Systematic analysis of transcriptome and proteome in opportunistic bacterium Pseudomonas aeruginosa
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Transcription and translation are the two most important central mechanisms to control gene regulation in living organism. Although these two mechanisms have been studied intensively for last several decades, it is still not clear how all the information encoded on genomic DNA is converted to mRNA and proteins, the molecular functional components that change the characteristics of cells, depending on their needs. Here, I investigated the gene regulation of opportunistic bacterium Pseudomonas aeruginosa, using recently developed high-throughput techniques, microarray for transcriptomics and LC-MS/MS for proteomics. By analyzing transcriptome of 17 strains isolated over time from three individuals with cystic fibrosis, I identified 24 genes showing significant expression changes consistently across all strains, as evidence of parallel evolution of common traits that were beneficial in establishing chronic infection. Also, by analyzing proteome and transcriptome of two reference Pseudomonas aeruginosa strains, PAO1 and PA14, under growth condition mimicking in vivo nutrition environment in cystic fibrosis patients, I revealed that protein abundances are less correlated than mRNA abundance between them, and many proteins known as virulence factors showed different abundances only in protein level, demonstrating that post-transcriptional regulation is important to understand pathogenesis of Pseudomonas aeruginosa. To boost sensitivity both in identification and quantification in shotgun proteomics, I also created a novel integrative database search algorithm, and released freely available software package termed in MSblender. These results would be valuable information for the research community to understand the regulatory mechanism of gene expression both in transcription and translation, especially related to infectious diseases caused by pathogenic bacteria. Also, I present an integrative analysis method would be generally beneficial to extract more information from conventionally used shotgun proteomics experiments.