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Sánchez Rivera FJ, Dow LE. How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research. Cold Spring Harb Perspect Med 2024; 14:a041384. [PMID: 37487630 PMCID: PMC11065179 DOI: 10.1101/cshperspect.a041384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.
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Affiliation(s)
- Francisco J Sánchez Rivera
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
| | - Lukas E Dow
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York 10065, USA
- Department of Biochemistry, Weill Cornell Medicine, New York, New York 10065, USA
- Department of Medicine, Weill Cornell Medicine, New York, New York 10065, USA
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2
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Gentili M, Carlson RJ, Liu B, Hellier Q, Andrews J, Qin Y, Blainey PC, Hacohen N. Classification and functional characterization of regulators of intracellular STING trafficking identified by genome-wide optical pooled screening. bioRxiv 2024:2024.04.07.588166. [PMID: 38645119 PMCID: PMC11030420 DOI: 10.1101/2024.04.07.588166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
STING is an innate immune sensor that traffics across many cellular compartments to carry out its function of detecting cyclic di-nucleotides and triggering defense processes. Mutations in factors that regulate this process are often linked to STING-dependent human inflammatory disorders. To systematically identify factors involved in STING trafficking, we performed a genome-wide optical pooled screen and examined the impact of genetic perturbations on intracellular STING localization. Based on subcellular imaging of STING protein and trafficking markers in 45 million cells perturbed with sgRNAs, we defined 464 clusters of gene perturbations with similar cellular phenotypes. A higher-dimensional focused optical pooled screen on 262 perturbed genes which assayed 11 imaging channels identified 73 finer phenotypic clusters. In a cluster containing USE1, a protein that mediates Golgi to ER transport, we found a gene of unknown function, C19orf25. Consistent with the known role of USE1, loss of C19orf25 enhanced STING signaling. Other clusters contained subunits of the HOPS, GARP and RIC1-RGP1 complexes. We show that HOPS deficiency delayed STING degradation and consequently increased signaling. Similarly, GARP/RIC1-RGP1 loss increased STING signaling by delaying STING exit from the Golgi. Our findings demonstrate that genome-wide genotype-phenotype maps based on high-content cell imaging outperform other screening approaches, and provide a community resource for mining for factors that impact STING trafficking as well as other cellular processes observable in our dataset.
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Carlson RJ, Patten JJ, Stefanakis G, Soong BY, Radhakrishnan A, Singh A, Thakur N, Amarasinghe GK, Hacohen N, Basler CF, Leung D, Uhler C, Davey RA, Blainey PC. Single-cell image-based genetic screens systematically identify regulators of Ebola virus subcellular infection dynamics. bioRxiv 2024:2024.04.06.588168. [PMID: 38617272 PMCID: PMC11014611 DOI: 10.1101/2024.04.06.588168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Ebola virus (EBOV) is a high-consequence filovirus that gives rise to frequent epidemics with high case fatality rates and few therapeutic options. Here, we applied image-based screening of a genome-wide CRISPR library to systematically identify host cell regulators of Ebola virus infection in 39,085,093 million single cells. Measuring viral RNA and protein levels together with their localization in cells identified over 998 related host factors and provided detailed information about the role of each gene across the virus replication cycle. We trained a deep learning model on single-cell images to associate each host factor with predicted replication steps, and confirmed the predicted relationship for select host factors. Among the findings, we showed that the mitochondrial complex III subunit UQCRB is a post-entry regulator of Ebola virus RNA replication, and demonstrated that UQCRB inhibition with a small molecule reduced overall Ebola virus infection with an IC50 of 5 μM. Using a random forest model, we also identified perturbations that reduced infection by disrupting the equilibrium between viral RNA and protein. One such protein, STRAP, is a spliceosome-associated factor that was found to be closely associated with VP35, a viral protein required for RNA processing. Loss of STRAP expression resulted in a reduction in full-length viral genome production and subsequent production of non-infectious virus particles. Overall, the data produced in this genome-wide high-content single-cell screen and secondary screens in additional cell lines and related filoviruses (MARV and SUDV) revealed new insights about the role of host factors in virus replication and potential new targets for therapeutic intervention.
