Gut microbial communities represent one source of human genetic and metabolic diversity. To examine how gut microbiomes differ among human populations, here we characterize bacterial species in fecal samples from 531 individuals, plus the gene content of 110 of them. The cohort encompassed healthy children and adults from the Amazonas of Venezuela, rural Malawi and US metropolitan areas and included mono- and dizygotic twins. Shared features of the functional maturation of the gut microbiome were identified during the first three years of life in all three populations, including age-associated changes in the genes involved in vitamin biosynthesis and metabolism. Pronounced differences in bacterial assemblages and functional gene repertoires were noted between US residents and those in the other two countries. These distinctive features are evident in early infancy as well as adulthood. Our findings underscore the need to consider the microbiome when evaluating human development, nutritional needs, physiological variations and the impact of westernization.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


Data deposits

DNA sequences have been deposited in MG-RAST (http://metagenomics.anl.gov/) under accession numbers ‘qiime:850’ for Illumina V4 16S rRNA data sets, and ‘qiime:621’ for fecal microbiome shotgun sequencing data sets.


  1. 1.

    et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study. Appl. Environ. Microbiol. 72, 1027–1033 (2006)

  2. 2.

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

  3. 3.

    et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc. Natl Acad. Sci. USA 105, 2117–2122 (2008)

  4. 4.

    et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res. 14, 169–181 (2007)

  5. 5.

    et al. Microbes and Health Sackler Colloquium: Succession of microbial consortia in the developing infant gut microbiome. Proc. Natl Acad. Sci. USA 108 (suppl. 1). 4578–4585 (2011)

  6. 6.

    , , & Molecular monitoring of succession of bacterial communities in human neonates. Appl. Environ. Microbiol. 68, 219–226 (2002)

  7. 7.

    What immunologists should know about bacterial communities of the human bowel. Semin. Immunol. 19, 94–105 (2007)

  8. 8.

    et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc. Natl Acad. Sci. USA 107, 11971–11975 (2010)

  9. 9.

    & What are the consequences of the disappearing human microbiota? Nature Rev. Microbiol. 7, 887–894 (2009)

  10. 10.

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

  11. 11.

    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)

  12. 12.

    , , & The non-sporing anaerobic bacteria in human faeces. J. Med. Microbiol. 7, 213–221 (1974)

  13. 13.

    , & Developmental microbial ecology of the neonatal gastrointestinal tract. Am. J. Clin. Nutr. 69, 1035S–1045S (1999)

  14. 14.

    , , , & Development of the human infant intestinal microbiota. PLoS Biol. 5, e177 (2007)

  15. 15.

    et al. Factors influencing the composition of the intestinal microbiota in early infancy. Pediatrics 118, 511–521 (2006)

  16. 16.

    & UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

  17. 17.

    , & Supervised classification of human microbiota. FEMS Microbiol. Rev. 35, 343–359 (2011)

  18. 18.

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

  19. 19.

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

  20. 20.

    , & ShotgunFunctionalizeR: an R-package for functional comparison of metagenomes. Bioinformatics 25, 2737–2738 (2009)

  21. 21.

    Vitamin B12: chemistry and biochemistry. Biochem. Soc. Trans. 33, 806–810 (2005)

  22. 22.

    , , & Cobalamin status and its biochemical markers methylmalonic acid and homocysteine in different age groups from 4 days to 19 years. Clin. Chem. 49, 2067–2075 (2003)

  23. 23.

    , & Mucosal glycan foraging enhances fitness and transmission of a saccharolytic human gut bacterial symbiont. Cell Host Microbe 4, 447–457 (2008)

  24. 24.

    , , , & A molecular sensor that allows a gut commensal to control its nutrient foundation in a competitive ecosystem. Proc. Natl Acad. Sci. USA 96, 9833–9838 (1999)

  25. 25.

    , & Human milk nonprotein nitrogen components: changing patterns of free amino acids and urea in the course of early lactation. Am. J. Clin. Nutr. 40, 303–309 (1984)

  26. 26.

    et al. Incorporation of urea and ammonia nitrogen into ileal and fecal microbial proteins and plasma free amino acids in normal men and ileostomates. Am. J. Clin. Nutr. 70, 1046–1058 (1999)

  27. 27.

    et al. The transfer of 15N from urea to lysine in the human infant. Br. J. Nutr. 83, 505–512 (2000)

  28. 28.

    & Salvage of exogenous urea nitrogen enhances nitrogen balance in normal men consuming marginally inadequate protein diets. Clin. Sci. (Lond.) 90, 215–225 (1996)

  29. 29.

    , , & Adaptation to a diet low in protein: effect of complex carbohydrate upon urea kinetics in normal man. Clin. Sci. (Lond.) 82, 191–198 (1992)

  30. 30.

    et al. Characterization of urease genes cluster of Streptococcus thermophilus. J. Appl. Microbiol. 96, 209–219 (2004)

  31. 31.

    et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970–974 (2011)

  32. 32.

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

  33. 33.

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

  34. 34.

