CRISPR-Suppressor Scanning for Systematic Discovery of Drug-Resistance Mutations

Abstract

CRISPR-Cas9 genome editing technologies have enabled complex genetic manipulations in situ, including large-scale, pooled screening approaches to probe and uncover mechanistic insights across various biological processes. The RNA-programmable nature of CRISPR-Cas9 greatly empowers tiling mutagenesis approaches to elucidate molecular details of protein function, in particular the interrogation of mechanisms of resistance to small molecules, an approach termed CRISPR-suppressor scanning. In a typical CRISPR-suppressor scanning experiment, a pooled library of single-guide RNAs is designed to target across the coding sequence(s) of one or more genes, enabling the Cas9 nuclease to systematically mutate the targeted proteins and generate large numbers of diverse protein variants in situ. This cellular pool of protein variants is then challenged with drug treatment to identify mutations conferring a fitness advantage. Drug-resistance mutations identified with this approach can not only elucidate drug mechanism of action but also reveal deeper mechanistic insights into protein structure-function relationships. In this article, we outline the framework for a standard CRISPR-suppressor scanning experiment. Specifically, we provide instructions for the design and construction of a pooled sgRNA library, execution of a CRISPR-suppressor scanning screen, and basic computational analysis of the resulting data. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Design and generation of a pooled sgRNA library Support Protocol 1: sgRNA library design using command-line CRISPOR Support Protocol 2: Production and titering of pooled sgRNA library lentivirus Basic Protocol 2: Execution and analysis of a CRISPR-suppressor scanning experiment.

Keywords: CRISPR; CRISPR-suppressor scanning; drug resistance; functional genomics; genetic engineering; tiling mutagenesis.

Figure 1.. Overview of CRISPR-suppressor scanning.

Schematic of a typical CRISPR-suppressor scanning experiment highlighting key insights that can be gained: (1) analysis of sgRNA dropout (e.g., in control vehicle-treated cells) can yield information on how mutations impact cellular fitness, (2) analysis of sgRNA enrichment in drug-treated versus vehicle-treated cells can reveal mutations perturbing drug action, (3) comparing resistance profiles of structurally related drugs can illuminate structure-function relationships.

Figure 2.. Key considerations in planning a CRISPR-suppressor scanning experiment.

Before conducting a CRISPR-suppressor scanning experiment, the target protein and associated selection strategy should be chosen carefully, as well as the cell line model system and form of genetic perturbation employed.

Figure 3.. Construction of an sgRNA library.

Schematic of Basic Protocol 1, in which an sgRNA library is designed using CRISPOR, amplified through two rounds of PCR, assembled into lentiCRISPRv2 through Gibson assembly, and transformed into bacteria. The plasmid library DNA is then purified and validated by deep sequencing to confirm library representation.

Figure 4.. CRISPR-suppressor scanning execution and analysis.

Schematic of Basic Protocol 2, in which the sgRNA library is introduced into cells by lentiviral transduction, followed by treatment of cells with drug or vehicle to perform CRISPR-suppressor scanning. Genomic DNA is purified and the sgRNA abundances are quantified by deep sequencing.

Figure 5.. Example results for Basic Protocols 1 and 2.

Example results. (A) Agarose gel showing the effect of different cycle numbers on PCR product yield for the round 2 PCR in Basic Protocol 1. Based on these results, 10 cycles (marked with arrow) was chosen for excision and gel purification. (B) Plots showing sgRNA distribution in the sequenced plasmid library obtained in Basic Protocol 1. AUC, area under curve. (C) CRISPR-suppressor scanning results obtained in Basic Protocol 2. Data are from a screen of sgRNAs targeting the RBM39 coding sequence using the drugs indisulam and E7820 (Gosavi et al., 2022). Left, scatterplot showing each sgRNA’s indisulam resistance score plotted against its targeted residue in the coding sequence of RBM39. sgRNAs >2 standard deviations above the mean of negative controls are shown in red. The highlighted yellow region of the RRM2 domain corresponds to the structural degron of RBM39. Right, scatterplot showing E7820 resistance scores compared to indisulam resistance scores for each sgRNA. Dotted lines indicate 2 standard deviations above the mean of negative controls.