Genomic variation landscape of the human gut microbiome

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Abstract

Whereas large-scale efforts have rapidly advanced the understanding and practical impact of human genomic variation, the practical impact of variation is largely unexplored in the human microbiome. We therefore developed a framework for metagenomic variation analysis and applied it to 252 faecal metagenomes of 207 individuals from Europe and North America. Using 7.4 billion reads aligned to 101 reference species, we detected 10.3 million single nucleotide polymorphisms (SNPs), 107,991 short insertions/deletions, and 1,051 structural variants. The average ratio of non-synonymous to synonymous polymorphism rates of 0.11 was more variable between gut microbial species than across human hosts. Subjects sampled at varying time intervals exhibited individuality and temporal stability of SNP variation patterns, despite considerable composition changes of their gut microbiota. This indicates that individual-specific strains are not easily replaced and that an individual might have a unique metagenomic genotype, which may be exploitable for personalized diet or drug intake.

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Figure 1: Genomic variation statistics for 101 gut microbial species prevalent in 252 samples from 207 individuals.
Figure 2: pN/pS ratios of 66 dominant species reveal more variation between species than between individuals.
Figure 3: Individuality and temporal stability of genomic variation patterns.
Figure 4: Inter-continental comparison of gut microbial species.

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Data deposits

Single nucleotide polymorphism data have been submitted to dbSNP under accession numbers ss539238913–ss549853572.

References

  1. 1

    International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007)

  2. 2

    The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010)

  3. 3

    Backhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A. & Gordon, J. I. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920 (2005)

  4. 4

    Hooper, L. V., Midtvedt, T. & Gordon, J. I. How host-microbial interactions shape the nutrient environment of the mammalian intestine. Annu. Rev. Nutr. 22, 283–307 (2002)

  5. 5

    Bagel, S., Hüllen, V., Wiedemann, B. & Heisig, P. Impact of gyrA and parC mutations on quinolone resistance, doubling time, and supercoiling degree of Escherichia coli . Antimicrob. Agents Chemother. 43, 868–875 (1999)

  6. 6

    Eckburg, P. B. et al. Diversity of the human intestinal microbial flora. Science 308, 1635–1638 (2005)

  7. 7

    Morowitz, M. J. et al. Strain-resolved community genomic analysis of gut microbial colonization in a premature infant. Proc. Natl Acad. Sci. USA 108, 1128–1133 (2011)

  8. 8

    Sokurenko, E. V. et al. Pathogenic adaptation of Escherichia coli by natural variation of the FimH adhesin. Proc. Natl Acad. Sci. USA 95, 8922–8926 (1998)

  9. 9

    The Human Microbiome Project Consortium. A framework for human microbiome research. Nature 486, 215–221 (2012)

  10. 10

    Lay, C. et al. Colonic microbiota signatures across five northern European countries. Appl. Environ. Microbiol. 71, 4153–4155 (2005)

  11. 11

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

  12. 12

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

  13. 13

    Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011)

  14. 14

    Tyson, G. W. et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37–43 (2004)

  15. 15

    Allen, E. E. et al. Genome dynamics in a natural archaeal population. Proc. Natl Acad. Sci. USA 104, 1883–1888 (2007)

  16. 16

    Harris, S. R. et al. Evolution of MRSA during hospital transmission and intercontinental spread. Science 327, 469–474 (2010)

  17. 17

    Peterson, J. et al. The NIH Human Microbiome Project. Genome Res. 19, 2317–2323 (2009)

  18. 18

    Ciccarelli, F. D. et al. Toward automatic reconstruction of a highly resolved tree of life. Science 311, 1283–1287 (2006)

  19. 19

    Sorek, R. et al. Genome-wide experimental determination of barriers to horizontal gene transfer. Science 318, 1449–1452 (2007)

  20. 20

    Konstantinidis, K. T. & Tiedje, J. M. Prokaryotic taxonomy and phylogeny in the genomic era: advancements and challenges ahead. Curr. Opin. Microbiol. 10, 504–509 (2007)

  21. 21

    Touchon, M. et al. Organised genome dynamics in the Escherichia coli species results in highly diverse adaptive paths. PLoS Genet. 5, e1000344 (2009)

  22. 22

    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genet. 43, 491–498 (2011)

  23. 23

    Muller, J. et al. eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations. Nucleic Acids Res. 38, D190–D195 (2010)

  24. 24

    Kunz, B. A. & Glickman, B. W. The infidelity of conjugal DNA transfer in Escherichia coli . Genetics 105, 489–500 (1983)

  25. 25

    Simmons, S. L. et al. Population genomic analysis of strain variation in Leptospirillum group II bacteria involved in acid mine drainage formation. PLoS Biol. 6, e177 (2008)

  26. 26

    McDonald, J. H. & Kreitman, M. Adaptive protein evolution at the Adh locus in Drosophila . Nature 351, 652–654 (1991)

  27. 27

    Friedman, R., Drake, J. W. & Hughes, A. L. Genome-wide patterns of nucleotide substitution reveal stringent functional constraints on the protein sequences of thermophiles. Genetics 167, 1507–1512 (2004)

  28. 28

    Novichkov, P. S., Wolf, Y. I., Dubchak, I. & Koonin, E. V. Trends in prokaryotic evolution revealed by comparison of closely related bacterial and archaeal genomes. J. Bacteriol. 191, 65–73 (2009)

  29. 29

    Frey, P. A. The Leloir pathway: a mechanistic imperative for three enzymes to change the stereochemical configuration of a single carbon in galactose. FASEB J. 10, 461–470 (1996)

