1
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Tsai SJ, Gong Y, Dabbs A, Zahra F, Xu J, Geske A, Caterina MJ, Gould SJ. Enhanced kinase translocation reporters for simultaneous real-time measurement of PKA, ERK, and calcium. J Biol Chem 2025; 301:108183. [PMID: 39814226 PMCID: PMC11871455 DOI: 10.1016/j.jbc.2025.108183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2024] [Revised: 12/24/2024] [Accepted: 01/08/2025] [Indexed: 01/18/2025] Open
Abstract
Kinase translocation reporters (KTRs) are powerful tools for single-cell measurement of time-integrated kinase activity but suffer from restricted dynamic range and limited sensitivity, particularly in neurons. To address these limitations, we developed enhanced KTRs (eKTRs) for PKA and extracellular signal-regulated kinase (ERK) by (i) increasing KTR size, which reduces the confounding effect of KTR diffusion through the nuclear pore and (ii) modulating the strength of the bipartite nuclear localization signal in their kinase sensor domains, to ensure that the relative distribution of the KTR between the nucleus and cytoplasmic is determined by active nuclear import, active nuclear export, and relative activity of their cognate kinase. The resultant sets of ePKA-KTRs and eERK-KTRs display high sensitivity, broad dynamic range, and cell type-specific tuning. Moreover, co-expression of optically separable ePKA-KTRs and eERK-KTRs allowed us to simultaneously monitor the activation and inhibition of PKA and ERK, together with calcium levels, in live cells. These eKTRs responded as expected to direct agonists and inhibitors, and also confirmed that crosstalk between the PKA and ERK pathways is highly unbalanced, with the activation of PKA suppressing ERK activity, while activation of ERK induces PKA activity. Taken together, our findings highlight the importance of KTR size and bipartite nuclear localization signal strength to KTR sensitivity and dynamic range, show that different cell types require different eKTRs, and identify ePKA-KTR1.4 and eERK-KTR1.2 as particularly well-suited for monitoring PKA and ERK in primary sensory neurons.
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Affiliation(s)
- Shang-Jui Tsai
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
| | - Yijing Gong
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Austin Dabbs
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Fiddia Zahra
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Junhao Xu
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Aleksander Geske
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael J Caterina
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Stephen J Gould
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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2
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Kudo T, Meireles AM, Moncada R, Chen Y, Wu P, Gould J, Hu X, Kornfeld O, Jesudason R, Foo C, Höckendorf B, Corrada Bravo H, Town JP, Wei R, Rios A, Chandrasekar V, Heinlein M, Chuong AS, Cai S, Lu CS, Coelho P, Mis M, Celen C, Kljavin N, Jiang J, Richmond D, Thakore P, Benito-Gutiérrez E, Geiger-Schuller K, Hleap JS, Kayagaki N, de Sousa E Melo F, McGinnis L, Li B, Singh A, Garraway L, Rozenblatt-Rosen O, Regev A, Lubeck E. Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView. Nat Biotechnol 2024:10.1038/s41587-024-02391-0. [PMID: 39375449 DOI: 10.1038/s41587-024-02391-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 08/20/2024] [Indexed: 10/09/2024]
Abstract
Optical pooled screening (OPS) is a scalable method for linking image-based phenotypes with cellular perturbations. However, it has thus far been restricted to relatively low-plex phenotypic readouts in cancer cell lines in culture due to limitations associated with in situ sequencing of perturbation barcodes. Here, we develop PerturbView, an OPS technology that leverages in vitro transcription to amplify barcodes before in situ sequencing, enabling screens with highly multiplexed phenotypic readouts across diverse systems, including primary cells and tissues. We demonstrate PerturbView in induced pluripotent stem cell-derived neurons, primary immune cells and tumor tissue sections from animal models. In a screen of immune signaling pathways in primary bone marrow-derived macrophages, PerturbView uncovered both known and novel regulators of NF-κB signaling. Furthermore, we combine PerturbView with spatial transcriptomics in tissue sections from a mouse xenograft model, paving the way to in situ screens with rich optical and transcriptomic phenotypes. PerturbView broadens the scope of OPS to a wide range of models and applications.
