4.8 Article

Enterotypes of the human gut microbiome

Journal

NATURE
Volume 473, Issue 7346, Pages 174-180

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nature09944

Keywords

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Funding

  1. European Community [HEALTH-F4-2007-201052]
  2. Lundbeck Foundation Centre for Applied Medical Genomics in Personalized Disease Prediction, Prevention and Care (LuCAMP)
  3. Novo Nordisk Foundation
  4. International Science and Technology Cooperation Project in China [0806]
  5. Agence Nationale de la Recherche (ANR)
  6. Institute for the encouragement of Scientific Research and Innovation of Brussels (ISRIB)
  7. Fund for Scientific Research Flanders (FWO)
  8. ICREA Funding Source: Custom
  9. Novo Nordisk Fonden [NNF10CC1016517] Funding Source: researchfish
  10. Grants-in-Aid for Scientific Research [221S0002] Funding Source: KAKEN

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Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host-microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers.

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