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Affiliation(s)
- Rebecca J Carlson
- Massachusetts Institute of Technology, Department of Health Sciences and Technology, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - J J Patten
- Department of Virology, Immunology, and Microbiology, Boston University School of Medicine, Boston, MA, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA
| | - George Stefanakis
- Laboratory for Information & Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Brian Y Soong
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Adityanarayanan Radhakrishnan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard School of Engineering and Applied Sciences, Cambridge, MA, USA
| | - Avtar Singh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Naveen Thakur
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gaya K Amarasinghe
- Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Cancer Center, Boston, MA, USA
| | - Christopher F Basler
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daisy Leung
- Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
| | - Caroline Uhler
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Laboratory for Information & Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert A Davey
- Department of Virology, Immunology, and Microbiology, Boston University School of Medicine, Boston, MA, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA
| | - Paul C Blainey
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Institute of Technology, Department of Biological Engineering, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
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4
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Georges A, Chahal CAA. Pooled Genetic Screenings to Identify Likely Pathogenic Variants in Hypertrophic Cardiomyopathy. Circ Genom Precis Med 2024; 17:e004599. [PMID: 38497213 DOI: 10.1161/circgen.124.004599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Affiliation(s)
- Adrien Georges
- Université Paris Cité, Inserm, Paris Centre de Recherche Cardiovasculaire (PARCC), France (A.G.)
| | - Choudhary Anwar A Chahal
- Department of Cardiology, Center for Inherited Cardiovascular Diseases, WellSpan Health, York, PA (C.A.A.C.)
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN (C.A.A.C.)
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Centre, Queen Mary University London, United Kingdom (C.A.A.C.)
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Walton RT, Qin Y, Blainey PC. CROPseq-multi: a versatile solution for multiplexed perturbation and decoding in pooled CRISPR screens. bioRxiv 2024:2024.03.17.585235. [PMID: 38558968 PMCID: PMC10979941 DOI: 10.1101/2024.03.17.585235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Forward genetic screens seek to dissect complex biological systems by systematically perturbing genetic elements and observing the resulting phenotypes. While standard screening methodologies introduce individual perturbations, multiplexing perturbations improves the performance of single-target screens and enables combinatorial screens for the study of genetic interactions. Current tools for multiplexing perturbations are incompatible with pooled screening methodologies that require mRNA-embedded barcodes, including some microscopy and single cell sequencing approaches. Here, we report the development of CROPseq-multi, a CROPseq1-inspired lentiviral system to multiplex Streptococcus pyogenes (Sp) Cas9-based perturbations with mRNA-embedded barcodes. CROPseq-multi has equivalent per-guide activity to CROPseq and low lentiviral recombination frequencies. CROPseq-multi is compatible with enrichment screening methodologies and optical pooled screens, and is extensible to screens with single-cell sequencing readouts. For optical pooled screens, an optimized and multiplexed in situ detection protocol improves barcode detection efficiency 10-fold, enables detection of recombination events, and increases decoding efficiency 3-fold relative to CROPseq. CROPseq-multi is a widely applicable multiplexing solution for diverse SpCas9-based genetic screening approaches.
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Affiliation(s)
- Russell T. Walton
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Yue Qin
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Paul C. Blainey
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
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Binan L, Danquah S, Valakh V, Simonton B, Bezney J, Nehme R, Cleary B, Farhi SL. Simultaneous CRISPR screening and spatial transcriptomics reveals intracellular, intercellular, and functional transcriptional circuits. bioRxiv 2023:2023.11.30.569494. [PMID: 38076932 PMCID: PMC10705493 DOI: 10.1101/2023.11.30.569494] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but have not yet leveraged the power of highly-plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present Perturb-FISH, which bridges these approaches by combining imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs. We show that Perturb-FISH recovers intracellular effects that are consistent with Perturb-seq results in a screen of lipopolysaccharide response in cultured monocytes, and uncover new intercellular and density-dependent regulation of the innate immune response. We further pair Perturb-FISH with a functional readout in a screen of autism spectrum disorder risk genes, showing common calcium activity phenotypes in induced pluripotent stem cell derived astrocytes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a generally applicable method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.
