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:

Viruses in the faecal microbiota of monozygotic twins and their mothers

Nature volume 466, pages 334–338 (2010)Cite this article

Subjects

Abstract

Viral diversity and life cycles are poorly understood in the human gut and other body habitats. Phages and their encoded functions may provide informative signatures of a human microbiota and of microbial community responses to various disturbances, and may indicate whether community health or dysfunction is manifest after apparent recovery from a disease or therapeutic intervention. Here we report sequencing of the viromes (metagenomes) of virus-like particles isolated from faecal samples collected from healthy adult female monozygotic twins and their mothers at three time points over a one-year period. We compared these data sets with data sets of sequenced bacterial 16S ribosomal RNA genes and total-faecal-community DNA. Co-twins and their mothers share a significantly greater degree of similarity in their faecal bacterial communities than do unrelated individuals. In contrast, viromes are unique to individuals regardless of their degree of genetic relatedness. Despite remarkable interpersonal variations in viromes and their encoded functions, intrapersonal diversity is very low, with >95% of virotypes retained over the period surveyed, and with viromes dominated by a few temperate phages that exhibit remarkable genetic stability. These results indicate that a predatory viral–microbial dynamic, manifest in a number of other characterized environmental ecosystems, is notably absent in the very distal intestine.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Classification of viruses present in VLP preparations generated from faecal samples collected from four families of monozygotic twins and their mothers.
Figure 2: Sample-by-sample view of the proportional representation of KEGG second-level pathways in sequenced VLP-associated viromes and gut microbiomes.
Figure 3: Gnotobiotic mice reveal in vivo activation of the transcriptome of an M. formatexigens prophage.

Similar content being viewed by others

Accession codes

Primary accessions

GenBank/EMBL/DDBJ

Gene Expression Omnibus

Data deposits

Virome data sets reported here are accessible in the NCBI Short Read Archive under accession number SRA012183. 16S rRNA data sets are available in GenBank under accession number SRA020605. RNA-Seq data have been deposited in the Gene Expression Omnibus as series GSE21906 (see Methods for further details).

References

  1. Kunin, V. et al. A bacterial metapopulation adapts locally to phage predation despite global dispersal. Genome Res. 18, 293–297 (2008)

    Article  CAS  Google Scholar 

  2. Tyson, G. W. & Banfield, J. F. Rapidly evolving CRISPRs implicated in acquired resistance of microorganisms to viruses. Environ. Microbiol. 10, 200–207 (2008)

    CAS  Google Scholar 

  3. Angly, F. et al. Genomic analysis of multiple Roseophage SIO1 strains. Environ. Microbiol. 11, 2863–2873 (2009)

    Article  CAS  Google Scholar 

  4. Oliver, K. M., Degnan, P. H., Hunter, M. S. & Moran, N. A. Bacteriophages encode factors required for protection in a symbiotic mutualism. Science 325, 992–994 (2009)

    Article  CAS  ADS  Google Scholar 

  5. Schuch, R. & Fischetti, V. A. The secret life of the anthrax agent Bacillus anthracis: bacteriophage-mediated ecological adaptations. PLoS ONE 4, e6532 (2009)

    Article  ADS  Google Scholar 

  6. Casjens, S. Prophages and bacterial genomics: what have we learned so far? Mol. Microbiol. 49, 277–300 (2003)

    Article  CAS  Google Scholar 

  7. Tettelin, H. et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”. Proc. Natl Acad. Sci. USA 102, 13950–13955 (2005)

    Article  CAS  ADS  Google Scholar 

  8. Finkbeiner, S. R. et al. Metagenomic analysis of human diarrhea: viral detection and discovery. PLoS Pathog. 4, e1000011 (2008)

    Article  Google Scholar 

  9. Breitbart, M. et al. Metagenomic analyses of an uncultured viral community from human feces. J. Bacteriol. 185, 6220–6223 (2003)

    Article  CAS  Google Scholar 

  10. Zhang, T. et al. RNA viral community in human feces: prevalence of plant pathogenic viruses. PLoS Biol. 4, e3 (2006)

    Article  Google Scholar 

  11. Breitbart, M. et al. Viral diversity and dynamics in an infant gut. Res. Microbiol. 159, 367–373 (2008)

    Article  CAS  Google Scholar 

  12. Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009)

    Article  CAS  ADS  Google Scholar 

  13. Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006)

