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Moving pictures of the human microbiome
Open accessAbstract
BACKGROUND: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. RESULTS: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members. CONCLUSIONS: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
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![Figure 1 Principal coordinates analysis of unweighted UniFrac distances between samples. (a) Costello et al. [6] samples. (b) M3, F4 time series samples. (c) M3, F4 time series, PC1 versus time (days). Panels (a,b) and (c) show two independent principal coordinates analyses. To compare the Costello et al. 454 data (a) with the time series Illumina data (b), these data were generated in a single principal coordinates analysis of UniFrac distances at 500 sequences per sample. Panel (c) does not contain the 454 data, so makes use of the increased sampling depth possible on Illumina (evenly sampled to 5,000 sequences per sample for UniFrac calculations).](/paper-figures/601978f4a5f14dce850c1ad072f786d6/moving-pictures-of-the-human-microbiome-figure-1.jpg)
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“the fine structure of the healthy microbiota seems to be unique to individuals; intra-individual differences across time are typically much smaller than differences between individuals (Caporaso et al., 2011;Costello et al., 2009).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Caporaso et al., 2011
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Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
Self-citationDiversity of the Human Intestinal Microbial Flora
Eckburg, P. B., Bik, E. M., Bernstein, C. N., Purdom, E., Dethlefsen, L., Sargent, M., Gill, S. R., Nelson, K. E., & Relman, D. A. (2005) · Science · doi:10.1126/science.1110591 · Cited by 7,913
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823
Self-citationVaginal microbiome of reproductive-age women
Ravel, J., Gajer, P., Abdo, Z., Schneider, G. M., Koenig, S. S. K., McCulle, S. L., Karlebach, S., Gorle, R., Russell, J., Tacket, C. O., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002611107 · Cited by 4,254
Self-citationBacterial Community Variation in Human Body Habitats Across Space and Time
Costello, E. K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J. I., & Knight, R. (2009) · Science · doi:10.1126/science.1177486 · Cited by 3,231
Self-citationThe Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice
Turnbaugh, P. J., Ridaura, V. K., Faith, J. J., Rey, F. E., Knight, R., & Gordon, J. I. (2009) · Science Translational Medicine · doi:10.1126/scitranslmed.3000322 · Cited by 3,058 · cited 2×
“…together, our observations paint a picture of a human microbiome that is highly variable over time (Figures 2 and 3; Additional files 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15), but from which stable patterns of similarities and differences among body habitats and individuals emerge (Figure…”
BackgroundSelf-citationDevelopment of the Human Infant Intestinal Microbiota
Palmer, C., Bik, E. M., DiGiulio, D. B., Relman, D. A., & Brown, P. O. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050177 · Cited by 2,877
Cited by
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Human gut microbiome viewed across age and geography
Yatsunenko, T., Rey, F. E., Manary, M. J., Trehan, I., Dominguez-Bello, M. G., Contreras, M., Magris, M., Hidalgo, G., Baldassano, R. N., Anokhin, A. P., et al. (2012) · Nature · doi:10.1038/nature11053 · Cited by 7,815
Self-citationDiversity, stability and resilience of the human gut microbiota
Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K., & Knight, R. (2012) · Nature · doi:10.1038/nature11550 · Cited by 5,533
Self-citationCryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286
Microbial interactions: from networks to models
Faust, K., & Raes, J. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2832 · Cited by 4,268
Metadata
- Authors
- Caporaso, J. G., Lauber, C. L., Costello, E. K., Berg-Lyons, D., Gonzalez, A., Stombaugh, J., Knights, D., Gajer, P., Ravel, J., Fierer, N., Gordon, J. I., & Knight, R.
- Affiliations
- University of Colorado Boulder (US)
- Cooperative Institute for Research in Environmental Sciences (US)
- Stanford Medicine (US)
- University of Maryland, Baltimore (US)
- Washington University in St. Louis (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Knight, Rob
- ORCID
- Venue
- Genome Biology
- Published
- 2011-05-30
- Volume
- 12
- Issue
- 5
- Pages
- R50-R50
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC3271711
- OpenAlex
- W2126218947
- Cited by
- 1,138
- References
- 21
- Citations by year
- 2026: 25 · 2025: 50 · 2024: 69 · 2023: 80 · 2022: 68 · 2021: 88 · 2020: 102 · 2019: 93 · 2018: 83 · 2017: 84 · 2016: 78 · 2015: 79 · 2014: 78 · 2013: 82 · 2012: 61
- FWCI
- 30.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Bill and Melinda Gates Foundation
- Crohn's and Colitis Foundation of America
- Amazon Web Services
- Crohn's and Colitis Foundation
- National Institutes of Health (5u01ai070921-07, DK078669)
- National Human Genome Research Institute (R01HG004872, HG004872, HG004872-02S1)
- National Institute of Allergy and Infectious Diseases (AI070921, AI083264, UH2AI083264)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK078669, P01DK078669)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- human microbiome, temporal variation, core microbiome, microbial community dynamics, body site differences, interindividual variability, microbiome sequencing
- MeSH terms
- Bacteria, Computer Simulation, Humans, Obesity, Organ Specificity, RNA, Ribosomal, 16S, Seasons, Time Factors, Inflammatory Bowel Diseases, Genomics, Gastrointestinal Tract, Metagenome, High-Throughput Nucleotide Sequencing
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