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Affiliation(s)
- Takamasa Kudo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Ana M Meireles
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Reuben Moncada
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Yushu Chen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Ping Wu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Joshua Gould
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Xiaoyu Hu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Opher Kornfeld
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Rajiv Jesudason
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Conrad Foo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Burkhard Höckendorf
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Hector Corrada Bravo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Jason P Town
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Runmin Wei
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Antonio Rios
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Melanie Heinlein
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Amy S Chuong
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Shuangyi Cai
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Cherry Sakura Lu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Faculty of Environment and Information Studies, Keio University, Tokyo, Japan
| | - Paula Coelho
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Monika Mis
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Cemre Celen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Noelyn Kljavin
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Jian Jiang
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - David Richmond
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Pratiksha Thakore
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Elia Benito-Gutiérrez
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Jose Sergio Hleap
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Bioinformatics Department, ProCogia, Toronto, Ontario, Canada
| | - Nobuhiko Kayagaki
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Lisa McGinnis
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Bo Li
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Avtar Singh
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Levi Garraway
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Orit Rozenblatt-Rosen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Aviv Regev
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA.
| | - Eric Lubeck
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA.
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3
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Tsai SJ, Gong Y, Dabbs A, Zahra F, Xu J, Geske A, Caterina MJ, Gould SJ. Enhanced kinase translocation reporters for simultaneous real-time measurement of PKA, ERK, and Ca 2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.30.615856. [PMID: 39411162 PMCID: PMC11475874 DOI: 10.1101/2024.09.30.615856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/23/2024]
Abstract
Kinase translocation reporters (KTRs) are powerful tools for single-cell measurement of time-integrated kinase activity but suffer from restricted dynamic range and limited sensitivity, particularly in neurons. To address these limitations, we developed enhanced KTRs (eKTRs) for protein kinase A (PKA) and extracellular signal-regulated kinase (ERK) that display high sensitivity, rapid response kinetics, broad dynamic range, cell type-specific tuning, and an ability to detect PKA and ERK activity in primary sensory neurons. Moreover, co-expression of optically separable eKTRs for PKA and ERK revealed the kinetics of expected and unexpected crosstalk between PKA, ERK, protein kinase C, and calcium signaling pathways, demonstrating the utility of eKTRs for live cell monitoring of diverse and interacting signaling pathways. These results open the door to improved live-cell and in vivo measurements of key signaling pathways in neurons, while at the same time demonstrating the importance of KTR size and NLS strength to KTR dynamics.
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Affiliation(s)
- Shang-Jui Tsai
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Yijing Gong
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Austin Dabbs
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Fiddia Zahra
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Junhao Xu
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Aleksander Geske
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | - Michael J. Caterina
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Stephen J. Gould
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
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4
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Rood JE, Hupalowska A, Regev A. Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas. Cell 2024; 187:4520-4545. [PMID: 39178831 DOI: 10.1016/j.cell.2024.07.035] [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: 05/03/2024] [Revised: 07/15/2024] [Accepted: 07/21/2024] [Indexed: 08/26/2024]
Abstract
Comprehensively charting the biologically causal circuits that govern the phenotypic space of human cells has often been viewed as an insurmountable challenge. However, in the last decade, a suite of interleaved experimental and computational technologies has arisen that is making this fundamental goal increasingly tractable. Pooled CRISPR-based perturbation screens with high-content molecular and/or image-based readouts are now enabling researchers to probe, map, and decipher genetically causal circuits at increasing scale. This scale is now eminently suitable for the deployment of artificial intelligence and machine learning (AI/ML) to both direct further experiments and to predict or generate information that was not-and sometimes cannot-be gathered experimentally. By combining and iterating those through experiments that are designed for inference, we now envision a Perturbation Cell Atlas as a generative causal foundation model to unify human cell biology.
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Affiliation(s)
| | | | - Aviv Regev
- Genentech, South San Francisco, CA, USA.
