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Moving pictures of the human microbiome

J Gregory Caporaso1, Christian L Lauber2, Elizabeth K Costello3, Donna Berg-Lyons2, Antonio Gonzalez4, Jesse Stombaugh1, Dan Knights4, Pawel Gajer5, Jacques Ravel5, Noah Fierer26, Jeffrey I Gordon7 and Rob Knight18*

Author affiliations

1 Department of Chemistry and Biochemistry, University of Colorado, 215 UCB, Boulder, CO 80309, USA

2 Cooperative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA

3 Department of Microbiology and Immunology, Stanford University School of Medicine, 299 Campus Drive, Stanford, CA 94305, USA

4 Department of Computer Science, University of Colorado, 430 UCB, Boulder, CO 80309, USA

5 Institute for Genome Sciences, University of Maryland School of Medicine, 801 W. Baltimore Street, Baltimore, MD 21201, USA

6 Department of Ecology and Evolutionary Biology, University of Colorado, UCB 334, Boulder, CO 80309, USA

7 Center for Genome Sciences and Systems Biology, Washington University School of Medicine, 4444 Forest Park Blvd, St Louis, MO 63108, USA

8 Howard Hughes Medical Institute, University of Colorado, 215 UCB, Boulder, CO 80309, USA

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Citation and License

Genome Biology 2011, 12:R50  doi:10.1186/gb-2011-12-5-r50

Published: 30 May 2011

Abstract

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.