Daniel Szymanski - New functional looks into the proteome using LC/MS and protein correlation profiling

Speaker: Daniel Szymanski

Title: New functional looks into the proteome using LC/MS and protein correlation profiling 

Abstract:

Protein complexes assemble in cells to carry out activities that could never be achieved by a single polypeptide. Oligomeric protein machines coordinate information flow, dictate metabolic flux patterns, and direct intracellular transport and cell wall secretion. Protein complex activities change to enable the plant to respond to developmental or environmental cues. However, despite the importance and ubiquity of protein oligomerization, broad knowledge about complex composition and regulation is lacking. I will describe our use of label-free protein correlation profiling to broadly analzye protein oligomerization at the time scales that span from evolution to short-term adaptation to metabolic stress. Protein cofractionation is also being used to analyze the localization and composition of novel protein complexes.  A major challenge in the field is to statistically evaluate the accuracies of co-fractionation-based composition predictions using “golden standard” complexes predicted from databases like CORUM. The problem is that in cell extracts, and probably in living cells, the major cellular pool of the complex subunits does exist as the fully assembled state. In this presentation I will also describe our data mining and machine learning approaches to objectively identify true golden standards and how they can be used to evaluate co-fractionation-based predictions.