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. bacterial evolution ͉ chip technology ͉ population genetics P seudomonas aeruginosa is a metabolically versatile Gramnegative bacterium, which inhabits terrestrial, aquatic, animal-, human-, and plant-host-associated environments (1). This opportunistic pathogen is the most dominant bacterium causing chronic infections in the cystic fibrosis (CF) lung (2) and has emerged as an important causative agent of nosocomial infections, particularly in intensive-care units (3).The P. aeruginosa genome is a mosaic of a conserved core and variable accessory segments (4). The core genome is characterized by a conserved synteny of genes, a low average nucleotide divergence of 0.5%, and multiple alleles at a few loci that are subject to diversifying selection (4-6). The accessory genome consists of a variable set of genomic islets and genomic islands, most of which belong to an ancient tRNA-integrated island type (4, 7-11). Genome size ranges from 5.2 to 7 Mbp in the P. aeruginosa population (4).Typing informative traits allows identification of bacterial isolates to the strain level and provides basic information about the evolutionary biology, population biology, taxonomy, ecology, and genetics of bacteria. Typically, strains of bacteria, including P. aeruginosa, have been differentiated on the basis of specific phenotypic traits or anonymous ...

Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.

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The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss.