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      Temporal variability is a personalized feature of the human microbiome

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          Abstract

          Background

          It is now apparent that the complex microbial communities found on and in the human body vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over 3 months.

          Results

          We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were more stable in composition than individuals with less diverse communities.

          Conclusions

          Longitudinal sampling of a relatively large number of individuals allowed us to observe high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status. Furthermore, our findings show that, not only is the composition of an individual’s microbiome highly personalized, but their degree of temporal variability is also a personalized feature.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13059-014-0531-y) contains supplementary material, which is available to authorized users.

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          Most cited references 15

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          Measuring biological diversity

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            Examining the global distribution of dominant archaeal populations in soil.

            Archaea, primarily Crenarchaeota, are common in soil; however, the structure of soil archaeal communities and the factors regulating their diversity and abundance remain poorly understood. Here, we used barcoded pyrosequencing to comprehensively survey archaeal and bacterial communities in 146 soils, representing a multitude of soil and ecosystem types from across the globe. Relative archaeal abundance, the percentage of all 16S rRNA gene sequences recovered that were archaeal, averaged 2% across all soils and ranged from 0% to >10% in individual soils. Soil C:N ratio was the only factor consistently correlated with archaeal relative abundances, being higher in soils with lower C:N ratios. Soil archaea communities were dominated by just two phylotypes from a constrained clade within the Crenarchaeota, which together accounted for >70% of all archaeal sequences obtained in the survey. As one of these phylotypes was closely related to a previously identified putative ammonia oxidizer, we sampled from two long-term nitrogen (N) addition experiments to determine if this taxon responds to experimental manipulations of N availability. Contrary to expectations, the abundance of this dominant taxon, as well as archaea overall, tended to decline with increasing N. This trend was coupled with a concurrent increase in known N-oxidizing bacteria, suggesting competitive interactions between these groups.
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              Xenobiotics shape the physiology and gene expression of the active human gut microbiome.

              The human gut contains trillions of microorganisms that influence our health by metabolizing xenobiotics, including host-targeted drugs and antibiotics. Recent efforts have characterized the diversity of this host-associated community, but it remains unclear which microorganisms are active and what perturbations influence this activity. Here, we combine flow cytometry, 16S rRNA gene sequencing, and metatranscriptomics to demonstrate that the gut contains a distinctive set of active microorganisms, primarily Firmicutes. Short-term exposure to a panel of xenobiotics significantly affected the physiology, structure, and gene expression of this active gut microbiome. Xenobiotic-responsive genes were found across multiple bacterial phyla, encoding antibiotic resistance, drug metabolism, and stress response pathways. These results demonstrate the power of moving beyond surveys of microbial diversity to better understand metabolic activity, highlight the unintended consequences of xenobiotics, and suggest that attempts at personalized medicine should consider interindividual variations in the active human gut microbiome. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                gilberto.flores@csun.edu
                gregcaporaso@gmail.com
                jessicabhenley@gmail.com
                jai.rideout@gmail.com
                ddd38@nau.edu
                chase.john@gmail.com
                leff.jonathan@gmail.com
                yoshiki89@gmail.com
                antgonza@gmail.com
                rob.knight@colorado.edu
                rroberdeaudunn@gmail.com
                noahfierer@gmail.com
                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                3 December 2014
                3 December 2014
                2014
                : 15
                : 12
                Affiliations
                [ ]Department of Biology, California State University, Northridge, Northridge, CA 91330-8303 USA
                [ ]Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011 USA
                [ ]Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ 86011 USA
                [ ]Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309 USA
                [ ]Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
                [ ]Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309 USA
                [ ]Department of Computer Science, University of Colorado, Boulder, CO 80309 USA
                [ ]BioFrontiers Institute, University of Colorado, Boulder, CO 80309 USA
                [ ]Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309 USA
                [ ]Howard Hughes Medical Institute, University of Colorado, Boulder, CO 80309 USA
                [ ]Department of Biological Sciences and Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27607 USA
                Article
                531
                10.1186/s13059-014-0531-y
                4252997
                25517225
                © Flores et al.; licensee BioMed Central Ltd. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                © The Author(s) 2014

                Genetics

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