Departamento de Microbiología y Parasitología, Facultad de Farmacia, Universidad Complutense de Madrid, Spain.
Institute for Systems Biology, Seattle, WA, USA.
J Proteomics. 2021 May 15;239:104192. doi: 10.1016/j.jprot.2021.104192. Epub 2021 Mar 20.
Pseudomonas aeruginosa is an important opportunistic human pathogen with high prevalence in nosocomial infections. This microorganism is a good model for understanding biological processes such as the quorum-sensing response, the metabolic integration of virulence, the mechanisms of global regulation of bacterial physiology, and the evolution of antibiotic resistance. Till now, P. aeruginosa proteomic data, although available in several on-line repositories, were dispersed and difficult to access. In the present work, proteomes of the PAO1 strain grown under different conditions and from diverse cellular compartments have been joined to build the Pseudomonas PeptideAtlas. This resource is a comprehensive mass spectrometry-derived peptide and inferred protein database with 71.3% coverage of the total predicted proteome of P. aeruginosa PAO1, the highest coverage among bacterial PeptideAtlas datasets. The proteins included cover 89% of metabolic proteins, 72% of proteins involved in genetic information processing, 83% of proteins responsible for environmental information processing, more than 88% of the ones related to quorum sensing and biofilm formation, and 89% of proteins responsible for antimicrobial resistance. It exemplifies a necessary tool for targeted proteomics studies, system-wide observations, and cross-species observational studies. The manuscript describes the building of the PeptideAtlas and the contribution of the different proteomic data used. SIGNIFICANCE: Pseudomonas aeruginosa is among the most versatile human bacterial pathogens. Studies of its proteome are very important as they can reveal virulence factors and mechanisms of antibiotic resistance. The construction of a proteomic resource such as the PeptideAtlas enables targeted proteomics studies, system-wide observations, and cross-species observational studies.
铜绿假单胞菌是一种重要的机会性人类病原体,在医院感染中发病率很高。这种微生物是一个很好的模型,可用于理解生物过程,如群体感应反应、毒力的代谢整合、细菌生理学全局调控机制和抗生素耐药性的进化。到目前为止,虽然有几个在线数据库提供了铜绿假单胞菌的蛋白质组数据,但这些数据分散且难以获取。在本工作中,将不同条件下生长的 PAO1 菌株和来自不同细胞区室的蛋白质组数据合并,构建了铜绿假单胞菌肽图谱。该资源是一个全面的基于质谱的肽和推断蛋白质数据库,涵盖了铜绿假单胞菌 PAO1 总预测蛋白质组的 71.3%,是细菌肽图谱数据集的最高覆盖率。所包含的蛋白质涵盖了 89%的代谢蛋白、72%的参与遗传信息处理的蛋白、83%的负责环境信息处理的蛋白、超过 88%的与群体感应和生物膜形成相关的蛋白以及 89%的负责抗菌耐药性的蛋白。它是靶向蛋白质组学研究、系统范围观察和跨物种观察研究的必要工具。本文描述了肽图谱的构建以及所使用的不同蛋白质组学数据的贡献。意义:铜绿假单胞菌是最具多功能性的人类细菌病原体之一。对其蛋白质组的研究非常重要,因为它可以揭示毒力因子和抗生素耐药性的机制。构建像肽图谱这样的蛋白质组学资源,可以支持靶向蛋白质组学研究、系统范围观察和跨物种观察研究。