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      Antibiotic Treatment Drives the Diversification of the Human Gut Resistome

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          Abstract

          Despite the documented antibiotic-induced disruption of the gut microbiota, the impact of antibiotic intake on strain-level dynamics, evolution of resistance genes, and factors influencing resistance dissemination potential remains poorly understood. To address this gap we analyzed public metagenomic datasets from 24 antibiotic treated subjects and controls, combined with an in-depth prospective functional study with two subjects investigating the bacterial community dynamics based on cultivation-dependent and independent methods. We observed that short-term antibiotic treatment shifted and diversified the resistome composition, increased the average copy number of antibiotic resistance genes, and altered the dominant strain genotypes in an individual-specific manner. More than 30% of the resistance genes underwent strong differentiation at the single nucleotide level during antibiotic treatment. We found that the increased potential for horizontal gene transfer, due to antibiotic administration, was ∼3-fold stronger in the differentiated resistance genes than the non-differentiated ones. This study highlights how antibiotic treatment has individualized impacts on the resistome and strain level composition, and drives the adaptive evolution of the gut microbiota.

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            Short-Term Antibiotic Treatment Has Differing Long-Term Impacts on the Human Throat and Gut Microbiome

            Antibiotic administration is the standard treatment for the bacterium Helicobacter pylori, the main causative agent of peptic ulcer disease and gastric cancer. However, the long-term consequences of this treatment on the human indigenous microbiota are relatively unexplored. Here we studied short- and long-term effects of clarithromycin and metronidazole treatment, a commonly used therapy regimen against H. pylori, on the indigenous microbiota in the throat and in the lower intestine. The bacterial compositions in samples collected over a four-year period were monitored by analyzing the 16S rRNA gene using 454-based pyrosequencing and terminal-restriction fragment length polymorphism (T-RFLP). While the microbial communities of untreated control subjects were relatively stable over time, dramatic shifts were observed one week after antibiotic treatment with reduced bacterial diversity in all treated subjects in both locations. While the microbiota of the different subjects responded uniquely to the antibiotic treatment some general trends could be observed; such as a dramatic decline in Actinobacteria in both throat and feces immediately after treatment. Although the diversity of the microbiota subsequently recovered to resemble the pre treatment states, the microbiota remained perturbed in some cases for up to four years post treatment. In addition, four years after treatment high levels of the macrolide resistance gene erm(B) were found, indicating that antibiotic resistance, once selected for, can persist for longer periods of time than previously recognized. This highlights the importance of a restrictive antibiotic usage in order to prevent subsequent treatment failure and potential spread of antibiotic resistance.
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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
                Journal
                Genomics Proteomics Bioinformatics
                Genomics Proteomics Bioinformatics
                Genomics, Proteomics & Bioinformatics
                Elsevier
                1672-0229
                2210-3244
                23 April 2019
                February 2019
                23 April 2019
                : 17
                : 1
                : 39-51
                Affiliations
                [1 ]Department of Infectious Diseases and Public Health, Colleague of Veterinary Medicine and Life Sciences, City Univerity of Hong Kong, Hong Kong Special Administrative Region, China
                [2 ]School of Data Science, City Univerity of Hong Kong, Hong Kong Special Administrative Region, China
                [3 ]Novo Nordisk Foundation Center for Biosustainability, DK-2900 Hørsholm, Denmark
                [4 ]Systems Biology and Bioinformatics Unit, Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute, 07745 Jena, Germany
                [5 ]Systems Biology and Bioinformatics Group, School of Biological Sciences, Faculty of Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China
                [6 ]Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
                Author notes
                [#]

                Equal contribution.

                [a]

                ORCID: 0000-0001-7218-429X.

                [b]

                ORCID: 0000-0001-5586-0508.

                [c]

                ORCID: 0000-0002-1669-2529.

                [d]

                ORCID: 0000-0002-9736-0461.

                [e]

                ORCID: 0000-0001-9393-124X.

                [f]

                ORCID: 0000-0003-4005-5674.

                Article
                S1672-0229(19)30060-9
                10.1016/j.gpb.2018.12.003
                6520913
                31026582
                5b3632d4-43d3-44c3-bdf3-b9418e857da5
                © 2019 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 3 May 2018
                : 10 October 2018
                : 17 December 2018
                Categories
                Original Research

                antibiotics,resistome,gut microbiome,strain,evolution,horizontal gene transfer

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