51
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Shevade K, Peddada S, Mader K, Przybyla L. Functional genomics in stem cell models: considerations and applications. Front Cell Dev Biol 2023; 11:1236553. [PMID: 37554308 PMCID: PMC10404852 DOI: 10.3389/fcell.2023.1236553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/13/2023] [Indexed: 08/10/2023] Open
Abstract
Protocols to differentiate human pluripotent stem cells have advanced in terms of cell type specificity and tissue-level complexity over the past 2 decades, which has facilitated human disease modeling in the most relevant cell types. The ability to generate induced PSCs (iPSCs) from patients further enables the study of disease mutations in an appropriate cellular context to reveal the mechanisms that underlie disease etiology and progression. As iPSC-derived disease models have improved in robustness and scale, they have also been adopted more widely for use in drug screens to discover new therapies and therapeutic targets. Advancement in genome editing technologies, in particular the discovery of CRISPR-Cas9, has further allowed for rapid development of iPSCs containing disease-causing mutations. CRISPR-Cas9 technologies have now evolved beyond creating single gene edits, aided by the fusion of inhibitory (CRISPRi) or activation (CRISPRa) domains to a catalytically dead Cas9 protein, enabling inhibition or activation of endogenous gene loci. These tools have been used in CRISPR knockout, CRISPRi, or CRISPRa screens to identify genetic modifiers that synergize or antagonize with disease mutations in a systematic and unbiased manner, resulting in identification of disease mechanisms and discovery of new therapeutic targets to accelerate drug discovery research. However, many technical challenges remain when applying large-scale functional genomics approaches to differentiated PSC populations. Here we review current technologies in the field of iPSC disease modeling and CRISPR-based functional genomics screens and practical considerations for implementation across a range of modalities, applications, and disease areas, as well as explore CRISPR screens that have been performed in iPSC models to-date and the insights and therapies these screens have produced.
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Affiliation(s)
- Kaivalya Shevade
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Sailaja Peddada
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Karl Mader
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
| | - Laralynne Przybyla
- Laboratory for Genomics Research, San Francisco, CA, United States
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, United States
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52
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Kornienko J, Rodríguez-Martínez M, Fenzl K, Hinze F, Schraivogel D, Grosch M, Tunaj B, Lindenhofer D, Schraft L, Kueblbeck M, Smith E, Mao C, Brown E, Owens A, Saguner AM, Meder B, Parikh V, Gotthardt M, Steinmetz LM. Mislocalization of pathogenic RBM20 variants in dilated cardiomyopathy is caused by loss-of-interaction with Transportin-3. Nat Commun 2023; 14:4312. [PMID: 37463913 DOI: 10.1038/s41467-023-39965-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 07/05/2023] [Indexed: 07/20/2023] Open
Abstract
Severe forms of dilated cardiomyopathy (DCM) are associated with point mutations in the alternative splicing regulator RBM20 that are frequently located in the arginine/serine-rich domain (RS-domain). Such mutations can cause defective splicing and cytoplasmic mislocalization, which leads to the formation of detrimental cytoplasmic granules. Successful development of personalized therapies requires identifying the direct mechanisms of pathogenic RBM20 variants. Here, we decipher the molecular mechanism of RBM20 mislocalization and its specific role in DCM pathogenesis. We demonstrate that mislocalized RBM20 RS-domain variants retain their splice regulatory activity, which reveals that aberrant cellular localization is the main driver of their pathological phenotype. A genome-wide CRISPR knockout screen combined with image-enabled cell sorting identified Transportin-3 (TNPO3) as the main nuclear importer of RBM20. We show that the direct RBM20-TNPO3 interaction involves the RS-domain, and is disrupted by pathogenic variants. Relocalization of pathogenic RBM20 variants to the nucleus restores alternative splicing and dissolves cytoplasmic granules in cell culture and animal models. These findings provide proof-of-principle for developing therapeutic strategies to restore RBM20's nuclear localization in RBM20-DCM patients.
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Affiliation(s)
- Julia Kornienko
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Heidelberg, Germany
| | | | - Kai Fenzl
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Heidelberg, Germany
| | - Florian Hinze
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel Schraivogel
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Markus Grosch
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Heidelberg, Germany
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Brigit Tunaj
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Dominik Lindenhofer
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Laura Schraft
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Moritz Kueblbeck
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Eric Smith
- University of Michigan, Ann Arbor, MI, USA
| | - Chad Mao
- Children's Healthcare of Atlanta & Emory University, Atlanta, GA, USA
| | | | - Anjali Owens
- University of Pennsylvania, Philadelphia, PA, USA
| | - Ardan M Saguner
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Benjamin Meder
- Cardiogenetics Center Heidelberg, Department of Cardiology, Angiology and Pulmology, University Hospital Heidelberg, Heidelberg, Germany
| | - Victoria Parikh
- Stanford Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Gotthardt
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Lars M Steinmetz
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Heidelberg, Germany.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Genome Technology Center, Palo Alto, CA, USA.
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53
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Sansbury SE, Serebrenik YV, Lapidot T, Burslem GM, Shalem O. Pooled tagging and hydrophobic targeting of endogenous proteins for unbiased mapping of unfolded protein responses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.548611. [PMID: 37503003 PMCID: PMC10370017 DOI: 10.1101/2023.07.13.548611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
System-level understanding of proteome organization and function requires methods for direct visualization and manipulation of proteins at scale. We developed an approach enabled by high-throughput gene tagging for the generation and analysis of complex cell pools with endogenously tagged proteins. Proteins are tagged with HaloTag to enable visualization or direct perturbation. Fluorescent labeling followed by in situ sequencing and deep learning-based image analysis identifies the localization pattern of each tag, providing a bird's-eye-view of cellular organization. Next, we use a hydrophobic HaloTag ligand to misfold tagged proteins, inducing spatially restricted proteotoxic stress that is read out by single cell RNA sequencing. By integrating optical and perturbation data, we map compartment-specific responses to protein misfolding, revealing inter-compartment organization and direct crosstalk, and assigning proteostasis functions to uncharacterized genes. Altogether, we present a powerful and efficient method for large-scale studies of proteome dynamics, function, and homeostasis.
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54
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She R, Fair T, Schaefer NK, Saunders RA, Pavlovic BJ, Weissman JS, Pollen AA. Comparative landscape of genetic dependencies in human and chimpanzee stem cells. Cell 2023; 186:2977-2994.e23. [PMID: 37343560 PMCID: PMC10461406 DOI: 10.1016/j.cell.2023.05.043] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/14/2023] [Accepted: 05/26/2023] [Indexed: 06/23/2023]
Abstract
Comparative studies of great apes provide a window into our evolutionary past, but the extent and identity of cellular differences that emerged during hominin evolution remain largely unexplored. We established a comparative loss-of-function approach to evaluate whether human cells exhibit distinct genetic dependencies. By performing genome-wide CRISPR interference screens in human and chimpanzee pluripotent stem cells, we identified 75 genes with species-specific effects on cellular proliferation. These genes comprised coherent processes, including cell-cycle progression and lysosomal signaling, which we determined to be human-derived by comparison with orangutan cells. Human-specific robustness to CDK2 and CCNE1 depletion persisted in neural progenitor cells and cerebral organoids, supporting the G1-phase length hypothesis as a potential evolutionary mechanism in human brain expansion. Our findings demonstrate that evolutionary changes in human cells reshaped the landscape of essential genes and establish a platform for systematically uncovering latent cellular and molecular differences between species.
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Affiliation(s)
- Richard She
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Nathan K Schaefer
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Reuben A Saunders
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Department of Cellular and Molecular Pharmacology, University of California at San Francisco, San Francisco, CA, USA
| | - Bryan J Pavlovic
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan S Weissman
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute Technology, Cambridge, MA 02142, USA.
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
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55
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Tang YJ, Shuldiner EG, Karmakar S, Winslow MM. High-Throughput Identification, Modeling, and Analysis of Cancer Driver Genes In Vivo. Cold Spring Harb Perspect Med 2023; 13:a041382. [PMID: 37277208 PMCID: PMC10317066 DOI: 10.1101/cshperspect.a041382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The vast number of genomic and molecular alterations in cancer pose a substantial challenge to uncovering the mechanisms of tumorigenesis and identifying therapeutic targets. High-throughput functional genomic methods in genetically engineered mouse models allow for rapid and systematic investigation of cancer driver genes. In this review, we discuss the basic concepts and tools for multiplexed investigation of functionally important cancer genes in vivo using autochthonous cancer models. Furthermore, we highlight emerging technical advances in the field, potential opportunities for future investigation, and outline a vision for integrating multiplexed genetic perturbations with detailed molecular analyses to advance our understanding of the genetic and molecular basis of cancer.
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Affiliation(s)
- Yuning J Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Emily G Shuldiner
- Department of Biology, Stanford University, Stanford, California 94305, USA
| | - Saswati Karmakar
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Monte M Winslow
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA
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56
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Tian H, Davis HC, Wong-Campos JD, Park P, Fan LZ, Gmeiner B, Begum S, Werley CA, Borja GB, Upadhyay H, Shah H, Jacques J, Qi Y, Parot V, Deisseroth K, Cohen AE. Video-based pooled screening yields improved far-red genetically encoded voltage indicators. Nat Methods 2023; 20:1082-1094. [PMID: 36624211 PMCID: PMC10329731 DOI: 10.1038/s41592-022-01743-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023]
Abstract
Video-based screening of pooled libraries is a powerful approach for directed evolution of biosensors because it enables selection along multiple dimensions simultaneously from large libraries. Here we develop a screening platform, Photopick, which achieves precise phenotype-activated photoselection over a large field of view (2.3 × 2.3 mm, containing >103 cells, per shot). We used the Photopick platform to evolve archaerhodopsin-derived genetically encoded voltage indicators (GEVIs) with improved signal-to-noise ratio (QuasAr6a) and kinetics (QuasAr6b). These GEVIs gave improved signals in cultured neurons and in live mouse brains. By combining targeted in vivo optogenetic stimulation with high-precision voltage imaging, we characterized inhibitory synaptic coupling between individual cortical NDNF (neuron-derived neurotrophic factor) interneurons, and excitatory electrical synapses between individual hippocampal parvalbumin neurons. The QuasAr6 GEVIs are powerful tools for all-optical electrophysiology and the Photopick approach could be adapted to evolve a broad range of biosensors.
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Affiliation(s)
- He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hunter C Davis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - J David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Linlin Z Fan
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Benjamin Gmeiner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Shahinoor Begum
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | | | | | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Vicente Parot
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Karl Deisseroth
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
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57
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Schwartz M, Israel U, Wang XJ, Laubscher E, Yu C, Dilip R, Li Q, Mari J, Soro J, Yu K, Pradhan E, Ates A, Gallandt D, Barnowski R, Pao E, Van Valen D. Scaling biological discovery at the interface of deep learning and cellular imaging. Nat Methods 2023; 20:956-957. [PMID: 37434003 DOI: 10.1038/s41592-023-01931-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2023]
Affiliation(s)
- Morgan Schwartz
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Uriah Israel
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Xuefei Julie Wang
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Emily Laubscher
- Department of Chemistry, California Institute of Technology, Pasadena, CA, USA
| | - Changhua Yu
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Rohit Dilip
- Department of Computer Science, California Institute of Technology, Pasadena, CA, USA
| | - Qilin Li
- Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Joud Mari
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Johnathon Soro
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Kevin Yu
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Elora Pradhan
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Ada Ates
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Danielle Gallandt
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Ross Barnowski
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - Edward Pao
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA
| | - David Van Valen
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
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58
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Fei X, Huang J, Li F, Wang Y, Shao Z, Dong L, Wu Y, Li B, Zhang X, Lv B, Zhao Y, Weng Q, Chen K, Zhang M, Yang S, Zhang C, Zhang M, Li W, Ying S, Sun Q, Chen Z, Shen H. The Scap-SREBP1-S1P/S2P lipogenesis signal orchestrates the homeostasis and spatiotemporal activation of NF-κB. Cell Rep 2023; 42:112586. [PMID: 37267109 DOI: 10.1016/j.celrep.2023.112586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/05/2023] [Accepted: 05/16/2023] [Indexed: 06/04/2023] Open
Abstract
The nuclear factor κB (NF-κB) pathway plays essential roles in innate and adaptive immunity, but little is known how NF-κB signaling is compartmentalized and spatiotemporally activated in the cytoplasm. Here, we show that the lipogenesis signal cascade Scap-SREBP1-S1P/S2P orchestrates the homeostasis and spatiotemporal activation of NF-κB. SREBP cleavage-activating protein (Scap) and sterol regulatory element-binding protein 1 (SREBP1) form a super complex with inhibitors of NF-κB α (IκBα) to associate NF-κB close to the endoplasmic reticulum (ER). Upon lipopolysaccharide (LPS) stimulation, Scap transports the complex to the Golgi apparatus, where SREBP1 is cleaved by site-1 protease (S1P)/S2P, liberating IκBα for IκB kinase (Ikk)-mediated phosphorylation and subsequent activation of NF-κB. Loss of Scap or inhibition of S1P or S2P diminishes, while SREBP1 deficiency augments, LPS-induced NF-κB activation and subsequent inflammatory responses. Our results reveal the Scap-SREBP1 complex as an additional cytoplasmic checkpoint for NF-κB homeostasis and unveil the Golgi apparatus as the optimal cellular platform for NF-κB activation, providing insights into the crosstalk between lipogenesis signaling and immunity.
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Affiliation(s)
- Xia Fei
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China; Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Jiaqi Huang
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Fei Li
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yuejue Wang
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Zhehua Shao
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Lingling Dong
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yinfang Wu
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Boran Li
- Department of Biochemistry, Department of Cardiology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xue Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Baihui Lv
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Yun Zhao
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Qingyu Weng
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Kaijun Chen
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Min Zhang
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Shiyi Yang
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Chao Zhang
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Min Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Wen Li
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Songmin Ying
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Qiming Sun
- Department of Biochemistry, Department of Cardiology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
| | - Zhihua Chen
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
| | - Huahao Shen
- Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China; State Key Lab for Respiratory Diseases, National Clinical Research Centre for Respiratory Disease, Guangzhou, Guangdong 510120, China.
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59
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Tian L, Chen F, Macosko EZ. The expanding vistas of spatial transcriptomics. Nat Biotechnol 2023; 41:773-782. [PMID: 36192637 PMCID: PMC10091579 DOI: 10.1038/s41587-022-01448-2] [Citation(s) in RCA: 109] [Impact Index Per Article: 109.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/26/2022] [Indexed: 11/09/2022]
Abstract
The formation and maintenance of tissue integrity requires complex, coordinated activities by thousands of genes and their encoded products. Until recently, transcript levels could only be quantified for a few genes in tissues, but advances in DNA sequencing, oligonucleotide synthesis and fluorescence microscopy have enabled the invention of a suite of spatial transcriptomics technologies capable of measuring the expression of many, or all, genes in situ. These technologies have evolved rapidly in sensitivity, multiplexing and throughput. As such, they have enabled the determination of the cell-type architecture of tissues, the querying of cell-cell interactions and the monitoring of molecular interactions between tissue components. The rapidly evolving spatial genomics landscape will enable generalized high-throughput genomic measurements and perturbations to be performed in the context of tissues. These advances will empower hypothesis generation and biological discovery and bridge the worlds of tissue biology and genomics.
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Affiliation(s)
- Luyi Tian
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Harvard Stem Cell and Regenerative Biology, Cambridge, MA, USA.
| | - Evan Z Macosko
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
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60
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Kalamakis G, Platt RJ. CRISPR for neuroscientists. Neuron 2023:S0896-6273(23)00306-9. [PMID: 37201524 DOI: 10.1016/j.neuron.2023.04.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 03/14/2023] [Accepted: 04/18/2023] [Indexed: 05/20/2023]
Abstract
Genome engineering technologies provide an entry point into understanding and controlling the function of genetic elements in health and disease. The discovery and development of the microbial defense system CRISPR-Cas yielded a treasure trove of genome engineering technologies and revolutionized the biomedical sciences. Comprising diverse RNA-guided enzymes and effector proteins that evolved or were engineered to manipulate nucleic acids and cellular processes, the CRISPR toolbox provides precise control over biology. Virtually all biological systems are amenable to genome engineering-from cancer cells to the brains of model organisms to human patients-galvanizing research and innovation and giving rise to fundamental insights into health and powerful strategies for detecting and correcting disease. In the field of neuroscience, these tools are being leveraged across a wide range of applications, including engineering traditional and non-traditional transgenic animal models, modeling disease, testing genomic therapies, unbiased screening, programming cell states, and recording cellular lineages and other biological processes. In this primer, we describe the development and applications of CRISPR technologies while highlighting outstanding limitations and opportunities.
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Affiliation(s)
- Georgios Kalamakis
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland; Novartis Institutes for BioMedical Research, 4056 Basel, Switzerland
| | - Randall J Platt
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland; Department of Chemistry, University of Basel, Petersplatz 1, 4003 Basel, Switzerland; NCCR MSE, Mattenstrasse 24a, 4058 Basel, Switzerland; Botnar Research Center for Child Health, Mattenstrasse 24a, 4058 Basel, Switzerland.
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61
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Pan C, Qi Y. CRISPR-Combo-mediated orthogonal genome editing and transcriptional activation for plant breeding. Nat Protoc 2023:10.1038/s41596-023-00823-w. [PMID: 37085666 DOI: 10.1038/s41596-023-00823-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 02/09/2023] [Indexed: 04/23/2023]
Abstract
CRISPR-Cas nuclease systems, base editors, and CRISPR activation have greatly advanced plant genome engineering. However, the combinatorial approaches for multiplexed orthogonal genome editing and transcriptional regulation were previously unexploited in plants. We have recently established a single Cas9 protein-based CRISPR-Combo platform, enabling efficient multiplexed orthogonal genome editing (double-strand break-mediated genome editing or base editing) and transcriptional activation in plants via engineering the single guide RNA (sgRNA) structure. Here, we provide step-by-step instructions for constructing CRISPR-Combo systems for speed breeding of transgene-free, genome-edited Arabidopsis plants and enhancing rice regeneration with more heritable targeted mutations in a hormone-free manner. We also provide guidance on designing efficient sgRNA, Agrobacterium-mediated transformation of Arabidopsis and rice, rice regeneration without exogenous plant hormones, gene editing evaluation and visual identification of transgene-free Arabidopsis plants with high editing activity. With the use of this protocol, it takes ~2 weeks to establish the CRISPR-Combo systems, 4 months to obtain transgene-free genome-edited Arabidopsis plants and 4 months to obtain rice plants with enrichment of heritable targeted mutations by hormone-free tissue culture.
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Affiliation(s)
- Changtian Pan
- Department of Horticulture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, USA.
| | - Yiping Qi
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, USA.
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA.
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62
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Lutz ID, Wang S, Norn C, Courbet A, Borst AJ, Zhao YT, Dosey A, Cao L, Xu J, Leaf EM, Treichel C, Litvicov P, Li Z, Goodson AD, Rivera-Sánchez P, Bratovianu AM, Baek M, King NP, Ruohola-Baker H, Baker D. Top-down design of protein architectures with reinforcement learning. Science 2023; 380:266-273. [PMID: 37079676 DOI: 10.1126/science.adf6591] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 03/21/2023] [Indexed: 04/22/2023]
Abstract
As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a "top-down" reinforcement learning-based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo-electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
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Affiliation(s)
- Isaac D Lutz
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Shunzhi Wang
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Christoffer Norn
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- BioInnovation Institute, DK2200 Copenhagen N, Denmark
| | - Alexis Courbet
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Andrew J Borst
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Yan Ting Zhao
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
- Oral Health Sciences, University of Washington, Seattle, WA, USA
| | - Annie Dosey
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Longxing Cao
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Jinwei Xu
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Elizabeth M Leaf
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Catherine Treichel
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Patrisia Litvicov
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Zhe Li
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Alexander D Goodson
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | | | | | - Minkyung Baek
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
| | - Neil P King
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Hannele Ruohola-Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
- Oral Health Sciences, University of Washington, Seattle, WA, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
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63
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Carlson RJ, Leiken MD, Guna A, Hacohen N, Blainey PC. A genome-wide optical pooled screen reveals regulators of cellular antiviral responses. Proc Natl Acad Sci U S A 2023; 120:e2210623120. [PMID: 37043539 PMCID: PMC10120039 DOI: 10.1073/pnas.2210623120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/06/2023] [Indexed: 04/13/2023] Open
Abstract
The infection of mammalian cells by viruses and innate immune responses to infection are spatiotemporally organized processes. Cytosolic RNA sensors trigger nuclear translocation of the transcription factor interferon regulatory factor 3 (IRF3) and consequent induction of host immune responses to RNA viruses. Previous genetic screens for factors involved in viral sensing did not resolve changes in the subcellular localization of host or viral proteins. Here, we increased the throughput of our optical pooled screening technology by over fourfold. This allowed us to carry out a genome-wide CRISPR knockout screen using high-resolution multiparameter imaging of cellular responses to Sendai virus infection coupled with in situ cDNA sequencing by synthesis (SBS) to identify 80,408 single guide RNAs (sgRNAs) in 10,366,390 cells-over an order of magnitude more genomic perturbations than demonstrated previously using an in situ SBS readout. By ranking perturbations using human-designed and deep learning image feature scores, we identified regulators of IRF3 translocation, Sendai virus localization, and peroxisomal biogenesis. Among the hits, we found that ATP13A1, an ER-localized P5A-type ATPase, is essential for viral sensing and is required for targeting of mitochondrial antiviral signaling protein (MAVS) to mitochondrial membranes where MAVS must be localized for effective signaling through retinoic acid-inducible gene I (RIG-I). The ability to carry out genome-wide pooled screens with complex high-resolution image-based phenotyping dramatically expands the scope of functional genomics approaches.
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Affiliation(s)
- Rebecca J. Carlson
- Department of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA02139
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA02142
| | - Michael D. Leiken
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA02142
| | | | - Nir Hacohen
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA02142
- Center for Cancer Research, Massachusetts General Hospital, Boston, MA02114
| | - Paul C. Blainey
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA02142
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
- Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA02139
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64
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Ahmed M, Muffat J, Li Y. Understanding neural development and diseases using CRISPR screens in human pluripotent stem cell-derived cultures. Front Cell Dev Biol 2023; 11:1158373. [PMID: 37101616 PMCID: PMC10123288 DOI: 10.3389/fcell.2023.1158373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/30/2023] [Indexed: 04/28/2023] Open
Abstract
The brain is arguably the most complex part of the human body in form and function. Much remains unclear about the molecular mechanisms that regulate its normal and pathological physiology. This lack of knowledge largely stems from the inaccessible nature of the human brain, and the limitation of animal models. As a result, brain disorders are difficult to understand and even more difficult to treat. Recent advances in generating human pluripotent stem cells (hPSCs)-derived 2-dimensional (2D) and 3-dimensional (3D) neural cultures have provided an accessible system to model the human brain. Breakthroughs in gene editing technologies such as CRISPR/Cas9 further elevate the hPSCs into a genetically tractable experimental system. Powerful genetic screens, previously reserved for model organisms and transformed cell lines, can now be performed in human neural cells. Combined with the rapidly expanding single-cell genomics toolkit, these technological advances culminate to create an unprecedented opportunity to study the human brain using functional genomics. This review will summarize the current progress of applying CRISPR-based genetic screens in hPSCs-derived 2D neural cultures and 3D brain organoids. We will also evaluate the key technologies involved and discuss their related experimental considerations and future applications.
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Affiliation(s)
- Mai Ahmed
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Julien Muffat
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Yun Li
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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65
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She R, Fair T, Schaefer NK, Saunders RA, Pavlovic BJ, Weissman JS, Pollen AA. Comparative landscape of genetic dependencies in human and chimpanzee stem cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.19.533346. [PMID: 36993685 PMCID: PMC10055274 DOI: 10.1101/2023.03.19.533346] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Comparative studies of great apes provide a window into our evolutionary past, but the extent and identity of cellular differences that emerged during hominin evolution remain largely unexplored. We established a comparative loss-of-function approach to evaluate whether changes in human cells alter requirements for essential genes. By performing genome-wide CRISPR interference screens in human and chimpanzee pluripotent stem cells, we identified 75 genes with species-specific effects on cellular proliferation. These genes comprised coherent processes, including cell cycle progression and lysosomal signaling, which we determined to be human-derived by comparison with orangutan cells. Human-specific robustness to CDK2 and CCNE1 depletion persisted in neural progenitor cells, providing support for the G1-phase length hypothesis as a potential evolutionary mechanism in human brain expansion. Our findings demonstrate that evolutionary changes in human cells can reshape the landscape of essential genes and establish a platform for systematically uncovering latent cellular and molecular differences between species.
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Affiliation(s)
- Richard She
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- These authors contributed equally: Richard She, Tyler Fair
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
- These authors contributed equally: Richard She, Tyler Fair
| | - Nathan K. Schaefer
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Reuben A. Saunders
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Cellular and Molecular Pharmacology, University of California at San Francisco, San Francisco, CA, USA
| | - Bryan J. Pavlovic
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan S. Weissman
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute Technology, Cambridge 02142, MA
| | - Alex A. Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Lead contact
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66
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Schraivogel D, Steinmetz LM. Cell sorters see things more clearly now. Mol Syst Biol 2023; 19:e11254. [PMID: 36779527 PMCID: PMC9996229 DOI: 10.15252/msb.202211254] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 01/13/2023] [Indexed: 02/14/2023] Open
Abstract
Microscopy and fluorescence-activated cell sorting (FACS) are two of the most important tools for single-cell phenotyping in basic and biomedical research. Microscopy provides high-resolution snapshots of cell morphology and the inner workings of cells, while FACS isolates thousands of cells per second using simple parameters, such as the intensity of fluorescent protein labels. Recent technologies are now combining both methods to enable the fast isolation of cells with microscopic phenotypes of interest, thereby bridging a long-standing gap in the life sciences. In this Commentary, we discuss the technical advancements made by image-enabled cell sorting and highlight novel experimental strategies in functional genomics and single-cell research.
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Affiliation(s)
- Daniel Schraivogel
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Lars M Steinmetz
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.,Stanford Genome Technology Center, Palo Alto, CA, USA
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67
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Siu DMD, Lee KCM, Chung BMF, Wong JSJ, Zheng G, Tsia KK. Optofluidic imaging meets deep learning: from merging to emerging. LAB ON A CHIP 2023; 23:1011-1033. [PMID: 36601812 DOI: 10.1039/d2lc00813k] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microscopes now enables imaging over a range of spatial scales (from molecules to organisms) and temporal window (from microseconds to hours). On the other hand, the staggering diversity of DL algorithms has revolutionized image processing and analysis at the scale and complexity that were once inconceivable. Recognizing these exciting but overwhelming developments, we provide a timely review of their latest trends in the context of lab-on-a-chip imaging, or coined optofluidic imaging. More importantly, here we discuss the strengths and caveats of how to adopt, reinvent, and integrate these imaging techniques and DL algorithms in order to tailor different lab-on-a-chip applications. In particular, we highlight three areas where the latest advances in lab-on-a-chip imaging and DL can form unique synergisms: image formation, image analytics and intelligent image-guided autonomous lab-on-a-chip. Despite the on-going challenges, we anticipate that they will represent the next frontiers in lab-on-a-chip imaging that will spearhead new capabilities in advancing analytical chemistry research, accelerating biological discovery, and empowering new intelligent clinical applications.
