 contact map of the mock community.

Normalized contact map (bin = 16 kb) of the mock community. Black lines delineate the different DNA molecules. Genomic coordinates are indicated on the sides of the contact map and the scale bar is indicated under. Some bacteria exhibit an abundance below our detection threshold (~0.1 %) and therefore appear as white squares in the contact map.

Extended Data Fig. 2 datasets and pipeline used in the present study.

Datasets used in the present study. The number of each type of sample is indicated next to each drawing. The different softwares used to generate and analyze the data are indicated in diamond. (SG : Shotgun). Figure adapted from SVG Silh under a CC 1.0 license.

Extended Data Fig. 3 Phylogenetic tree of the MAGs.

Phylogenetic tree of medium and high-quality MAGs obtained across all datasets using MetaTOR. The tree is decorated with different annotations. From inner to outer: sample data (1- sample type: environment or gut; 2- ecosystem: wastewater, hydrothermal mat, fermenter, ocean, mammal, bird; 3- geographic location: Europe, North America, South America, Asia), MAG taxonomy (1- Phylum, 2- Class, 3- Order, 4- Family, 5- Genus), MAG quality (completion - green, contamination - red), MAG size in bp. The different legends for the annotations are indicated above the tree.

Extended Data Fig. 4 Contigs contact map of different large vMAGs.

Raw contact map of six vMAGs. Black lines delineate the boundaries of the different contigs. Sample (environment), vMAG ID, taxonomic annotation, quality and size are indicated above contact maps while scale bars are present on the left.

Extended Data Fig. 5 Contact maps of MGEMAGs and their different hosts.

Intra- and inter- contact maps obtained of vMAG exhibiting multiple hosts (50kb bins). Sample (environmental) origin and vMAG references are indicated above and below each contact map. Dark lines indicate boundaries of the different genomic entities. Black triangles point at vMAGS. Scale bars (raw scores) are indicated aside each contact map. a. vMAGs with clear contact with multiple microbial MAGs that do not display noise signals between them. b. vMAGs with clear contact with multiple microbial MAGs exhibiting noise signals between them. c. vMAGs with low contact signal with multiple microbial MAGs.

Extended Data Fig. 6 Multihost vMAGs features.

a. Violin plot of the log(size) of vMAGs as a function of their host number. b. Violin plot of the log(RPKM) of vMAGs as a function of their host number (RPKM: Reads Per Kilobase Million). c. Bar plot of vMAGs proportion as a function of their host assignment for the different processed environments encompassing a sufficient number of vMAGs (gut, ocean, hydrothermal mat and wastewater). The different categories are indicated by colors (white = no host assigned, orange = multiple host assigned, red = one contaminated [conta] host assigned, grey = one LQ host assigned, blue = one MQ characterized host assigned, darkblue = one HQ host assigned).

Extended Data Fig. 7 Proteomic tree of the Crassphages family and related phages infecting Bacteroidetes.

Proteomic tree of the different Crassvirales and related phages characterized in the present study. The Tree also encompasses different representative reference Crass genomes from Guerin et al.57, indicated by a black star. The different crass families are indicated by colored areas over the branches. The tree is decorated with different informations (from the inside to the outside): i) sample type, ii) reference genomes (black stars), iii) geNomad annotation (blue = virus; red = plasmid), iv) vMAG taxonomy (order, genus), v) host taxonomy (phylum, class, order, family, genus) white if no host or multiple host attributed), vi) vMAG exhibiting multiple hosts (red circles), vii) vMAG genome size (scale bar = 100 kb).

Supplementary information

Supplementary Information

Supplementary Figs. 1–3.

Reporting Summary

Peer Review File

Supplementary Table 1

Reference genomes of the different species present in the mock community. NA, not applicable.

Supplementary Table 2

Metagenomic datasets used in the present study. Grey colours delimit the different studies.

Supplementary Table 3

Metadata associated with the newly generated samples. ND, not determined.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bignaud, A., Conti, D.E., Thierry, A. et al. Phages with a broad host range are common across ecosystems. Nat Microbiol 10, 2537–2549 (2025). https://doi.org/10.1038/s41564-025-02108-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41564-025-02108-2

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology