Identifying chemogenetic interactions from CRISPR screens with drugZ.
ABSTRACT: BACKGROUND:Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of chemical compounds. This knowledge provides insights into drug mechanism of action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations and improve drug efficacy. CRISPR-based screening enables sensitive detection of drug-gene interactions directly in human cells, but until recently has primarily been used to screen only for resistance mechanisms. RESULTS:We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from CRISPR screens. DrugZ identifies synthetic lethal interactions between PARP inhibitors and both known and novel members of the DNA damage repair pathway, confirms KEAP1 loss as a resistance factor for ERK inhibitors in oncogenic KRAS backgrounds, and defines the genetic context for temozolomide activity. CONCLUSIONS:DrugZ is an open-source Python software for the analysis of genome-scale drug modifier screens. The software accurately identifies genetic perturbations that enhance or suppress drug activity. Interestingly, analysis of new and previously published data reveals tumor suppressor genes are drug-agnostic resistance genes in drug modifier screens. The software is available at github.com/hart-lab/drugz .
Project description:High-throughput CRISPR-Cas9 knockout screens using a tiling-sgRNA design permit in situ evaluation of protein domain function. Here, to facilitate de novo identification of essential protein domains from such screens, we propose ProTiler, a computational method for the robust mapping of CRISPR knockout hyper-sensitive (CKHS) regions, which refer to the protein regions associated with a strong sgRNA dropout effect in the screens. Applied to a published CRISPR tiling screen dataset, ProTiler identifies 175 CKHS regions in 83 proteins. Of these CKHS regions, more than 80% overlap with annotated Pfam domains, including all of the 15 known drug targets in the dataset. ProTiler also reveals unannotated essential domains, including the N-terminus of the SWI/SNF subunit SMARCB1, which is validated experimentally. Surprisingly, the CKHS regions are negatively correlated with phosphorylation and acetylation sites, suggesting that protein domains and post-translational modification sites have distinct sensitivities to CRISPR-Cas9 mediated amino acids loss.
Project description:High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. We chose three use cases that demonstrate the potential of HiTSeekR to fully exploit HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNF?, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is publicly available at http://hitseekr.compbio.sdu.dk It is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.
Project description:Predicting the response and identifying additional targets that will improve the efficacy of chemotherapy is a major goal in cancer research. Through large-scale in vivo and in vitro CRISPR knockout screens in pancreatic ductal adenocarcinoma cells, we identified genes whose genetic deletion or pharmacologic inhibition synergistically increase the cytotoxicity of MEK signaling inhibitors. Furthermore, we show that CRISPR viability scores combined with basal gene expression levels could model global cellular responses to the drug treatment. We develop drug response evaluation by in vivo CRISPR screening (DREBIC) method and validated its efficacy using large-scale experimental data from independent experiments. Comparative analyses demonstrate that DREBIC predicts drug response in cancer cells from a wide range of tissues with high accuracy and identifies therapeutic vulnerabilities of cancer-causing mutations to MEK inhibitors in various cancer types.
Project description:Pooled CRISPR-Cas9 knock out screens provide a valuable addition to the methods available for novel drug target identification and validation. However, where gene editing is targeted to amplified loci, the resulting multiple DNA cleavage events can be a cause of false positive hit identification. The generation of nuclease deficient versions of Cas9 has enabled the development of two additional techniques - CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) - that enable the repression or overexpression, respectively, of target genes. Here we report the first direct combination of all three approaches (CRISPRko, CRISPRi and CRISPRa) in the context of genome-wide screens to identify components that influence resistance and sensitivity to the BRAF inhibitor, vemurafenib. The pairing of both loss- and gain-of-function datasets reveals complex gene networks which control drug response and illustrates how such data can add substantial confidence to target identification and validation analyses.