    Article  CAS  Google Scholar 

  14. Turnbaugh, P. J. et al. Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins. Proc. Natl Acad. Sci. USA 107, 7503–7508 (2010)

    Article  CAS  ADS  Google Scholar 

  15. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010)

    Article  CAS  Google Scholar 

  16. Angly, F. E. et al. The marine viromes of four oceanic regions. PLoS Biol. 4, e368 (2006)

    Article  Google Scholar 

  17. Rodriguez-Brito, B. et al. Viral and microbial community dynamics in four aquatic environments. ISME J. 4, 739–751 (2010)

    Article  Google Scholar 

  18. White, J. R., Nagarajan, N. & Pop, M. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput. Biol. 5, e1000352 (2009)

    Article  ADS  Google Scholar 

  19. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004)

    Article  CAS  Google Scholar 

  20. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650 (2009)

    Article  CAS  Google Scholar 

  21. Sharon, I. et al. Photosystem I gene cassettes are present in marine virus genomes. Nature 461, 258–262 (2009)

    Article  CAS  ADS  Google Scholar 

  22. Rodriguez-Valera, F. et al. Explaining microbial population genomics through phage predation. Nature Rev. Microbiol. 7, 828–836 (2009)

    Article  CAS  Google Scholar 

  23. Rey, F. E. et al. Dissecting the in vivo metabolic potential of two human gut acetogens. J. Biol. Chem. 285, 22082–22090 (2010)

    Article  CAS  Google Scholar 

  24. Magnuson, R. D. Hypothetical functions of toxin-antitoxin systems. J. Bacteriol. 189, 6089–6092 (2007)

    Article  CAS  Google Scholar 

  25. DeShazer, D. Genomic diversity of Burkholderia pseudomallei clinical isolates: subtractive hybridization reveals a Burkholderia mallei-specific prophage in B. pseudomallei 1026b. J. Bacteriol. 186, 3938–3950 (2004)

    Article  CAS  Google Scholar 

  26. Heath, A. C. et al. Ascertainment of a mid-western US female adolescent twin cohort for alcohol studies: assessment of sample representativeness using birth record data. Twin Res. 5, 107–112 (2002)

    Article  Google Scholar 

  27. Thurber, R. V., Haynes, M., Breitbart, M., Wegley, L. & Rohwer, F. Laboratory procedures to generate viral metagenomes. Nature Protocols 4, 470–483 (2009)

    Article  CAS  Google Scholar 

  28. Becker, A., Kuster, H., Niehaus, K. & Puhler, A. Extension of the Rhizobium meliloti succinoglycan biosynthesis gene cluster: identification of the exsA gene encoding an ABC transporter protein, and the exsB gene which probably codes for a regulator of succinoglycan biosynthesis. Mol. Gen. Genet. 249, 487–497 (1995)

    Article  CAS  Google Scholar 

  29. Gon, S., Faulkner, M. J. & Beckwith, J. In vivo requirement for glutaredoxins and thioredoxins in the reduction of the ribonucleotide reductases of Escherichia coli. Antioxid. Redox Signal. 8, 735–742 (2006)

    Article  CAS  Google Scholar 

  30. Padovani, D., Thomas, F., Trautwein, A. X., Mulliez, E. & Fontecave, M. Activation of class III ribonucleotide reductase from E. coli. The electron transfer from the iron-sulfur center to S-adenosylmethionine. Biochemistry 40, 6713–6719 (2001)

    Article  CAS  Google Scholar 

  31. Garriga, X. et al. nrdD and nrdG genes are essential for strict anaerobic growth of Escherichia coli. Biochem. Biophys. Res. Commun. 229, 189–192 (1996)

    Article  CAS  Google Scholar 

  32. Tabor, C. W. & Tabor, H. 1,4-Diaminobutane (putrescine), spermidine, and spermine. Annu. Rev. Biochem. 45, 285–306 (1976)

    Article  CAS  Google Scholar 

  33. Gomez-Alvarez, V., Teal, T. K. & Schmidt, T. M. Systematic artifacts in metagenomes from complex microbial communities. ISME J. 3, 1314–1317 (2009)

    Article  Google Scholar 

  34. Hamady, M., Walker, J. J., Harris, J. K., Gold, N. J. & Knight, R. Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex. Nature Methods 5, 235–237 (2008)

    Article  CAS  Google Scholar 

  35. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

    Article  CAS  Google Scholar 

  36. Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007)

