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Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling
Yi Zhang1, Alejandro Wolf-Yadlin, Phillip L Ross
1Biological Engineering Division, Massachusetts Institute of Technnology, Cambridge, Massachusetts 02139, USA.
Abstract:
Ligand binding to cell surface receptors initiates a cascade of signaling events regulated by dynamic phosphorylation events on a multitude of pathway proteins. Quantitative features, including intensity, timing, and duration of phosphorylation of particular residues, may play a role in determining cellular response, but experimental data required for analysis of these features have not previously been available. To understand the dynamic operation of signaling cascades, we have developed a method enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins in a time-resolved manner, downstream of epidermal growth factor receptor (EGFR) activation. Tryptic peptides from four different EGFR stimulation time points were labeled with four isoforms of the iTRAQ reagent to enable downstream quantification. After mixing of the labeled samples, tyrosine-phosphorylated peptides were immunoprecipitated with an anti-phosphotyrosine antibody and further enriched by IMAC before LC/MS/MS analysis. Database searching and manual confirmation of peptide phosphorylation site assignments led to the identification of 78 tyrosine phosphorylation sites on 58 proteins from a single analysis. Replicate analyses of a separate biological sample provided both validation of this first data set and identification of 26 additional tyrosine phosphorylation sites and 18 additional proteins. iTRAQ fragment ion ratios provided time course phosphorylation profiles for each site. The data set of quantitative temporal phosphorylation profiles was further characterized by self-organizing maps, which resulted in identification of several cohorts of tyrosine residues exhibiting self-similar temporal phosphorylation profiles, operationally defining dynamic modules in the EGFR signaling network consistent with particular cellular processes. The presence of novel proteins and associated tyrosine phosphorylation sites within these modules indicates additional components of this network and potentially localizes the topological action of these proteins. Additional analysis and modeling of the data generated in this study are likely to yield more sophisticated models of receptor tyrosine kinase-initiated signal transduction, trafficking, and regulation.
Insights
This study introduces a new method to quantify tyrosine phosphorylation on many proteins over time after epidermal growth factor receptor (EGFR) activation. This reveals dynamic signaling modules and novel proteins in cellular pathways.
Area of Science:
- Molecular Biology
- Cell Signaling
- Proteomics
Background:
- Cell surface receptor activation triggers complex signaling cascades.
- Dynamic phosphorylation events regulate these signaling pathways.
- Previous methods lacked the ability to quantitatively measure temporal phosphorylation profiles.
Purpose of the Study:
- To develop a method for simultaneous, time-resolved quantification of tyrosine phosphorylation on multiple proteins.
- To analyze dynamic signaling events downstream of epidermal growth factor receptor (EGFR) activation.
- To identify temporal phosphorylation profiles and define dynamic signaling modules.
Main Methods:
- Utilized iTRAQ labeling for quantitative peptide analysis across four EGFR stimulation time points.
- Employed anti-phosphotyrosine immunoprecipitation and IMAC enrichment for phosphopeptide isolation.
- Performed LC/MS/MS analysis for identification and quantification of tyrosine phosphorylation sites.
Main Results:
- Identified 78 tyrosine phosphorylation sites on 58 proteins in a single analysis, with 26 additional sites on 18 proteins in replicate analyses.
- Generated time-course phosphorylation profiles for each identified site using iTRAQ fragment ion ratios.
- Defined dynamic signaling modules by clustering proteins with self-similar temporal phosphorylation profiles using self-organizing maps.
Conclusions:
- The developed method enables comprehensive, quantitative analysis of dynamic signaling networks.
- Identified novel proteins and phosphorylation sites, expanding the understanding of the EGFR signaling network.
- The findings provide a foundation for sophisticated modeling of receptor tyrosine kinase signaling.
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