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Affiliation(s)
- Loϊc Binan
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Serwah Danquah
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Vera Valakh
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brooke Simonton
- Present address: The Ken & Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. (Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA)
| | - Jon Bezney
- Present address: Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. (Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA)
| | - Ralda Nehme
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brian Cleary
- Faculty of Computing and Data Sciences, Boston University, Boston, MA, USA; Department of Biology, Boston University, Boston, MA, USA; Department of Biomedical Engineering, Boston University, Boston, MA, USA; Program in Bioinformatics, Boston University, Boston, MA, USA; Biological Design Center, Boston University, Boston, MA, USA
| | - Samouil L Farhi
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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Abstract
The CRISPR genome editing technology has revolutionized the way gene function is studied. Genome editing can be achieved in single genes or for thousands of genes simultaneously in sensitive genetic screens. While conventional genetic screens are limited to bulk measurements of cell behavior, recent developments in single-cell technologies make it possible to combine CRISPR screening with single-cell profiling. In this way, cell behavior and gene expression can be monitored simultaneously, with the additional possibility of including data on chromatin accessibility and protein levels. Moreover, the availability of various Cas proteins leading to inactivation, activation, or other effects on gene function further broadens the scope of such screens. The integration of single-cell multi-omics approaches with CRISPR screening open the path to high-content information on the impact of genetic perturbations at single-cell resolution. Current limitations in cell throughput and data density need to be taken into consideration, but new technologies are rapidly evolving and are likely to easily overcome these limitations. In this review, we discuss the use of bulk CRISPR screening in hematology research, as well as the emergence of single-cell CRISPR screening and its added value to the field.
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Affiliation(s)
- Sarah Meyers
- Center for Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium
| | - Sofie Demeyer
- Center for Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium
| | - Jan Cools
- Center for Human Genetics, KU Leuven, Leuven, Belgium.
- Center for Cancer Biology, VIB, Leuven, Belgium.
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium.
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Stossi F, Singh PK, Safari K, Marini M, Labate D, Mancini MA. High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery. Biochem Pharmacol 2023; 216:115770. [PMID: 37660829 DOI: 10.1016/j.bcp.2023.115770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/05/2023]
Abstract
Measuring single cell responses to the universe of chemicals (drugs, natural products, environmental toxicants etc.) is of paramount importance to human health as phenotypic variability in sensing stimuli is a hallmark of biology that is considered during high throughput screening. One of the ways to approach this problem is via high throughput, microscopy-based assays coupled with multi-dimensional single cell analysis methods. Here, we will summarize some of the efforts in this vast and growing field, focusing on phenotypic screens (e.g., Cell Painting), single cell analytics and quality control, with particular attention to environmental toxicology and drug screening. We will discuss advantages and limitations of high throughput assays with various end points and levels of complexity.
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Affiliation(s)
- Fabio Stossi
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA; GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA.
| | - Pankaj K Singh
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA; Center for Translational Cancer Research, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA
| | - Kazem Safari
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA; Center for Translational Cancer Research, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA
| | - Michela Marini
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA; Department of Mathematics, University of Houston, Houston, TX, USA
| | - Demetrio Labate
- GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA; Department of Mathematics, University of Houston, Houston, TX, USA
| | - Michael A Mancini
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA; GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, USA; Center for Translational Cancer Research, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA
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Ramezani M, Bauman J, Singh A, Weisbart E, Yong J, Lozada M, Way GP, Kavari SL, Diaz C, Haghighi M, Batista TM, Pérez-Schindler J, Claussnitzer M, Singh S, Cimini BA, Blainey PC, Carpenter AE, Jan CH, Neal JT. A genome-wide atlas of human cell morphology. bioRxiv 2023:2023.08.06.552164. [PMID: 37609130 PMCID: PMC10441312 DOI: 10.1101/2023.08.06.552164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
A key challenge of the modern genomics era is developing data-driven representations of gene function. Here, we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-scale genotype-phenotype maps comprising >20,000 single-gene CRISPR-Cas9-based knockout experiments in >30 million cells. Our optical pooled cell profiling approach (PERISCOPE) combines a de-stainable high-dimensional phenotyping panel (based on Cell Painting1,2) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This approach provides high-dimensional phenotypic profiles of individual cells, while simultaneously enabling interrogation of subcellular processes. Our atlas reconstructs known pathways and protein-protein interaction networks, identifies culture media-specific responses to gene knockout, and clusters thousands of human genes by phenotypic similarity. Using this atlas, we identify the poorly-characterized disease-associated transmembrane protein TMEM251/LYSET as a Golgi-resident protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes, showing the power of these representations. In sum, our atlas and screening technology represent a rich and accessible resource for connecting genes to cellular functions at scale.
