Author:
Lin Kevin,Chang Ya-Chu,Billmann Maximilian,Ward Henry N.,Le Khoi,Hassan Arshia Z.,Bhojoo Urvi,Chan Katherine,Costanzo Michael,Moffat Jason,Boone Charles,Bielinsky Anja-Katrin,Myers Chad L.
Abstract
AbstractCurrent approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds’ known modes-of-action (MoA) were enriched among the compounds’ CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.
Funder
National Science Foundation, United States
National Institutes of Health,United States
National Cancer Institute
Ontario Research Foundation
Canadian Institutes of Health Research
Publisher
Springer Science and Business Media LLC