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.

  • Review Article
  • Published:

Current understanding of the human microbiome

Nature Medicine volume 24, pages 392–400 (2018)Cite this article

Subjects

This article has been updated

Abstract

Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities that are associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes and by mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this review, we focus on studies in humans to describe these challenges and propose strategies that leverage existing knowledge to move rapidly from correlation to causation and ultimately to translation into therapies.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Figure 1: The human microbiome is highly personalized.
Figure 2: The dynamics of the human microbiome.
Figure 3: Iterative experiment and observation to understand and develop microbiome therapies.

Similar content being viewed by others

Change history

  • 12 June 2018

    In the version of this paper originally published, the text was truncated after the first four paragraphs. The full HTML version of the paper now appears correctly.

References

  1. Sender, R., Fuchs, S. & Milo, R. Are we really vastly outnumbered? Revisiting the ratio of bacterial to host cells in humans. Cell 164, 337–340 (2016).

    Google Scholar 

  2. Turnbaugh, P.J. et al. The human microbiome project. Nature 449, 804–810 (2007).

    Google Scholar 

  3. Locey, K.J. & Lennon, J.T. Scaling laws predict global microbial diversity. Proc. Natl. Acad. Sci. USA 113, 5970–5975 (2016).

    Google Scholar 

  4. Frank, D.N. et al. Molecular–phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc. Natl. Acad. Sci. USA 104, 13780–13785 (2007).

    Google Scholar 

  5. Gevers, D. et al. The treatment-naive microbiome in new-onset Crohn's disease. Cell Host Microbe 15, 382–392 (2014).

    Google Scholar 

  6. Ni, J. et al. A role for bacterial urease in gut dysbiosis and Crohn's disease. Sci. Transl. Med. 9, eaah6888 (2017).

    Google Scholar 

  7. Kostic, A.D. et al. Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 14, 207–215 (2013).

    Google Scholar 

  8. Jiang, H. et al. Altered fecal microbiota composition in patients with major depressive disorder. Brain Behav. Immun. 48, 186–194 (2015).

    Google Scholar 

  9. Zheng, P. et al. Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host's metabolism. Mol. Psychiatry 21, 786–796 (2016).

    Google Scholar 

  10. Gilbert, J.A. et al. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature 535, 94–103 (2016).

    Google Scholar 

  11. Punt, C.J.A., Koopman, M. & Vermeulen, L. From tumour heterogeneity to advances in precision treatment of colorectal cancer. Nat. Rev. Clin. Oncol. 14, 235–246 (2017).

    Google Scholar 

  12. Debelius, J. et al. Tiny microbes, enormous impacts: what matters in gut microbiome studies? Genome Biol. 17, 217 (2016).

    Google Scholar 

  13. Integrative HMP (iHMP) Research Network Consortium. The Integrative Human Microbiome Project: dynamic analysis of microbiome-host omics profiles during periods of human health and disease. Cell Host Microbe 16, 276–289 (2014).

  14. Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052 (2014).

    Google Scholar 

  15. Goodrich, J.K. et al. Human genetics shape the gut microbiome. Cell 159, 789–799 (2014).

    Google Scholar 

  16. Ridaura, V.K. et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 341, 1241214 (2013).

    Google Scholar 

  17. 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).

    Google Scholar 

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

    Google Scholar 

  19. Seedorf, H. et al. Bacteria from diverse habitats colonize and compete in the mouse gut. Cell 159, 253–266 (2014).

    Google Scholar 

  20. Karczewski, J., Poniedziałek, B., Adamski, Z. & Rzymski, P. The effects of the microbiota on the host immune system. Autoimmunity 47, 494–504 (2014).

    Google Scholar 

  21. Schirmer, M. et al. Linking the human gut microbiome to inflammatory cytokine production capacity. Cell 167, 1897 (2016).

    Google Scholar 

  22. Lozupone, C.A., Stombaugh, J.I., Gordon, J.I., Jansson, J.K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).

    Google Scholar 

  23. O'Toole, P.W. Changes in the intestinal microbiota from adulthood through to old age. Clin. Microbiol. Infect. 18 (Suppl. 4), 44–46 (2012).

    Google Scholar 

  24. Koenig, J.E. et al. Succession of microbial consortia in the developing infant gut microbiome. Proc. Natl. Acad. Sci. USA 108 (Suppl. 1), 4578–4585 (2011).

    Google Scholar 

  25. Weng, M. & Walker, W.A. The role of gut microbiota in programming the immune phenotype. J. Dev. Orig. Health Dis. 4, 203–214 (2013).

    Google Scholar 

  26. Maynard, C.L., Elson, C.O., Hatton, R.D. & Weaver, C.T. Reciprocal interactions of the intestinal microbiota and immune system. Nature 489, 231–241 (2012).

