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

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 (FAG). A plugin was developed for the open source software mu Manager to automate the phenotypic identification and photoactivation of cells, allowing similar to 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.

Automated summary

A microscopy-based optical enrichment approach was developed for selecting and marking cells displaying specific CRISPR-induced phenotypes, followed by isolation using fluorescence-activated cell sorting (FAG). Automated phenotypic identification and photoactivation of cells were achieved through a plugin developed for the open source software mu Manager, allowing screening of approximately 1.5 million individual cells in 8 hours. This scalable approach facilitated the identification of 14 bona fide hits out of 6,092 sgRNAs targeting 544 genes in terms of their effects on nuclear size regulation.