Development and application of quantitative proteomic strategy for kinase substrate screening

Liang Xue, Purdue University

Abstract

Protein kinases are implicated in multiple diseases such as cancer, diabetes, cardiovascular diseases, and central nervous system disorders. Identification of kinase substrates is critical to dissecting signaling pathways and to understanding disease pathologies. However, methods and techniques used to identify bona fide kinase substrates have remained elusive. I have been developing an integrated proteomic strategy, termed kinase assay linked with phosphoproteomics (KALIP), which combines a sensitive kinase reaction with endogenous kinase-dependent phosphoproteomics to identify direct substrates of protein kinases. The in vitro kinase reaction in the first designed version of KALIP is carried out using a pool of peptides derived directly from cellular kinase substrates and then dephosphorylated as substrate candidates. The resulting newly phosphorylated peptides are then isolated and identified by mass spectrometry. In contrast, the evolved version of KALIP was developed for the protein level kinase reaction instead of peptide level. A further comparison of these in vitro phosphorylated peptides/proteins with phosphopeptides derived from endogenous proteins isolated from cells in which the kinase is either active or inhibited reveals new candidate protein substrates. Both of the strategies were applied to identify unique substrates of spleen tyrosine kinase (SYK), a protein-tyrosine kinase with duel properties of an oncogene and a tumor suppressor in distinctive cell types, including B cells and breast cancer cells. Several known and novel substrates, including multiple centrosomal substrates for SYK, were identified, supporting a unique mechanism that SYK negatively affects cell division through its centrosomal kinase activity. To assist the phosphoproteomics data analysis, I have developed a novel mass spectrometry-based label-free quantitation method that facilitates phosphoproteomics data analysis with high efficiency and accuracy. This method employs synthetic peptide libraries tailored specifically as internal standards for complex phosphopeptide samples and accordingly, a local normalization algorithm, which calculates phosphopeptide abundance normalized locally with co-eluting library peptides. The label-free LAXIC method was further treated with a linear regression function to accurately measure phosphoproteome responses to osmotic stress in Arabidopsis. Several known and novel components in the abiotic stress pathway were identified, illustrating the capability of this method to identify critical signaling events among dynamic and complex phosphorylation. Overall, kinase assay linked phosphoproteomics (KALIP) has demonstrated outstanding sensitivity and low false positive rate for kinase substrate screening. In addition, Library-Assisted Extracted Ion Chromatogram (LAXIC) has shown to achieve an accurate and robust normalization for the quantitation process. They have the potential to become powerful tools for quantitative phosphoproteomics to illuminate biological signaling networks.

Degree

Ph.D.

Advisors

Tao, Purdue University.

Subject Area

Biochemistry|Bioinformatics

COinS