Abstract
Cell-based transcriptional reporters are invaluable in high-throughput compound and CRISPR screens for identifying compounds or genes that can impact a pathway of interest. However, many transcriptional reporters have weak activities and transient responses. This can result in overlooking therapeutic targets and compounds that are difficult to detect, necessitating the resource-consuming process of running multiple screens at various timepoints. Here, we present RADAR, a digitizer circuit for amplifying reporter activity and retaining memory of pathway activation. Reporting on the AP-1 pathway, our circuit identifies compounds with known activity against PKC-related pathways and shows an enhanced dynamic range with improved sensitivity compared to a classical reporter in compound screens. In the first genome-wide pooled CRISPR screen for the AP-1 pathway, RADAR identifies canonical genes from the MAPK and PKC pathways, as well as non-canonical regulators. Thus, our scalable system highlights the benefit and versatility of using genetic circuits in large-scale cell-based screening.
Highlights
Cell-based transcriptional reporters are invaluable in high-throughput compound and CRISPR screens for identifying compounds or genes that can impact a pathway of interest
Using Recombinasebased Analog-to-DigitAl Reporter” (RADAR) in a pooled CRISPR screen, we identified many canonical MAPK and protein kinase C (PKC)-related genes, consistent with their function in the AP-1 pathway
As a proof of concept, an AP-1 pathway-sensitive promoter was used to drive expression of a FlpO recombinase, and both GFP and luciferase were included as the reporter genes to allow for flexibility in bulk or single-cell readout
Summary
Cell-based transcriptional reporters are invaluable in high-throughput compound and CRISPR screens for identifying compounds or genes that can impact a pathway of interest. Many output measurements cannot discern nuanced perturbations, overlooking important drug and gene candidates, and the application of high-content approaches to large-scale screens remains challenging While these approaches have proven useful, they illustrate the need for the design and optimization of output quantification for cell-based screening experiments. One of the most widely used and important phenotypic readout methods in cell-based screenings involves pathwayspecific transcription reporters, which express reporter genes in response to pathway activation[4,5,6,7] These reporters are costefficient to implement and highly scalable, making them an ideal tool for large-scale chemical and genetic screens[8,9,10]. We have termed this system “Recombinasebased Analog-to-DigitAl Reporter” (RADAR)
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