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  • Perspective
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Enterotypes in the landscape of gut microbial community composition

A Publisher Correction to this article was published on 13 February 2018

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Abstract

Population stratification is a useful approach for a better understanding of complex biological problems in human health and wellbeing. The proposal that such stratification applies to the human gut microbiome, in the form of distinct community composition types termed enterotypes, has been met with both excitement and controversy. In view of accumulated data and re-analyses since the original work, we revisit the concept of enterotypes, discuss different methods of dividing up the landscape of possible microbiome configurations, and put these concepts into functional, ecological and medical contexts. As enterotypes are of use in describing the gut microbial community landscape and may become relevant in clinical practice, we aim to reconcile differing views and encourage a balanced application of the concept.

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Fig. 1: The microbiota of distinct body locations within the healthy human is separable at the genus level.
Fig. 2: Stratification of the microbial composition landscape of the human gut microbiome.
Fig. 3: The microbiota of human faecal samples has local substructure.
Fig. 4: Determination of enterotype structure.

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Change history

  • 13 February 2018

    In the version of this Perspective originally published, the first and last name of co-author Manimozhiyan Arumugam were switched. This has now been corrected in all versions of the Perspective.

References

  1. Huttenhower, C. et al. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

    CAS  Google Scholar 

  2. Sender, R., Fuchs, S. & Milo, R. Revised estimates for the number of human and bacteria cells in the body. PLoS Biol. 14, e1002533 (2016).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  5. Faith, J. J. et al. The long-term stability of the human gut microbiota. Science 341, 1237439 (2013).

    PubMed  PubMed Central  Google Scholar 

  6. Le Chatelier, E. et al. Richness of human gut microbiome correlates with metabolic markers. Nature 500, 541–546 (2013).

    PubMed  Google Scholar 

  7. Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016).

    CAS  PubMed  Google Scholar 

  8. Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jeffery, I. B., Claesson, M. J., O’Toole, P. W. & Shanahan, F. Categorization of the gut microbiota: enterotypes or gradients? Nat. Rev. Microbiol. 10, 591–592 (2012).

    CAS  PubMed  Google Scholar 

  10. Lahti, L., Salojärvi, J., Salonen, A., Scheffer, M. & de Vos, W.  M. Tipping elements in the human intestinal ecosystem. Nat. Commun. 5, 4344 (2014).

    CAS  PubMed  Google Scholar 

  11. Sørlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).

    PubMed  PubMed Central  Google Scholar 

  12. Sorlie, T. et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl Acad. Sci. USA 100, 8418–8423 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Yamauchi, M. et al. Assessment of colorectal cancer molecular features along bowel subsites challenges the conception of distinct dichotomy of proximal versus distal colorectum. Gut 61, 847–854 (2012).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Ravel, J. et al. Vaginal microbiome of reproductive-age women. Proc. Natl Acad. Sci. USA 108, 4680–4687 (2011).

    CAS  PubMed  Google Scholar 

  16. Koren, O. et al. A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets. PLoS Comput. Biol. 9, e1002863 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Ding, T. & Schloss, P.  D. Dynamics and associations of microbial community types across the human body. Nature 509, 357–360 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhou, Y. et al. Exploration of bacterial community classes in major human habitats. Genome Biol. 15, R66 (2014).

    PubMed  PubMed Central  Google Scholar 

  19. Qin, J. et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012).

    CAS  PubMed  Google Scholar 

  20. Dethlefsen, L., Eckburg, P.  B., Bik, E.  M. & Relman, D.  A. Assembly of the human intestinal microbiota. Trends Ecol. Evol. 21, 517–523 (2006).

    PubMed  Google Scholar 

  21. Schloissnig, S. et al. Genomic variation landscape of the human gut microbiome. Nature 493, 45–50 (2013).

    PubMed  Google Scholar 

  22. Zhu, A., Sunagawa, S., Mende, D.  R. & Bork, P. Inter-individual differences in the gene content of human gut bacterial species. Genome Biol. 16, 82 (2015).

    PubMed  PubMed Central  Google Scholar 

  23. Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Karlsson, F. H., Nookaew, I. & Nielsen, J. Metagenomic data utilization and analysis (MEDUSA) and construction of a global gut microbial gene catalogue. PLoS Comput. Biol. 10, e1003706 (2014).

