Decoding the cellular effects of genetic variation through interaction proteomics

Abstract

It is often unclear how genetic variation translates into cellular phenotypes, including how much of the coding variation can be recovered in the proteome. Proteogenomic analyses of heterogenous cell lines revealed that the genetic differences impact mostly the abundance and stoichiometry of protein complexes, with the effects propagating post-transcriptionally via protein interactions onto other subunits. Conversely, large scale binary interaction analyses of missense variants revealed that loss of interaction is widespread and caused by about 50% disease-associated mutations, while deep scanning mutagenesis of binary interactions identified thousands of interaction-deficient variants per interaction. The idea that phenotypes arise from genetic variation through protein-protein interaction is therefore substantiated by both forward and reverse interaction proteomics. With improved methodologies, these two approaches combined can close the knowledge gap between nucleotide sequence variation and its functional consequences on the cellular proteome.

Keywords: Deep mutagenesis; Interactome mapping; Missense mutation; Protein complexes; Protein–protein interaction network; Yeast two-hybrid analysis.