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Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs
Author(s) -
Tomoya Niinae,
Koshi Imami,
Naoyuki Sugiyama,
Yasushi Ishihama
Publication year - 2021
Publication title -
molecular and cellular proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.757
H-Index - 187
eISSN - 1535-9484
pISSN - 1535-9476
DOI - 10.1016/j.mcpro.2021.100119
Subject(s) - phosphoproteomics , kinase , phosphorylation , casein kinase 2 , casein kinase 1 , map2k7 , biochemistry , biology , microbiology and biotechnology , protein phosphorylation , protein kinase a , chemistry , cyclin dependent kinase 2 , computational biology
Mass-spectrometry-based phosphoproteomics can identify more than 10,000 phosphorylated sites in a single experiment. But, despite the fact that enormous phosphosite information has been accumulated in public repositories, protein kinase–substrate relationships remain largely unknown. Here, we describe a method to identify endogenous substrates of kinases by using a combination of a proximity-dependent biotin identification method, called BioID, with two other independent methods, kinase-perturbed phosphoproteomics and phosphorylation motif matching. For proof of concept, this approach was applied to casein kinase 2 (CK2) and protein kinase A (PKA), and we identified 24 and 35 putative substrates, respectively. We also show that known cancer-associated missense mutations near phosphosites of substrates affect phosphorylation by CK2 or PKA and thus might alter downstream signaling in cancer cells bearing these mutations. This approach extends our ability to probe physiological kinase–substrate networks by providing new methodology for large-scale identification of endogenous substrates of kinases.

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