    Google Scholar 

  27. Knights, D. et al. Rethinking “enterotypes”. Cell Host Microbe 16, 433–437 (2014).

    Google Scholar 

  28. 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).

    Google Scholar 

  29. Grice, E.A. & Segre, J.A. The skin microbiome. Nat. Rev. Microbiol. 9, 244–253 (2011).

    Google Scholar 

  30. Grice, E.A. et al. Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009).

    Google Scholar 

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

    Google Scholar 

  32. Kort, R. et al. Shaping the oral microbiota through intimate kissing. Microbiome 2, 41 (2014).

    Google Scholar 

  33. Lazarevic, V., Whiteson, K., Hernandez, D., François, P. & Schrenzel, J. Study of inter- and intra-individual variations in the salivary microbiota. BMC Genomics 11, 523 (2010).

    Google Scholar 

  34. David, L.A. et al. Host lifestyle affects human microbiota on daily timescales. Genome Biol. 15, R89 (2014).

    Google Scholar 

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

    Google Scholar 

  36. Maier, T.V. et al. Impact of dietary resistant starch on the human gut microbiome, metaproteome, and metabolome. MBio. 8, e01343–e17 (2017).

    Google Scholar 

  37. Hannigan, G.D. et al. The human skin double-stranded DNA virome: topographical and temporal diversity, genetic enrichment, and dynamic associations with the host microbiome. MBio 6, e01578–e15 (2015).

    Google Scholar 

  38. Vandeputte, D. et al. Quantitative microbiome profiling links gut community variation to microbial load. Nature 551, 507–511 (2017).

    Google Scholar 

  39. 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).

    Google Scholar 

  40. Ma, B., Forney, L.J. & Ravel, J. Vaginal microbiome: rethinking health and disease. Annu. Rev. Microbiol. 66, 371–389 (2012).

    Google Scholar 

  41. Ravel, J. et al. Daily temporal dynamics of vaginal microbiota before, during and after episodes of bacterial vaginosis. Microbiome 1, 29 (2013).

    Google Scholar 

  42. Romero, R. et al. The composition and stability of the vaginal microbiota of normal pregnant women is different from that of non-pregnant women. Microbiome 2, 4 (2014).

    Google Scholar 

  43. Xiao, B. et al. Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora. Sci. Rep. 6, 26674 (2016).

    Google Scholar 

  44. Albenberg, L.G. & Wu, G.D. Diet and the intestinal microbiome: associations, functions, and implications for health and disease. Gastroenterology 146, 1564–1572 (2014).

    Google Scholar 

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

    Google Scholar 

  46. Zeevi, D. et al. Personalized nutrition by prediction of glycemic responses. Cell 163, 1079–1094 (2015).

    Google Scholar 

  47. Zhang, C. et al. Dietary Modulation of gut microbiota contributes to alleviation of both genetic and simple obesity in children. EBioMedicine 2, 968–984 (2015).

    Google Scholar 

  48. Modi, S.R., Collins, J.J. & Relman, D.A. Antibiotics and the gut microbiota. J. Clin. Invest. 124, 4212–4218 (2014).

    Google Scholar 

  49. 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 (Suppl. 1), 4554–4561 (2011).

    Google Scholar 

  50. Maurice, C.F., Haiser, H.J. & Turnbaugh, P.J. Xenobiotics shape the physiology and gene expression of the active human gut microbiome. Cell 152, 39–50 (2013).

    Google Scholar 

  51. Trasande, L. et al. Infant antibiotic exposures and early-life body mass. Int. J. Obes. (Lond). 37, 16–23 (2013).

    Google Scholar 

  52. Song, S.J. et al. Cohabiting family members share microbiota with one another and with their dogs. eLife 2, e00458 (2013).

    Google Scholar 

  53. von Mutius, E. The microbial environment and its influence on asthma prevention in early life. J. Allergy Clin. Immunol. 137, 680–689 (2016).

    Google Scholar 

  54. Stein, M.M. et al. Innate immunity and asthma risk in Amish and hutterite farm children. N. Engl. J. Med. 375, 411–421 (2016).

    Google Scholar 

  55. Cook, M.D. et al. Exercise and gut immune function: evidence of alterations in colon immune cell homeostasis and microbiome characteristics with exercise training. Immunol. Cell Biol. 94, 158–163 (2016).

    Google Scholar 

  56. Benedict, C. et al. Gut microbiota and glucometabolic alterations in response to recurrent partial sleep deprivation in normal-weight young individuals. Mol. Metab. 5, 1175–1186 (2016).