    PubMed  PubMed Central  Google Scholar 

  25. Bergstrom, A. et al. Establishment of intestinal microbiota during early life: a longitudinal, explorative study of a large cohort of Danish infants. Appl. Environ. Microbiol. 80, 2889–2900 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Holmes, I., Harris, K. & Quince, C. Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS ONE 7, e30126 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Quince, C. et al. The impact of Crohn’s disease genes on healthy human gut microbiota: a pilot study. Gut 62, 952–954 (2013).

    PubMed  Google Scholar 

  28. Roager, H. M., Licht, T. R., Poulsen, S. K., Larsen, T. M. & Bahl, M. I. Microbial enterotypes, inferred by the Prevotella-to-Bacteroides ratio, remained stable during a 6-month randomized controlled diet intervention with the new nordic diet. Appl. Environ. Microbiol. 80, 1142–1149 (2014).

    PubMed  PubMed Central  Google Scholar 

  29. Zupancic, M. L. et al. Analysis of the gut microbiota in the Old Order Amish and its relation to the metabolic syndrome. PLoS ONE 7, e43052 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Claesson, M. J. et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178–184 (2012).

    CAS  PubMed  Google Scholar 

  31. Gibson, T. E., Bashan, A., Cao, H.-T., Weiss, S. T. & Liu, Y.-Y. On the origins and control of community types in the human microbiome. PLoS Comput. Biol. 12, e1004688 (2016).

    PubMed  PubMed Central  Google Scholar 

  32. Hildebrand, F. et al. Inflammation-associated enterotypes, host genotype, cage and inter-individual effects drive gut microbiota variation in common laboratory mice. Genome Biol. 14, R4 (2013).

    PubMed  PubMed Central  Google Scholar 

  33. Wang, J. et al. Dietary history contributes to enterotype-like clustering and functional metagenomic content in the intestinal microbiome of wild mice. Proc. Natl Acad. Sci. USA 111, 2703–2710 (2014).

    Google Scholar 

  34. Moeller, A. H. et al. Chimpanzees and humans harbour compositionally similar gut enterotypes. Nat. Commun. 3, 1179 (2012).

    PubMed  Google Scholar 

  35. Moeller, A. H. et al. Stability of the gorilla microbiome despite simian immunodeficiency virus infection. Mol. Ecol. 24, 690–697 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Mach, N. et al. Early-life establishment of the swine gut microbiome and impact on host phenotypes. Environ. Microbiol. Rep. 7, 554–569 (2015).

    CAS  PubMed  Google Scholar 

  37. Ramayo-Caldas, Y. et al. Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits. ISME J. 10, 2973–2977 (2016).

    PubMed  PubMed Central  Google Scholar 

  38. Li, J. et al. Two gut community enterotypes recur in diverse bumblebee species. Curr. Biol. 25, R652–R653 (2015).

    CAS  PubMed  Google Scholar 

  39. Moeller, A.  H. et al. Rapid changes in the gut microbiome during human evolution. Proc. Natl Acad. Sci. USA 111, 16431–16435 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Foster, K. R., Schluter, J., Coyte, K. Z. & Rakoff-Nahoum, S. The evolution of the host microbiome as an ecosystem on a leash. Nature 548, 43–51 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Scheffer, M. & Carpenter, S. R. Catastrophic regime shifts in ecosystems: linking theory to observation. Trends Ecol. Evol. 18, 648–656 (2003).

    Google Scholar 

  42. Huse, S. M., Ye, Y., Zhou, Y. & Fodor, A. A. A core human microbiome as viewed through 16S rRNA sequence clusters. PLoS ONE 7, e34242 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Gorvitovskaia, A., Holmes, S. P. & Huse, S. M. Interpreting Prevotella and Bacteroides as biomarkers of diet and lifestyle. Microbiome 4, 15 (2016).

    PubMed  PubMed Central  Google Scholar 

  44. Vieira-Silva, S. et al. Species–function relationships shape ecological properties of the human gut microbiome. Nat. Microbiol. 1, 16088 (2016).

    CAS  PubMed  Google Scholar 

  45. Sankaran, M. et al. Determinants of woody cover in African savannas. Nature 438, 846–849 (2005).

    CAS  PubMed  Google Scholar 

  46. Staver, A.  C., Archibald, S. & Levin, S. Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states. Ecology 92, 1063–1072 (2011).

    PubMed  Google Scholar 

  47. Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Huerta-Cepas, J. et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 44, 286–293 (2016).

