The proteomic landscape of genome-wide genetic perturbations

Christoph B. Messner, Vadim Demichev, Julia Muenzner, Simran K. Aulakh, Natalie Barthel, Annika Röhl, 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

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Number of pages39
JournalCell
Volume186
Issue number9
Early online date19 Apr 2023
DOIs
Publication statusPublished - 27 Apr 2023

Keywords / Materials (for Non-textual outputs)

  • saccharomyces cerevisiae
  • quantitative proteomics
  • data-independent acquisition
  • knockout
  • deletion
  • systems biology
  • functional proteomics
  • high throughput
  • functional genomics
  • gene annotation

Fingerprint

Dive into the research topics of 'The proteomic landscape of genome-wide genetic perturbations'. Together they form a unique fingerprint.

Cite this