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 phen...
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Published in | The Journal of cell biology Vol. 220; no. 2 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Rockefeller University Press
01.02.2021
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Subjects | |
Online Access | Get full text |
ISSN | 0021-9525 1540-8140 1540-8140 |
DOI | 10.1083/jcb.202008158 |
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Abstract | 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. |
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AbstractList | 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. Yan et al. demonstrate high-throughput screening of pooled CRISPR libraries for phenotypes detectable by microscopy. Their approach uses photoactivation of cells displaying the phenotype of interest and FACS sorting of marked cells, followed by sequencing, and facilitates discovery of genes involved in cell biological processes. 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. 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.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. |
Author | Vale, Ronald D. Jost, Marco Ribeiro, Susana A. Stuurman, Nico Horlbeck, Max A. Liem, Christina R. Weissman, Jonathan S. Yan, Xiaowei Tanenbaum, Marvin E. |
AuthorAffiliation | 2 Cairn Biosciences, Inc., San Francisco, CA 4 Boston Children's Hospital, Boston, MA 6 Whitehead Institute and Department of Biology, MIT, Cambridge, MA 1 Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 7 Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 5 University of California, San Diego, San Diego, CA 3 Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, Netherlands |
AuthorAffiliation_xml | – name: 5 University of California, San Diego, San Diego, CA – name: 6 Whitehead Institute and Department of Biology, MIT, Cambridge, MA – name: 7 Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA – name: 3 Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, Netherlands – name: 2 Cairn Biosciences, Inc., San Francisco, CA – name: 1 Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA – name: 4 Boston Children's Hospital, Boston, MA |
Author_xml | – sequence: 1 givenname: Xiaowei orcidid: 0000-0002-4846-8812 surname: Yan fullname: Yan, Xiaowei – sequence: 2 givenname: Nico orcidid: 0000-0002-6179-8613 surname: Stuurman fullname: Stuurman, Nico – sequence: 3 givenname: Susana A. orcidid: 0000-0003-3807-7540 surname: Ribeiro fullname: Ribeiro, Susana A. – sequence: 4 givenname: Marvin E. surname: Tanenbaum fullname: Tanenbaum, Marvin E. – sequence: 5 givenname: Max A. orcidid: 0000-0002-3875-871X surname: Horlbeck fullname: Horlbeck, Max A. – sequence: 6 givenname: Christina R. orcidid: 0000-0003-2744-6312 surname: Liem fullname: Liem, Christina R. – sequence: 7 givenname: Marco orcidid: 0000-0002-1369-4908 surname: Jost fullname: Jost, Marco – sequence: 8 givenname: Jonathan S. surname: Weissman fullname: Weissman, Jonathan S. – sequence: 9 givenname: Ronald D. orcidid: 0000-0003-3460-2758 surname: Vale fullname: Vale, Ronald D. |
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Snippet | CRISPR (clustered regularly interspaced short palindromic repeats)-based gene inactivation provides a powerful means for linking genes to particular cellular... Yan et al. demonstrate high-throughput screening of pooled CRISPR libraries for phenotypes detectable by microscopy. Their approach uses photoactivation of... |
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SubjectTerms | 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 |
Title | High-content imaging-based pooled CRISPR screens in mammalian cells |
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