A Quantitative Chemical Proteomic Strategy for Profiling Phosphoprotein Phosphatases from Yeast to Humans

Autor: Arminja N. Kettenbach, Isha Nasa, Meng S. Choy, Nicole P. Jenkins, Wolfgang Peti, Rebecca Page, Greg B. G. Moorhead, Mark E. Adamo, Scott P. Lyons
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Popis: A “tug-of-war” between kinases and phosphatases establishes the phosphorylation states of proteins. While serine and threonine phosphorylation can be catalyzed by more than 400 protein kinases, the majority of serine and threonine dephosphorylation is carried out by seven phosphoprotein phosphatases (PPPs). The PPP family consists of protein phosphatases 1 (PP1), 2A (PP2A), 2B (PP2B), 4 (PP4), 5 (PP5), 6 (PP6), and 7 (PP7). The imbalance in numbers between serine- and threonine-directed kinases and phosphatases led to the early belief that PPPs are unspecific and that kinases are the primary determinants of protein phosphorylation. However, it is now clear that PPPs achieve specificity through association with noncatalytic subunits to form multimeric holoenzymes, which expands the number of functionally distinct signaling entities to several hundred. Although there has been great progress in deciphering signaling by kinases, much less is known about phosphatases. We have developed a chemical proteomic strategy for the systematic interrogation of endogenous PPP catalytic subunits and their interacting proteins, including regulatory and scaffolding subunits (the “PPPome”). PP1, PP2A, PP4, PP5, and PP6 were captured using an immobilized, specific but nonselective PPP inhibitor microcystin-LR (MCLR), followed by protein identification by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a single analysis. Here, we combine this approach of phosphatase inhibitor bead profiling and mass spectrometry (PIB-MS) with label-free and tandem mass tag (TMT) quantification to map the PPPome in human cancer cell lines, mouse tissues, and yeast species, through which we identify cell- and tissue-type-specific PPP expression patterns and discover new PPP interacting proteins.
Databáze: OpenAIRE