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      ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

      research-article
      Author(s): 1 , * , 2 , 3 , *
      Editor(s):
      Publication date (Electronic):
      Journal: PLoS Computational Biology
      Publisher: Public Library of Science

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          Abstract

          Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.

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          Most cited references50

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          Dating of the human-ape splitting by a molecular clock of mitochondrial DNA.

          H Kishino, T Yano, M. Hasegawa (1984)
          A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed. This method takes into account effectively the information contained in a set of DNA sequence data. The molecular clock of mitochondrial DNA (mtDNA) was calibrated by setting the date of divergence between primates and ungulates at the Cretaceous-Tertiary boundary (65 million years ago), when the extinction of dinosaurs occurred. A generalized least-squares method was applied in fitting a model to mtDNA sequence data, and the clock gave dates of 92.3 +/- 11.7, 13.3 +/- 1.5, 10.9 +/- 1.2, 3.7 +/- 0.6, and 2.7 +/- 0.6 million years ago (where the second of each pair of numbers is the standard deviation) for the separation of mouse, gibbon, orangutan, gorilla, and chimpanzee, respectively, from the line leading to humans. Although there is some uncertainty in the clock, this dating may pose a problem for the widely believed hypothesis that the pipedal creature Australopithecus afarensis, which lived some 3.7 million years ago at Laetoli in Tanzania and at Hadar in Ethiopia, was ancestral to man and evolved after the human-ape splitting. Another likelier possibility is that mtDNA was transferred through hybridization between a proto-human and a proto-chimpanzee after the former had developed bipedalism.
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            Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms.

            M. C. J. Maiden, J. Bygraves, E Feil … (1998)
            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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              Transforming clinical microbiology with bacterial genome sequencing.

              Xavier Didelot, Rory Bowden, Daniel J Wilson … (2012)
              Whole-genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for addressing many microbiological questions. Here, we review the current status of clinical microbiology and how it has already begun to be transformed by using next-generation sequencing. We focus on three essential tasks: identifying the species of an isolate, testing its properties, such as resistance to antibiotics and virulence, and monitoring the emergence and spread of bacterial pathogens. We predict that the application of next-generation sequencing will soon be sufficiently fast, accurate and cheap to be used in routine clinical microbiology practice, where it could replace many complex current techniques with a single, more efficient workflow.
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                Author and article information

                Contributors
                Andreas Prlic: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS Comput Biol
                Journal ID (iso-abbrev): PLoS Comput. Biol
                Journal ID (publisher-id): plos
                Journal ID (pmc): ploscomp
                Title: PLoS Computational Biology
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Print): 1553-734X
                ISSN (Electronic): 1553-7358
                Publication date Collection: February 2015
                Publication date (Electronic): 12 February 2015
                Volume: 11
                Issue: 2
                Electronic Location Identifier: e1004041
                Affiliations
                [1 ]Department of Infectious Disease Epidemiology, Imperial College, London, United Kingdom
                [2 ]Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
                [3 ]Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
                UCSD, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: XD DJW. Performed the experiments: XD DJW. Analyzed the data: XD DJW. Contributed reagents/materials/analysis tools: XD DJW. Wrote the paper: XD DJW.

                Article
                Publisher ID: PCOMPBIOL-D-14-01517
                DOI: 10.1371/journal.pcbi.1004041
                PMC ID: 4326465
                PubMed ID: 25675341
                SO-VID: 828f2890-47f2-4f63-b236-aa133dcbad19
                Copyright statement: Copyright @ 2015
                License:

                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
                Date received : 19 August 2014
                Date accepted : 16 November 2014
                Page count
                Figures: 5, Tables: 0, Pages: 18
                Funding
                XD is funded by the National Institute for Health Research through Health Protection Research Unit funding. DJW is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (Grant 101237/Z/13/Z). This study was supported by the Oxford NIHR Biomedical Research Centre and the UKCRC Modernising Medical Microbiology Consortium, the latter funded under the UKCRC Translational Infection Research Initiative supported by the Medical Research Council, the Biotechnology and Biological Sciences Research Council and the National Institute for Health Research on behalf of the UK Department of Health (Grant G0800778) and the Wellcome Trust (Grant 087646/Z/08/Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Custom metadata
                Data Availability All data files are available from the author’s website http://www.danielwilson.me.uk/files/cfml.tgz

                ScienceOpen disciplines: Quantitative & Systems biology
                Data availability:
                ScienceOpen disciplines: Quantitative & Systems biology

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