Quantitative proteome analyses of phosphorylated proteins and alternative splice variants in human cell lines and urine

Abstract

In this thesis, a general phosphoproteomics workflow was established by careful evaluation of the different steps for phosphopeptide enrichment. In addition, the application of two different collision energies for MS2 fragmentation has improved the sequence coverage of identified phosphopeptides. Moreover, the use of a peptide database generated out of the results using standard mass spectrometry (MS) database searches has proved to be advantageous for the quantification of multiphosphorylated proteins. This workflow was applied to cisplatin-induced apoptotic and control Jurkat T cells, resulting in the identification of more than 7,000 phosphopeptides from more than 2,000 proteins. In particular, several members of the MAP kinase family were found to be upregulated during apoptosis. Two proteins belonging to this family, cyclic AMP-dependent transcription factor ATF-2 (ATF2) and transcription factor AP-1 (JUN), were selected and further validated, showing that phosphoproteomics data must be interpreted with care. Proteomics studies focusing on alternative splicing are scarce. To facilitate the analysis of alternative splice variants, two customized databases were generated. These customized databases were also applied to the phosphoproteomics data to obtain potential insights into the interplay between alternative splicing and phosphorylation in Jurkat T cells upon cisplatin-induced apoptosis. In addition, the phosphoproteomics workflow was also applied to study urine from patients with indolent or aggressive prostate cancer (PCa) and revealed three particular significant changed phosphopeptides, supported by targeted analysis using parallel reaction monitoring (PRM). To enable cost-effective downstream absolute quantification, a novel approach for targeted protein analysis was established based on dimethylation of peptides. A special feature of this approach is that the accuracy to determine the amount of endogenous peptides can be validated using two references against each other.