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Phosphoproteomic Analysis of Protein Phosphorylation Networks in Tetrahymena thermophila a Model Single-celled Organism

机译:嗜热四膜虫模型单细胞生物中的蛋白质磷酸化网络的磷酸化蛋白质组学分析。

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摘要

Tetrahymena thermophila is a widely used unicellular eukaryotic model organism in biological research and contains more than 1000 protein kinases and phosphatases with specificity for Ser/Thr/Tyr residues. However, only a few dozen phosphorylation sites in T. thermophila are known, presenting a major obstacle to further understanding of the regulatory roles of reversible phosphorylation in this organism. In this study, we used high-accuracy mass-spectrometry-based proteomics to conduct global and site-specific phosphoproteome profiling of T. thermophila. In total, 1384 phosphopeptides and 2238 phosphorylation sites from 1008 T. thermophila proteins were identified through the combined use of peptide prefractionation, TiO2 enrichment, and two-dimensional LC-MS/MS analysis. The identified phosphoproteins are implicated in the regulation of various biological processes such as transport, gene expression, and mRNA metabolic process. Moreover, integrated analysis of the T. thermophila phosphoproteome and gene network revealed the potential biological functions of many previously unannotated proteins and predicted some putative kinase–substrate pairs. Our data provide the first global survey of phosphorylation in T. thermophila using a phosphoproteomic approach and suggest a wide-ranging regulatory scope of this modification. The provided dataset is a valuable resource for the future understanding of signaling pathways in this important model organism.
机译:嗜热四膜菌是在生物学研究中广泛使用的单细胞真核模型生物,包含超过1000种对Ser / Thr / Tyr残基具有特异性的蛋白激酶和磷酸酶。但是,仅已知嗜热衣原体中有几十个磷酸化位点,这是进一步了解可逆磷酸化在该生物中的调节作用的主要障碍。在这项研究中,我们使用了高精度的基于蛋白质组学的蛋白质组学来进行嗜热链球菌的全局和位点特异性磷酸化蛋白质组分析。通过结合使用肽预分离,TiO2富集和二维LC-MS / MS分析,总共鉴定出了1008个嗜热链球菌蛋白的1384个磷酸肽和2238个磷酸化位点。鉴定出的磷蛋白与各种生物学过程的调控有关,例如运输,基因表达和mRNA代谢过程。此外,对嗜热毁丝菌磷酸化蛋白质组和基因网络的综合分析揭示了许多以前未注释的蛋白质的潜在生物学功能,并预测了一些假定的激酶-底物对。我们的数据提供了使用磷酸蛋白质组学方法进行的嗜热链球菌磷酸化的首次全球调查,并提出了该修饰的广泛调节范围。所提供的数据集是宝贵的资源,可用于将来对该重要模型生物中信号通路的理解。

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