    Article  CAS  Google Scholar 

  37. Fouts, D. E. Phage_Finder: automated identification and classification of prophage regions in complete bacterial genome sequences. Nucleic Acids Res. 34, 5839–5851 (2006)

    Article  CAS  Google Scholar 

  38. Angly, F. E. et al. The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes. PLoS Comput. Biol. 5, e1000593 (2009)

    Article  MathSciNet  Google Scholar 

  39. Angly, F. et al. PHACCS, an online tool for estimating the structure and diversity of uncultured viral communities using metagenomic information. BMC Bioinformatics 6, 41 (2005)

    Article  Google Scholar 

  40. Breitbart, M. et al. Genomic analysis of uncultured marine viral communities. Proc. Natl Acad. Sci. USA 99, 14250–14255 (2002)

    Article  CAS  ADS  Google Scholar 

  41. Delcher, A. L., Bratke, K. A., Powers, E. C. & Salzberg, S. L. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics 23, 673–679 (2007)

    Article  CAS  Google Scholar 

  42. Jensen, L. J. et al. STRING 8–a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 37, D412–D416 (2009)

    Article  CAS  Google Scholar 

  43. Finn, R. D. et al. The Pfam protein families database. Nucleic Acids Res. 36, D281–D288 (2008)

    Article  CAS  Google Scholar 

  44. Haft, D. H., Selengut, J. D. & White, O. The TIGRFAMs database of protein families. Nucleic Acids Res. 31, 371–373 (2003)

    Article  CAS  Google Scholar 

  45. Faith, J. J., Olson, A. J., Gardner, T. S. & Sachidanandam, R. Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context. BMC Bioinformatics 8, 344 (2007)

    Article  Google Scholar 

  46. Rohwer, F., Seguritan, V., Choi, D. H., Segall, A. M. & Azam, F. Production of shotgun libraries using random amplification. Biotechniques 31, 108–112, 114–106 118 (2001)

    Article  CAS  Google Scholar 

  47. Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome Biol. 5, R12 (2004)

    Article  Google Scholar 

  48. Grissa, I., Vergnaud, G. & Pourcel, C. CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res. 35, W52–W57 (2007)

    Article  Google Scholar 

  49. Gordon, D., Desmarais, C. & Green, P. Automated finishing with Autofinish. Genome Res. 11, 614–625 (2001)

    Article  CAS  Google Scholar 

  50. R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna) 〈http://www.r-project.org〉 (2009)

Download references

Acknowledgements

We thank S. Wagoner and J. Manchester for technical assistance, J. Faith for help developing Phage_omics and, together with F. Rey, for microbial RNA-Seq data sets, P. Turnbaugh for assistance with faecal metagenomic studies, and B. Rodriguez-Mueller and D. Willner for valuable discussions. This work was supported in part by grants from the NIH (American Recovery and Reinvestment Act supplemental funding of DK78669), the Crohn’s and Colitis Foundation of America and the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. A.R. is the recipient of an International Fulbright Science and Technology Program award.

Author information

Authors and Affiliations

  1. Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, 63108, Missouri, USA

    Alejandro Reyes & Jeffrey I. Gordon

  2. Department of Biology, San Diego State University, San Diego, 92182, California, USA

    Matthew Haynes, Nicole Hanson, Florent E. Angly & Forest Rohwer

  3. Advanced Water Management Centre, The University of Queensland, Brisbane, 4072, Queensland, Australia

    Florent E. Angly

  4. Department of Psychiatry, Washington University School of Medicine, St Louis, 63108, Missouri, USA

    Andrew C. Heath

Authors
  1. Alejandro Reyes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matthew Haynes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nicole Hanson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Florent E. Angly
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrew C. Heath
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Forest Rohwer
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jeffrey I. Gordon
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.R. and J.I.G. designed the experiments; A.C.H. recruited the patients; A.R., M.H. and N.H. generated the data; A.R., F.E.A., F.R. and J.I.G. interpreted the results; and A.R., F.R. and J.I.G. wrote the paper.

Corresponding author

Correspondence to Jeffrey I. Gordon.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains a Supplementary Discussion, Supplementary Figures 1-15 with legends and Supplementary Tables 1-11. (PDF 1245 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Reyes, A., Haynes, M., Hanson, N. et al. Viruses in the faecal microbiota of monozygotic twins and their mothers. Nature 466, 334–338 (2010). https://doi.org/10.1038/nature09199

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature09199

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research