小柯机器人

英国弗朗西斯·克里克研究所Markus Ralser等研究人员合作绘制出全基因组遗传扰动的蛋白质组学景观。2023年4月19日，《细胞》杂志在线发表了这项研究成果。

研究人员将功能基因组学与蛋白质组学结合起来，使用数据非依赖采集质谱法，对酿酒酵母的基因组规模的基因剔除库中的蛋白质丰度进行定量分析。研究人员发现，全局蛋白质的表达是由（1）一般生物属性，包括翻译率、蛋白质周转率、蛋白质复合物的形成、生长速度和基因组结构，以及（2）功能属性，如一个蛋白质在遗传、代谢和物理相互作用网络中的连接性等复杂的相互作用所驱动。此外，研究人员表明功能蛋白质组学通过评估蛋白质组图谱的相似性、蛋白质共变性和反向蛋白质组图谱来补充目前的基因注释策略。因此，这项研究揭示了支配蛋白质表达的原则，并为功能注释提供了一个跨越基因组的资源。

据悉，功能基因组学策略已经成为注释基因功能和调节网络的基础。

附：英文原文

Title: The proteomic landscape of genome-wide genetic perturbations

Author: Christoph B. Messner, Vadim Demichev, Julia Muenzner, Simran K. Aulakh, Natalie Barthel, Annika Rhl, Lucía Herrera-Domínguez, Anna-Sophia Egger, Stephan Kamrad, Jing Hou, Guihong Tan, Oliver Lemke, Enrica Calvani, Lukasz Szyrwiel, Michael Mülleder, Kathryn S. Lilley, Charles Boone, Georg Kustatscher, Markus Ralser

Issue&Volume: 2023-04-19

Abstract: Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

DOI: 10.1016/j.cell.2023.03.026

Source: https://www.cell.com/cell/fulltext/S0092-8674(23)00300-8