PT  - JOURNAL ARTICLE
AU  - Ella Doron-Mandel
AU  - Benjamin J. Bokor
AU  - Yanzhe Ma
AU  - Lena A. Street
AU  - Lauren C. Tang
AU  - Ahmed A. Abdou
AU  - Neel H. Shah
AU  - George A. Rosenberger
AU  - Marko Jovanovic
TI  - SEC-TMT facilitates quantitative differential analysis of protein interaction networks
AID  - 10.1101/2023.01.12.523793
DP  - 2023 Jan 01
TA  - bioRxiv
PG  - 2023.01.12.523793
4099  - http://biorxiv.org/content/early/2023/01/13/2023.01.12.523793.short
4100  - http://biorxiv.org/content/early/2023/01/13/2023.01.12.523793.full
AB  - The majority of cellular proteins interact with at least one partner or assemble into molecular-complexes to exert their function. This network of protein-protein interactions (PPIs) and the composition of macromolecular machines differ between cell types and physiological conditions. Therefore, characterizing PPI networks and their dynamic changes is vital for discovering novel biological functions and underlying mechanisms of cellular processes. However, producing an in-depth, global snapshot of PPIs from a given specimen requires measuring tens to thousands of LC-MS/MS runs. Consequently, while recent works made seminal contributions by mapping PPIs at great depth, almost all focused on just 1-2 conditions, generating comprehensive but mostly static PPI networks.In this study we report the development of SEC-TMT, a method that enables identifying and measuring PPIs in a quantitative manner from only 4-8 LC-MS/MS runs per biological sample. This was accomplished by incorporating tandem mass tag (TMT) multiplexing with a size exclusion chromatography mass spectrometry (SEC-MS) work-flow. SEC-TMT reduces measurement time by an order of magnitude while maintaining resolution and coverage of thousands of cellular interactions, equivalent to the gold standard in the field. We show that SEC-TMT provides benefits for conducting differential analyses to measure changes in the PPI network between conditions. This development makes it feasible to study dynamic systems at scale and holds the potential to drive more rapid discoveries of PPI impact on cellular processes.Competing Interest StatementThe authors have declared no competing interest.