Project description:The data set comprises results from the whole cellular proteome, secreted proteins and proteins located on the bacterial surface of Corynebacterium pseudotuberculosis. The theroretical proteome was created from genome analysis and characterized using bioinformatical analysis.
Project description:To further understand the gene expression characteristics of originating biocontrol strain Pseudomonas aeruginosa M18, we have applied whole genome microarray expression profiling as a discovery platform to to specify the PCA-dependent expression of M18 genome. We constructed a series of PCA-producing mutant strains (high PCA: M18MSU1; low PCA: M18MS; and no PCA: M18MSP1P2). The comparison analysis of the M18 mutants genome expressional profiles indicated that the expression of PCA in both M18MSU1 and M18MS alters the expression of a total of 545 different genes; however, the higher level of PCA in M18MSU1 altered more genes (489) as compared to M18MS (129).
Project description:Comparative genomics has greatly facilitated the identification of shared as well as unique features among individual cells or tissues, and thus offers the potential to find disease markers. While proteomics is recognized for its potential to generate quantitative maps of protein expression, comparative proteomics in bacteria has been largely restricted to the comparison of single cell lines or mutant strains. In this study, we used a data independent acquisition (DIA) technique, which enables global protein quantification of large sample cohorts, to record the proteome profiles of overall 27 whole genome sequenced and transcriptionally profiled clinical isolates of the opportunistic pathogen Pseudomonas aeruginosa. Analysis of the proteome profiles across the 27 clinical isolates grown under planktonic and biofilm growth conditions led to the identification of a core biofilm-associated protein profile. Furthermore, we found that protein-to-mRNA ratios between different P. aeruginosa strains are well correlated, indicating conserved patterns of post-transcriptional regulation. Uncovering core regulatory pathways, which drive biofilm formation and associated antibiotic tolerance in bacterial pathogens, promise to give clues to interactions between bacterial species and their environment and could provide useful targets for new clinical interventions to combat biofilm-associated infections.