A Comprehensive Subcellular Proteomic Survey of Salmonella Grown under Phagosome-Mimicking versus Standard Laboratory Conditions. (25th July 2012)

• Record Type: Journal Article
• Authors: Brown, Roslyn N.; Sanford, James A.; Park, Jea H.; Deatherage, Brooke L.; Champion, Boyd L.; Smith, Richard D.; Heffron, Fred; Adkins, Joshua N.
• Other Names: Smejkal Gary B. Academic Editor.
• Is Part Of: International journal of proteomics. Volume 2012(2012)
• Publication Date: 2012-07-25
• Subjects: Proteomics -- Periodicals; Proteomics; Proteomics; Electronic journals; Periodical; Fulltext; Internet Resources; Periodicals; Periodicals; 572.6
• DOI: 10.1155/2012/123076
• Languages: English
• ISSNs: 2090-2166

Abstract

Abstract : Towards developing a systems-level pathobiological understanding of Salmonella enterica, we performed a subcellular proteomic analysis of this pathogen grown under standard laboratory and phagosome-mimicking conditions in vitro . Analysis of proteins from cytoplasmic, inner membrane, periplasmic, and outer membrane fractions yielded coverage of 25% of the theoretical proteome. Confident subcellular location could be assigned to over 1000 proteins, with good agreement between experimentally observed location and predicted/known protein properties. Comparison of protein location under the different environmental conditions provided insight into dynamic protein localization and possible moonlighting (multiple function) activities. Notable examples of dynamic localization were the response regulators of two-component regulatory systems (e.g., ArcB and PhoQ). The DNA-binding protein Dps that is generally regarded as cytoplasmic was significantly enriched in the outer membrane for all growth conditions examined, suggestive of moonlighting activities. These observations imply the existence of unknown transport mechanisms and novel functions for a subset of Salmonella proteins. Overall, this work provides a catalog of experimentally verified subcellular protein locations for Salmonella and a framework for further investigations using computational modeling.