Hypothesis-free Illustration on How Phosphorylation Dynamically Impact Protein Turnover
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ABSTRACT: The turnover measurement of proteins and proteoforms has been largely facilitated by the metabolic labeling coupled with mass spectrometry (MS), such as the dynamic Stable isotope labeling by amino acids in cell culture (SILAC) experiments, i.e., the dynamic SILAC or pSILAC approach. Very recent studies including ours have integrated post-translational modification (PTM) proteomic methodology, such as phosphoproteomics, with pSILAC experiments in steady-state systems and revealed the link between protein PTM and turnover on the proteome-scale. In this study, we present a novel pSILAC phosphoproteomic dataset in a dynamic process of cell starvation using data-independent acquisition mass spectrometry (DIA-MS). We further propose a “hypothesis-free”, time series data analysis strategy to interrogate how phosphorylation dynamically impact protein turnover. With this strategy, we discovered complex relationship between phosphorylation and protein turnover that was previously underexplored. Our results further revealed potential biological features including phosphorylation stoichiometry that are associated with the peptideform turnover of phosphorylation. Our data also suggested that phosphoproteomic abundance regulation during starvation tends to be not correlated with turnover diversity, underscoring the importance of studying PTM site-resolved turnover datasets in the future.
INSTRUMENT(S): Orbitrap Fusion Lumos
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Epithelial Cell, Cell Culture
DISEASE(S): Disease Free
SUBMITTER: Wenxue Li
LAB HEAD: Yansheng Liu
PROVIDER: PXD037360 | Pride | 2022-12-01
REPOSITORIES: Pride
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