Abstract

Current 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.

Details

Title
A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds
Author
Lin, Kevin 1 ; Chang, Ya-Chu 2 ; Billmann, Maximilian 3 ; Ward, Henry N. 4 ; Le, Khoi 2 ; Hassan, Arshia Z. 5 ; Bhojoo, Urvi 6 ; Chan, Katherine 7 ; Costanzo, Michael 6 ; Moffat, Jason 8 ; Boone, Charles 6 ; Bielinsky, Anja-Katrin 9 ; Myers, Chad L. 1 

 University of Minnesota–Twin Cities, Department of Computer Science and Engineering, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657); University of Minnesota–Twin Cities, Bioinformatics and Computational Biology Graduate Program, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657) 
 University of Minnesota–Twin Cities, Department of Biochemistry, Molecular Biology and Biophysics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657) 
 University of Minnesota–Twin Cities, Department of Computer Science and Engineering, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657); University of Bonn, School of Medicine and University Hospital Bonn, Institute of Human Genetics, Bonn, Germany (GRID:grid.10388.32) (ISNI:0000 0001 2240 3300) 
 University of Minnesota–Twin Cities, Bioinformatics and Computational Biology Graduate Program, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657) 
 University of Minnesota–Twin Cities, Department of Computer Science and Engineering, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657) 
 University of Toronto, Donnelly Centre, Toronto, Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938); University of Toronto, Department of Molecular Genetics, Toronto, Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938) 
 The Hospital for Sick Children, Program in Genetics and Genome Biology, Toronto, Canada (GRID:grid.430185.b) 
 University of Toronto, Department of Molecular Genetics, Toronto, Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938); The Hospital for Sick Children, Program in Genetics and Genome Biology, Toronto, Canada (GRID:grid.430185.b); University of Toronto, Institute for Biomedical Engineering, Toronto, Canada (GRID:grid.17063.33) (ISNI:0000 0001 2157 2938) 
 University of Minnesota–Twin Cities, Department of Biochemistry, Molecular Biology and Biophysics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657); University of Virginia, Department of Biochemistry and Molecular Genetics, Charlottesville, USA (GRID:grid.27755.32) (ISNI:0000 0000 9136 933X) 
Pages
2508
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2919972296
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.