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      Current understanding of the human microbiome

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          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 associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and 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.

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          Most cited references43

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          Temporal dynamics of the human vaginal microbiota.

          Elucidating the factors that impinge on the stability of bacterial communities in the vagina may help in predicting the risk of diseases that affect women's health. Here, we describe the temporal dynamics of the composition of vaginal bacterial communities in 32 reproductive-age women over a 16-week period. The analysis revealed the dynamics of five major classes of bacterial communities and showed that some communities change markedly over short time periods, whereas others are relatively stable. Modeling community stability using new quantitative measures indicates that deviation from stability correlates with time in the menstrual cycle, bacterial community composition, and sexual activity. The women studied are healthy; thus, it appears that neither variation in community composition per se nor higher levels of observed diversity (co-dominance) are necessarily indicative of dysbiosis.
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            Meta-analyses of human gut microbes associated with obesity and IBD.

            Recent studies have linked human gut microbes to obesity and inflammatory bowel disease, but consistent signals have been difficult to identify. Here we test for indicator taxa and general features of the microbiota that are generally consistent across studies of obesity and of IBD, focusing on studies involving high-throughput sequencing of the 16S rRNA gene (which we could process using a common computational pipeline). We find that IBD has a consistent signature across studies and allows high classification accuracy of IBD from non-IBD subjects, but that although subjects can be classified as lean or obese within each individual study with statistically significant accuracy, consistent with the ability of the microbiota to experimentally transfer this phenotype, signatures of obesity are not consistent between studies even when the data are analyzed with consistent methods. The results suggest that correlations between microbes and clinical conditions with different effect sizes (e.g. the large effect size of IBD versus the small effect size of obesity) may require different cohort selection and analysis strategies.
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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

                Journal
                9502015
                8791
                Nat Med
                Nat. Med.
                Nature medicine
                1078-8956
                1546-170X
                12 December 2019
                10 April 2018
                26 February 2020
                : 24
                : 4
                : 392-400
                Affiliations
                [1. ]The Microbiome Center, Department of Surgery, University of Chicago, Chicago, IL, 60637
                [2. ]Bioscience Division, Argonne National Laboratory, Lemont, IL, 60439
                [3. ]The Marine Biological Laboratory, Woods Hole, MA, 02543
                [4. ]New York University Langone Medical Center, New York, NY 10016.
                [5. ]Pathogen and Microbiome Institute, Northern Arizona University, 1350 S Knoles Drive, Flagstaff, AZ 86011..
                [6. ]Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA 99354
                [7. ]Department of Medicine, University of California San Francisco, San Francisco, CA 94143..
                [8. ]Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA 92093
                [9. ]Department of Computer Science & Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, CA 92093
                [10. ]Center for Microbiome Innovation, University of California San Diego, La Jolla, CA 92093
                Author notes
                [* ]Corresponding Author: Rob Knight, robknight@ 123456ucsd.edu , 303-818-3879
                Article
                NIHMS1006252
                10.1038/nm.4517
                7043356
                29634682
                46a5f428-9cf1-4647-b14c-c248012005fb

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