    CAS  PubMed  Google Scholar 

  49. Ou, J. et al. Diet, microbiota, and microbial metabolites in colon cancer risk in rural Africans and African Americans. Am. J. Clin. Nutr. 98, 111–120 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Nakayama, J. et al. Diversity in gut bacterial community of school-age children in Asia. Sci. Rep. 5, 8397 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Smith, M. I. et al. Gut microbiomes of Malawian twin pairs discordant for Kwashiorkor. Science 339, 548–554 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. De Filippo, C. et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl Acad. Sci. USA 107, 14691–14696 (2010).

    PubMed  PubMed Central  Google Scholar 

  53. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).

    CAS  PubMed  Google Scholar 

  54. Purushe, J. et al. Comparative genome analysis of Prevotella ruminicola and Prevotella bryantii: insights into their environmental niche. Microb. Ecol. 60, 721–729 (2010).

    PubMed  Google Scholar 

  55. Cantarel, B. L. et al. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res. 37, D233–D238 (2009).

    CAS  PubMed  Google Scholar 

  56. Pereira, F. C. & Berry, D. Microbial nutrient niches in the gut. Environ. Microbiol. 19, 1366–1378 (2017).

    PubMed  PubMed Central  Google Scholar 

  57. Vandeputte, D. et al. Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates. Gut 65, 57–62 (2016).

    CAS  PubMed  Google Scholar 

  58. Roager, H. M. et al. Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut. Nat. Microbiol. 1, 16093 (2016).

    CAS  PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  60. Gibbons, S. M., Kearney, S. M., Smillie, C.  S. & Alm, E.  J. Two dynamic regimes in the human gut microbiome. PLoS Comput. Biol. 13, e1005364 (2017).

    PubMed  PubMed Central  Google Scholar 

  61. Voigt, A. Y. et al. Temporal and technical variability of human gut metagenomes. Genome Biol. 16, 73 (2015).

    PubMed  PubMed Central  Google Scholar 

  62. 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).

    CAS  PubMed  Google Scholar 

  63. Van Nood, E. et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N. Engl. J. Med. 368, 407–415 (2013).

    PubMed  Google Scholar 

  64. Kovatcheva-Datchary, P. et al. Dietary fiber-induced improvement in glucose metabolism is associated with increased abundance of Prevotella. Cell Metab. 22, 971–982 (2015).

    CAS  PubMed  Google Scholar 

  65. Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J.  I. Human gut microbes associated with obesity. Nature 444, 1022–1023 (2006).

    CAS  PubMed  Google Scholar 

  66. Haiser, H. J. et al. Predicting and manipulating cardiac drug inactivation by the human gut bacterium Eggerthella lenta. Science 341, 295–298 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Liang, X. et al. Bidirectional interactions between indomethacin and the murine intestinal microbiota. eLife 4, e08973 (2015).

    PubMed  PubMed Central  Google Scholar 

  68. Spanogiannopoulos, P., Bess, E. N., Carmody, R.  N. & Turnbaugh, P.  J. The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Nat. Rev. Microbiol. 14, 273–287 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Forslund, K. et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature 528, 262–266 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Zhu, L. et al. Characterization of gut microbiomes in nonalcoholic steatohepatitis (NASH) patients: a connection between endogenous alcohol and NASH. Hepatology 57, 601–609 (2013).

    CAS  PubMed  Google Scholar 

  71. Zeller, G. et al. Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol. Syst. Biol. 10, 766 (2014).

    PubMed  PubMed Central  Google Scholar 

  72. Sobhani, I. et al. Microbial dysbiosis in colorectal cancer (CRC) patients. PLoS ONE 6, e16393 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. De Palma, G. et al. Intestinal dysbiosis and reduced immunoglobulin-coated bacteria associated with coeliac disease in children. Microbiology 10, 63 (2010).

    PubMed  PubMed Central  Google Scholar 

  74. Jernberg, C., Löfmark, S., Edlund, C. & Jansson, J. K. Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology 156, 3216–3223 (2010).

    CAS  PubMed  Google Scholar 

  75. Scher, J. U. et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2, e01202 (2013).

    PubMed  PubMed Central  Google Scholar 

  76. Larsen, N. et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS ONE 5, e9085 (2010).

    PubMed  PubMed Central  Google Scholar 

  77. Lozupone, C. A. et al. Alterations in the gut microbiota associated with HIV-1 infection. Cell Host Microbe 14, 329–339 (2013).

