NEW METHODS FOR PHOSPHOPEPTIDE IDENTIFICATION


Year of Award:
2007
Award Type:
R21
Project Number:
CA125291
RFA Number:
RFA-CA-07-015
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
RESING, KATHERYN A
Other PI or Project Leader:
N/A
Institution:
UNIVERSITY OF COLORADO
New mass spectrometers capable of data dependent data acquisition and new database search algorithms have enabled proteomics profiling of complex samples by multidimensional LC/MSMS, where proteins are proteolyzed, separated chromatographically, and identified in a high throughput manner by peptide MSMS sequencing. An important goal is to identify phosphoproteins in complex mixtures and map their sites of modification by profiling phosphopeptides. Protein phosphorylation events are prevalent in cell regulatory and signaling pathways, and aberrations that lead to changes in phosphorylation are underlying causes of cancer and many other human diseases. Thus, the ability to profile phosphopeptides and monitor their changes in abundance is of key importance for cancer treatment and diagnosis. However, technical methods to achieve phosphoproteomics profiling have proven very difficult due to the chemical properties of the phosphate, the large database size when searching a protein database allowing variable phosphorylation on Ser, Thr, and Tyr, and the resulting low sensitivity and specificity of current scoring methods. In order to match MSMS spectra to phosphopeptide sequences with greater accuracy, it is critical to develop a greater understanding about the MS behavior of phosphopeptides and chemistry of gas phase fragmentation, and evaluate the factors that interfere with their detection and identification. Therefore, studies in this proposal will improve the ability to identify phosphopeptides from high resolution MSMS spectra. In Sp. Aim 1, we will rigorously compare the performance of the most promising MS protocols currently available for phosphoproteomics. In Sp. Aim 2, we will improve computational technologies for automated searching of phosphopeptides by positive ion MSMS, by incorporating information about their unique chemistry into scoring algorithms. In Sp. Aim 3 we will test the performance of negative ion MSMS for phosphopeptides, which is very promising but relatively unexplored, and compare it against the most promising positive ion methods, asking whether preferential ionization of phosphopeptides by negative ion MSMS alleviates the need for enrichment. Our optimized methods will be applied in future studies to identify signal transduction targets and biomarkers in melanoma and prostate cancer, and will be widely useful to basic researchers and clinician scientists in the cancer research community. Dysregulation of protein phosphorylation in response to signal transduction pathways is commonly observed in diseases such as cancer and as a side effect of drug treatment. Therefore, methods that screen for changes in protein phosphorylation under disease conditions would reveal targets that can be used to design new therapeutic or diagnostic methods. Our proposal will rigorously compare MS protocols for phosphoproteomics and develop improved experimental and computational approaches to improve the sensitivity and specificity of this experiment. These methods will be applied in future studies to identify signal transduction targets and biomarkers in melanoma and prostate cancer, and will be widely useful and freely available to basic researchers and clinician scientists in the cancer and biomedical research community.