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      Catalogue of antibiotic resistome and host-tracking in drinking water deciphered by a large scale survey

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          Abstract

          Background

          Excesses of antibiotic resistance genes (ARGs), which are regarded as emerging environmental pollutants, have been observed in various environments. The incidence of ARGs in drinking water causes potential risks to human health and receives more attention from the public. However, ARGs harbored in drinking water remain largely unexplored. In this study, we aimed at establishing an antibiotic resistome catalogue in drinking water samples from a wide range of regions and to explore the potential hosts of ARGs.

          Results

          A catalogue of antibiotic resistome in drinking water was established, and the host-tracking of ARGs was conducted through a large-scale survey using metagenomic approach. The drinking water samples were collected at the point of use in 25 cities in mainland China, Hong Kong, Macau, Taiwan, South Africa, Singapore and the USA. In total, 181 ARG subtypes belonging to 16 ARG types were detected with an abundance range of 2.8 × 10 −2 to 4.2 × 10 −1 copies of ARG per cell. The highest abundance was found in northern China (Henan Province). Bacitracin, multidrug, aminoglycoside, sulfonamide, and beta-lactam resistance genes were dominant in drinking water. Of the drinking water samples tested, 84% had a higher ARG abundance than typical environmental ecosystems of sediment and soil. Metagenomic assembly-based host-tracking analysis identified Acidovorax, Acinetobacter, Aeromonas, Methylobacterium, Methyloversatilis, Mycobacterium, Polaromonas, and Pseudomonas as the hosts of ARGs. Moreover, potential horizontal transfer of ARGs in drinking water systems was proposed by network and Procrustes analyses.

          Conclusions

          The antibiotic resistome catalogue compiled using a large-scale survey provides a useful reference for future studies on the global surveillance and risk management of ARGs in drinking water.

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          Electronic supplementary material

          The online version of this article (10.1186/s40168-017-0369-0) contains supplementary material, which is available to authorized users.

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          Most cited references31

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Modularity and community structure in networks

            M. Newman (2006)
            Many networks of interest in the sciences, including a variety of social and biological networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure has attracted considerable recent attention. One of the most sensitive detection methods is optimization of the quality function known as "modularity" over the possible divisions of a network, but direct application of this method using, for instance, simulated annealing is computationally costly. Here we show that the modularity can be reformulated in terms of the eigenvectors of a new characteristic matrix for the network, which we call the modularity matrix, and that this reformulation leads to a spectral algorithm for community detection that returns results of better quality than competing methods in noticeably shorter running times. We demonstrate the algorithm with applications to several network data sets.
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              ARDB—Antibiotic Resistance Genes Database

              The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database—the Antibiotic Resistance Genes Database (ARDB)—unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13 293 genes, 377 types, 257 antibiotics, 632 genomes, 933 species and 124 genera. ARDB is available at http://ardb.cbcb.umd.edu/.
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                Author and article information

                Contributors
                +852-28578551 , zhangt@hku.hk
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                28 November 2017
                28 November 2017
                2017
                : 5
                : 154
                Affiliations
                [1 ]ISNI 0000000121742757, GRID grid.194645.b, Environmental Biotechnology Laboratory, , The University of Hong Kong, ; Pokfulam Road, Hong Kong, China
                [2 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Graduate School at Shenzhen, , Tsinghua University, ; Shenzhen, China
                Author information
                http://orcid.org/0000-0003-1148-4322
                Article
                369
                10.1186/s40168-017-0369-0
                5704573
                29179769
                f5f4c17b-3ebe-4f77-8458-5d8efb52930e
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                : 27 April 2017
                : 2 November 2017
                Funding
                Funded by: Hong Kong General Research Fund
                Award ID: 172057/15E
                Award Recipient :
                Funded by: Shenzhen Knowledge Innovation Program-Basic Research Project
                Award ID: JCYJ20150831192847649
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                drinking water,public health,antibiotic resistome,host-tracking,horizontal gene transfer,bacterial community

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