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Affiliation(s)
- Dickson M D Siu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Kelvin C M Lee
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Bob M F Chung
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Justin S J Wong
- Conzeb Limited, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Guoan Zheng
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, USA
| | - Kevin K Tsia
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
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68
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Wong CH, Wingett SW, Qian C, Taliaferro JM, Ross-Thriepland D, Bullock SL. Genome-scale requirements for dynein-based trafficking revealed by a high-content arrayed CRISPR screen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.01.530592. [PMID: 36909483 PMCID: PMC10002790 DOI: 10.1101/2023.03.01.530592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
The cytoplasmic dynein-1 (dynein) motor plays a key role in cellular organisation by transporting a wide variety of cellular constituents towards the minus ends of microtubules. However, relatively little is known about how the biosynthesis, assembly and functional diversity of the motor is orchestrated. To address this issue, we have conducted an arrayed CRISPR loss-of-function screen in human cells using the distribution of dynein-tethered peroxisomes and early endosomes as readouts. From a guide RNA library targeting 18,253 genes, 195 validated hits were recovered and parsed into those impacting multiple dynein cargoes and those whose effects are restricted to a subset of cargoes. Clustering of high-dimensional phenotypic fingerprints generated from multiplexed images revealed co-functional genes involved in many cellular processes, including several candidate novel regulators of core dynein functions. Mechanistic analysis of one of these proteins, the RNA-binding protein SUGP1, provides evidence that it promotes cargo trafficking by sustaining functional expression of the dynein activator LIS1. Our dataset represents a rich source of new hypotheses for investigating microtubule-based transport, as well as several other aspects of cellular organisation that were captured by our high-content imaging.
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Affiliation(s)
- Chun Hao Wong
- Cell Biology Division, MRC Laboratory of Molecular Biology, Cambridge, CB2 0QH, UK
- Discovery Biology, Discovery Sciences, AstraZeneca, R&D, Cambridge, CB4 0WG, UK
- Current address: Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Steven W. Wingett
- Cell Biology Division, MRC Laboratory of Molecular Biology, Cambridge, CB2 0QH, UK
| | - Chen Qian
- Quantitative Biology, Discovery Sciences, AstraZeneca, R&D, Cambridge, CB4 0WG, UK
| | - J. Matthew Taliaferro
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Simon L. Bullock
- Cell Biology Division, MRC Laboratory of Molecular Biology, Cambridge, CB2 0QH, UK
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69
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Duran-Frigola M, Cigler M, Winter GE. Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence. J Am Chem Soc 2023; 145:2711-2732. [PMID: 36706315 PMCID: PMC9912273 DOI: 10.1021/jacs.2c11098] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Indexed: 01/28/2023]
Abstract
Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.
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Affiliation(s)
- Miquel Duran-Frigola
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria
- Ersilia
Open Source Initiative, 28 Belgrave Road, CB1 3DE, Cambridge, United Kingdom
| | - Marko Cigler
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria
| | - Georg E. Winter
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria
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70
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Huang S, Baskin JM. Adding a Chemical Biology Twist to CRISPR Screening. Isr J Chem 2023; 63:e202200056. [PMID: 37588264 PMCID: PMC10427134 DOI: 10.1002/ijch.202200056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Indexed: 11/09/2022]
Abstract
In less than a decade, CRISPR screening has revolutionized forward genetics and cell and molecular biology. Advances in screening technologies, including sgRNA libraries, Cas9-expressing cell lines, and streamlined sequencing pipelines, have democratized pooled CRISPR screens at genome-wide scale. Initially, many such screens were survival-based, identifying essential genes in physiological or perturbed processes. With the application of new chemical biology tools to CRISPR screening, the phenotypic space is no longer limited to live/dead selection or screening for levels of conventional fluorescent protein reporters. Further, the resolution has been increased from cell populations to single cells or even the subcellular level. We highlight advances in pooled CRISPR screening, powered by chemical biology, that have expanded phenotypic space, resolution, scope, and scalability as well as strengthened the CRISPR/Cas enzyme toolkit to enable biological hypothesis generation and discovery.
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Affiliation(s)
- Shiying Huang
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853 USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853 USA
| | - Jeremy M Baskin
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853 USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853 USA
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71
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Pan C, Li G, Bandyopadhyay A, Qi Y. Guide RNA library-based CRISPR screens in plants: opportunities and challenges. Curr Opin Biotechnol 2023; 79:102883. [PMID: 36603502 DOI: 10.1016/j.copbio.2022.102883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/21/2022] [Accepted: 12/08/2022] [Indexed: 01/04/2023]
Abstract
Next-generation sequencing technologies have revolutionized our ability to read sequence information at the genome and transcriptome levels in a high-throughput manner. However, genetic screening at a large or genomic scale remains challenging in plants. Recently, the RNA-guided CRISPR-Cas nucleases have been optimized for high-throughput functional genomic screens combined with guide RNA (gRNA) libraries in plants. This approach has shown great promise in facilitating genetic screening, directed evolution, and quantitative trait engineering. However, this technology is still in its infancy. In this short review, we describe the recent progress in gRNA library-based CRISPR screens in plants. We provide a critical assessment of the current approaches and emerging delivery methods for CRISPR screens. We also highlight the challenges and present future perspectives on CRISPR screens in plants.
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Affiliation(s)
- Changtian Pan
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD 20742, USA
| | - Gen Li
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD 20742, USA
| | | | - Yiping Qi
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD 20742, USA; Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA.
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72
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Cheng J, Lin G, Wang T, Wang Y, Guo W, Liao J, Yang P, Chen J, Shao X, Lu X, Zhu L, Wang Y, Fan X. Massively Parallel CRISPR-Based Genetic Perturbation Screening at Single-Cell Resolution. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2204484. [PMID: 36504444 PMCID: PMC9896079 DOI: 10.1002/advs.202204484] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/09/2022] [Indexed: 06/17/2023]
Abstract
The clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic screening has been demonstrated as a powerful approach for unbiased functional genomics research. Single-cell CRISPR screening (scCRISPR) techniques, which result from the combination of single-cell toolkits and CRISPR screening, allow dissecting regulatory networks in complex biological systems at unprecedented resolution. These methods allow cells to be perturbed en masse using a pooled CRISPR library, followed by high-content phenotyping. This is technically accomplished by annotating cells with sgRNA-specific barcodes or directly detectable sgRNAs. According to the integration of distinct single-cell technologies, these methods principally fall into four categories: scCRISPR with RNA-seq, scCRISPR with ATAC-seq, scCRISPR with proteome probing, and imaging-based scCRISPR. scCRISPR has deciphered genotype-phenotype relationships, genetic regulations, tumor biological issues, and neuropathological mechanisms. This review provides insight into the technical breakthrough of scCRISPR by systematically summarizing the advancements of various scCRISPR methodologies and analyzing their merits and limitations. In addition, an application-oriented approach guide is offered to meet researchers' individualized demands.
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Affiliation(s)
- Junyun Cheng
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Gaole Lin
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Tianhao Wang
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Yunzhu Wang
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Wenbo Guo
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Jie Liao
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Penghui Yang
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Jie Chen
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Xin Shao
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
| | - Xiaoyan Lu
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
- State Key Laboratory of Component‐Based Chinese MedicineInnovation Center in Zhejiang UniversityHangzhou310058China
- Jinhua Institute of Zhejiang UniversityJinhua321016China
| | - Ling Zhu
- The Save Sight InstituteFaculty of Medicine and Healththe University of SydneySydneyNSW2000Australia
| | - Yi Wang
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
- State Key Laboratory of Component‐Based Chinese MedicineInnovation Center in Zhejiang UniversityHangzhou310058China
- Future Health LaboratoryInnovation Center of Yangtze River DeltaZhejiang UniversityJiaxing314100China
| | - Xiaohui Fan
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhouZhejiang310058China
- State Key Laboratory of Component‐Based Chinese MedicineInnovation Center in Zhejiang UniversityHangzhou310058China
- Jinhua Institute of Zhejiang UniversityJinhua321016China
- The Save Sight InstituteFaculty of Medicine and Healththe University of SydneySydneyNSW2000Australia
- Future Health LaboratoryInnovation Center of Yangtze River DeltaZhejiang UniversityJiaxing314100China
- Westlake Laboratory of Life Sciences and BiomedicineHangzhou310024China
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73
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Mccauley KB, Kukreja K, Jaffe AB, Klein AM. A map of signaling responses in the human airway epithelium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.12.21.521460. [PMID: 36597531 PMCID: PMC9810218 DOI: 10.1101/2022.12.21.521460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Receptor-mediated signaling plays a central role in tissue regeneration, and it is dysregulated in disease. Here, we build a signaling-response map for a model regenerative human tissue: the airway epithelium. We analyzed the effect of 17 receptor-mediated signaling pathways on organotypic cultures to determine changes in abundance and phenotype of all epithelial cell types. This map recapitulates the gamut of known airway epithelial signaling responses to these pathways. It defines convergent states induced by multiple ligands and diverse, ligand-specific responses in basal-cell and secretory-cell metaplasia. We show that loss of canonical differentiation induced by multiple pathways is associated with cell cycle arrest, but that arrest is not sufficient to block differentiation. Using the signaling-response map, we show that a TGFB1-mediated response underlies specific aberrant cells found in multiple lung diseases and identify interferon responses in COVID-19 patient samples. Thus, we offer a framework enabling systematic evaluation of tissue signaling responses.