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Affiliation(s)
- Meraj Ramezani
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Julia Bauman
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Current address: Stanford University, Stanford, CA, USA
| | - Avtar Singh
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Current address: Genentech Department of Cellular and Tissue Genomics, South San Francisco, CA, USA
| | - Erin Weisbart
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - John Yong
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Maria Lozada
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gregory P Way
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Current address: Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Sanam L Kavari
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Current address: University of Pennsylvania, Philadelphia, PA, USA
| | - Celeste Diaz
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Current address: Stanford University, Stanford, CA, USA
| | | | - Thiago M Batista
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at Broad Institute, Cambridge, MA, USA
| | - Joaquín Pérez-Schindler
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at Broad Institute, Cambridge, MA, USA
| | - Melina Claussnitzer
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at Broad Institute, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Beth A Cimini
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Paul C Blainey
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- MIT Department of Biological Engineering, Cambridge, MA, USA
- Koch Institute for Integrative Research at MIT, Cambridge, MA, USA
| | | | - Calvin H Jan
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - James T Neal
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
- Type 2 Diabetes Systems Genomics Initiative of the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at Broad Institute, Cambridge, MA, USA
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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11
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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 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] [What about the content of this article? (0)] [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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12
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Ghamsari R, Rosenbluh J, Menon AV, Lovell NH, Alinejad-Rokny H. Technological Convergence: Highlighting the Power of CRISPR Single-Cell Perturbation Toolkit for Functional Interrogation of Enhancers. Cancers (Basel) 2023; 15:3566. [PMID: 37509229 PMCID: PMC10377346 DOI: 10.3390/cancers15143566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/30/2023] [Accepted: 07/03/2023] [Indexed: 07/30/2023] Open
Abstract
Higher eukaryotic enhancers, as a major class of regulatory elements, play a crucial role in the regulation of gene expression. Over the last decade, the development of sequencing technologies has flooded researchers with transcriptome-phenotype data alongside emerging candidate regulatory elements. Since most methods can only provide hints about enhancer function, there have been attempts to develop experimental and computational approaches that can bridge the gap in the causal relationship between regulatory regions and phenotypes. The coupling of two state-of-the-art technologies, also referred to as crisprQTL, has emerged as a promising high-throughput toolkit for addressing this question. This review provides an overview of the importance of studying enhancers, the core molecular foundation of crisprQTL, and recent studies utilizing crisprQTL to interrogate enhancer-phenotype correlations. Additionally, we discuss computational methods currently employed for crisprQTL data analysis. We conclude by pointing out common challenges, making recommendations, and looking at future prospects, with the aim of providing researchers with an overview of crisprQTL as an important toolkit for studying enhancers.