    & Finding Groups in Data: an Introduction to Cluster Analysis Ch. 2 68–125 (Wiley, 1990)

  35. 35.

    Silhouettes — a graphical aid to the interpretation and validation of cluster-analysis. J. Comput. Appl. Math. 20, 53–65 (1987)

  36. 36.

    & Cluster validation by prediction strength. J. Comput. Graph. Statist. 14, 511–528 (2005)

  37. 37.

    & Identifying and removing artificial replicates from 454 pyrosequencing data. Cold Spring Harb. Protoc. 2010, pdb.prot5409 (2010)

  38. 38.

    . R: A Language and Envirnoment for Statistical Compuiting (R Foundation for Statistical Computing, 2010)

  39. 39.

    & Classification and regression by randomForest. R News 2, 18–22 (2002)

Download references


We thank S. Wagoner and J. Manchester for superb technical assistance, plus B. Muegge, A. Grimm, A. Hsiao, N. Griffin and P. Tarr for suggestions, and M. Ndao, T. Tinnin and R. Mkakosya for patient recruitment and/or technical assistance. This work was supported in part by grants from the National Institutes of Health (DK078669, T32-HD049338), St. Louis Children’s Discovery Institute (MD112009-201), the Howard Hughes Medical Institute, the Crohn’s and Colitis Foundation of America, and the Bill and Melinda Gates Foundation. Parts of this work used the Janus supercomputer, which is supported by National Science Foundation grant CNS-0821794, the University of Colorado, Boulder, the University of Colorado, Denver, and the National Center for Atmospheric Research.

Author information


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

    • Tanya Yatsunenko
    • , Federico E. Rey
    •  & Jeffrey I. Gordon
  2. Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri 63110, USA

    • Mark J. Manary
    • , Indi Trehan
    •  & Barbara Warner
  3. Department of Community Health, University of Malawi College of Medicine, Blantyre, Malawi

    • Mark J. Manary
  4. Department of Paediatrics and Child Health, University of Malawi College of Medicine, Blantyre, Malawi

    • Indi Trehan
  5. Department of Biology, University of Puerto Rico - Rio Piedras, Puerto Rico 00931-3360

    • Maria Gloria Dominguez-Bello
  6. Venezuelan Institute of Scientific Research (IVIC), Carretera Panamericana, Km 11, Altos de Pipe, Venezuela

    • Monica Contreras
  7. Amazonic Center for Research and Control of Tropical Diseases (CAICET), Puerto Ayacucho 7101, Amazonas, Venezuela

    • Magda Magris
    •  & Glida Hidalgo
  8. Division of Gastroenterology and Nutrition, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA

    • Robert N. Baldassano
  9. Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri 63110, USA

    • Andrey P. Anokhin
    •  & Andrew C. Heath
  10. Department of Chemistry and Biochemistry, University of Colorado, Boulder 80309, USA

    • Jens Reeder
    • , Justin Kuczynski
    • , Catherine A. Lozupone
    • , Christian Lauber
    • , Jose Carlos Clemente
    • , Dan Knights
    •  & Rob Knight
  11. Department of Computer Science, Northern Arizona University, Flagstaff, Arizona 86001, USA

    • J. Gregory Caporaso
  12. Howard Hughes Medical Institute, University of Colorado, Boulder 80309, USA

    • Rob Knight


  1. Search for Tanya Yatsunenko in:

  2. Search for Federico E. Rey in:

  3. Search for Mark J. Manary in:

  4. Search for Indi Trehan in:

  5. Search for Maria Gloria Dominguez-Bello in:

  6. Search for Monica Contreras in:

  7. Search for Magda Magris in:

  8. Search for Glida Hidalgo in:

  9. Search for Robert N. Baldassano in:

  10. Search for Andrey P. Anokhin in:

  11. Search for Andrew C. Heath in:

  12. Search for Barbara Warner in:

  13. Search for Jens Reeder in:

  14. Search for Justin Kuczynski in:

  15. Search for J. Gregory Caporaso in:

  16. Search for Catherine A. Lozupone in:

  17. Search for Christian Lauber in:

  18. Search for Jose Carlos Clemente in:

  19. Search for Dan Knights in:

  20. Search for Rob Knight in:

  21. Search for Jeffrey I. Gordon in:


T.Y., R.K. and J.I.G. designed the experiments, M.J.M., I.T., M.G.D.-B., M.C., M.M., G.H., A.C.H., A.P.A., R.K., R.N.B., C.A.L., C.L. and B.W. participated in patient recruitment, T.Y. generated the data, T.Y., F.E.R., J.R., J.K., J.G.C., J.C.C., D.K., R.K. and J.I.G. analysed the results, T.Y., R.K. and J.I.G. wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Jeffrey I. Gordon.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Text, Supplementary References, Supplementary Figures 1-20 and Legends for Supplementary Tables 1-11.

Zip files

  1. 1.

    Supplementary Tables

    This file contains supplementary Tables 1-11.

About this article

Publication history






Further reading


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.