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      Population structure of Pseudomonas aeruginosa

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          Abstract

          The metabolically versatile Gram-negative bacterium Pseudomonas aeruginosa inhabits terrestrial, aquatic, animal-, human-, and plant-host-associated environments and is an important causative agent of nosocomial infections, particularly in intensive-care units. The population genetics of P. aeruginosa was investigated by an approach that is generally applicable to the rapid, robust, and informative genotyping of bacteria. DNA, amplified from the bacterial colony by circles of multiplex primer extension, is hybridized onto a microarray to yield an electronically portable binary multimarker genotype that represents the core genome by single nucleotide polymorphisms and the accessory genome by markers of genomic islets and islands. The 240 typed P. aeruginosa strains of diverse habitats and geographic origin segregated into two large nonoverlapping clusters and 45 isolated clonal complexes with few or no partners. The majority of strains belonged to few dominant clones widespread in disease and environmental habitats. The most frequent genotype was represented by the sequenced strain PA14. Core and accessory genome were found to be nonrandomly assembled in P. aeruginosa. Individual clones preferred a specific repertoire of accessory segments. Even the most promiscuous genomic island, pKLC102, had integrated preferentially into a subset of clones. Moreover, some physically distant loci of the core genome, including oriC, showed nonrandom associations of genotypes, whereas other segments in between were freely recombining. Thus, the P. aeruginosa genome is made up of clone-typical segments in core and accessory genome and of blocks in the core with unrestricted gene flow in the population.

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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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            Lung infections associated with cystic fibrosis.

            While originally characterized as a collection of related syndromes, cystic fibrosis (CF) is now recognized as a single disease whose diverse symptoms stem from the wide tissue distribution of the gene product that is defective in CF, the ion channel and regulator, cystic fibrosis transmembrane conductance regulator (CFTR). Defective CFTR protein impacts the function of the pancreas and alters the consistency of mucosal secretions. The latter of these effects probably plays an important role in the defective resistance of CF patients to many pathogens. As the modalities of CF research have changed over the decades from empirical histological studies to include biophysical measurements of CFTR function, the clinical management of this disease has similarly evolved to effectively address the ever-changing spectrum of CF-related infectious diseases. These factors have led to the successful management of many CF-related infections with the notable exception of chronic lung infection with the gram-negative bacterium Pseudomonas aeruginosa. The virulence of P. aeruginosa stems from multiple bacterial attributes, including antibiotic resistance, the ability to utilize quorum-sensing signals to form biofilms, the destructive potential of a multitude of its microbial toxins, and the ability to acquire a mucoid phenotype, which renders this microbe resistant to both the innate and acquired immunologic defenses of the host.
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              Multilocus sequence typing of bacteria.

              Multilocus sequence typing (MLST) was proposed in 1998 as a portable, universal, and definitive method for characterizing bacteria, using the human pathogen Neisseria meningitidis as an example. In addition to providing a standardized approach to data collection, by examining the nucleotide sequences of multiple loci encoding housekeeping genes, or fragments of them, MLST data are made freely available over the Internet to ensure that a uniform nomenclature is readily available to all those interested in categorizing bacteria. At the time of writing, over thirty MLST schemes have been published and made available on the Internet, mostly for pathogenic bacteria, although there are schemes for pathogenic fungi and some nonpathogenic bacteria. MLST data have been employed in epidemiological investigations of various scales and in studies of the population biology, pathogenicity, and evolution of bacteria. The increasing speed and reduced cost of nucleotide sequence determination, together with improved web-based databases and analysis tools, present the prospect of increasingly wide application of MLST.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                May 08 2007
                May 08 2007
                April 27 2007
                May 08 2007
                : 104
                : 19
                : 8101-8106
                Article
                10.1073/pnas.0609213104
                1876578
                17468398
                9734328d-0a8d-43be-953e-382c9a71d6cc
                © 2007
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