    Google Scholar 

  57. Karl, J.P. et al. Changes in intestinal microbiota composition and metabolism coincide with increased intestinal permeability in young adults under prolonged physiological stress. Am. J. Physiol. Gastrointest. Liver Physiol. 312, G559–G571 (2017).

    Google Scholar 

  58. Ying, S. et al. The influence of age and gender on skin-associated microbial communities in urban and rural human populations. PLoS One 10, e0141842 (2015).

    Google Scholar 

  59. Zheng, W. et al. Metagenomic sequencing reveals altered metabolic pathways in the oral microbiota of sailors during a long sea voyage. Sci. Rep. 5, 9131 (2015).

    Google Scholar 

  60. Zozaya, M. et al. Bacterial communities in penile skin, male urethra, and vaginas of heterosexual couples with and without bacterial vaginosis. Microbiome 4, 16 (2016).

    Google Scholar 

  61. Fei, N. & Zhao, L. An opportunistic pathogen isolated from the gut of an obese human causes obesity in germfree mice. ISME J. 7, 880–884 (2013).

    Google Scholar 

  62. Leone, V. et al. Effects of diurnal variation of gut microbes and high-fat feeding on host circadian clock function and metabolism. Cell Host Microbe 17, 681–689 (2015).

    Google Scholar 

  63. Knight, R. et al. Unlocking the potential of metagenomics through replicated experimental design. Nat. Biotechnol. 30, 513–520 (2012).

    Google Scholar 

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

    Google Scholar 

  65. Flores, G.E. et al. Temporal variability is a personalized feature of the human microbiome. Genome Biol. 15, 531 (2014).

    Google Scholar 

  66. Gajer, P. et al. Temporal dynamics of the human vaginal microbiota. Sci. Transl. Med. 4, 132ra52 (2012).

    Google Scholar 

  67. Livanos, A.E. et al. Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice. Nat. Microbiol. 1, 16140 (2016).

    Google Scholar 

  68. Sugihara, G. et al. Detecting causality in complex ecosystems. Science 338, 496–500 (2012).

    Google Scholar 

  69. Knights, D. et al. Bayesian community-wide culture-independent microbial source tracking. Nat. Methods 8, 761–763 (2011).

    Google Scholar 

  70. Larsen, P.E., Field, D. & Gilbert, J.A. Predicting bacterial community assemblages using an artificial neural network approach. Nat. Methods 9, 621–625 (2012).

    Google Scholar 

  71. Larsen, P.E. & Dai, Y. Metabolome of human gut microbiome is predictive of host dysbiosis. Gigascience 4, 42 (2015).

    Google Scholar 

  72. Browne, H.P. et al. Culturing of 'unculturable' human microbiota reveals novel taxa and extensive sporulation. Nature 533, 543–546 (2016).

    Google Scholar 

  73. Geva-Zatorsky, N. et al. Mining the human gut microbiota for immunomodulatory organisms. Cell 168, 928–943. e11 (2017).

    Google Scholar 

  74. Vatanen, T. et al. Variation in microbiome LPS immunogenicity contributes to autoimmunity in humans. Cell 165, 842–853 (2016).

    Google Scholar 

  75. Sivan, A. et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 350, 1084–1089 (2015).

    Google Scholar 

  76. Dubin, K. et al. Intestinal microbiome analyses identify melanoma patients at risk for checkpoint-blockade-induced colitis. Nat. Commun. 7, 10391 (2016).

    Google Scholar 

  77. Mueller, N.T. et al. Does vaginal delivery mitigate or strengthen the intergenerational association of overweight and obesity? Findings from the Boston Birth Cohort. Int. J. Obes. (Lond). 41, 497–501 (2017).

    Google Scholar 

  78. Raveh-Sadka, T. et al. Gut bacteria are rarely shared by co-hospitalized premature infants, regardless of necrotizing enterocolitis development. eLife 4, 4 (2015).

    Google Scholar 

  79. Zhang, X. et al. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nat. Med. 21, 895–905 (2015).

    Google Scholar 

  80. 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).

    Google Scholar 

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

    Google Scholar 

  82. Alivisatos, A.P. et al. MICROBIOME. A unified initiative to harness Earth's microbiomes. Science 350, 507–508 (2015).

    Google Scholar 

  83. Biteen, J.S. et al. Tools for the microbiome: nano and beyond. ACS Nano 10, 6–37 (2016).

    Google Scholar 

  84. Luckey, T.D. Introduction to intestinal microecology. Am. J. Clin. Nutr. 25, 1292–1294 (1972).

    Google Scholar 

  85. Rosner, J.L. Ten times more microbial cells than body cells in humans? Microbe 9, 47 (2014).

    Google Scholar 

  86. Reyes, A. et al. Viruses in the faecal microbiota of monozygotic twins and their mothers. Nature 466, 334–338 (2010).

