Institute for Microbiology, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany.
PLoS One. 2009 Dec 4;4(12):e8176. doi: 10.1371/journal.pone.0008176.
The genome sequence is the "blue-print of life," but proteomics provides the link to the actual physiology of living cells. Because of their low complexity bacteria are excellent model systems to identify the entire protein assembly of a living organism. Here we show that the majority of proteins expressed in growing and non-growing cells of the human pathogen Staphylococcus aureus can be identified and even quantified by a metabolic labeling proteomic approach. S. aureus has been selected as model for this proteomic study, because it poses a major risk to our health care system by combining high pathogenicity with an increasing frequency of multiple antibiotic resistance, thus requiring the development of new anti-staphylococcal therapy strategies. Since such strategies will likely have to target extracellular and surface-exposed virulence factors as well as staphylococcal survival and adaptation capabilities, we decided to combine four subproteomic fractions: cytosolic proteins, membrane-bound proteins, cell surface-associated and extracellular proteins, to comprehensively cover the entire proteome of S. aureus. This quantitative proteomics approach integrating data ranging from gene expression to subcellular localization in growing and non-growing cells is a proof of principle for whole-cell physiological proteomics that can now be extended to address physiological questions in infection-relevant settings. Importantly, with more than 1700 identified proteins (and 1450 quantified proteins) corresponding to a coverage of about three-quarters of the expressed proteins, our model study represents the most comprehensive quantification of a bacterial proteome reported to date. It thus paves the way towards a new level in understanding of cell physiology and pathophysiology of S. aureus and related pathogenic bacteria, opening new avenues for infection-related research on this crucial pathogen.
基因组序列是“生命蓝图”,但蛋白质组学提供了与活细胞实际生理学相关的联系。由于其复杂性较低,细菌是鉴定生物体完整蛋白质组的优秀模型系统。在这里,我们表明,通过代谢标记蛋白质组学方法,可以鉴定和定量鉴定生长和非生长细胞中的大多数金黄色葡萄球菌(一种人类病原体)表达的蛋白质。金黄色葡萄球菌被选为该蛋白质组学研究的模型,因为它具有高致病性和越来越多的多种抗生素耐药性的结合,对我们的医疗保健系统构成了重大风险,因此需要开发新的抗葡萄球菌治疗策略。由于这些策略可能必须针对细胞外和表面暴露的毒力因子以及金黄色葡萄球菌的生存和适应能力,因此我们决定将四个亚蛋白质组部分结合起来:细胞质蛋白、膜结合蛋白、细胞表面相关蛋白和细胞外蛋白,以全面涵盖金黄色葡萄球菌的整个蛋白质组。这种将数据从基因表达到生长和非生长细胞的亚细胞定位整合起来的定量蛋白质组学方法,是全细胞生理蛋白质组学的原理证明,现在可以扩展到解决与感染相关的生理问题。重要的是,通过鉴定超过 1700 种蛋白质(和 1450 种定量蛋白质),对应于约四分之三表达蛋白质的覆盖率,我们的模型研究代表了迄今为止报道的细菌蛋白质组的最全面定量。因此,它为金黄色葡萄球菌和相关病原菌的细胞生理学和病理生理学的理解开辟了新的途径,为该关键病原体的感染相关研究开辟了新的途径。