One of the hallmarks of the Gram-negative bacterium Pseudomonas aeruginosa is its ability to thrive in diverse environments that includes humans with a variety of debilitating diseases or immune deficiencies. Here we report the complete sequence and comparative analysis of the genomes of two representative P. aeruginosa strains isolated from cystic fibrosis (CF) patients whose genetic disorder predisposes them to infections by this pathogen. The comparison of the genomes of the two CF strains with those of other P. aeruginosa presents a picture of a mosaic genome, consisting of a conserved core component, interrupted in each strain by combinations of specific blocks of genes. These strain-specific segments of the genome are found in limited chromosomal locations, referred to as regions of genomic plasticity. The ability of P. aeruginosa to shape its genomic composition to favor survival in the widest range of environmental reservoirs, with corresponding enhancement of its metabolic capacity is supported by the identification of a genomic island in one of the sequenced CF isolates, encoding enzymes capable of degrading terpenoids produced by trees. This work suggests that niche adaptation is a major evolutionary force influencing the composition of bacterial genomes. Unlike genome reduction seen in host-adapted bacterial pathogens, the genetic capacity of P. aeruginosa is determined by the ability of individual strains to acquire or discard genomic segments, giving rise to strains with customized genomic repertoires. Consequently, this organism can survive in a wide range of environmental reservoirs that can serve as sources of the infecting organisms.

Mutations in the 81-bp rifampin resistance determining region (RRDR) and mutation V176F locating at the beginning of the ropB gene were analyzed by DNA sequencing of 86 Mycobacterium tuberculosis clinical isolates (72 resistant and 14 sensitive) from different parts of China. Sixty-five mutations of 22 distinct kinds, 21 point mutations, and 1 insertion were found in 65 of 72 resistant isolates. The most common mutations were in codons 531 (41%), 526 (40%), and 516 (4%). Mutations were not found in seven (10%) of the resistant isolates. Six new alleles within the RRDR, along with five novel mutations outside the RRDR, are reported. None of isolates contained the V176 mutation.Tuberculosis (TB) remains one of the main threats to humans, causing 8 million new cases and 2 million deaths each year. The problem is becoming more critical with the emergence and spread of multidrug-resistant (MDR) strains of Mycobacterium tuberculosis, defined as resistant to at least isoniazid and rifampin (RIF). About 2 to 3% of all new TB cases worldwide are due to MDR strain, and the highest MDR populations among new cases have been found in China (11%) and eastern Europe (7 to 14%) (1, 6, 7). China is not only one of the 22 high-burden countries that collectively account for ca. 80% of the world's TB cases but it is also the hotspot area of very high prevalence of MDR TB identified by the World Health Organization (4, 5). Because of the very large financial implications of the treatment and spread of MDR strains due to globalization, MDR TB has been classified as a global pandemic more deadly than AIDS, with the potential to destabilize society.RIF is one of the principal first-line drugs used in combination chemotherapy and RIF resistance (Rif r ) is a valuable surrogate marker of MDR TB (3). RIF interferes with transcription and elongation of RNA by binding to the ␤-subunit of RNA polymerase. It has been observed that Ͼ90% of Rif r strains of M. tuberculosis possess genetic alterations within an 81-bp fragment, the so-called Rif r -determining region (RRDR), of the rpoB gene, which codes for the beta subunit of the RNA polymerase (17). The types of mutations include single-nucleotide changes and deletions and insertions.

BackgroundMarine and freshwater zooplankton exhibit daily rhythmic patterns of behavior and physiology which may be regulated directly by the light:dark (LD) cycle and/or a molecular circadian clock. One of the best-studied zooplankton taxa, the freshwater crustacean Daphnia, has a 24 h diel vertical migration (DVM) behavior whereby the organism travels up and down through the water column daily. DVM plays a critical role in resource tracking and the behavioral avoidance of predators and damaging ultraviolet radiation. However, there is little information at the transcriptional level linking the expression patterns of genes to the rhythmic physiology/behavior of Daphnia.ResultsHere we analyzed genome-wide temporal transcriptional patterns from Daphnia pulex collected over a 44 h time period under a 12:12 LD cycle (diel) conditions using a cosine-fitting algorithm. We used a comprehensive network modeling and analysis approach to identify novel co-regulated rhythmic genes that have similar network topological properties and functional annotations as rhythmic genes identified by the cosine-fitting analyses. Furthermore, we used the network approach to predict with high accuracy novel gene-function associations, thus enhancing current functional annotations available for genes in this ecologically relevant model species. Our results reveal that genes in many functional groupings exhibit 24 h rhythms in their expression patterns under diel conditions. We highlight the rhythmic expression of immunity, oxidative detoxification, and sensory process genes. We discuss differences in the chronobiology of D. pulex from other well-characterized terrestrial arthropods.ConclusionsThis research adds to a growing body of literature suggesting the genetic mechanisms governing rhythmicity in crustaceans may be divergent from other arthropod lineages including insects. Lastly, these results highlight the power of using a network analysis approach to identify differential gene expression and provide novel functional annotation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2998-2) contains supplementary material, which is available to authorized users.

Clustering of gene expression data is a stan-