    Google Scholar 

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

    Google Scholar 

  88. Weingarden, A. et al. Dynamic changes in short- and long-term bacterial composition following fecal microbiota transplantation for recurrent Clostridium difficile infection. Microbiome 3, 10 (2015).

    Google Scholar 

  89. Kassam, Z., Lee, C.H., Yuan, Y. & Hunt, R.H. Fecal microbiota transplantation for Clostridium difficile infection: systematic review and meta-analysis. Am. J. Gastroenterol. 108, 500–508 (2013).

    Google Scholar 

  90. Knights, D., Parfrey, L.W., Zaneveld, J., Lozupone, C. & Knight, R. Human-associated microbial signatures: examining their predictive value. Cell Host Microbe 10, 292–296 (2011).

    Google Scholar 

  91. Walters, W.A., Xu, Z. & Knight, R. Meta-analyses of human gut microbes associated with obesity and IBD. FEBS Lett. 588, 4223–4233 (2014).

    Google Scholar 

  92. Sze, M.A. & Schloss, P.D. Looking for a signal in the noise: revisiting obesity and the microbiome. MBio 7 (2016).

  93. Sahin, M. & Sur, M. Genes, circuits, and precision therapies for autism and related neurodevelopmental disorders. Science 350, aab3897 (2015).

    Google Scholar 

  94. McDonald, D. et al. Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients. Microb. Ecol. Health Dis. 26, 26555 (2015).

    Google Scholar 

  95. Kang, D.-W. et al. Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children. PLoS One 8, e68322 (2013).

    Google Scholar 

  96. Hsiao, E.Y. et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell 155, 1451–1463 (2013).

    Google Scholar 

  97. Kang, D.-W. et al. Microbiota transfer therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study. Microbiome 5, 10 (2017).

    Google Scholar 

  98. Snijders, A.M. et al. Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome. Nat. Microbiol. 2, 16221 (2016).

    Google Scholar 

  99. Knights, D. et al. Complex host genetics influence the microbiome in inflammatory bowel disease. Genome Med. 6, 107 (2014).

    Google Scholar 

  100. Halfvarson, J. et al. Dynamics of the human gut microbiome in inflammatory bowel disease. Nat. Microbiol. 2, 17004 (2017).

    Google Scholar 

  101. Uusitalo, U. et al. Association of early exposure of probiotics and islet autoimmunity in the TEDDY study. JAMA Pediatr. 170, 20–28 (2016).

    Google Scholar 

  102. Blaser, M.J. The theory of disappearing microbiota and the epidemics of chronic diseases. Nat. Rev. Immunol. 17, 461–463 (2017).

    Google Scholar 

  103. Arrieta, M.-C. et al. Early infancy microbial and metabolic alterations affect risk of childhood asthma. Sci. Transl. Med. 7, 307ra152 (2015).

    Google Scholar 

  104. Durack, J. et al. Delayed gut microbiota development in high-risk for asthma infants is temporarily modifiable by Lactobacillus supplementation. Nat. Commun. 9, 707 (2018).

    Google Scholar 

  105. Fujimura, K.E. et al. Neonatal gut microbiota associates with childhood multisensitized atopy and T cell differentiation. Nat. Med. 22, 1187–1191 (2018).

    Google Scholar 

Download references

Acknowledgements

Many of the studies described here in our laboratories were supported by the National Institutes of Health, National Science Foundation, Department of Energy and the Alfred P. Sloan Foundation. We thank numerous members of our laboratories for constructive criticism on drafts of this article.

Author information

Authors and Affiliations

  1. Department of Surgery, Microbiome Center, University of Chicago, Chicago, Illinois, USA

    Jack A Gilbert

  2. Bioscience Division, Argonne National Laboratory, Lemont, Illinois, USA

    Jack A Gilbert

  3. Marine Biological Laboratory, Woods Hole, Massachusetts, USA

    Jack A Gilbert

  4. New York University Langone Medical Center, New York, New York, USA

    Martin J Blaser

  5. Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA

    J Gregory Caporaso

  6. Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA

    Janet K Jansson

  7. Department of Medicine, University of California San Francisco, San Francisco, California, USA

    Susan V Lynch

  8. Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA

    Rob Knight

  9. Department of Computer Science & Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA

    Rob Knight

  10. Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA

    Rob Knight

Authors
  1. Jack A Gilbert
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Martin J Blaser
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J Gregory Caporaso
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Janet K Jansson
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Susan V Lynch
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rob Knight
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rob Knight.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gilbert, J., Blaser, M., Caporaso, J. et al. Current understanding of the human microbiome. Nat Med 24, 392–400 (2018). https://doi.org/10.1038/nm.4517

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nm.4517

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing