A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Kevin Lin; Ya-Chu Chang; Maximilian Billmann; Henry N Ward; Khoi Le; Arshia Z Hassan; Urvi Bhojoo; Katherine Chan; Michael Costanzo; Jason Moffat; Charles Boone; Anja-Katrin Bielinsky; Chad L Myers

doi:10.1038/s41598-024-51735-y

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Sci Rep. 2024 Jan 30;14(1):2508. doi: 10.1038/s41598-024-51735-y.

Authors

Kevin Lin^{1

2}, Ya-Chu Chang³, Maximilian Billmann^{1

4}, Henry N Ward², Khoi Le³, Arshia Z Hassan¹, Urvi Bhojoo^{5

6}, Katherine Chan⁷, Michael Costanzo^{5

6}, Jason Moffat^{6

7

8}, Charles Boone^{5

6}, Anja-Katrin Bielinsky^{9

10}, Chad L Myers^{11

12}

Affiliations

¹ Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA.
² Bioinformatics and Computational Biology Graduate Program, University of Minnesota-Twin Cities, Minneapolis, MN, USA.
³ Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota-Twin Cities, Minneapolis, MN, USA.
⁴ Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany.
⁵ Donnelly Centre, University of Toronto, Toronto, ON, Canada.
⁶ Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
⁷ Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
⁸ Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
⁹ Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota-Twin Cities, Minneapolis, MN, USA. azu3jn@virginia.edu.
¹⁰ Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA. azu3jn@virginia.edu.
¹¹ Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA. chadm@umn.edu.
¹² Bioinformatics and Computational Biology Graduate Program, University of Minnesota-Twin Cities, Minneapolis, MN, USA. chadm@umn.edu.

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.

MeSH terms

CRISPR-Cas Systems*
DNA Damage
Genetic Testing
Genome
Humans
RNA, Guide, CRISPR-Cas Systems*

Substances

RNA, Guide, CRISPR-Cas Systems

Abstract

MeSH terms

Substances

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