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Affiliation(s)
- Katherine B Mccauley
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Disease Area X, Respiratory Therapeutic Area, Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Kalki Kukreja
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Aron B Jaffe
- Disease Area X, Respiratory Therapeutic Area, Novartis Institutes for BioMedical Research, Cambridge, MA, USA
- Current address: Chroma Medicine, Boston, MA, USA
| | - Allon M Klein
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
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74
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Shi H, Doench JG, Chi H. CRISPR screens for functional interrogation of immunity. Nat Rev Immunol 2022:10.1038/s41577-022-00802-4. [DOI: 10.1038/s41577-022-00802-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2022] [Indexed: 12/13/2022]
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75
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Tabet D, Parikh V, Mali P, Roth FP, Claussnitzer M. Scalable Functional Assays for the Interpretation of Human Genetic Variation. Annu Rev Genet 2022; 56:441-465. [PMID: 36055970 DOI: 10.1146/annurev-genet-072920-032107] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.
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Affiliation(s)
- Daniel Tabet
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Victoria Parikh
- Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Prashant Mali
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Frederick P Roth
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Genomic Medicine and Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA;
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76
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Funk L, Su KC, Ly J, Feldman D, Singh A, Moodie B, Blainey PC, Cheeseman IM. The phenotypic landscape of essential human genes. Cell 2022; 185:4634-4653.e22. [PMID: 36347254 PMCID: PMC10482496 DOI: 10.1016/j.cell.2022.10.017] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/01/2022] [Accepted: 10/14/2022] [Indexed: 11/09/2022]
Abstract
Understanding the basis for cellular growth, proliferation, and function requires determining the roles of essential genes in diverse cellular processes, including visualizing their contributions to cellular organization and morphology. Here, we combined pooled CRISPR-Cas9-based functional screening of 5,072 fitness-conferring genes in human HeLa cells with microscopy-based imaging of DNA, the DNA damage response, actin, and microtubules. Analysis of >31 million individual cells identified measurable phenotypes for >90% of gene knockouts, implicating gene targets in specific cellular processes. Clustering of phenotypic similarities based on hundreds of quantitative parameters further revealed co-functional genes across diverse cellular activities, providing predictions for gene functions and associations. By conducting pooled live-cell screening of ∼450,000 cell division events for 239 genes, we additionally identified diverse genes with functional contributions to chromosome segregation. Our work establishes a resource detailing the consequences of disrupting core cellular processes that represents the functional landscape of essential human genes.
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Affiliation(s)
- Luke Funk
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA 02142, USA; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Kuan-Chung Su
- Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Jimmy Ly
- Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - David Feldman
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA 02142, USA
| | - Avtar Singh
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA 02142, USA
| | - Brittania Moodie
- Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Paul C Blainey
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA 02142, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA 02142, USA.
| | - Iain M Cheeseman
- Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
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77
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Holcomb EA, Pearson AN, Jungles KM, Tate A, James J, Jiang L, Huber AK, Green MD. High-content CRISPR screening in tumor immunology. Front Immunol 2022; 13:1041451. [PMID: 36479127 PMCID: PMC9721350 DOI: 10.3389/fimmu.2022.1041451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 10/21/2022] [Indexed: 11/22/2022] Open
Abstract
CRISPR screening is a powerful tool that links specific genetic alterations to corresponding phenotypes, thus allowing for high-throughput identification of novel gene functions. Pooled CRISPR screens have enabled discovery of innate and adaptive immune response regulators in the setting of viral infection and cancer. Emerging methods couple pooled CRISPR screens with parallel high-content readouts at the transcriptomic, epigenetic, proteomic, and optical levels. These approaches are illuminating cancer immune evasion mechanisms as well as nominating novel targets that augment T cell activation, increase T cell infiltration into tumors, and promote enhanced T cell cytotoxicity. This review details recent methodological advances in high-content CRISPR screens and highlights the impact this technology is having on tumor immunology.
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Affiliation(s)
- Erin A. Holcomb
- Graduate Program in Immunology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Ashley N. Pearson
- Graduate Program in Immunology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Kassidy M. Jungles
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Pharmacology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, United States
| | - Akshay Tate
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Jadyn James
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Long Jiang
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, China
| | - Amanda K. Huber
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Michael D. Green
- Graduate Program in Immunology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Radiation Oncology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, United States
- Department of Microbiology and Immunology, School of Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Radiation Oncology, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
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78
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Leng K, Kampmann M. Towards elucidating disease-relevant states of neurons and glia by CRISPR-based functional genomics. Genome Med 2022; 14:130. [PMID: 36401300 PMCID: PMC9673433 DOI: 10.1186/s13073-022-01134-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/02/2022] [Indexed: 11/19/2022] Open
Abstract
Our understanding of neurological diseases has been tremendously enhanced over the past decade by the application of new technologies. Genome-wide association studies have highlighted glial cells as important players in diseases. Single-cell profiling technologies are providing descriptions of disease states of neurons and glia at unprecedented molecular resolution. However, significant gaps remain in our understanding of the mechanisms driving disease-associated cell states, and how these states contribute to disease. These gaps in our understanding can be bridged by CRISPR-based functional genomics, a powerful approach to systematically interrogate gene function. In this review, we will briefly review the current literature on neurological disease-associated cell states and introduce CRISPR-based functional genomics. We discuss how advances in CRISPR-based screens, especially when implemented in the relevant brain cell types or cellular environments, have paved the way towards uncovering mechanisms underlying neurological disease-associated cell states. Finally, we will delineate current challenges and future directions for CRISPR-based functional genomics to further our understanding of neurological diseases and potential therapeutic strategies.
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Affiliation(s)
- Kun Leng
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA.
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
- Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
| | - Martin Kampmann
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA.
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
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79
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Hoberecht L, Perampalam P, Lun A, Fortin JP. A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies. Nat Commun 2022; 13:6568. [PMID: 36323688 PMCID: PMC9630310 DOI: 10.1038/s41467-022-34320-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
The success of CRISPR-mediated gene perturbation studies is highly dependent on the quality of gRNAs, and several tools have been developed to enable optimal gRNA design. However, these tools are not all adaptable to the latest CRISPR modalities or nucleases, nor do they offer comprehensive annotation methods for advanced CRISPR applications. Here, we present a new ecosystem of R packages, called crisprVerse, that enables efficient gRNA design and annotation for a multitude of CRISPR technologies. This includes CRISPR knockout (CRISPRko), CRISPR activation (CRISPRa), CRISPR interference (CRISPRi), CRISPR base editing (CRISPRbe) and CRISPR knockdown (CRISPRkd). The core package, crisprDesign, offers a user-friendly and unified interface to add off-target annotations, rich gene and SNP annotations, and on- and off-target activity scores. These functionalities are enabled for any RNA- or DNA-targeting nucleases, including Cas9, Cas12, and Cas13. The crisprVerse ecosystem is open-source and deployed through the Bioconductor project ( https://github.com/crisprVerse ).
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Affiliation(s)
- Luke Hoberecht
- Genentech Research and Early Development, Genentech, Inc., 1 DNA Way, South San Francisco, CA, 94080, USA
| | | | - Aaron Lun
- Genentech Research and Early Development, Genentech, Inc., 1 DNA Way, South San Francisco, CA, 94080, USA
| | - Jean-Philippe Fortin
- Genentech Research and Early Development, Genentech, Inc., 1 DNA Way, South San Francisco, CA, 94080, USA.
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80
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Walton RT, Singh A, Blainey PC. Pooled genetic screens with image-based profiling. Mol Syst Biol 2022; 18:e10768. [PMID: 36366905 PMCID: PMC9650298 DOI: 10.15252/msb.202110768] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 11/13/2022] Open
Abstract
Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.
