High-content imaging-based pooled CRISPR screens in mammalian cells

• Published in: The Journal of cell biology Vol. 220; no. 2
• Main Authors: Yan, Xiaowei, Stuurman, Nico, Ribeiro, Susana A., Tanenbaum, Marvin E., Horlbeck, Max A., Liem, Christina R., Jost, Marco, Weissman, Jonathan S., Vale, Ronald D.
• Format: Journal Article
• Language: English
• Published: United States Rockefeller University Press 01.02.2021
• Subjects: Automation; Cell Cycle and Division; Cell Line; Cell Nucleus - genetics; Cell Nucleus Size - genetics; CRISPR; CRISPR-Cas Systems - genetics; Flow Cytometry; Fluorescence; Genes; Genetic Testing; Green Fluorescent Proteins - metabolism; Humans; Imaging; Imaging, Three-Dimensional; Inactivation; Mammalian cells; Optics and Photonics; Phenotype; Phenotypes; Photoactivation; Technology
• ISSN: 0021-9525; 1540-8140; 1540-8140
• DOI: 10.1083/jcb.202008158

CRISPR (clustered regularly interspaced short palindromic repeats)-based gene inactivation provides a powerful means for linking genes to particular cellular phenotypes. CRISPR-based screening typically uses large genomic pools of single guide RNAs (sgRNAs). However, this approach is limited to phenotypes that can be enriched by chemical selection or FACS sorting. Here, we developed a microscopy-based approach, which we name optical enrichment, to select cells displaying a particular CRISPR-induced phenotype by automated imaging-based computation, mark them by photoactivation of an expressed photoactivatable fluorescent protein, and then isolate the fluorescent cells using fluorescence-activated cell sorting (FACS). A plugin was developed for the open source software μManager to automate the phenotypic identification and photoactivation of cells, allowing ∼1.5 million individual cells to be screened in 8 h. We used this approach to screen 6,092 sgRNAs targeting 544 genes for their effects on nuclear size regulation and identified 14 bona fide hits. These results present a scalable approach to facilitate imaging-based pooled CRISPR screens.