Maximizing binary interactome mapping with a minimal number of assays
Soon Gang ChoiiD, Julien OlivetiD, Patricia CassonnetiD, Pierre‐Olivier VidalainiD, Katja LuckiD, Luke LambourneiD, Kerstin SpirohniD, Irma H. LemmensiD, Mélanie Dos SantosiD, Caroline DemeretiD, Louis M. JonesiD, Sudharshan Rangarajan, Wenting Bian, Eloi P. CoutantiD, Yves Louis JaniniD, Sylvie van der WerfiD, Philipp TrepteiD, Erich E. WankeriD, Javier De Las RivasiD, Jan H. TavernieriD, Jean‐Claude TwizereiD, Tong HaoiD, DAVID EDWIN HILLiD, Marc VidaliD, Michael A. CalderwoodiD, Yves JacobiD
Abstract
Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose the concept of an "assayome" for binary protein-protein interaction (PPI) mapping as an optimal combination of assays and/or assay versions that maximizes detection of true positive interactions, while avoiding detection of random protein pairs. We engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions differing by protein expression systems and tagging configurations. The resulting N2H assayome recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our assayome concept should be applicable to systematic mapping of other biological landscapes.
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