Temperature Sensitive Mutant Proteome Profiling (TeMPP) A Tool for the Characterization of Global Impacts of Missense Mutations on the Proteome

Abstract

Thousands of missense mutations have been found to be associated with human diseases, ~60% of which have been predicted to affect protein stability and/or protein-protein interactions (PPIs). Current proteomic methods for studying the effects of mutations on the cell focus on measures of protein abundance or post-translational modifications (PTMs), which cannot directly be used for PPI analysis. High-throughput methodology to evaluate how mutations in a single protein affect PPI networks would help streamline the characterization of global effects caused by mutant proteins and aid in the prediction of phenotypic outcomes resulting from genomic mutations. Temperature sensitive Mutant Proteome Profiling (TeMPP) is a novel application of a mass spectrometry (MS) based thermal proteome profiling (TPP) approach that measures changes in missense mutant containing proteomes without the requirement for large amounts of starting material, specific antibodies against proteins of interest, and/or genetic manipulation of the biological system. This study measures the impact of temperature sensitivity-inducing missense mutations of proteins in the ubiquitin proteasome system and the transcription termination machinery on the thermal stability of the proteome at large. Results reveal distinct mechanistic details that were not obtained using only steady-state transcriptome and proteome analyses. Furthermore, my data suggests that TeMPP is highly specific to proteins functionally related to the mutated protein of interest and capable of differentiating effects between two proteins in the same complex. Overall, TeMPP provides unique mechanistic insights into missense mutation dysfunction and connection of genotype to phenotype in a rapid, non-biased fashion. Use of this method along with other complementary -omics approaches will help to characterize how missense mutations affect cellular protein homeostasis and thus enable deeper insight into disease phenotypes.