Minimized combinatorial CRISPR screens identify genetic interactions in autophagy
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE166851 | GEO | 2021/06/16
REPOSITORIES: GEO
Similar Datasets
Project description:Minimized combinatorial CRISPR screens identify genetic interactions in autophagy
| PRJNA702116 | ENA
Project description:Combinatorial CRISPR-Cas screens have advanced the mapping of genetic interactions, but their experimental scale limits the number of targetable gene combinations. Here, we describe 3Cs multiplexing, a rapid and scalable method to generate highly diverse and uniformly distributed combinatorial CRISPR libraries. We demonstrate that the library distribution skew is the critical determinant of its required screening coverage. By circumventing iterative cloning of PCR-amplified oligonucleotides, 3Cs multiplexing facilitates the generation of combinatorial CRISPR libraries with low distribution skews. We show that combinatorial 3Cs libraries can be screened with minimal coverages, reducing associated efforts and costs at least 10-fold. We apply a 3Cs multiplexing library targeting 12,736 autophagy gene combinations with 247,032 paired gRNAs in viability and reporter-based enrichment screens. In the viability screen, we identify, among others, the synthetic lethal WDR45B-PIK3R4 and the proliferation-enhancing ATG7-KEAP1 genetic interactions. In the reporter-based screen, we identify over 1,570 essential genetic interactions for autophagy flux, including interactions among paralogous genes, namely ATG2A-ATG2B, GABARAP-MAP1LC3B and GABARAP-GABARAPL2. However, we only observe few genetic interactions within paralogous gene families of more than two members, indicating functional compensation between them. This work establishes 3Cs multiplexing as a platform for genetic interaction screens at scale.
| S-EPMC8191801 | biostudies-literature
Project description:CRISPR-based gene perturbation enables unbiased investigations of single and combinatorial genotype-to-phenotype associations. In light of efforts to map combinatorial gene dependencies at scale, choosing an efficient and robust CRISPR-associated (Cas) nuclease is of utmost importance. Even though SpCas9 and AsCas12a are widely used for single, combinatorial, and orthogonal screenings, side-by-side comparisons remain sparse. Here, we systematically compared combinatorial SpCas9, AsCas12a, and CHyMErA in hTERT-immortalized retinal pigment epithelial cells and extracted performance-critical parameters for combinatorial and orthogonal CRISPR screens. Our analyses identified SpCas9 to be superior to enhanced and optimized AsCas12a, with CHyMErA being largely inactive in the tested conditions. Since AsCas12a contains RNA processing activity, we used arrayed dual-gRNAs to improve AsCas12a and CHyMErA applications. While this negatively influenced the effect size of combinatorial AsCas12a applications, it enhanced the performance of CHyMErA. This improved performance, however, was limited to AsCas12a dual-gRNAs, as SpCas9 gRNAs remained largely inactive. To avoid the use of hybrid gRNAs for orthogonal applications, we engineered the multiplex SpCas9-enAsCas12a system (multiSPAS) that avoids RNA processing for efficient orthogonal gene editing.
2023-05-10 | GSE215175 | GEO
Project description:Systems for CRISPR-based combinatorial perturbation of two or more genes are emerging as powerful tools for uncovering genetic interactions. However, systematic identification of these relationships is complicated by sample, reagent, and biological variability. We develop a variational Bayes approach (GEMINI) that jointly analyzes all samples and reagents to identify genetic interactions in pairwise knockout screens. The improved accuracy and scalability of GEMINI enables the systematic analysis of combinatorial CRISPR knockout screens, regardless of design and dimension. GEMINI is available as an open source R package on GitHub at https://github.com/sellerslab/gemini .
| S-EPMC6624979 | biostudies-literature
Project description:To identify genes regulating autophagy in human T-cells (Jurkat cell line) a CRISPR screen was conducted. Populations with low autophagic flux was sorted and the contained sgRNAs analysed by next-generation sequencing. Bioinformatic analysis compared the input of the screen versus the 'autophagy low' population.
