Elucidating drug targets and mechanisms of action by genetic screens in mammalian cells

Abstract

Phenotypic screening is a powerful approach to discover small molecules with desired effects on biological systems, which can then be developed into therapeutic drugs. The identification of the target and mechanism of action of compounds discovered in phenotypic screens remains a major challenge. This feature article describes the use of genetic tools to reveal drug targets and mechanisms in mammalian cells. Until recently, RNA interference was the method of choice for such studies. Here, we highlight very recent additions to the genetic toolkit in mammalian cells, including CRISPR, CRISPR interference, and CRISPR activation, and illustrate their usefulness for drug target identification.

Fig. 1

Pooled genetic screening strategy to identify the target of cytotoxic compounds. Mammalian cells are stably transduced with a pooled lentiviral library to integrate expression cassettes for shRNAs or sgRNAs into the genomic DNA. The library targets a large number of genes each with several shRNAs/sgRNAs and contains non-targeting negative-control shRNAs/sgRNAs. Each cell typically expresses one element of the library. This population is either cultured in the absence of treatment, or treated with several pulses of the compound of interest, at a concentration that kills approximately 50% of the cells (IC50). Then, genomic DNA is isolated and the shRNA/sgRNA expression cassette is subjected to next-generation sequencing, enabling quantification of the frequencies of cells expressing each shRNA/sgRNA in the different cell populations. Using our quantitative framework, genes controlling sensitivity to the compound are robustly identified. Adapted from ref.

Fig. 2

Genetic tools in mammalian cells. RNA interference (RNAi): short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) direct the RISC complex to degrade protein-coding mRNAs with complementary RNA sequences, thereby leading to a loss of function of the encoded protein. CRISPR cutting: a single guide RNA (sgRNA) directs the bacterial Cas9 protein to cleave DNA. This can lead to error-prone non-homologous end-joining repair, thus inactivating the encoded gene. Catalytically dead Cas9 (dCas9) can be used to recruit transcriptional repressors or activators to endogenous genes to enable inducible and reversible gene repression (CRISPRi) or activation (CRISPRa). Our screening platform uses the KRAB repressor domain, and the SunTag, in which several copies of the activator VP64 are recruited to a dCas9-fused tandem repeat of the GCN4 epitope via a superfolder GFP (sfGFP)-stabilized nanobody targeting the GCN4 epitope (scFv-GCN4).

Fig. 3

Investigating the relationship between drug target expression and sensitivity. (a) Structure of CB-5083. (b) Sensitivity to CB-5083 was determined in a panel of 340 cancer cell lines (each represented by a dot), and displayed as a function of the expression level of p97/VCP, the intended target of CB-5083. (c) p97/VCP expression levels were controlled in a K562 leukemia cell line using different sgRNAs to mediate knockdown via CRISPRi or overexpression via CRISPRa (each point is one sgRNA, error bars indicate the standard error of the mean for p97/VCP mRNA levels measured in triplicate by quantitative PCR). The relative resistance to CB-5083 is shown on the y axis, using the rho metric we previously defined. Figure adapted, with permission, from ref.

Fig. 4

Identification of the target of an anti-cancer compound. (a) Structure of STF-118804. (b) An shRNA screen was conducted in MV411 leukemia cells to identify genes controlling sensitivity to the compound STF-118804, following the experimental strategy outlined in Fig. 2. Knockdown of the gene NAMPT significantly sensitized cells to the compound in two experimental replicates (P value from Mann-Whitney U test, each gene targeted by the shRNA library is shown as a dot). In follow-up experiments, we confirmed NAMPT as the target of STF-118804. Adapted, with permission, from ref.

Fig. 5

Genetic screen reveals biomarkers for patient response and potential combination therapy targets. An shRNA screen in the multiple myeloma cell line U266 revealed genes controlling sensitivity to the proteasome inhibitor carfilzomib. (a,b) For the genes targeted by the shRNA library, effect of knockdown on carfilzomib sensitivity and P value for the statistical significance of the effect are displayed in a volcano plot. Grey dots represent “quasi-genes” generated by grouping non-targeting negative control shRNAs. Dots in other colors represent protein-coding human genes. The same data is shown in (a) and (b), with different groups of genes highlighted and labelled in the two panels. (c) Validation of the effect of knockdown of a 20S proteasomal subunit (PSMB5) and a 19S proteasomal subunit (PSMD12) on carfilzomib sensitivity. Mean and standard deviation of two experimental replicates are shown. (d) Pre-therapy expression levels of the 19S proteasomal subunit S7 (quantified by flow cytometry in CD138 + bone marrow cells, which encompass plasma cells and multiple myeloma cells) are predictive of multiple myeloma patient response to carfilzomib. Figure adapted from ref .

Fig. 6

Identification of a drug target based on a complex phenotype. (a) Structure of ISRIB (b) A fluorescent reporter for the phenotype of interest, the integrated stress response. Activation of this stress response can be induced with ER stressors such as thapsigargin, and leads to translation of the Venus fluorescent protein, which is encoded downstream of the 5′ region of the ATF4 mRNA. We established a monoclonal reporter cell line was established in human K562 leukemia cells. (c) The reporter activity of this cell line in response to 300 nM thapsigargin is inhibited by the small molecule ISRIB in a dose-dependent manner (mean and standard deviation for experimental triplicates are shown). (d) Experimental strategy: the reporter cell line was transduced with an shRNA library targeting genes related to protein homeostasis, and exposed to thapsigargin in the presence or absence of ISRIB around its EC50 concentration. Cells with high and low levels of reporter activity were isolated by fluorescence-activated cell sorting (FACS), and the frequencies of cells expressing each shRNA were quantified in the different populations by next-generation sequencing. (e) The effect of gene knockdown on reporter activation either in the presence or absence of ISRIB are shown, each dot is a gene and P values for the statistical significance of the effect of a gene were calculated using the Mann-Whitney U test as previously described. Knockdown of eIF2B4 and eIF2B5, two subunits of the eIF2B complex, blocked ISRIB action, and we validated biochemically that ISRIB is an activator of eIF2B. Figure adapted from ref .