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Affiliation(s)
- Russell T Walton
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
| | - Avtar Singh
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Present address:
Department of Cellular and Tissue GenomicsGenentechSouth San FranciscoCAUSA
| | - Paul C Blainey
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
- Koch Institute for Integrative Cancer ResearchMITCambridgeMAUSA
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81
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Yenkin AL, Bramley JC, Kremitzki CL, Waligorski JE, Liebeskind MJ, Xu XE, Chandrasekaran VD, Vakaki MA, Bachman GW, Mitra RD, Milbrandt JD, Buchser WJ. Pooled image-base screening of mitochondria with microraft isolation distinguishes pathogenic mitofusin 2 mutations. Commun Biol 2022; 5:1128. [PMID: 36284160 PMCID: PMC9596453 DOI: 10.1038/s42003-022-04089-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 10/11/2022] [Indexed: 11/08/2022] Open
Abstract
Most human genetic variation is classified as variants of uncertain significance. While advances in genome editing have allowed innovation in pooled screening platforms, many screens deal with relatively simple readouts (viability, fluorescence) and cannot identify the complex cellular phenotypes that underlie most human diseases. In this paper, we present a generalizable functional genomics platform that combines high-content imaging, machine learning, and microraft isolation in a method termed "Raft-Seq". We highlight the efficacy of our platform by showing its ability to distinguish pathogenic point mutations of the mitochondrial regulator Mitofusin 2, even when the cellular phenotype is subtle. We also show that our platform achieves its efficacy using multiple cellular features, which can be configured on-the-fly. Raft-Seq enables a way to perform pooled screening on sets of mutations in biologically relevant cells, with the ability to physically capture any cell with a perturbed phenotype and expand it clonally, directly from the primary screen.
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Affiliation(s)
- Alex L Yenkin
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - John C Bramley
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Colin L Kremitzki
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Jason E Waligorski
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Mariel J Liebeskind
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Xinyuan E Xu
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Vinay D Chandrasekaran
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Maria A Vakaki
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Graham W Bachman
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Robi D Mitra
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - Jeffrey D Milbrandt
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA
| | - William J Buchser
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA.
- Functional Imaging for Variant Elucidation at the McDonnell Genome Institute, St Louis, MO, USA.
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82
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Cooper YA, Guo Q, Geschwind DH. Multiplexed functional genomic assays to decipher the noncoding genome. Hum Mol Genet 2022; 31:R84-R96. [PMID: 36057282 PMCID: PMC9585676 DOI: 10.1093/hmg/ddac194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 11/14/2022] Open
Abstract
Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.
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Affiliation(s)
- Yonatan A Cooper
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Qiuyu Guo
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California Los Angeles, Los Angeles, CA, USA
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83
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Jones IR, Ren X, Shen Y. High-throughput CRISPRi and CRISPRa technologies in 3D genome regulation for neuropsychiatric diseases. Hum Mol Genet 2022; 31:R47-R53. [PMID: 35972825 PMCID: PMC9585669 DOI: 10.1093/hmg/ddac193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/05/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Advances in genomics have led to the identification of many risk loci with hundreds of genes and thousands of DNA variants associated with neuropsychiatric disorders. A significant barrier to understanding the genetic underpinnings of complex diseases is the lack of functional characterization of risk genes and variants in biological systems relevant to human health and connecting disease-associated variants to pathological phenotypes. Characterizing gene and DNA variant functions requires genetic perturbations followed by molecular and cellular assays of neurobiological phenotypes. However, generating null or mutant alleles is low throughput, making it impossible to characterize disease-associated variants in large quantities efficiently. CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) screens can be leveraged to dissect the biological consequences of the tested genes and variants in their native context. Nevertheless, testing non-coding variants associated with complex diseases remains non-trivial. In this review, we first discuss the current challenges of interpreting the function of the non-coding genome and approaches to prioritizing disease-associated variants in the context of the 3D epigenome. Second, we provide a brief overview of high-throughput CRISPRi and CRISPRa screening strategies applicable for characterizing non-coding sequences in appropriate biological systems. Lastly, we discuss the promising prospects of using CRISPR-based technologies to dissect DNA sequences associated with neuropsychiatric diseases.
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Affiliation(s)
- Ian R Jones
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Xingjie Ren
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
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84
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Nowakowski TJ, Salama SR. Cerebral Organoids as an Experimental Platform for Human Neurogenomics. Cells 2022; 11:2803. [PMID: 36139380 PMCID: PMC9496777 DOI: 10.3390/cells11182803] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 01/25/2023] Open
Abstract
The cerebral cortex forms early in development according to a series of heritable neurodevelopmental instructions. Despite deep evolutionary conservation of the cerebral cortex and its foundational six-layered architecture, significant variations in cortical size and folding can be found across mammals, including a disproportionate expansion of the prefrontal cortex in humans. Yet our mechanistic understanding of neurodevelopmental processes is derived overwhelmingly from rodent models, which fail to capture many human-enriched features of cortical development. With the advent of pluripotent stem cells and technologies for differentiating three-dimensional cultures of neural tissue in vitro, cerebral organoids have emerged as an experimental platform that recapitulates several hallmarks of human brain development. In this review, we discuss the merits and limitations of cerebral organoids as experimental models of the developing human brain. We highlight innovations in technology development that seek to increase its fidelity to brain development in vivo and discuss recent efforts to use cerebral organoids to study regeneration and brain evolution as well as to develop neurological and neuropsychiatric disease models.
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Affiliation(s)
- Tomasz J. Nowakowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94158, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94158, USA
| | - Sofie R. Salama
- Department of Molecular, Cellular and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA 95060, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
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85
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Nishiga M, Liu C, Qi LS, Wu JC. The use of new CRISPR tools in cardiovascular research and medicine. Nat Rev Cardiol 2022; 19:505-521. [PMID: 35145236 PMCID: PMC10283450 DOI: 10.1038/s41569-021-00669-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2021] [Indexed: 02/07/2023]
Abstract
Many novel CRISPR-based genome-editing tools, with a wide variety of applications, have been developed in the past few years. The original CRISPR-Cas9 system was developed as a tool to alter genomic sequences in living organisms in a simple way. However, the functions of new CRISPR tools are not limited to conventional genome editing mediated by non-homologous end-joining or homology-directed repair but expand into gene-expression control, epigenome editing, single-nucleotide editing, RNA editing and live-cell imaging. Furthermore, genetic perturbation screening by multiplexing guide RNAs is gaining popularity as a method to identify causative genes and pathways in an unbiased manner. New CRISPR tools can also be applied to ex vivo or in vivo therapeutic genome editing for the treatment of conditions such as hyperlipidaemia. In this Review, we first provide an overview of the diverse new CRISPR tools that have been developed to date. Second, we summarize how these new CRISPR tools are being used to study biological processes and disease mechanisms in cardiovascular research and medicine. Finally, we discuss the prospect of therapeutic genome editing by CRISPR tools to cure genetic cardiovascular diseases.
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Affiliation(s)
- Masataka Nishiga
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA.
| | - Chun Liu
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Lei S Qi
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Chemical & Systems Biology, Stanford University, Stanford, CA, USA
- ChEM-H Institute, Stanford University, Stanford, CA, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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86
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Moffitt JR, Lundberg E, Heyn H. The emerging landscape of spatial profiling technologies. Nat Rev Genet 2022; 23:741-759. [PMID: 35859028 DOI: 10.1038/s41576-022-00515-3] [Citation(s) in RCA: 143] [Impact Index Per Article: 71.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/16/2022] [Indexed: 01/04/2023]
Abstract
Improved scale, multiplexing and resolution are establishing spatial nucleic acid and protein profiling methods as a major pillar for cellular atlas building of complex samples, from tissues to full organisms. Emerging methods yield omics measurements at resolutions covering the nano- to microscale, enabling the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease. We present an overview of the developing landscape of in situ spatial genome, transcriptome and proteome technologies, exemplify their impact on cell biology and translational research, and discuss current challenges for their community-wide adoption. Among many transformative applications, we envision that spatial methods will map entire organs and enable next-generation pathology.
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Affiliation(s)
- Jeffrey R Moffitt
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA.,Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.,Department of Bioengineering, Stanford University, Stanford, CA, USA.,Department of Pathology, Stanford University, Stanford, CA, USA.,Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | - Holger Heyn
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
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87
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Replogle JM, Saunders RA, Pogson AN, Hussmann JA, Lenail A, Guna A, Mascibroda L, Wagner EJ, Adelman K, Lithwick-Yanai G, Iremadze N, Oberstrass F, Lipson D, Bonnar JL, Jost M, Norman TM, Weissman JS. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell 2022; 185:2559-2575.e28. [PMID: 35688146 PMCID: PMC9380471 DOI: 10.1016/j.cell.2022.05.013] [Citation(s) in RCA: 183] [Impact Index Per Article: 91.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/07/2022] [Accepted: 05/16/2022] [Indexed: 11/23/2022]
Abstract
A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena-from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function.
