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

TY - JOUR

T1 - High-content imaging-based pooled CRISPR screens in mammalian cells

AU - Yan, Xiaowei

AU - Stuurman, Nico

AU - Ribeiro, Susana A

AU - Tanenbaum, Marvin E

AU - Horlbeck, Max A

AU - Liem, Christina R

AU - Jost, Marco

AU - Weissman, Jonathan S

AU - Vale, Ronald D

N1 - © 2021 Yan et al.

PY - 2021/2/1

Y1 - 2021/2/1

N2 - 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.

AB - 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.

KW - CRISPR-Cas Systems/genetics

KW - Cell Line

KW - Cell Nucleus/genetics

KW - Cell Nucleus Size/genetics

KW - Flow Cytometry

KW - Genetic Testing

KW - Green Fluorescent Proteins/metabolism

KW - Humans

KW - Imaging, Three-Dimensional

KW - Optics and Photonics

KW - Phenotype

U2 - 10.1083/jcb.202008158

DO - 10.1083/jcb.202008158

M3 - Article

C2 - 33465779

SN - 0021-9525

VL - 220

JO - Journal of Cell Biology

JF - Journal of Cell Biology

IS - 2

ER -