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      Genome Sequence of the Versatile Fish Pathogen Edwardsiella tarda Provides Insights into its Adaptation to Broad Host Ranges and Intracellular Niches

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          Abstract

          Background

          Edwardsiella tarda is the etiologic agent of edwardsiellosis, a devastating fish disease prevailing in worldwide aquaculture industries. Here we describe the complete genome of E. tarda, EIB202, a highly virulent and multi-drug resistant isolate in China.

          Methodology/Principal Findings

          E. tarda EIB202 possesses a single chromosome of 3,760,463 base pairs containing 3,486 predicted protein coding sequences, 8 ribosomal rRNA operons, and 95 tRNA genes, and a 43,703 bp conjugative plasmid harboring multi-drug resistant determinants and encoding type IV A secretion system components. We identified a full spectrum of genetic properties related to its genome plasticity such as repeated sequences, insertion sequences, phage-like proteins, integrases, recombinases and genomic islands. In addition, analysis also indicated that a substantial proportion of the E. tarda genome might be devoted to the growth and survival under diverse conditions including intracellular niches, with a large number of aerobic or anaerobic respiration-associated proteins, signal transduction proteins as well as proteins involved in various stress adaptations. A pool of genes for secretion systems, pili formation, nonfimbrial adhesions, invasions and hemagglutinins, chondroitinases, hemolysins, iron scavenging systems as well as the incomplete flagellar biogenesis might feature its surface structures and pathogenesis in a fish body.

          Conclusion/Significance

          Genomic analysis of the bacterium offered insights into the phylogeny, metabolism, drug-resistance, stress adaptation, and virulence characteristics of this versatile pathogen, which constitutes an important first step in understanding the pathogenesis of E. tarda to facilitate construction of a practical effective vaccine used for combating fish edwardsiellosis.

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          Most cited references52

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          Quorum sensing: cell-to-cell communication in bacteria.

          Bacteria communicate with one another using chemical signal molecules. As in higher organisms, the information supplied by these molecules is critical for synchronizing the activities of large groups of cells. In bacteria, chemical communication involves producing, releasing, detecting, and responding to small hormone-like molecules termed autoinducers . This process, termed quorum sensing, allows bacteria to monitor the environment for other bacteria and to alter behavior on a population-wide scale in response to changes in the number and/or species present in a community. Most quorum-sensing-controlled processes are unproductive when undertaken by an individual bacterium acting alone but become beneficial when carried out simultaneously by a large number of cells. Thus, quorum sensing confuses the distinction between prokaryotes and eukaryotes because it enables bacteria to act as multicellular organisms. This review focuses on the architectures of bacterial chemical communication networks; how chemical information is integrated, processed, and transduced to control gene expression; how intra- and interspecies cell-cell communication is accomplished; and the intriguing possibility of prokaryote-eukaryote cross-communication.
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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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              Cytoplasmic flagellin activates caspase-1 and secretion of interleukin 1beta via Ipaf.

              Macrophages respond to Salmonella typhimurium infection via Ipaf, a NACHT-leucine-rich repeat family member that activates caspase-1 and secretion of interleukin 1beta. However, the specific microbial salmonella-derived agonist responsible for activating Ipaf is unknown. We show here that cytosolic bacterial flagellin activated caspase-1 through Ipaf but was independent of Toll-like receptor 5, a known flagellin sensor. Stimulation of the Ipaf pathway in macrophages after infection required a functional salmonella pathogenicity island 1 type III secretion system but not the flagellar type III secretion system; furthermore, Ipaf activation could be recapitulated by the introduction of purified flagellin directly into the cytoplasm. These observations raise the possibility that the salmonella pathogenicity island 1 type III secretion system cannot completely exclude 'promiscuous' secretion of flagellin and that the host capitalizes on this 'error' by activating a potent host-defense pathway.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                29 October 2009
                : 4
                : 10
                : e7646
                Affiliations
                [1 ]State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
                [2 ]Shanghai - MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, China
                University of Hyderabad, India
                Author notes

                Conceived and designed the experiments: QW MY QL YZ. Performed the experiments: QW MY JX XW YL LX HZ SW GZ. Analyzed the data: QW MY JX HW QL YZ. Wrote the paper: QW MY QL YZ.

                Article
                09-PONE-RA-11733R1
                10.1371/journal.pone.0007646
                2764856
                19865481
                ecf964c4-b889-4d6d-bee9-78c48f547a37
                Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 18 July 2009
                : 7 October 2009
                Page count
                Pages: 16
                Categories
                Research Article
                Microbiology/Applied Microbiology
                Microbiology/Cellular Microbiology and Pathogenesis
                Microbiology/Microbial Evolution and Genomics

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