Development of mass spectrometry based technologies for quantitative cell signaling phosphoproteomics : the epidermal growth factor receptor family as a model system

Abstract

Ligand binding to cell surface receptors initiates a cascade of signaling events regulated by dynamic phosphorylation on a multitude of pathway proteins. Quantitative features, including intensity, timing, and duration of phosphorylation of particular residues play a role in determining cellular response. Mass spectrometry has been previously used to identify and catalog phosphorylation sites or quantify the phosphorylation dynamics of proteins in cell signaling networks. However, identification of phosphorylation sites presents little insight on cellular processes and quantification of phosphorylation dynamics of whole proteins masks the different roles that several phosphorylation sites within one protein have in the network. We have designed a mass spectrometry technique allowing site-specific quantification of dynamic phosphorylation in the cell. We have applied this technique to study signaling events triggered by different members of the epidermal growth factor receptor (EGFR) family. Self organizing maps (SOMs) analysis of our data has highlighted potential biological functions for phosphorylation sites previously unrelated to EGFR signaling and identified network modules regulated by different combinations of EGFR family members. Partial least square regression (PLSR) analysis of our data identified combination of signals strongly correlating with cellular proliferation and migration.

(cont.) Because our method was based on information dependent acquisition (IDA) the reproducibility of peptides identified across multiple analyses was low. To improve our methodology to permit both discovery of new phosphorylation sites and robust quantification of hundreds of nodes within a signaling network we combined IDA-analysis with multiple reaction monitoring (MRM) of selected precursor ions. MRM quantification of high resolution temporal profiles of the EGFR network provided 88% reproducibility across four different samples, as compared to 34% reproducibility by IDA only. In summary, we have developed a new robust mass spectrometry technique allowing site specific identification, quantification and monitoring of dynamic phosphorylation in the cell with high temporal resolution and under any number of biological conditions. Because the data obtained with this method is not sparse it is especially well suited to mathematical and computational analyses. The methodology is also broadly applicable to multiple signaling networks and to a variety of samples, including quantitative analysis of signaling networks in clinical samples.