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      Genomic characterization of Nocardia seriolae strains isolated from diseased fish

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          Abstract

          Members of the genus Nocardia are widespread in diverse environments; a wide range of Nocardia species are known to cause nocardiosis in several animals, including cat, dog, fish, and humans. Of the pathogenic Nocardia species, N. seriolae is known to cause disease in cultured fish, resulting in major economic loss. We isolated two N. seriolae strains, CK‐14008 and EM15050, from diseased fish and sequenced their genomes using the PacBio sequencing platform. To identify their genomic features, we compared their genomes with those of other Nocardia species. Phylogenetic analysis showed that N. seriolae shares a common ancestor with a putative human pathogenic Nocardia species. Moreover, N. seriolae strains were phylogenetically divided into four clusters according to host fish families. Through genome comparison, we observed that the putative pathogenic Nocardia strains had additional genes for iron acquisition. Dozens of antibiotic resistance genes were detected in the genomes of N. seriolae strains; most of the antibiotics were involved in the inhibition of the biosynthesis of proteins or cell walls. Our results demonstrated the virulence features and antibiotic resistance of fish pathogenic N. seriolae strains at the genomic level. These results may be useful to develop strategies for the prevention of fish nocardiosis.

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          Most cited references42

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          tRNAscan-SE: A Program for Improved Detection of Transfer RNA Genes in Genomic Sequence

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            antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification

            Abstract Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
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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
                bykim@chunlab.com
                immu@korea.kr
                Journal
                Microbiologyopen
                Microbiologyopen
                10.1002/(ISSN)2045-8827
                MBO3
                MicrobiologyOpen
                John Wiley and Sons Inc. (Hoboken )
                2045-8827
                16 August 2018
                March 2019
                : 8
                : 3 ( doiID: 10.1002/mbo3.2019.8.issue-3 )
                : e00656
                Affiliations
                [ 1 ] Pathology Research Division National Institute of Fisheries Science Busan Korea
                [ 2 ] ChunLab Inc. Seoul Korea
                [ 3 ] Laboratory of evolutionary bioinformatics Seoul National University Seoul Korea
                Author notes
                [*] [* ] Correspondence

                Byung‐Yong Kim, ChunLab Inc., JW TOWER, Nambusunhwan‐ro 2477, Seocho‐gu, Seoul 06725, Korea.

                Email: bykim@ 123456chunlab.com

                and

                Sung‐Hee Jung, Pathology Research Division, National Institute of Fisheries Science, Gijanghaean‐ro 216, Gijang‐eup, Busan, 46083, Korea.

                Email: immu@ 123456korea.kr

                [†]

                Co‐first authors.

                Author information
                http://orcid.org/0000-0002-4229-8859
                Article
                MBO3656
                10.1002/mbo3.656
                6436429
                30117297
                48a14141-98df-4da6-91fc-90125066f48d
                © 2018 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 March 2018
                : 23 April 2018
                : 24 April 2018
                Page count
                Figures: 5, Tables: 2, Pages: 12, Words: 8752
                Funding
                Funded by: National Institute of Fisheries Science, Republic of Korea
                Award ID: R2018062
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                mbo3656
                March 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.1 mode:remove_FC converted:27.03.2019

                Microbiology & Virology
                anguilla japonica,channa argus,comparative genomics,fish pathogen,norcardia seriolae

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