Assessment of Universal Approaches to Proteome Prefractionation

Abstract

Protein prefractionation is a popular and effective strategy for improved MS analysis of complex proteome mixtures. A challenge of prefractionation is the even partitioning with high recovery of all components of the mixture, particularly hydrophobic proteins. This thesis assesses various proteome prefractionation platforms, with a goal of comprehensive proteome analysis. A more reliable dataset of 1136 S. cerevisiae transmembrane proteins was computationally generated, and used to assess two gel-based platforms (GeLC/MS and GELFrEE/MS). These platforms were determined to be comparable for proteome analysis. The requirement for high-throughput, automated fractionation demands a gel-free separation workflow. Here, a LC-based workflow was optimized, relying on SDS-assisted yeast extraction, organic solvent protein precipitation, and reversed phase separation in a formic acid/isopropanol solvent system. Though this workflow afforded improvements over conventional LC strategies to proteome fractionation, the gel-based platforms were demonstrated to be superior, in terms of their unbiased separation of hydrophobic vs hydrophilic proteins.