2021-01-13 | GSE147488 | GEO
Project description:We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies.
| S-EPMC5449203 | biostudies-literature
Project description:Combinatorial genetic screening using CRISPR-Cas9 is a useful approach to uncover redundant genes and to explore complex gene networks. However, current methods suffer from interference between the single-guide RNAs (sgRNAs) and from limited gene targeting activity. To increase the efficiency of combinatorial screening, we employ orthogonal Cas9 enzymes from Staphylococcus aureus and Streptococcus pyogenes. We used machine learning to establish S. aureus Cas9 sgRNA design rules and paired S. aureus Cas9 with S. pyogenes Cas9 to achieve dual targeting in a high fraction of cells. We also developed a lentiviral vector and cloning strategy to generate high-complexity pooled dual-knockout libraries to identify synthetic lethal and buffering gene pairs across multiple cell types, including MAPK pathway genes and apoptotic genes. Our orthologous approach also enabled a screen combining gene knockouts with transcriptional activation, which revealed genetic interactions with TP53. The "Big Papi" (paired aureus and pyogenes for interactions) approach described here will be widely applicable for the study of combinatorial phenotypes.
| S-EPMC5800952 | biostudies-literature
Project description:Macroautophagy (hereafter, autophagy) is a process that directs the degradation of cytoplasmic material in lysosomes. In addition to its homeostatic roles, autophagy undergoes dynamic positive and negative regulation in response to multiple forms of cellular stress, thus enabling the survival of cells. However, the precise mechanisms of autophagy regulation are not fully understood. To identify potential negative regulators of autophagy, we performed a genome-wide CRISPR screen using the quantitative autophagic flux reporter GFP-LC3-RFP. We identified phosphoribosylformylglycinamidine synthase (PFAS), a component of the de novo purine synthesis pathway, as one such negative regulator of autophagy. Autophagy was activated in cells lacking PFAS or phosphoribosyl pyrophosphate amidotransferase (PPAT), another de novo purine synthesis enzyme, or treated with methotrexate when exogenous levels of purines were insufficient. Purine starvation-induced autophagy activation was concomitant with mTORC1 suppression, and was profoundly suppressed in cells deficient for TSC2, which negatively regulates mTORC1 through inhibition of RHEB, suggesting that purines regulate autophagy through the TSC-RHEB-mTORC1 signaling axis. Moreover, depletion of the pyrimidine synthesis enzymes carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) and dihydroorotate dehydrogenase (DHODH) activated autophagy as well, although mTORC1 activity was not altered by pyrimidine shortage. These results suggest a different mechanism of autophagy induction between purine and pyrimidine starvation. These findings provide novel insights into the regulation of autophagy by nucleotides and possibly the role of autophagy in nucleotide metabolism, leading to further developing anticancer strategies involving nucleotide synthesis and autophagy.
2021-05-11 | GSE164778 | GEO
Project description:Murine pancreatic cancer cells (HY15549 cells) established from genetically engineered mouse models (GEMM) of PDAC (p48-Cre+, KrasLSL-G12D/+, Trp53lox/+; KPC mice) were transfected with the GFP-LC3-RFP autophagy flux reporter from Mizushima lab, wherein reduction in the GFP/RFP ratio indicates increase in autophagy flux. Organoids derived from these cells were dissociated into single cells and sorted into autophagy-high (AThi) and autophagy-low (ATlo) populations according to GFP/RFP signal ratio. To validate this reporter, RNA was extracted from these two populations and expression of autophagy/lysosome related genes was examined.
2020-04-16 | GSE145766 | GEO
Project description:Cancer is a complex disease resulting from the accumulation of genetic dysfunctions. Tumor heterogeneity causes the molecular variety that divergently controls responses to chemotherapy, leading to the recurrent problem of cancer reappearance. For many decades, efforts have focused on identifying essential tumoral genes and cancer driver mutations. More recently, prompted by the clinical success of the synthetic lethality (SL)-based therapy of the PARP inhibitors in homologous recombinant deficient tumors, scientists have centered their novel research on SL interactions (SLI). The state of the art to find new genetic interactions are currently large-scale forward genetic CRISPR screens. CRISPR technology has rapidly evolved to be a common tool in the vast majority of laboratories, as tools to implement CRISPR screen protocols are available to all researchers. Taking advantage of SLI, combinatorial therapies have become the ultimate model to treat cancer with lower toxicity, and therefore better efficiency. This review explores the CRISPR screen methodology, integrates the up-to-date published findings on CRISPR screens in the cancer field and proposes future directions to uncover cancer regulation and individual responses to chemotherapy.
| S-EPMC8037779 | biostudies-literature