  30. 30

    Kuhner, S. et al. Proteome organization in a genome-reduced bacterium. Science 326, 1235–1240 (2009)

  31. 31

    Holdeman, L. V. & Moore, W. E. C. New genus, Coprococcus, twelve new species, and emended descriptions of four previously described species of bacteria from human feces. Int. J. Syst. Bacteriol. 24, 260–277 (1974)

  32. 32

    Duncan, S. H., Hold, G. L., Barcenilla, A., Stewart, C. S. & Flint, H. J. Roseburia intestinalis sp. nov., a novel saccharolytic, butyrate-producing bacterium from human faeces. Int. J. Syst. Evol. Microbiol. 52, 1615–1620 (2002)

  33. 33

    Alvarez-Martinez, C. E. & Christie, P. J. Biological diversity of prokaryotic type IV secretion systems. Microbiol. Mol. Biol. Rev. 73, 775–808 (2009)

  34. 34

    Nagai, H. & Roy, C. R. Show me the substrates: modulation of host cell function by type IV secretion systems. Cell Microbiol. 5, 373–383 (2003)

  35. 35

    Kelly, D., Conway, S. & Aminov, R. Commensal gut bacteria: mechanisms of immune modulation. Trends Immunol. 26, 326–333 (2005)

  36. 36

    Jones, B. V., Begley, M., Hill, C., Gahan, C. G. M. & Marchesi, J. R. Functional and comparative metagenomic analysis of bile salt hydrolase activity in the human gut microbiome. Proc. Natl Acad. Sci. USA 105, 13580–13585 (2008)

  37. 37

    Begley, M., Hill, C. & Gahan, C. G. M. Bile salt hydrolase activity in probiotics. Appl. Environ. Microbiol. 72, 1729–1738 (2006)

  38. 38

    Caporaso, J. G. et al. Moving pictures of the human microbiome. Genome Biol. 12, R50 (2011)

  39. 39

    Dethlefsen, L. & Relman, D. A. Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc. Natl Acad. Sci. USA 108, 4554–4561 (2011)

  40. 40

    Zoetendal, E. G., Akkermans, A. D. & De Vos, W. M. Temperature gradient gel electrophoresis analysis of 16S rRNA from human fecal samples reveals stable and host-specific communities of active bacteria. Appl. Environ. Microbiol. 64, 3854–3859 (1998)

  41. 41

    Fierer, N. et al. Forensic identification using skin bacterial communities. Proc. Natl Acad. Sci. USA 107, 6477–6481 (2010)

  42. 42

    Tenaillon, O., Skurnik, D., Picard, B. & Denamur, E. The population genetics of commensal Escherichia coli . Nature Rev. Microbiol. 8, 207–217 (2010)

  43. 43

    Jernberg, C., Lofmark, S., Edlund, C. & Jansson, J. K. Long-term ecological impacts of antibiotic administration on the human intestinal microbiota. ISME J. 1, 56–66 (2007)

  44. 44

    Suzuki, R., Shiota, S. & Yamaoka, Y. Molecular epidemiology, population genetics, and pathogenic role of Helicobacter pylori . Infect. Genet. Evol. 12, 203–213 (2012)

  45. 45

    Yamaoka, Y. Helicobacter pylori typing as a tool for tracking human migration. Clin. Microbiol. Infect. 15, 829–834 (2009)

  46. 46

    Achtman, M. & Wagner, M. Microbial diversity and the genetic nature of microbial species. Nature Rev. Microbiol. 6, 431–440 (2008)

  47. 47

    Morelli, G. et al. Yersinia pestis genome sequencing identifies patterns of global phylogenetic diversity. Nature Genet. 42, 1140–1143 (2010)

  48. 48

    Ye, K., Schulz, M. H., Long, Q., Apweiler, R. & Ning, Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865–2871 (2009)

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Acknowledgements

The authors are grateful to J. Korbel and the members of the Bork group at EMBL for discussions and assistance, especially S. Powell for performing some of the computations. We thank the EMBL IT core facility and Y. Yuan for managing the high-performance computing resources. We would like to thank J. I. Gordon for providing three of the samples used. We are also grateful to the European MetaHIT consortium and the NIH Common Fund Human Microbiome Project Consortium for generating and making available the data sets used in this study. The research leading to these results has received funding from EMBL, the European Community’s Seventh Framework Programme via the MetaHIT (HEALTH-F4-2007-201052) and IHMS (HEALTH-F4-2010-261376) grants as well as from the National Institutes of Health grants U54HG003079 and U54HG004968.

Author information

P.B. and G.M.W. conceived the study. P.B., M.A., G.M.W. and S.R.S. designed the analyses. Si.S., Sh.S., M.A., M.M., J.T., A.Z., A.W., D.R.M., J.R.K., J.M. and K.K. performed the analyses. M.A., Sh.S., Si.S. and P.B. wrote the manuscript. All authors read and approved the manuscript.

Correspondence to George M. Weinstock or Peer Bork.

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The authors declare no competing financial interests.

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Supplementary Information

This file contains Supplementary Methods and Notes, additional references, Supplementary Figures 1-8 and legends for Supplementary Tables 1-15. (PDF 1947 kb)

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This file contains Supplementary Tables 1-15 (see Supplementary Information file for Supplementary Table legends). (XLS 5425 kb)

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Schloissnig, S., Arumugam, M., Sunagawa, S. et al. Genomic variation landscape of the human gut microbiome. Nature 493, 45–50 (2013) doi:10.1038/nature11711

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