Structural and functional determinants inferred from deep mutational scans

Abstract

ABSTRACTMutations that affect protein binding to a cognate partner primarily occur either at buried residues or at exposed residues directly involved in partner binding. Distinguishing between these two categories based solely on mutational phenotypes is challenging. The bacterial toxin CcdB kills cells by binding to DNA Gyrase. Cell death is prevented by binding to its cognate antitoxin CcdA, at an extended interface that partially overlaps with the GyrA binding site. Using the CcdAB toxin-antitoxin (TA) system as a model, a comprehensive site-saturation mutagenesis library of CcdB was generated in its native operonic context. The mutational sensitivity of each mutant was estimated by evaluating the relative abundance of each mutant in two strains, one resistant and the other sensitive to the toxic activity of the CcdB toxin, through deep sequencing. The ability to bind CcdA was inferred through a RelE reporter gene assay, since the CcdAB complex binds to its own promoter, repressing transcription. By analysing mutant phenotypes in the CcdB sensitive, CcdB resistant and RelE reporter strains, it was possible to assign residues to buried, CcdA interacting or GyrA interacting sites. A few mutants were individually constructed, expressed, and biophysically characterised to validate molecular mechanisms responsible for the observed phenotypes. Residues inferred to be important for antitoxin binding, are also likely to be important for rejuvenating CcdB from the CcdB-Gyrase complex. Therefore, even in the absence of structural information, when coupled to appropriate genetic screens, such high-throughput strategies can be deployed for predicting structural and functional determinants of proteins.Broader Impact StatementPartial loss-of-function mutations predominantly occur either at buried-site or exposed, active-site residues. We report a facile method to identify multiple binding sites for different interacting partners for a protein, and distinguish them from buried site and exposed non active-site residues, solely from mutational data.