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      Failure of phylogeny inferred from multilocus sequence typing to represent bacterial phylogeny

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          Abstract

          Although multilocus sequence typing (MLST) is highly discriminatory and useful for outbreak investigations and epidemiological surveillance, it has always been controversial whether clustering and phylogeny inferred from the MLST gene loci can represent the real phylogeny of bacterial strains. In this study, we compare the phylogenetic trees constructed using three approaches, (1) concatenated blocks of homologous sequence shared between the bacterial genomes, (2) genome single-nucleotide polymorphisms (SNP) profile and (3) concatenated nucleotide sequences of gene loci in the corresponding MLST schemes, for 10 bacterial species with >30 complete genome sequences available. Major differences in strain clustering at more than one position were observed between the phylogeny inferred using genome/SNP data and MLST for all 10 bacterial species. Shimodaira-Hasegawa test revealed significant difference between the topologies of the genome and MLST trees for nine of the 10 bacterial species, and significant difference between the topologies of the SNP and MLST trees were present for all 10 bacterial species. Matching Clusters and R-F Clusters metrics showed that the distances between the genome/SNP and MLST trees were larger than those between the SNP and genome trees. Phylogeny inferred from MLST failed to represent genome phylogeny with the same bacterial species.

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms.

            Traditional and molecular typing schemes for the characterization of pathogenic microorganisms are poorly portable because they index variation that is difficult to compare among laboratories. To overcome these problems, we propose multilocus sequence typing (MLST), which exploits the unambiguous nature and electronic portability of nucleotide sequence data for the characterization of microorganisms. To evaluate MLST, we determined the sequences of approximately 470-bp fragments from 11 housekeeping genes in a reference set of 107 isolates of Neisseria meningitidis from invasive disease and healthy carriers. For each locus, alleles were assigned arbitrary numbers and dendrograms were constructed from the pairwise differences in multilocus allelic profiles by cluster analysis. The strain associations obtained were consistent with clonal groupings previously determined by multilocus enzyme electrophoresis. A subset of six gene fragments was chosen that retained the resolution and congruence achieved by using all 11 loci. Most isolates from hyper-virulent lineages of serogroups A, B, and C meningococci were identical for all loci or differed from the majority type at only a single locus. MLST using six loci therefore reliably identified the major meningococcal lineages associated with invasive disease. MLST can be applied to almost all bacterial species and other haploid organisms, including those that are difficult to cultivate. The overwhelming advantage of MLST over other molecular typing methods is that sequence data are truly portable between laboratories, permitting one expanding global database per species to be placed on a World-Wide Web site, thus enabling exchange of molecular typing data for global epidemiology via the Internet.
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              MLST revisited: the gene-by-gene approach to bacterial genomics.

              Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.
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                Author and article information

                Contributors
                skplau@hku.hk
                pcywoo@hku.hk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                3 July 2017
                3 July 2017
                2017
                : 7
                : 4536
                Affiliations
                [1 ]ISNI 0000000121742757, GRID grid.194645.b, Department of Microbiology, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                [2 ]ISNI 0000000121742757, GRID grid.194645.b, Department of Computer Science, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                [3 ]ISNI 0000000121742757, GRID grid.194645.b, State Key Laboratory of Emerging Infectious Diseases, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                [4 ]ISNI 0000000121742757, GRID grid.194645.b, Research Centre of Infection and Immunology, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                [5 ]ISNI 0000000121742757, GRID grid.194645.b, Carol Yu Centre for Infection, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                [6 ]ISNI 0000000121742757, GRID grid.194645.b, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, , The University of Hong Kong, ; Pok Fu Lam, Hong Kong
                Article
                4707
                10.1038/s41598-017-04707-4
                5495804
                28674428
                33ba5111-8439-4a0b-8cb7-13b7cdb790f2
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 December 2016
                : 18 May 2017
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