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      Genomic heterogeneity differentiates clinical and environmental subgroups of Legionella pneumophila sequence type 1

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          Abstract

          Legionella spp. are the cause of a severe bacterial pneumonia known as Legionnaires’ disease (LD). In some cases, current genetic subtyping methods cannot resolve LD outbreaks caused by common, potentially endemic L. pneumophila (Lp) sequence types (ST), which complicates laboratory investigations and environmental source attribution. In the United States (US), ST1 is the most prevalent clinical and environmental Lp sequence type. In order to characterize the ST1 population, we sequenced 289 outbreak and non-outbreak associated clinical and environmental ST1 and ST1-variant Lp strains from the US and, together with international isolate sequences, explored their genetic and geographic diversity. The ST1 population was highly conserved at the nucleotide level; 98% of core nucleotide positions were invariant and environmental isolates unassociated with human disease (n = 99) contained ~65% more nucleotide diversity compared to clinical-sporadic (n = 139) or outbreak-associated (n = 28) ST1 subgroups. The accessory pangenome of environmental isolates was also ~30–60% larger than other subgroups and was enriched for transposition and conjugative transfer-associated elements. Up to ~10% of US ST1 genetic variation could be explained by geographic origin, but considerable genetic conservation existed among strains isolated from geographically distant states and from different decades. These findings provide new insight into the ST1 population structure and establish a foundation for interpreting genetic relationships among ST1 strains; these data may also inform future analyses for improved outbreak investigations.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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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

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – review & editing
                Role: Investigation
                Role: ConceptualizationRole: InvestigationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: Funding acquisitionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                18 October 2018
                2018
                : 13
                : 10
                : e0206110
                Affiliations
                [001]Pneumonia Response and Surveillance Laboratory, Respiratory Diseases Branch, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
                University of Mississippi Medical Center, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2553-1230
                http://orcid.org/0000-0001-9111-406X
                http://orcid.org/0000-0003-1652-5795
                Article
                PONE-D-18-17595
                10.1371/journal.pone.0206110
                6193728
                30335848
                a247c896-d18d-4e81-aacf-1edcc957c1ba

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 18 June 2018
                : 5 October 2018
                Page count
                Figures: 5, Tables: 2, Pages: 24
                Funding
                This study was supported by funding made available through the CDC Office of Advanced Molecular Detection. No additional external funding was received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Bacteria
                Legionella
                Legionella Pneumophila
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Legionella
                Legionella Pneumophila
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Legionella
                Legionella Pneumophila
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Biology and Life Sciences
                Computational Biology
                Comparative Genomics
                Biology and Life Sciences
                Genetics
                Genomics
                Comparative Genomics
                Research and Analysis Methods
                Database and Informatics Methods
                Biological Databases
                Sequence Databases
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Databases
                Biology and Life Sciences
                Biogeography
                Phylogeography
                Ecology and Environmental Sciences
                Biogeography
                Phylogeography
                Earth Sciences
                Geography
                Biogeography
                Phylogeography
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Genetics
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Gene Mapping
                Nucleotide Mapping
                Research and Analysis Methods
                Molecular Biology Techniques
                Gene Mapping
                Nucleotide Mapping
                People and places
                Geographical locations
                North America
                United States
                Biology and life sciences
                Genetics
                DNA
                DNA recombination
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA recombination
                Custom metadata
                Sequencing data derived from this study have been deposited with links to BioProject accession number PRJNA423272 in the NCBI BioProject Database ( https://www.ncbi.nlm.nih.gov/bioproject/). Raw Illumina sequencing reads were assigned the SRA accession SRP127407 (Sequence Read Archive, https://www.ncbi.nlm.nih.gov/sra) and individual isolate SRA sequence accession IDs are listed in S1 Table.

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