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      Multilocus Sequence Typing of Borrelia burgdorferi Suggests Existence of Lineages with Differential Pathogenic Properties in Humans

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          Abstract

          The clinical manifestations of Lyme disease, caused by Borrelia burgdorferi, vary considerably in different patients, possibly due to infection by strains with varying pathogenicity. Both rRNA intergenic spacer and ospC typing methods have proven to be useful tools for categorizing B. burgdorferi strains that vary in their tendency to disseminate in humans. Neither method, however, is suitable for inferring intraspecific relationships among strains that are important for understanding the evolution of pathogenicity and the geographic spread of disease. In this study, multilocus sequence typing (MLST) was employed to investigate the population structure of B. burgdorferi recovered from human Lyme disease patients. A total of 146 clinical isolates from patients in New York and Wisconsin were divided into 53 sequence types (STs). A goeBURST analysis, that also included previously published STs from the northeastern and upper Midwestern US and adjoining areas of Canada, identified 11 major and 3 minor clonal complexes, as well as 14 singletons. The data revealed that patients from New York and Wisconsin were infected with two distinct, but genetically and phylogenetically closely related, populations of B. burgdorferi. Importantly, the data suggest the existence of B. burgdorferi lineages with differential capabilities for dissemination in humans. Interestingly, the data also indicate that MLST is better able to predict the outcome of localized or disseminated infection than is ospC typing.

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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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            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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              The evolutionary history of methicillin-resistant Staphylococcus aureus (MRSA).

              Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of hospital-acquired infections that are becoming increasingly difficult to combat because of emerging resistance to all current antibiotic classes. The evolutionary origins of MRSA are poorly understood, no rational nomenclature exists, and there is no consensus on the number of major MRSA clones or the relatedness of clones described from different countries. We resolve all of these issues and provide a more thorough and precise analysis of the evolution of MRSA clones than has previously been possible. Using multilocus sequence typing and an algorithm, BURST, we analyzed an international collection of 912 MRSA and methicillin-susceptible S. aureus (MSSA) isolates. We identified 11 major MRSA clones within five groups of related genotypes. The putative ancestral genotype of each group and the most parsimonious patterns of descent of isolates from each ancestor were inferred by using BURST, which, together with analysis of the methicillin resistance genes, established the likely evolutionary origins of each major MRSA clone, the genotype of the original MRSA clone and its MSSA progenitor, and the extent of acquisition and horizontal movement of the methicillin resistance genes. Major MRSA clones have arisen repeatedly from successful epidemic MSSA strains, and isolates with decreased susceptibility to vancomycin, the antibiotic of last resort, are arising from some of these major MRSA clones, highlighting a depressing progression of increasing drug resistance within a small number of ecologically successful S. aureus genotypes.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                17 September 2013
                : 8
                : 9
                : e73066
                Affiliations
                [1 ]Department of Microbiology and Immunology, New York Medical College, Valhalla, New York, United States of America
                [2 ]Zoonoses Division, Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Ottawa, Ontario, Canada
                [3 ]Institute for Infectious Diseases and Zoonoses, Ludwig-Maximilians-University Munich and National Reference Centre for Borrelia at the Bavarian Health and Food Safety Authority, Oberschleissheim, Germany
                [4 ]Division of Infectious Diseases, Department of Medicine, New York Medical College, Valhalla, New York, United States of America
                [5 ]Department of Pathology and Laboratory Medicine, University of Wisconsin, Madison, Wisconsin, United States of America
                [6 ]Marshfield Clinic Research Foundation, Marshfield, Wisconsin, United States of America
                University of Kentucky College of Medicine, United States of America
                Author notes

                Competing Interests: All the authors with exception of Dr. Wormser have declared that no competing interests exist. Dr. Gary Wormser has following conflicts/disclosures: Research grants from CDC, NIH, Immunetics, Inc., BioRad, DiaSorin, Inc., and BioMerieux; Equity in Abbott; Expert witness in malpractice cases involving Lyme disease; Unpaid board member American Lyme Disease Foundation; Expert witness regarding Lyme disease in a disciplinary action for the Missouri Board of Registration for the Healing Arts. Consultant to Baxter for Lyme vaccine development. GPW is on the Editorial Board of PLOS ONE.

                Conceived and designed the experiments: IS KH. Performed the experiments: KH PM. Analyzed the data: KH PM NO. Contributed reagents/materials/analysis tools: IS GW KR JM MV NO GM. Wrote the paper: KH NO GM IS PM.

                Article
                PONE-D-13-18343
                10.1371/journal.pone.0073066
                3775742
                24069170
                517d0928-eeb6-4a02-a43b-415353b7e0a1
                Copyright @ 2013

                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
                : 3 May 2013
                : 17 July 2013
                Page count
                Pages: 11
                Funding
                This work was supported by grants from the National Institutes of Health (AR41511 and AI45801) and the William and Sylvia Silberstein Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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