Large-scale determination of absolute phosphorylation stoichiometries in human cells by motif-targeting quantitative proteomics
Year: 2015
Type: article
Abstract: Our ability to model the dynamics of signal transduction networks will depend on accurate methods to quantify levels of protein phosphorylation on a global scale. Here we describe a motif-targeting quantitation method for phosphorylation stoichiometry typing. Proteome-wide phosphorylation stoichiometry can be obtained by a simple phosphoproteomic workflow integrating dephosphorylation and isotope tagging with enzymatic kinase reaction. Proof-of-concept experiments using CK2-, MAPK- and EGFR-targeting assays in lung cancer cells demonstrate the advantage of kinase-targeted complexity reduction, resulting in deeper phosphoproteome quantification. We measure the phosphorylation stoichiometry of >1,000 phosphorylation sites including 366 low-abundance tyrosine phosphorylation sites, with high reproducibility and using small sample sizes. Comparing drug-resistant and sensitive lung cancer cells, we reveal that post-translational phosphorylation changes are significantly more dramatic than those at the protein and messenger RNA levels, and suggest potential drug targets within the kinase-substrate network associated with acquired drug resistance.
Source: Nature Communications
DOI: 10.1038/ncomms7622
Authors: Chia-Feng Tsai, Yi-Ting Wang, Hsin-Yung Yen, Chih-Chiang Tsou, Wei-Chi Ku, Pei-Yi Lin, Hsuan-Yu Chen, Alexey I. Nesvizhskii, Yasushi Ishihama, Yu-Ju Chen
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,990
Awards: G2583803382, G2614357421, G2813926369, G3251019257, Discovery of Biomarker Candidates in Cancer Tissues: Development of an Integrated Proteomics Platform for Identification and Validation of the Membrane Proteome and Ptmome, Enrichment of low abundant proteome in plasma, Elucidation of intracellular phosphorylation network for molecular targeting drug discovery, G9000257730
OpenAlex ID: W2085705974
