Quantitative analysis of protein interaction network dynamics in yeast

• DOI: 10.15252/msb.20177532
• Publication Date: 2017-07-14T00:10:17Z
• Authors: Albi Celaj; Ulrich Schlecht; Justin D Smith; Weihong Xu; Sundari Suresh; Molly Miranda; Ana Maria Aparicio; Michael Proctor; Ronald W Davis; Frederick P Roth; Robert P St.Onge
• Keywords: 0301 basic medicine; Medicine (General); 0303 health sciences; Saccharomyces cerevisiae Proteins; QH301-705.5; Gene Expression Profiling; Systems Biology; mRNA expression; RNA, Fungal; protein–protein interactions; Articles; Saccharomyces cerevisiae; Models, Biological; network dynamics; 03 medical and health sciences; R5-920; environmental response; Protein Interaction Mapping; DNA Barcoding, Taxonomic; Computer Simulation; Protein Interaction Maps; RNA, Messenger; Biology (General); protein complementation assay; Peptide Hydrolases

Many cellular functions are mediated by protein-protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment-dependent protein complex dynamics, we used a DNA-barcode-based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that "concerted" protein-centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass-action-based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.