Omics : a journal of integrative biology · 2018
Comparison of three methods for cell surface proteome extraction of Listeria monocytogenes biofilms.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Esbelin Julia, Santos Tiago, Ribière Céline, Desvaux Mickaël, Viala Didier, Chambon Christophe, Hébraud Michel
Аннотация
The cell surface proteome of the foodborne pathogen Listeria monocytogenes, the etiological agent of listeriosis, is critical for understanding the physiological processes associated with stress resistance and persistence in the environment. In this context, the most widespread mode of growth for bacterial cells in natural and industrial environments is in biofilms. Cell surface proteins are, however, challenging to characterize because of their low abundance and poor solubility. Moreover, cell surface protein extracts are usually contaminated with cytoplasmic proteins that constitute the main signal in proteomic analysis. This study aimed to compare the efficiency of three methods to extract and explore surface proteins of L. monocytogenes growing in a biofilm: trypsin shaving, biotinylation, and cell fractionation. Peptide separation and identification were performed by shotgun proteomics using high-performance liquid chromatography combined with tandem mass spectrometry (LC-MS/MS). The biotinylation method was the most effective in extracting surface proteins, with the lowest rate of contamination by cytoplasmic proteins. Although presenting a higher contamination rate in cytoplasmic proteins, the other two techniques allowed the identification of additional surface proteins. Seven proteins were commonly retrieved by the three methods. The extracted proteins belong to several functional classes, involved in virulence, transport, or metabolic pathways. Finally, the three extraction methods seemed complementary and their combined use improved the exploration of the bacterial surface proteome. These new findings collectively inform future discovery and translational proteomics for clinical, environmental health, and industrial applications.