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      Implication of Lateral Genetic Transfer in the Emergence of Aeromonas hydrophila Isolates of Epidemic Outbreaks in Channel Catfish

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          Abstract

          To investigate the molecular basis of the emergence of Aeromonas hydrophila responsible for an epidemic outbreak of motile aeromonad septicemia of catfish in the Southeastern United States, we sequenced 11 A. hydrophila isolates that includes five reference and six recent epidemic isolates. Comparative genomics revealed that recent epidemic A. hydrophila isolates are highly clonal, whereas reference isolates are greatly diverse. We identified 55 epidemic-associated genetic regions with 313 predicted genes that are present in epidemic isolates but absent from reference isolates and 35% of these regions are located within genomic islands, suggesting their acquisition through lateral gene transfer. The epidemic-associated regions encode predicted prophage elements, pathogenicity islands, metabolic islands, fitness islands and genes of unknown functions, and 34 of the genes encoded in these regions were predicted as virulence factors. We found two pilus biogenesis gene clusters encoded within predicted pathogenicity islands. A functional metabolic island that encodes a complete pathway for myo-inositol catabolism was evident by the ability of epidemic A. hydrophila isolates to use myo-inositol as a sole carbon source. Testing of A. hydrophila field isolates found a consistent correlation between myo-inositol utilization as a sole carbon source and the presence of an epidemic-specific genetic marker. All epidemic isolates and one reference isolate shared a novel O-antigen cluster. Altogether we identified four different O-antigen biosynthesis gene clusters within the 11 sequenced A. hydrophila genomes. Our study reveals new insights into the evolutionary changes that have resulted in the emergence of recent epidemic A. hydrophila strains.

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          Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome".

          The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.
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            GeneMark.hmm: new solutions for gene finding.

            The number of completely sequenced bacterial genomes has been growing fast. There are computer methods available for finding genes but yet there is a need for more accurate algorithms. The GeneMark. hmm algorithm presented here was designed to improve the gene prediction quality in terms of finding exact gene boundaries. The idea was to embed the GeneMark models into naturally derived hidden Markov model framework with gene boundaries modeled as transitions between hidden states. We also used the specially derived ribosome binding site pattern to refine predictions of translation initiation codons. The algorithm was evaluated on several test sets including 10 complete bacterial genomes. It was shown that the new algorithm is significantly more accurate than GeneMark in exact gene prediction. Interestingly, the high gene finding accuracy was observed even in the case when Markov models of order zero, one and two were used. We present the analysis of false positive and false negative predictions with the caution that these categories are not precisely defined if the public database annotation is used as a control.
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              Genomic islands: tools of bacterial horizontal gene transfer and evolution

              Bacterial genomes evolve through mutations, rearrangements or horizontal gene transfer. Besides the core genes encoding essential metabolic functions, bacterial genomes also harbour a number of accessory genes acquired by horizontal gene transfer that might be beneficial under certain environmental conditions. The horizontal gene transfer contributes to the diversification and adaptation of microorganisms, thus having an impact on the genome plasticity. A significant part of the horizontal gene transfer is or has been facilitated by genomic islands (GEIs). GEIs are discrete DNA segments, some of which are mobile and others which are not, or are no longer mobile, which differ among closely related strains. A number of GEIs are capable of integration into the chromosome of the host, excision, and transfer to a new host by transformation, conjugation or transduction. GEIs play a crucial role in the evolution of a broad spectrum of bacteria as they are involved in the dissemination of variable genes, including antibiotic resistance and virulence genes leading to generation of hospital ‘superbugs’, as well as catabolic genes leading to formation of new metabolic pathways. Depending on the composition of gene modules, the same type of GEIs can promote survival of pathogenic as well as environmental bacteria.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                20 November 2013
                : 8
                : 11
                : e80943
                Affiliations
                [1 ]Department of Biological Sciences, Auburn University, Auburn, Alabama, United States of America
                [2 ]USDA, Catfish Genetics Research Unit, Stoneville, Mississippi, United States of America
                [3 ]Department of Fisheries & Allied Aquacultures, Auburn University, Auburn, Alabama, United States of America
                [4 ]Alabama Fish Farming Center, Greensboro, Alabama, United States of America
                [5 ]Mississippi State University, College Veterinary Medicine, Stoneville, Mississippi, United States of America
                [6 ]Aquaculture & Fisheries Center, The University of Arkansas at Pine Bluff, Pine Bluff, Arkansas, United States of America
                [7 ]Bovine Functional Genomics Laboratory, USDA, ARS, Beltsville, Maryland, United States of America
                [8 ]Department of Pathobiology, Auburn University, Auburn, Alabama, United States of America
                Institut National de la Recherche Agronomique, France
                Author notes

                Competing Interests: Co-author Mark Liles is a PLOS ONE Editorial Board member, and this does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: MJH GCW LK AEG JCN JST MRL. Performed the experiments: MJH GCW DS NKC WBH KC MJG TSS SS KH. Analyzed the data: MJH GCW MRL. Contributed reagents/materials/analysis tools: WBH TSS SS. Wrote the manuscript: MJH MRL.

                Article
                PONE-D-13-33827
                10.1371/journal.pone.0080943
                3835674
                24278351
                0db1a828-e957-4836-b990-b83e99a7c239
                Copyright @ 2013

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 16 August 2013
                : 8 October 2013
                Funding
                The Alabama Agricultural Experiment Station (Hatch project #ALA021-1-09005) provided research funding and the Alabama EPSCoR program provided stipend support for the first author MJH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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