    CAS  PubMed  Google Scholar 

  78. Noguera-Julian, M. et al. Gut microbiota linked to sexual preference and HIV infection. EBioMedicine 5, 135–146 (2016).

    PubMed  PubMed Central  Google Scholar 

  79. Karlsson, F. H. et al. Symptomatic atherosclerosis is associated with an altered gut metagenome. Nat. Commun. 3, 1245 (2012).

    PubMed  Google Scholar 

  80. Knights, D. et al. Rethinking ‘enterotypes’. Cell Host Microbe 16, 433–437 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Schubert, A. M. et al. Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls. mBio 5, e01021-14 (2014).

    PubMed  PubMed Central  Google Scholar 

  82. Flegal, K. M., Kit, B.  K., Orpana, H. & Graubard, B.  I. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA 309, 71–82 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Wu, G. D. et al. Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags. Microbiology 10, 206 (2010).

    PubMed  PubMed Central  Google Scholar 

  84. Morton, J. T. et al. Uncovering the horseshoe effect in microbial analyses. mSystems 2, e00166–16 (2017).

    PubMed  PubMed Central  Google Scholar 

  85. Costea, P. et al. Towards standards for human fecal sample processing in metagenomic studies. Nat. Biotechnol. 35, 1069–1076 (2017).

  86. Sinha, R. et al. Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium. Nat. Biotechnol. 35, 1077–1086 (2017).

  87. Mardanov, A. V. et al. Metagenomic analysis of the dynamic changes in the gut microbiome of the participants of the MARS-500 experiment, simulating long term space flight. Acta Naturae 5, 116–125 (2013).

  88. Segata, N. et al. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat. Methods 9, 811–814 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Karlsson, F. H., Nookaew, I. & Nielsen, J. Metagenomic data utilization and analysis (MEDUSA) and construction of a global gut microbial gene catalogue. PLoS Comput. Biol. 10, e1003706 (2014).

  90. MacDonald, N. J., Parks, D. H. & Beiko, R. G. Rapid identification of high-confidence taxonomic assignments for metagenomic data. Nucleic Acids Res. 40, e111 (2012).

  91. Zhang, J. et al. Mongolians core gut microbiota and its correlation with seasonal dietary changes. Sci. Rep. 4, 5001 (2014).

  92. Morotomi, N. et al. Evaluation of intestinal microbiotas of healthy japanese adults and effect of antibiotics using the 16S ribosomal RNA gene based clone library method. Biol. Pharm. Bull. 34, 1011–1020 (2011).

    CAS  Google Scholar 

  93. Eloe-Fadrosh, E. A. et al. Impact of oral typhoid vaccination on the human gut microbiota and correlations with S. typhi-specific immunological responses. PLoS ONE 4, e62026 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors are grateful to the members of the Bork group at EMBL for discussions and assistance. The research leading to these results has received funding from EMBL, the VIB, the Rega institute for Medical Research, the European Research Council via the CancerBiome project (project reference 268985), MicrobesInside (250172) and the European Community’s Seventh Framework Programme via the MetaHIT (HEALTH-F4-2007-201052), the METACARDIS project (FP7-HEALTH-2012-INNOVATION-I-305312), the European Union’s Horizon 2020 research and innovation programme (Marie Sklodowska-Curie grant 600375), Metagenopolis grant ANR-11-DPBS-0001 and the IHMS project (FP7-HEALTH-2010-single-stage-261376).

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P.B., R.K. and J.R. conceived the review. P.I.C., F.H. and G.Z. performed data analysis. F.H., P.I.C., J.R. and P.B. performed the literature research, with input from all co-authors. P.I.C., F.H., S.S., R.K., J.R. and P.B. wrote the manuscript with contributions from M.A., F.B., M.J.B., F.D.B., W.M.d.V., S.D.E., C.m.F., M.H., C.H., I.B.J., D.K., J.D.L., R.E.L., H.O., P.W.O., C.Q., D.A.R., F.S., J.W., G.M.W., G.D.W., G.Z. and L.Z.

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Correspondence to Jeroen Raes, Rob Knight or Peer Bork.

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Supplementary Table 3

Functional differences between three different enterotype models.

Supplementary Table 4

Associations between obesity-related parameters.

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Costea, P.I., Hildebrand, F., Arumugam, M. et al. Enterotypes in the landscape of gut microbial community composition. Nat Microbiol 3, 8–16 (2018). https://doi.org/10.1038/s41564-017-0072-8

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