Project description:BACKGROUND:The introduction of genome-wide shRNA and CRISPR libraries has facilitated cell-based screens to identify loss-of-function mutations associated with a phenotype of interest. Approaches to perform analogous gain-of-function screens are less common, although some reports have utilized arrayed viral expression libraries or the CRISPR activation system. However, a variety of technical and logistical challenges make these approaches difficult for many labs to execute. In addition, genome-wide shRNA or CRISPR libraries typically contain of hundreds of thousands of individual engineered elements, and the associated complexity creates issues with replication and reproducibility for these methods. RESULTS:Here we describe a simple, reproducible approach using the SB transposon system to perform phenotypic cell-based genetic screens. This approach employs only three plasmids to perform unbiased, whole-genome transposon mutagenesis. We also describe a ligation-mediated PCR method that can be used in conjunction with the included software tools to map raw sequence data, identify candidate genes associated with phenotypes of interest, and predict the impact of recurrent transposon insertions on candidate gene function. Finally, we demonstrate the high reproducibility of our approach by having three individuals perform independent replicates of a mutagenesis screen to identify drivers of vemurafenib resistance in cultured melanoma cells. CONCLUSIONS:Collectively, our work establishes a facile, adaptable method that can be performed by labs of any size to perform robust, genome-wide screens to identify genes that influence phenotypes of interest.
Project description:Over the last decade Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) has been developed into a potent molecular biology tool used to rapidly modify genes or their expression in a multitude of ways. In parallel, CRISPR-based screening approaches have been developed as powerful discovery platforms for dissecting the genetic basis of cellular behavior, as well as for drug target discovery. CRISPR screens can be designed in numerous ways. Here, we give a brief background to CRISPR screens and discuss the pros and cons of different design approaches, including unbiased genome-wide screens that target all known genes, as well as hypothesis-driven custom screens in which selected subsets of genes are targeted (Fig. 1). We provide several suggestions for how a custom screen can be designed, which could broadly serve as inspiration for any experiment that includes candidate gene selection. Finally, we discuss how results from CRISPR screens could be translated into drug development, as well as future trends we foresee in the rapidly evolving CRISPR screen field.
Project description:The development of high-throughput gene manipulating tools such as short hairpin RNA (shRNA) and CRISPR/Cas9 libraries has enabled robust characterization of novel functional genes contributing to the pathological states of the diseases. In acute myeloid leukemia (AML), these genetic screen approaches have been used to identify effector genes with previously unknown roles in AML. These AML-related genes centralize alongside the cellular pathways mediating epigenetics, signaling transduction, transcriptional regulation, and energy metabolism. The shRNA/CRISPR genetic screens also realized an array of candidate genes amenable to pharmaceutical targeting. This review aims to summarize genes, mechanisms, and potential therapeutic strategies found via high-throughput genetic screens in AML. We also discuss the potential of these findings to instruct novel AML therapies for combating drug resistance in this genetically heterogeneous disease.
Project description:BACKGROUND:Drug resistance is a major obstacle in cancer therapy. To elucidate the genetic factors that regulate sensitivity to anti-cancer drugs, we performed CRISPR-Cas9 knockout screens for resistance to a spectrum of drugs. RESULTS:In addition to known drug targets and resistance mechanisms, this study revealed novel insights into drug mechanisms of action, including cellular transporters, drug target effectors, and genes involved in target-relevant pathways. Importantly, we identified ten multi-drug resistance genes, including an uncharacterized gene C1orf115, which we named Required for Drug-induced Death 1 (RDD1). Loss of RDD1 resulted in resistance to five anti-cancer drugs. Finally, targeting RDD1 leads to chemotherapy resistance in mice and low RDD1 expression is associated with poor prognosis in multiple cancers. CONCLUSIONS:Together, we provide a functional landscape of resistance mechanisms to a broad range of chemotherapeutic drugs and highlight RDD1 as a new factor controlling multi-drug resistance. This information can guide personalized therapies or instruct rational drug combinations to minimize acquisition of resistance.
Project description:The noncoding genome affects gene regulation and disease, yet we lack tools for rapid identification and manipulation of noncoding elements. We developed a CRISPR screen using ~18,000 single guide RNAs targeting >700 kilobases surrounding the genes NF1, NF2, and CUL3, which are involved in BRAF inhibitor resistance in melanoma. We find that noncoding locations that modulate drug resistance also harbor predictive hallmarks of noncoding function. With a subset of regions at the CUL3 locus, we demonstrate that engineered mutations alter transcription factor occupancy and long-range and local epigenetic environments, implicating these sites in gene regulation and chemotherapeutic resistance. Through our expansion of the potential of pooled CRISPR screens, we provide tools for genomic discovery and for elucidating biologically relevant mechanisms of gene regulation.