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Affiliation(s)
- Reza Ghamsari
- BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
- Epigenetics and Development Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Joseph Rosenbluh
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC 3800, Australia
| | - A Vipin Menon
- Epigenetics and Development Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Nigel H Lovell
- The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
- Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW 2052, Australia
| | - Hamid Alinejad-Rokny
- BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
- UNSW Data Science Hub, UNSW Sydney, Sydney, NSW 2052, Australia
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Doron M, Moutakanni T, Chen ZS, Moshkov N, Caron M, Touvron H, Bojanowski P, Pernice WM, Caicedo JC. Unbiased single-cell morphology with self-supervised vision transformers. bioRxiv 2023:2023.06.16.545359. [PMID: 37398158 PMCID: PMC10312751 DOI: 10.1101/2023.06.16.545359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Accurately quantifying cellular morphology at scale could substantially empower existing single-cell approaches. However, measuring cell morphology remains an active field of research, which has inspired multiple computer vision algorithms over the years. Here, we show that DINO, a vision-transformer based, self-supervised algorithm, has a remarkable ability for learning rich representations of cellular morphology without manual annotations or any other type of supervision. We evaluate DINO on a wide variety of tasks across three publicly available imaging datasets of diverse specifications and biological focus. We find that DINO encodes meaningful features of cellular morphology at multiple scales, from subcellular and single-cell resolution, to multi-cellular and aggregated experimental groups. Importantly, DINO successfully uncovers a hierarchy of biological and technical factors of variation in imaging datasets. The results show that DINO can support the study of unknown biological variation, including single-cell heterogeneity and relationships between samples, making it an excellent tool for image-based biological discovery.
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Affiliation(s)
- Michael Doron
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Nikita Moshkov
- Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary
| | | | | | | | - Wolfgang M. Pernice
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
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14
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Abstract
The zebrafish is a powerful model system for studying animal development, for modeling genetic diseases, and for large-scale in vivo functional genetics. Because of its ease of use and its high efficiency in targeted gene perturbation, CRISPR-Cas9 has recently gained prominence as the tool of choice for genetic manipulation in zebrafish. However, scaling up the technique for high-throughput in vivo functional genetics has been a challenge. We recently developed a method, Multiplexed Intermixed CRISPR Droplets (MIC-Drop), that makes large-scale CRISPR screening in zebrafish possible. Here, we outline the step-by-step protocol for performing functional genetic screens in zebrafish by using MIC-Drop. MIC-Drop uses multiplexed single-guide RNAs to generate biallelic mutations in injected zebrafish embryos, allowing genetic screens to be performed in F0 animals. Combining microfluidics and DNA barcoding enables simultaneous targeting of tens to hundreds of genes from a single injection needle, while also enabling retrospective and rapid identification of the genotype responsible for an observed phenotype. The primary target audiences for MIC-Drop are developmental biologists, zebrafish geneticists, and researchers interested in performing in vivo functional genetic screens in a vertebrate model system. MIC-Drop will also prove useful in the hands of chemical biologists seeking to identify targets of small molecules that cause phenotypic changes in zebrafish. By using MIC-Drop, a typical screen of 100 genes can be conducted within 2-3 weeks by a single user.
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Affiliation(s)
- Saba Parvez
- Department of Pharmacology & Toxicology, College of Pharmacy, University of Utah, Salt Lake City, UT, USA
| | - Zachary J Brandt
- Department of Pharmacology & Toxicology, College of Pharmacy, University of Utah, Salt Lake City, UT, USA
| | - Randall T Peterson
- Department of Pharmacology & Toxicology, College of Pharmacy, University of Utah, Salt Lake City, UT, USA.
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15
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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16
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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. Adv Sci (Weinh) 2023; 10:e2204484. [PMID: 36504444 PMCID: PMC9896079 DOI: 10.1002/advs.202204484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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17
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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: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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18
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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] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [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,*Correspondence: Michael D. Green,
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19
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [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 Harvard Cambridge MA USA
- Department of Biological Engineering MIT Cambridge MA USA
| | - Avtar Singh
- Broad Institute of MIT and Harvard Cambridge MA USA
| | - Paul C Blainey
- Broad Institute of MIT and Harvard Cambridge MA USA
- Department of Biological Engineering MIT Cambridge MA USA
- Koch Institute for Integrative Cancer Research MIT Cambridge MA USA
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20
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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 DOI: 10.1038/s42003-022-04089-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [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. Raft-Seq is a generalizable pooled screening platform that combines high-content imaging, machine learning and microraft isolation, and enables efficient screening of genetic perturbations based on their impact on phenotypes.
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21
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Silge A, Weber K, Cialla-may D, Müller-bötticher L, Fischer D, Popp J. Trends in pharmaceutical analysis and quality control by modern Raman spectroscopic techniques. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116623] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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