A wide-ranging Pseudomonas aeruginosa PeptideAtlas build: a useful proteomic resource for a versatile pathogen.

Pseudomonas aeruginosa is an important opportunistic pathogen with high prevalence in nosocomial infections. This microorganism is a good model for understanding biological processes such as the quorum-sensing response, the metabolic integration of virulence, the mechanisms of global regulation of bacterial physiology, and the evolution of antibiotic resistance. Till now, P. aeruginosa proteomic data, although available in several on-line repositories, were dispersed and difficult to access. In the present work, proteomes of the PAO1 strain grown under very different conditions and from diverse cellular compartments have been analyzed and joined to build the Pseudomonas PeptideAtlas. This resource is a comprehensive mass spectrometry-derived peptide and inferred protein database with 71.3% coverage of the total predicted proteome of P. aeruginosa PAO1. This is the highest published coverage among the eight bacterial PeptideAtlas datasets currently available. The proteins in the Pseudomonas PeptideAtlas cover 84% of metabolic proteins, 71% of proteins involved in genetic information processing, 72% of proteins responsible for environmental information processing, more than 80% of proteins related to quorum sensing and biofilm formation, and 81% of proteins responsible for antimicrobial resistance. It exemplifies a necessary tool for targeted proteomics studies, system-wide observations, and cross-species observational studies. Here we describe how this resource was built and some of the physiologically important proteins of this pathogen. SignificancePseudomonas aeruginosa is among the most versatile bacterial pathogens. Studies of its proteome are very important as they can reveal virulence factors and mechanisms of antibiotic resistance. The construction of a proteomic resource such as the PeptideAtlas enables targeted proteomics studies, system-wide observations, and cross-species observational studies.