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A computational framework for the inference of protein complex remodeling from whole-proteome measurements.
Buljan, Marija; Banaei-Esfahani, Amir; Blattmann, Peter; Meier-Abt, Fabienne; Shao, Wenguang; Vitek, Olga; Tang, Hua; Aebersold, Ruedi.
Affiliation
  • Buljan M; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland. marija.buljan@empa.ch.
  • Banaei-Esfahani A; EMPA, Swiss Federal Laboratories for Materials Science and Technology, St Gallen, Switzerland. marija.buljan@empa.ch.
  • Blattmann P; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. marija.buljan@empa.ch.
  • Meier-Abt F; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Shao W; Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
  • Vitek O; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Tang H; Idorsia Pharmaceuticals, Allschwil, Switzerland.
  • Aebersold R; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Nat Methods ; 20(10): 1523-1529, 2023 10.
Article in En | MEDLINE | ID: mdl-37749212
ABSTRACT
Protein complexes are responsible for the enactment of most cellular functions. For the protein complex to form and function, its subunits often need to be present at defined quantitative ratios. Typically, global changes in protein complex composition are assessed with experimental approaches that tend to be time consuming. Here, we have developed a computational algorithm for the detection of altered protein complexes based on the systematic assessment of subunit ratios from quantitative proteomic measurements. We applied it to measurements from breast cancer cell lines and patient biopsies and were able to identify strong remodeling of HDAC2 epigenetic complexes in more aggressive forms of cancer. The presented algorithm is available as an R package and enables the inference of changes in protein complex states by extracting functionally relevant information from bottom-up proteomic datasets.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteome / Proteomics Limits: Humans Language: En Journal: Nat Methods Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteome / Proteomics Limits: Humans Language: En Journal: Nat Methods Year: 2023 Document type: Article