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      Multi locus sequence typing of Chlamydiales: clonal groupings within the obligate intracellular bacteria Chlamydia trachomatis

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          Abstract

          Background

          The obligate intracellular growing bacterium Chlamydia trachomatis causes diseases like trachoma, urogenital infection and lymphogranuloma venereum with severe morbidity. Several serovars and genotypes have been identified, but these could not be linked to clinical disease or outcome. The related Chlamydophila pneumoniae, of which no subtypes are recognized, causes respiratory infections worldwide. We developed a multi locus sequence typing (MLST) scheme to understand the population genetic structure and diversity of these species and to evaluate the association between genotype and disease.

          Results

          A collection of 26 strains of C. trachomatis of different serovars and clinical presentation and 18 strains of C. pneumoniae were included in the study. For comparison, sequences of C. abortus, C. psittaci, C. caviae, C. felis, C. pecorum ( Chlamydophila), C. muridarum ( Chlamydia) and of Candidatus protochlamydia and Simkania negevensis were also included. Sequences of fragments (400 – 500 base pairs) from seven housekeeping genes ( enoA, fumC, gatA, gidA, hemN, hlfX, oppA) were analysed. Analysis of allelic profiles by eBurst revealed three non-overlapping clonal complexes among the C. trachomatis strains, while the C. pneumoniae strains formed a single group. An UPGMA tree produced from the allelic profiles resulted in three groups of sequence types. The LGV strains grouped in a single cluster, while the urogenital strains were distributed over two separated groups, one consisted solely of strains with frequent occurring serovars (E, D and F). The distribution of the different serovars over the three groups was not consistent, suggesting exchange of serovar encoding ompA sequences. In one instance, exchange of fumC sequences between strains of different groups was observed. Cluster analyses of concatenated sequences of the Chlamydophila and Chlamydia species together with those of Candidatus Protochlamydia amoebophila and Simkania negevensis resulted in a tree identical to that obtained with 23S RNA gene sequences.

          Conclusion

          These data show that C. trachomatis and C. pneumoniae are highly uniform. The difference in genetic diversity between C. trachomatis and C. pneumoniae is in concordance with a later assimilation to the human host of the latter. Our data supports the taxonomy of the order of Chlamydiales.

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          Most cited references45

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          MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment.

          S. KUMAR (2004)
          With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.
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            DnaSP, DNA polymorphism analyses by the coalescent and other methods.

            DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp
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              eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

              The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.
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                Author and article information

                Journal
                BMC Microbiol
                BMC Microbiology
                BioMed Central
                1471-2180
                2008
                28 February 2008
                : 8
                : 42
                Affiliations
                [1 ]Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, Amsterdam, The Netherlands
                [2 ]Department of Molecular Biology, Max Planck Institute for Infection Biology, Berlin, Germany
                [3 ]Department of Pathology, Laboratory of Immunogenetics, Section Immunogenetics of Infectious Diseases, & Department of Internal Medicine, Section Infectious Diseases, Free University Medical Center, Amsterdam, The Netherlands
                [4 ]Department of Medical Microbiology and Infectious Diseases, Erasmus Medical Centre and Laboratory of Medical Microbiology, Medisch Centrum Rijnmond-Zuid, Rotterdam, The Netherlands
                Article
                1471-2180-8-42
                10.1186/1471-2180-8-42
                2268939
                18307777
                07ec5377-a7c6-4062-b8f2-edb66967b0e5
                Copyright © 2008 Pannekoek 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
                : 16 October 2007
                : 28 February 2008
                Categories
                Research Article

                Microbiology & Virology
                Microbiology & Virology

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