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Affiliation(s)
- Joseph M Replogle
- Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA 94158, USA; Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Reuben A Saunders
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Angela N Pogson
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Jeffrey A Hussmann
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Alexander Lenail
- Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Alina Guna
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Lauren Mascibroda
- Department of Biochemistry & Molecular Biology, The University of Texas Medical Branch at Galveston, Galveston, TX 77555, USA
| | - Eric J Wagner
- Department of Biochemistry & Molecular Biology, The University of Texas Medical Branch at Galveston, Galveston, TX 77555, USA; Department of Biochemistry & Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Karen Adelman
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | | | | | | | | | - Jessica L Bonnar
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Marco Jost
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA
| | - Thomas M Norman
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
| | - Jonathan S Weissman
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
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88
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Kizilirmak C, Bianchi ME, Zambrano S. Insights on the NF-κB System Using Live Cell Imaging: Recent Developments and Future Perspectives. Front Immunol 2022; 13:886127. [PMID: 35844496 PMCID: PMC9277462 DOI: 10.3389/fimmu.2022.886127] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/25/2022] [Indexed: 11/29/2022] Open
Abstract
The transcription factor family of nuclear factor kappa B (NF-κB) proteins is widely recognized as a key player in inflammation and the immune responses, where it plays a fundamental role in translating external inflammatory cues into precise transcriptional programs, including the timely expression of a wide variety of cytokines/chemokines. Live cell imaging in single cells showed approximately 15 years ago that the canonical activation of NF-κB upon stimulus is very dynamic, including oscillations of its nuclear localization with a period close to 1.5 hours. This observation has triggered a fruitful interdisciplinary research line that has provided novel insights on the NF-κB system: how its heterogeneous response differs between cell types but also within homogeneous populations; how NF-κB dynamics translate external cues into intracellular signals and how NF-κB dynamics affects gene expression. Here we review the main features of this live cell imaging approach to the study of NF-κB, highlighting the key findings, the existing gaps of knowledge and hinting towards some of the potential future steps of this thriving research field.
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Affiliation(s)
- Cise Kizilirmak
- School of Medicine, Vita-Salute San Raffaele University, Milan, Italy
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco E. Bianchi
- School of Medicine, Vita-Salute San Raffaele University, Milan, Italy
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Samuel Zambrano
- School of Medicine, Vita-Salute San Raffaele University, Milan, Italy
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
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89
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CRISPR screening in cancer stem cells. Essays Biochem 2022; 66:305-318. [PMID: 35713228 DOI: 10.1042/ebc20220009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/04/2022] [Accepted: 06/07/2022] [Indexed: 12/14/2022]
Abstract
Cancer stem cells (CSCs) are a subpopulation of tumor cells with self-renewal ability. Increasing evidence points to the critical roles of CSCs in tumorigenesis, metastasis, therapy resistance, and cancer relapse. As such, the elimination of CSCs improves cancer treatment outcomes. However, challenges remain due to limited understanding of the molecular mechanisms governing self-renewal and survival of CSCs. Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screening has been increasingly used to identify genetic determinants in cancers. In this primer, we discuss the progress made and emerging opportunities of coupling advanced CRISPR screening systems with CSC models to reveal the understudied vulnerabilities of CSCs.
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90
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Le P, Ahmed N, Yeo GW. Illuminating RNA biology through imaging. Nat Cell Biol 2022; 24:815-824. [PMID: 35697782 PMCID: PMC11132331 DOI: 10.1038/s41556-022-00933-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 05/06/2022] [Indexed: 12/14/2022]
Abstract
RNA processing plays a central role in accurately transmitting genetic information into functional RNA and protein regulators. To fully appreciate the RNA life-cycle, tools to observe RNA with high spatial and temporal resolution are critical. Here we review recent advances in RNA imaging and highlight how they will propel the field of RNA biology. We discuss current trends in RNA imaging and their potential to elucidate unanswered questions in RNA biology.
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Affiliation(s)
- Phuong Le
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Noorsher Ahmed
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
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91
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Albers JJ, Pelka K. Listening in on Multicellular Communication in Human Tissue Immunology. Front Immunol 2022; 13:884185. [PMID: 35634333 PMCID: PMC9136009 DOI: 10.3389/fimmu.2022.884185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
Immune responses in human tissues rely on the concerted action of different cell types. Inter-cellular communication shapes both the function of the multicellular interaction networks and the fate of the individual cells that comprise them. With the advent of new methods to profile and experimentally perturb primary human tissues, we are now in a position to systematically identify and mechanistically dissect these cell-cell interactions and their modulators. Here, we introduce the concept of multicellular hubs, functional modules of immune responses in tissues. We outline a roadmap to discover multicellular hubs in human tissues and discuss how emerging technologies may further accelerate progress in this field.
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Affiliation(s)
- Julian J. Albers
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, United States
- Department of Medicine III, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Karin Pelka
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, United States
- Gladstone-University of California San Francisco (UCSF) Institute of Genomic Immunology, Gladstone Institutes, San Francisco, CA, United States
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92
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Affiliation(s)
- Andrew Filby
- From the Innovation, Methodology, and Application Research Theme, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom (A.F.); and the Broad Institute of MIT and Harvard, Cambridge, MA (A.E.C.)
| | - Anne E Carpenter
- From the Innovation, Methodology, and Application Research Theme, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom (A.F.); and the Broad Institute of MIT and Harvard, Cambridge, MA (A.E.C.)
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93
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LaFleur MW, Sharpe AH. CRISPR Screens to Identify Regulators of Tumor Immunity. ANNUAL REVIEW OF CANCER BIOLOGY 2022; 6:103-122. [PMID: 35989706 PMCID: PMC9389862 DOI: 10.1146/annurev-cancerbio-070120-094725] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cancer immunotherapies, such as immune checkpoint blockade (ICB), have been used in a wide range of tumor types with immense clinical benefit. However, ICB does not work in all patients, and attempts to combine ICB with other immune-based therapies have not lived up to their initial promise. Thus, there is a significant unmet need to discover new targets and combination therapies to extend the benefits of immunotherapy to more patients. Systems biology approaches are well suited for addressing this problem because these approaches enable evaluation of many gene targets simultaneously and ranking their relative importance for a phenotype of interest. As such, loss-of-function CRISPR screens are an emerging set of tools being used to prioritize gene targets for modulating pathways of interest in tumor and immune cells. This review describes the first screens performed to discover cancer immunotherapy targets and the technological advances that will enable next-generation screens.
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Affiliation(s)
- Martin W LaFleur
- Department of Immunology and Blavatnik Institute, Harvard Medical School, Boston, Massachusetts, USA
- Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Arlene H Sharpe
- Department of Immunology and Blavatnik Institute, Harvard Medical School, Boston, Massachusetts, USA
- Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA
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94
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Dhainaut M, Rose SA, Akturk G, Wroblewska A, Nielsen SR, Park ES, Buckup M, Roudko V, Pia L, Sweeney R, Le Berichel J, Wilk CM, Bektesevic A, Lee BH, Bhardwaj N, Rahman AH, Baccarini A, Gnjatic S, Pe'er D, Merad M, Brown BD. Spatial CRISPR genomics identifies regulators of the tumor microenvironment. Cell 2022; 185:1223-1239.e20. [PMID: 35290801 PMCID: PMC8992964 DOI: 10.1016/j.cell.2022.02.015] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 12/02/2021] [Accepted: 02/12/2022] [Indexed: 12/15/2022]
Abstract
While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying extracellular gene functions, particularly in the tissue context. Here, we developed an approach for spatial functional genomics called Perturb-map. We applied Perturb-map to knock out dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Moreover, we paired Perturb-map and spatial transcriptomics for unbiased analysis of CRISPR-edited tumors. We found that in Tgfbr2 knockout tumors, the tumor microenvironment (TME) was converted to a fibro-mucinous state, and T cells excluded, concomitant with upregulated TGFβ and TGFβ-mediated fibroblast activation, indicating that TGFβ-receptor loss on cancer cells increased TGFβ bioavailability and its immunosuppressive effects on the TME. These studies establish Perturb-map for functional genomics within the tissue at single-cell resolution with spatial architecture preserved and provide insight into how TGFβ responsiveness of cancer cells can affect the TME.
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Affiliation(s)
- Maxime Dhainaut
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Samuel A Rose
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Guray Akturk
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aleksandra Wroblewska
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sebastian R Nielsen
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eun Sook Park
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mark Buckup
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vladimir Roudko
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Luisanna Pia
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Sweeney
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica Le Berichel
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - C Matthias Wilk
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anela Bektesevic
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian H Lee
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nina Bhardwaj
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Adeeb H Rahman
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alessia Baccarini
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sacha Gnjatic
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dana Pe'er
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Miriam Merad
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center of Excellence for Thoracic Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian D Brown
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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95
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Bao F, Deng Y, Wan S, Shen SQ, Wang B, Dai Q, Altschuler SJ, Wu LF. Integrative spatial analysis of cell morphologies and transcriptional states with MUSE. Nat Biotechnol 2022; 40:1200-1209. [PMID: 35347329 DOI: 10.1038/s41587-022-01251-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 02/08/2022] [Indexed: 12/11/2022]
Abstract
Spatial transcriptomics enables the simultaneous measurement of morphological features and transcriptional profiles of the same cells or regions in tissues. Here we present multi-modal structured embedding (MUSE), an approach to characterize cells and tissue regions by integrating morphological and spatially resolved transcriptional data. We demonstrate that MUSE can discover tissue subpopulations missed by either modality as well as compensate for modality-specific noise. We apply MUSE to diverse datasets containing spatial transcriptomics (seqFISH+, STARmap or Visium) and imaging (hematoxylin and eosin or fluorescence microscopy) modalities. MUSE identified biologically meaningful tissue subpopulations and stereotyped spatial patterning in healthy brain cortex and intestinal tissues. In diseased tissues, MUSE revealed gene biomarkers for proximity to tumor region and heterogeneity of amyloid precursor protein processing across Alzheimer brain regions. MUSE enables the integration of multi-modal data to provide insights into the states, functions and organization of cells in complex biological tissues.
