Signaling network dynamics investigated by quantitative phosphoproteomics

Abstract

This thesis describes the application of proteomics technologies to get insight into several aspects of phosphorylation signaling dynamics. The core tool in all performed experiments is mass spectrometry (MS)-based phosphoproteomics. In Chapter 1, a general introduction is given into proteomics and MS-based proteomics workflows. In Chapter 2, we evaluate and explore a peptide-centric antibody generated to selectively enrich peptides containing the PKA consensus phosphorylation motif [R/K][R/K/X]X[pS/pT]. This targeted phosphoproteomic strategy, in combination with stable isotope dimethyl labeling, is used to profile temporal changes of potential PKA substrates in Jurkat T lymphocytes upon PGE2 stimulation, which increases intracellular cAMP, thereby activating PKA. It is shown that this approach is very specific and highly complementary to a large-scale phosphoproteomics approach, enabling to profile hundreds of putative PKA sites. In Chapter 3, the phosphopeptide enrichment robustness of Ti4+-IMAC is evaluated. First, we prove that Ti4+-IMAC enrichment allows a highly reproducible quantification of phosphorylation sites in HeLa cells. Subsequently, we apply this strategy to monitor the phosphoproteome of Jurkat T lymphocytes upon PGE2 stimulation, covering extended time series. We demonstrate that this enrichment strategy in combination with label-free quantification enables in-depth investigation of phosphorylation dynamics, highlighting differential regulation of different kinases over time. In Chapter 4, we employ a three-pronged MS-based proteomics strategy to identify the direct targets and downstream signaling effect of four tyrosine kinase inhibitors (imatinib, dasatinib, bosutinib, and nilotinib) in A431 epidermoid carcinoma cells, as a model system for skin-cancer. The integration of chemical proteomics and phosphoproteomics allows us to define a set of signaling nodes modulated by each individual drug that can be considered putative targets in epithelial cancers. In Chapter 5, we assess the beneficial use of complementary proteases, namely trypsin, LysC, GluC, AspN and chymotrypsin for the phosphoproteome analysis of Jurkat T cells, analyzed by using Ti4+-IMAC enrichment. The obtained results are a significant improvement upon data from a single protease digest. We demonstrate that nearly each phosphosite can be linked to a preferred protease forming detectable phosphopeptides, whereby the gain in using alternative proteases can be more than 10,000 fold for specific sites in intensity. Moreover, many of the identified sites are not yet reported in currently available and public depositories, demonstrating the complementary nature of these enzymes, through which different parts of the phosphoproteome can be uncovered