Integrative approaches to expand the utility of CRISPR tiling mutagenesis screens for biological discovery

Abstract

The development of CRISPR–Cas genome editing technologies has transformed our ability to perform complex genetic manipulations in situ. Furthermore, the programmable nature of CRISPR–Cas systems has enabled these manipulations to be performed at scale, as exemplified by pooled CRISPR screening approaches. Pooled CRISPR screens have become widely adopted as powerful tools for biological discovery and uncovering mechanistic insights across diverse biological processes. Common formats for pooled CRISPR screens employ perturbations that modulate gene-level activity (e.g., knockout, activation, interference) across a large set of targets or even the entire genome. The resolution of these approaches is coarse-grained (i.e., gene-level) by design to broadly assess a large breadth of genes to identify those that contribute to a phenotype of interest. As a result, such approaches preclude the systematic, fine-grained dissection of individual genes and their protein products. On the other hand, CRISPR tiling mutagenesis screens—which we term CRISPR scanning—are designed to systematically mutagenize a select set of genes at high density to characterize gene function at finer resolution. Although less frequently used, CRISPR scanning approaches have been highly successful at elucidating structure-function relationships and molecular details underlying protein function and regulation. In this thesis, I present two projects that illustrate my efforts to refine and expand the utility of the CRISPR scanning methodology. In chapter one, I introduce key concepts and examples that have informed the innovations in the design, execution, and analysis of CRISPR scanning experiments. In chapter two, I describe our efforts to characterize mechanisms of acquired resistance to molecular glue degraders, a new therapeutic modality. In this study, we used CRISPR scanning to profile resistance mutations in two neosubstrates, GSPT1 and RBM39, and observed distinct mutational landscapes arise in response to degrader treatment. Integrative analysis with evolutionary sequence conservation data revealed varying levels of sequence conservation across resistance sites in GSPT1 and RBM39. These results led us to propose a model where the structural and functional requirements of protein regions constrain the accessible mutational space and thereby drive divergent mutational outcomes across targets. The observation that mutational constraints exert significant influence over the resulting landscape of resistance mutations led us to consider whether such constraints could be exploited as a rational design principle for CRISPR scanning screens. More specifically, we hypothesized that an activity-based inhibitor that mimics the target protein’s native substrate would preclude mutations that disrupt drug binding and enrich for distal resistance mutations that operate through alternative mechanisms. In chapter three, I describe our efforts to explore this concept by using the activity-based inhibitor decitabine in tandem with CRISPR scanning to systematically identify allosteric regulatory mechanisms in the essential components of the DNA methylation maintenance machinery, DNMT1 and UHRF1. Through novel computational analyses, we identified putative mutational hotspots in DNMT1 spanning a multi-domain autoinhibitory interface and the uncharacterized BAH2 domain. We biochemically characterized these mutations as gain-of-function mutations that enhance DNMT1 activity. Finally, we extrapolated our analysis to nominate putative gain-of-function mutations in multiple domains of UHRF1, including key residues in the autoinhibitory TTD–PBR interface. Collectively, these projects demonstrate how concepts from allied fields (e.g., mutational constraint, cancer driver mutation discovery) can be applied to inform the design and interpretation of CRISPR scanning experiments and how orthogonal information (e.g., evolutionary sequence conservation, protein structure) can complement CRISPR scanning data to provide deeper mechanistic insights. Altogether, this work establishes how such integrative approaches can broaden the scope and increase the power of the CRISPR scanning framework as a tool for biological discovery.