Department of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Children's Cancer Research Institute, St. Anna Kinderspital, Vienna, Austria.
Cell Commun Signal. 2019 Jun 17;17(1):66. doi: 10.1186/s12964-019-0381-z.
Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which remains challenging, given that the overlap between these datasets is not necessarily comprehensive. In a previous study we analyzed the impact of the yeast mitogen-activated protein kinase (MAPK) Hog1 on the hyperosmotic stress-affected phosphorylome. Using a combination of a series of hyperosmotic stress and kinase inhibition experiments, we identified a broad range of direct and indirect substrates of the MAPK. Here we re-evaluate this extensive MS dataset and demonstrate that a combined analysis based on two software packages, MaxQuant and Proteome Discoverer, increases the coverage of Hog1-target proteins by 30%. Using protein-protein proximity assays we show that the majority of new targets gained by this analysis are indeed Hog1-interactors. Additionally, kinetic profiles indicate differential trends of Hog1-dependent versus Hog1-independent phosphorylation sites. Our findings highlight a previously unrecognized interconnection between Hog1 signaling and the RAM signaling network, as well as sphingolipid homeostasis.
基于现代定量质谱(MS)的蛋白质组学使研究人员能够通过监测细胞对不同刺激的全蛋白质组反应来揭示信号转导网络。基于 MS 的信号系统分析通常需要整合多个定量 MS 实验,这仍然具有挑战性,因为这些数据集之间的重叠不一定全面。在之前的研究中,我们分析了酵母丝裂原活化蛋白激酶(MAPK)Hog1 对高渗胁迫影响磷酸化组的影响。我们使用一系列高渗胁迫和激酶抑制实验的组合,鉴定了 MAPK 的广泛的直接和间接底物。在这里,我们重新评估了这个广泛的 MS 数据集,并证明基于两个软件包 MaxQuant 和 Proteome Discoverer 的联合分析将 Hog1 靶蛋白的覆盖率提高了 30%。通过蛋白质-蛋白质接近测定,我们表明,通过这种分析获得的大多数新靶标确实是 Hog1 相互作用蛋白。此外,动力学谱表明 Hog1 依赖性和 Hog1 非依赖性磷酸化位点的差异趋势。我们的研究结果突出了 Hog1 信号与 RAM 信号网络以及神经酰胺稳态之间以前未被认识到的联系。