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      A Reservoir of Drug-Resistant Pathogenic Bacteria in Asymptomatic Hosts

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      PLoS ONE
      Public Library of Science

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          Abstract

          The population genetics of pathogenic bacteria has been intensively studied in order to understand the spread of disease and the evolution of virulence and drug resistance. However, much less attention has been paid to bacterial carriage populations, which inhabit hosts without producing disease. Since new virulent strains that cause disease can be recruited from the carriage population of bacteria, our understanding of infectious disease is seriously incomplete without knowledge on the population structure of pathogenic bacteria living in an asymptomatic host. We report the first extensive survey of the abundance and diversity of a human pathogen in asymptomatic animal hosts. We have found that asymptomatic swine from livestock productions frequently carry populations of Salmonella enterica with a broad range of drug-resistant strains and genetic diversity greatly exceeding that previously described. This study shows how agricultural practice and human intervention may lead and influence the evolution of a hidden reservoir of pathogens, with important implications for human health.

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          Most cited references49

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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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              Adaptive radiation in a heterogeneous environment.

              Successive adaptive radiations have played a pivotal role in the evolution of biological diversity. The effects of adaptive radiation are often seen, but the underlying causes are difficult to disentangle and remain unclear. Here we examine directly the role of ecological opportunity and competition in driving genetic diversification. We use the common aerobic bacterium Pseudomonas fluorescens, which evolves rapidly under novel environmental conditions to generate a large repertoire of mutants. When provided with ecological opportunity (afforded by spatial structure), identical populations diversify morphologically, but when ecological opportunity is restricted there is no such divergence. In spatially structured environments, the evolution of variant morphs follows a predictable sequence and we show that competition among the newly evolved niche-specialists maintains this variation. These results demonstrate that the elementary processes of mutation and selection alone are sufficient to promote rapid proliferation of new designs and support the theory that trade-offs in competitive ability drive adaptive radiation.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2008
                18 November 2008
                : 3
                : 11
                : e3749
                Affiliations
                [1 ]Department of Biology, McGill University, Montreal, Quebec, Canada
                [2 ]Département de Pathologie et Microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Quebec, Canada
                University of Sydney, Australia
                Author notes

                Conceived and designed the experiments: GGP SQ GB. Performed the experiments: GGP. Analyzed the data: GGP SQ GB. Wrote the paper: GGP SQ GB.

                [¤]

                Current address: Department of Zoology, University of Oxford, Oxford, United Kingdom

                Article
                08-PONE-RA-04505R3
                10.1371/journal.pone.0003749
                2581806
                19015729
                12cde762-2f08-4302-8358-ee91b3675fcf
                Perron et al. 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
                : 28 April 2008
                : 26 October 2008
                Page count
                Pages: 5
                Categories
                Research Article
                Ecology/Population Ecology
                Evolutionary Biology/Microbial Evolution and Genomics
                Infectious Diseases/Antimicrobials and Drug Resistance
                Infectious Diseases/Bacterial Infections
                Infectious Diseases/Epidemiology and Control of Infectious Diseases
                Public Health and Epidemiology/Epidemiology
                Public Health and Epidemiology/Infectious Diseases

                Uncategorized
                Uncategorized

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