MassIVE MSV000091351

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DIA-MS of 202 Pseudomonas aeruginosa clinical isolates

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Description

We gathered the proteomic profile of 202 clinical P. aeruginosa isolates derived from a cystic fibrosis lung under planktonic growth conditions. Firstly, a comprehensive transcript/protein correlation across 174 clinical isolates at the same growth stage was performed allowing a characterization of proteins with long and short lifetimes. Consistent with the results from previous studies, proteins of the translational machinery and the key Quorum sensing mediators RpoS, Vfr, RhlR and MvfR were characterized as short-lived proteins. Again, no biochemical metric could explain differences between protein lifetimes further demonstrating a potentially undervalued importance of post-transcriptional regulation. Secondly, a comparative multi-omics analysis was performed that highlighted the capacity to unearth novel characteristics for both antibiotic resistance and virulence traits. Investigating various tobramycin resistance mechanisms, the efflux pump system MexXY-OprM was determined as a key contributor of aminoglycoside modifying enzyme-driven resistance. MexY protein abundance was furthermore found to be directly regulated by the negative regulator MexZ. In tobramycin resistant isolates, the MexZ regulator was frequently identified as mutated or completely absent due to a possibly unidentified mechanism. This work found novel possible bacterial virulence factors by statistically comparing quantitative data and phenotypic survival data from a Galleria mellonella infection model. Additionally, a Random forest machine learning model was applied. The predictors with the highest predictive importance for the phenotypes of swarming motility, various antibiotic resistance phenotypes, and virulence were listed and discussed. [doi:10.25345/C5ZS2KP59] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: multi-omics ; clinical isolates ; clinical isolate selection ; 202 clinical isolates ; three biological replicates

Contact

Principal Investigators:
(in alphabetical order) 		Susanne Haessler, Helmholtz Zentrum Braunschweig, Germany
Submitting User: KarambolageNed
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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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