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5
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Alieva M, Wezenaar AKL, Wehrens EJ, Rios AC. Bridging live-cell imaging and next-generation cancer treatment. Nat Rev Cancer 2023; 23:731-745. [PMID: 37704740 DOI: 10.1038/s41568-023-00610-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/25/2023] [Indexed: 09/15/2023]
Abstract
By providing spatial, molecular and morphological data over time, live-cell imaging can provide a deeper understanding of the cellular and signalling events that determine cancer response to treatment. Understanding this dynamic response has the potential to enhance clinical outcome by identifying biomarkers or actionable targets to improve therapeutic efficacy. Here, we review recent applications of live-cell imaging for uncovering both tumour heterogeneity in treatment response and the mode of action of cancer-targeting drugs. Given the increasing uses of T cell therapies, we discuss the unique opportunity of time-lapse imaging for capturing the interactivity and motility of immunotherapies. Although traditionally limited in the number of molecular features captured, novel developments in multidimensional imaging and multi-omics data integration offer strategies to connect single-cell dynamics to molecular phenotypes. We review the effect of these recent technological advances on our understanding of the cellular dynamics of tumour targeting and discuss their implication for next-generation precision medicine.
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Affiliation(s)
- Maria Alieva
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Instituto de Investigaciones Biomedicas Sols-Morreale (IIBM), CSIC-UAM, Madrid, Spain
| | - Amber K L Wezenaar
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Ellen J Wehrens
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
| | - Anne C Rios
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
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6
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Lin C, Liu L, Zou P. Functional imaging-guided cell selection for evolving genetically encoded fluorescent indicators. CELL REPORTS METHODS 2023; 3:100544. [PMID: 37671014 PMCID: PMC10475787 DOI: 10.1016/j.crmeth.2023.100544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/05/2023] [Accepted: 07/06/2023] [Indexed: 09/07/2023]
Abstract
Genetically encoded fluorescent indicators are powerful tools for tracking cellular dynamic processes. Engineering these indicators requires balancing screening dimensions with screening throughput. Herein, we present a functional imaging-guided photoactivatable cell selection platform, Faculae (functional imaging-activated molecular evolution), for linking microscopic phenotype with the underlying genotype in a pooled mutant library. Faculae is capable of assessing tens of thousands of variants in mammalian cells simultaneously while achieving photoactivation with single-cell resolution in seconds. To demonstrate the feasibility of this approach, we applied Faculae to perform multidimensional directed evolution for far-red genetically encoded calcium indicators (FR-GECIs) with improved brightness (Nier1b) and signal-to-baseline ratio (Nier1s). We anticipate that this image-based pooled screening method will facilitate the development of a wide variety of biomolecular tools.
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Affiliation(s)
- Chang Lin
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing 100871, China
| | - Lihao Liu
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing 100871, China
| | - Peng Zou
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, PKU-Tsinghua Center for Life Science, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research (CIBR), Beijing 102206, China
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7
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Rovira-Clavé X, Drainas AP, Jiang S, Bai Y, Baron M, Zhu B, Dallas AE, Lee MC, Chu TP, Holzem A, Ayyagari R, Bhattacharya D, McCaffrey EF, Greenwald NF, Markovic M, Coles GL, Angelo M, Bassik MC, Sage J, Nolan GP. Spatial epitope barcoding reveals clonal tumor patch behaviors. Cancer Cell 2022; 40:1423-1439.e11. [PMID: 36240778 PMCID: PMC9673683 DOI: 10.1016/j.ccell.2022.09.014] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/22/2022] [Accepted: 09/21/2022] [Indexed: 01/09/2023]
Abstract
Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.
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Affiliation(s)
- Xavier Rovira-Clavé
- Department of Pathology, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Alexandros P Drainas
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Sizun Jiang
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Yunhao Bai
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Maya Baron
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Bokai Zhu
- Department of Pathology, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Alec E Dallas
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Myung Chang Lee
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Theresa P Chu
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Alessandra Holzem
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ramya Ayyagari
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Debadrita Bhattacharya
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Erin F McCaffrey
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Noah F Greenwald
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Maxim Markovic
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Garry L Coles
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Michael Angelo
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Michael C Bassik
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Julien Sage
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA.
| | - Garry P Nolan
- Department of Pathology, Stanford University, Stanford, CA 94305, USA.
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8
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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: 2.7] [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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