Abele Miriam, Soleymaniniya Armin, Bayer Florian P, Lomp Nina, Doll Etienne, Meng Chen, Neuhaus Klaus, Scherer Siegfried, Wenning Mareike, Wantia Nina, Kuster Bernhard, Wilhelm Mathias, Ludwig Christina
Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
Mol Cell Proteomics. 2025 Mar;24(3):100917. doi: 10.1016/j.mcpro.2025.100917. Epub 2025 Jan 27.
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.
基于质谱的蛋白质组学彻底改变了细菌鉴定方式，并阐明了许多细菌生长、群落形成和耐药性背后的分子机制。然而，大多数研究都集中在少数几种模式细菌上，忽视了细菌的多样性。在本研究中，我们展示了迄今为止最广泛的细菌蛋白质组资源，涵盖303个物种、119个属和五个门，有超过636,000种独特的表达蛋白，证实了超过38,700种假设蛋白的存在。通过公共资源ProteomicsDB可访问该数据集，它能够对物种内部和跨物种的蛋白质进行定量探索。此外，我们开发了MS2Bac，这是一种细菌鉴定算法，通过两次迭代查询NCBI的细菌蛋白质组空间。如食品来源的细菌分离株所示，MS2Bac在物种水平上的准确率超过99%，在菌株水平上的准确率为89%，超过了MALDI-TOF和FTIR等方法。MS2Bac还能有效鉴定临床样本中的细菌，突出了基于质谱的蛋白质组学作为常规诊断工具的潜力。