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Affiliation(s)
- Feng Bao
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Yue Deng
- School of Astronautics, Beihang University, Beijing, China.,Institute of Artificial Intelligence, Beihang University, Beijing, China
| | - Sen Wan
- Department of Automation and Institute for Brain and Cognitive Science, Tsinghua University, Beijing, China
| | - Susan Q Shen
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.,Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Bo Wang
- School of Astronautics, Beihang University, Beijing, China
| | - Qionghai Dai
- Department of Automation and Institute for Brain and Cognitive Science, Tsinghua University, Beijing, China. .,Beijing National Research Center for Information Science and Technology, Beijing, China. .,Beijing Laboratory of Brain and Cognitive Intelligence and Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Beijing, China.
| | - Steven J Altschuler
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.
| | - Lani F Wu
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.
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96
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A multiplexed epitope barcoding strategy that enables dynamic cellular phenotypic screens. Cell Syst 2022; 13:376-387.e8. [PMID: 35316656 DOI: 10.1016/j.cels.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 09/27/2021] [Accepted: 02/25/2022] [Indexed: 12/16/2022]
Abstract
Pooled genetic libraries have improved screening throughput for mapping genotypes to phenotypes. However, selectable phenotypes are limited, restricting screening to outcomes with a low spatiotemporal resolution. Here, we integrated live-cell imaging with pooled library-based screening. To enable intracellular multiplexing, we developed a method called EPICode that uses a combination of short epitopes, which can also appear in various subcellular locations. EPICode thus enables the use of live-cell microscopy to characterize a phenotype of interest over time, including after sequential stimulatory/inhibitory manipulations, and directly connects behavior to the cellular genotype. To test EPICode's capacity against an important milestone-engineering and optimizing dynamic, live-cell reporters-we developed a live-cell PKA kinase translocation reporter with improved sensitivity and specificity. The use of epitopes as fluorescent barcodes introduces a scalable strategy for high-throughput screening broadly applicable to protein engineering and drug discovery settings where image-based phenotyping is desired.
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97
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Dong MB, Tang K, Zhou X, Zhou JJ, Chen S. Tumor immunology CRISPR screening: present, past, and future. Trends Cancer 2022; 8:210-225. [PMID: 34920978 PMCID: PMC8854335 DOI: 10.1016/j.trecan.2021.11.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/21/2021] [Accepted: 11/22/2021] [Indexed: 02/08/2023]
Abstract
Recent advances in immunotherapy have fundamentally changed the landscape of cancer treatment by leveraging the specificity and selectivity of the adaptive immune system to kill cancer cells. These successes have ushered in a new wave of research aimed at understanding immune recognition with the hope of developing newer immunotherapies. The advent of clustered regularly interspaced short palindromic repeats (CRISPR) technologies and advancement of multiomics modalities have greatly accelerated the discovery process. Here, we review the current literature surrounding CRISPR screens within the context of tumor immunology, provide essential components needed to conduct immune-specific CRISPR screens, and present avenues for future research.
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Affiliation(s)
- Matthew B. Dong
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA,System Biology Institute, Yale University, West Haven, CT, USA,Center for Cancer Systems Biology, Yale University, West Haven, CT, USA,Immunobiology Program, Yale University, New Haven, CT, USA,Department of Immunobiology, Yale University, New Haven, CT, USA,M.D.-Ph.D. Program, Yale University, West Haven, CT, USA
| | - Kaiyuan Tang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA,System Biology Institute, Yale University, West Haven, CT, USA,Center for Cancer Systems Biology, Yale University, West Haven, CT, USA,Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA
| | - Xiaoyu Zhou
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA,System Biology Institute, Yale University, West Haven, CT, USA,Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Jingjia J. Zhou
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA,System Biology Institute, Yale University, West Haven, CT, USA,Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Sidi Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; System Biology Institute, Yale University, West Haven, CT, USA; Center for Cancer Systems Biology, Yale University, West Haven, CT, USA; Immunobiology Program, Yale University, New Haven, CT, USA; M.D.-Ph.D. Program, Yale University, West Haven, CT, USA; Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA; Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA; Yale Comprehensive Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT, USA; Yale Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA.
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98
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Bock C, Datlinger P, Chardon F, Coelho MA, Dong MB, Lawson KA, Lu T, Maroc L, Norman TM, Song B, Stanley G, Chen S, Garnett M, Li W, Moffat J, Qi LS, Shapiro RS, Shendure J, Weissman JS, Zhuang X. High-content CRISPR screening. NATURE REVIEWS. METHODS PRIMERS 2022; 2:9. [PMID: 37214176 PMCID: PMC10200264 DOI: 10.1038/s43586-022-00098-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
CRISPR screens are a powerful source of biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications and species. In pooled CRISPR screens, various genetically encoded perturbations are introduced into pools of cells. The targeted cells proliferate under a biological challenge such as cell competition, drug treatment or viral infection. Subsequently, the perturbation-induced effects are evaluated by sequencing-based counting of the guide RNAs that specify each perturbation. The typical results of such screens are ranked lists of genes that confer sensitivity or resistance to the biological challenge of interest. Contributing to the broad utility of CRISPR screens, adaptations of the core CRISPR technology make it possible to activate, silence or otherwise manipulate the target genes. Moreover, high-content read-outs such as single-cell RNA sequencing and spatial imaging help characterize screened cells with unprecedented detail. Dedicated software tools facilitate bioinformatic analysis and enhance reproducibility. CRISPR screening has unravelled various molecular mechanisms in basic biology, medical genetics, cancer research, immunology, infectious diseases, microbiology and other fields. This Primer describes the basic and advanced concepts of CRISPR screening and its application as a flexible and reliable method for biological discovery, biomedical research and drug development - with a special emphasis on high-content methods that make it possible to obtain detailed biological insights directly as part of the screen.
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Affiliation(s)
- Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Paul Datlinger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Florence Chardon
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Matthew B. Dong
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Systems Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Keith A. Lawson
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Tian Lu
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Laetitia Maroc
- Department of Molecular and Cellular Biology, University of Guelph, Guelph, Ontario, Canada
| | - Thomas M. Norman
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, CA, USA
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Bicna Song
- Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC, USA
- Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA
| | - Geoff Stanley
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sidi Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Systems Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Mathew Garnett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Wei Li
- Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC, USA
- Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA
| | - Jason Moffat
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Institute for Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Lei S. Qi
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA
- ChEM-H, Stanford University, Stanford, CA, USA
| | - Rebecca S. Shapiro
- Department of Molecular and Cellular Biology, University of Guelph, Guelph, Ontario, Canada
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Jonathan S. Weissman
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, CA, USA
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
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99
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Spatial components of molecular tissue biology. Nat Biotechnol 2022; 40:308-318. [PMID: 35132261 DOI: 10.1038/s41587-021-01182-1] [Citation(s) in RCA: 109] [Impact Index Per Article: 54.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 12/03/2021] [Indexed: 02/06/2023]
Abstract
Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics.
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100
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Feldman D, Funk L, Le A, Carlson RJ, Leiken MD, Tsai F, Soong B, Singh A, Blainey PC. Pooled genetic perturbation screens with image-based phenotypes. Nat Protoc 2022; 17:476-512. [PMID: 35022620 PMCID: PMC9654597 DOI: 10.1038/s41596-021-00653-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 10/28/2021] [Indexed: 11/09/2022]
Abstract
Discovery of the genetic components underpinning fundamental and disease-related processes is being rapidly accelerated by combining efficient, programmable genetic engineering with phenotypic readouts of high spatial, temporal and/or molecular resolution. Microscopy is a fundamental tool for studying cell biology, but its lack of high-throughput sequence readouts hinders integration in large-scale genetic screens. Optical pooled screens using in situ sequencing provide massively scalable integration of barcoded lentiviral libraries (e.g., CRISPR perturbation libraries) with high-content imaging assays, including dynamic processes in live cells. The protocol uses standard lentiviral vectors and molecular biology, providing single-cell resolution of phenotype and engineered genotype, scalability to millions of cells and accurate sequence reads sufficient to distinguish >106 perturbations. In situ amplification takes ~2 d, while sequencing can be performed in ~1.5 h per cycle. The image analysis pipeline provided enables fully parallel automated sequencing analysis using a cloud or cluster computing environment.
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Affiliation(s)
- David Feldman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Luke Funk
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anna Le
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Rebecca J Carlson
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - FuNien Tsai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- 10x Genomics, Pleasanton, CA, USA
| | - Brian Soong
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Avtar Singh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cellular and Tissue Genomics, Genentech Inc., South San Francisco, CA, USA
| | - Paul C Blainey
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
- Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA, USA.
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