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      Evolution in an oncogenic bacterial species with extreme genome plasticity: Helicobacter pylori East Asian genomes

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          Abstract

          Background

          The genome of Helicobacter pylori, an oncogenic bacterium in the human stomach, rapidly evolves and shows wide geographical divergence. The high incidence of stomach cancer in East Asia might be related to bacterial genotype. We used newly developed comparative methods to follow the evolution of East Asian H. pylori genomes using 20 complete genome sequences from Japanese, Korean, Amerind, European, and West African strains.

          Results

          A phylogenetic tree of concatenated well-defined core genes supported divergence of the East Asian lineage (hspEAsia; Japanese and Korean) from the European lineage ancestor, and then from the Amerind lineage ancestor. Phylogenetic profiling revealed a large difference in the repertoire of outer membrane proteins (including oipA, hopMN, babABC, sabAB and vacA-2) through gene loss, gain, and mutation. All known functions associated with molybdenum, a rare element essential to nearly all organisms that catalyzes two-electron-transfer oxidation-reduction reactions, appeared to be inactivated. Two pathways linking acetyl~CoA and acetate appeared intact in some Japanese strains. Phylogenetic analysis revealed greater divergence between the East Asian (hspEAsia) and the European (hpEurope) genomes in proteins in host interaction, specifically virulence factors ( tipα), outer membrane proteins, and lipopolysaccharide synthesis (human Lewis antigen mimicry) enzymes. Divergence was also seen in proteins in electron transfer and translation fidelity ( miaA, tilS), a DNA recombinase/exonuclease that recognizes genome identity ( addA), and DNA/RNA hybrid nucleases ( rnhAB). Positively selected amino acid changes between hspEAsia and hpEurope were mapped to products of cagA, vacA, homC (outer membrane protein), sotB (sugar transport), and a translation fidelity factor ( miaA). Large divergence was seen in genes related to antibiotics: frxA (metronidazole resistance), def (peptide deformylase, drug target), and ftsA (actin-like, drug target).

          Conclusions

          These results demonstrate dramatic genome evolution within a species, especially in likely host interaction genes. The East Asian strains appear to differ greatly from the European strains in electron transfer and redox reactions. These findings also suggest a model of adaptive evolution through proteome diversification and selection through modulation of translational fidelity. The results define H. pylori East Asian lineages and provide essential information for understanding their pathogenesis and designing drugs and therapies that target them.

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          Most cited references111

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          GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

          J Besemer (2001)
          Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
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            Neighbor-net: an agglomerative method for the construction of phylogenetic networks.

            We present Neighbor-Net, a distance based method for constructing phylogenetic networks that is based on the Neighbor-Joining (NJ) algorithm of Saitou and Nei. Neighbor-Net provides a snapshot of the data that can guide more detailed analysis. Unlike split decomposition, Neighbor-Net scales well and can quickly produce detailed and informative networks for several hundred taxa. We illustrate the method by reanalyzing three published data sets: a collection of 110 highly recombinant Salmonella multi-locus sequence typing sequences, the 135 "African Eve" human mitochondrial sequences published by Vigilant et al., and a collection of 12 Archeal chaperonin sequences demonstrating strong evidence for gene conversion. Neighbor-Net is available as part of the SplitsTree4 software package.
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              An algorithm for progressive multiple alignment of sequences with insertions.

              Dynamic programming algorithms guarantee to find the optimal alignment between two sequences. For more than a few sequences, exact algorithms become computationally impractical, and progressive algorithms iterating pairwise alignments are widely used. These heuristic methods have a serious drawback because pairwise algorithms do not differentiate insertions from deletions and end up penalizing single insertion events multiple times. Such an unrealistically high penalty for insertions typically results in overmatching of sequences and an underestimation of the number of insertion events. We describe a modification of the traditional alignment algorithm that can distinguish insertion from deletion and avoid repeated penalization of insertions and illustrate this method with a pair hidden Markov model that uses an evolutionary scoring function. In comparison with a traditional progressive alignment method, our algorithm infers a greater number of insertion events and creates gaps that are phylogenetically consistent but spatially less concentrated. Our results suggest that some insertion/deletion "hot spots" may actually be artifacts of traditional alignment algorithms.
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                Author and article information

                Journal
                BMC Microbiol
                BMC Microbiology
                BioMed Central
                1471-2180
                2011
                16 May 2011
                : 11
                : 104
                Affiliations
                [1 ]Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan
                [2 ]Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan
                [3 ]National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Aichi, 444-8585, Japan
                [4 ]Graduate School of Medicine, Kurume University, Kurume, Fukuoka, 830-0011, Japan
                [5 ]Fujitsu Kyushu Systems LTD, Fukuoka, Fukuoka 814-8589, Japan
                [6 ]Department of Biophysics and Biochemistry, Graduate School of Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan
                [7 ]Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, 277-8561, Japan
                [8 ]Department of Gastroenterology, Graduate School of Medicine, Kobe University, Chuou-ku, Kobe, Hyogo, 650-0017, Japan
                Article
                1471-2180-11-104
                10.1186/1471-2180-11-104
                3120642
                21575176
                d7eca8f0-df16-4ff4-8ef6-fff79160d713
                Copyright ©2011 Kawai et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 October 2010
                : 16 May 2011
                Categories
                Research Article

                Microbiology & Virology
                Microbiology & Virology

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