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Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs
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 descri...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Biochemistry and Molecular Biology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325102/ https://www.ncbi.nlm.nih.gov/pubmed/34186244 http://dx.doi.org/10.1016/j.mcpro.2021.100119 |
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author | Niinae, Tomoya Imami, Koshi Sugiyama, Naoyuki Ishihama, Yasushi |
author_facet | Niinae, Tomoya Imami, Koshi Sugiyama, Naoyuki Ishihama, Yasushi |
author_sort | Niinae, Tomoya |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8325102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-83251022021-08-04 Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs Niinae, Tomoya Imami, Koshi Sugiyama, Naoyuki Ishihama, Yasushi Mol Cell Proteomics Technological Innovation and Resources 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. American Society for Biochemistry and Molecular Biology 2021-06-27 /pmc/articles/PMC8325102/ /pubmed/34186244 http://dx.doi.org/10.1016/j.mcpro.2021.100119 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technological Innovation and Resources Niinae, Tomoya Imami, Koshi Sugiyama, Naoyuki Ishihama, Yasushi Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title | Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title_full | Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title_fullStr | Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title_full_unstemmed | Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title_short | Identification of Endogenous Kinase Substrates by Proximity Labeling Combined with Kinase Perturbation and Phosphorylation Motifs |
title_sort | identification of endogenous kinase substrates by proximity labeling combined with kinase perturbation and phosphorylation motifs |
topic | Technological Innovation and Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325102/ https://www.ncbi.nlm.nih.gov/pubmed/34186244 http://dx.doi.org/10.1016/j.mcpro.2021.100119 |
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