Proteomic diversity in bacteria: Insights and implications for bacterial identification.

Mol Cell Proteomics

Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany. Electronic address:

Published: January 2025

Mass spectrometry-based proteomics has revolutionized bacterial identification and elucidated many molecular mechanisms underlying bacterial growth, community formation, and drug resistance. However, most research has been focused on a few model bacteria, overlooking bacterial diversity. In this study, we present the most extensive bacterial proteomic resource to date, covering 303 species, 119 genera, and five phyla with over 636,000 unique expressed proteins, confirming the existence of over 38,700 hypothetical proteins. Accessible via the public resource ProteomicsDB, this dataset enables quantitative exploration of proteins within and across species. Additionally, we developed MS2Bac, a bacterial identification algorithm that queries NCBI's bacterial proteome space in two iterations. MS2Bac achieved over 99% species-level and 89% strain-level accuracy, surpassing methods like MALDI-TOF and FTIR, as demonstrated with food-derived bacterial isolates. MS2Bac also effectively identified bacteria in clinical samples, highlighting the potential of MS-based proteomics as a routine diagnostic tool.

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http://dx.doi.org/10.1016/j.mcpro.2025.100917DOI Listing

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