Institute of Pharmaceutical Sciences, Pharmaceutical Chemistry, University of Graz, Austria.
Institute of Pharmaceutical Sciences, Pharmaceutical Chemistry, University of Graz, Austria; BioTechMed-Graz, Austria; Field of Excellence BioHealth - University of Graz, Austria.
Curr Opin Chem Biol. 2022 Feb;66:102100. doi: 10.1016/j.cbpa.2021.102100. Epub 2021 Nov 18.
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.
遗传变异如何转化为细胞表型通常并不清楚,包括蛋白质组中可以恢复多少编码变异。异质细胞系的蛋白质基因组分析表明,遗传差异主要影响蛋白质复合物的丰度和化学计量,其影响通过蛋白质相互作用在后转录水平传递到其他亚基上。相反,错义变异的大规模二进制相互作用分析表明,相互作用的丧失很普遍,约有 50%的疾病相关突变会导致丧失相互作用,而二进制相互作用的深度扫描诱变则确定了每个相互作用中数千个相互作用缺陷的变体。因此,通过蛋白质-蛋白质相互作用,表型从遗传变异中产生的观点得到了正向和反向相互作用蛋白质组学的支持。随着方法的改进,这两种方法的结合可以缩小核苷酸序列变异与其在细胞蛋白质组上的功能后果之间的知识差距。