Proteomics

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Motif-centric phosphoproteomics to target kinase-mediated signaling pathways


ABSTRACT: Identifying cellular phosphorylation pathways based on kinase-substrate relationships is a critical step to understanding the regulation of physiological functions in cells. Mass spectrometry-based phosphoproteomics workflows have made it possible to comprehensively collect information on individual phosphorylation sites in a variety of samples. However, there is still no generic approach to uncover phosphorylation networks based on kinase-substrate relationships in rare cell populations. Here, we describe a motif-centric phosphoproteomics approach combined with multiplexed isobaric labeling, in which in vitro kinase reaction is used to generate the targeted phosphopeptides, which are spiked into one of the isobaric channels to increase detectability. Proof-of-concept experiments demonstrate selective and comprehensive quantification of targeted phosphopeptides by using multiple kinases for motif-centric channels. Over 7,000 tyrosine phosphorylation sites were quantified from several tens of µg of starting materials. This approach enables the quantification of multiple phosphorylation pathways under physiological or pathological regulation in a motif-centric manner.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Yasushi Ishihama 

PROVIDER: PXD026996 | JPOST Repository | Wed Dec 01 00:00:00 GMT 2021

REPOSITORIES: jPOST

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Motif-centric phosphoproteomics to target kinase-mediated signaling pathways.

Tsai Chia-Feng CF   Ogata Kosuke K   Sugiyama Naoyuki N   Ishihama Yasushi Y  

Cell reports methods 20220114 1


Identifying cellular phosphorylation pathways based on kinase-substrate relationships is a critical step to understanding the regulation of physiological functions in cells. Mass spectrometry-based phosphoproteomics workflows have made it possible to comprehensively collect information on individual phosphorylation sites in a variety of samples. However, there is still no generic approach to uncover phosphorylation networks based on kinase-substrate relationships in rare cell populations. Here,  ...[more]