1
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Hecker FA, Leggio B, König T, Kim V, Osterland M, Gnutt D, Niehaus K, Geibel S. Cell Painting unravels insecticidal modes of action on Spodoptera frugiperda insect cells. PESTICIDE BIOCHEMISTRY AND PHYSIOLOGY 2024; 203:105983. [PMID: 39084786 DOI: 10.1016/j.pestbp.2024.105983] [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: 04/16/2024] [Revised: 06/06/2024] [Accepted: 06/08/2024] [Indexed: 08/02/2024]
Abstract
The "Cell Painting" technology utilizes multiplexed fluorescent staining of various cell organelles, to produce high-content microscopy images of cells for multidimensional phenotype assessment. The phenotypic profiles extracted from those images can be analyzed upon perturbations with biologically active molecules to annotate the mode of action or biological activity by comparison with reference profiles of already known mechanisms of action, ultimately enabling the determination of on-target and off-target effects. This approach is already described in various human cell cultures, the most commonly used being the U2OS cell line, yet allows broad applications in additional areas of chemical-biological research. Here we describe for the first time the application and adaptation of Cell Painting to an insect cell line, the Sf9 cells from Spodoptera frugiperda. By adjusting image acquisition and analysis models, specific phenotypic profiles were obtained in a dose-dependent manner for 20 reference compounds, including representatives for the most relevant insecticidal modes of action categories (nerve & muscle, respiration and growth & development). Through a dimensionality-reduction method, both calculations of phenotypic half maximal inhibition concentration (IC50) values as well as similarity analysis of the obtained profiles by hierarchical clustering were performed. By Cell Painting effects on the phenotype could be obtained at higher sensitivity than in other assay formats, such as cytotoxicity assessments. More importantly, these analyses provide insight into mechanistic determinants of biological activity. Compounds with similar modes of action showed a high degree of proximity in a hierarchical clustering analysis while being distinct from actives with an unrelated mode of action. In essence, we provide strong evidence on the impact of Cell Painting mechanistic understanding of insecticides with regards to determinants of efficacy and safety utilizing an insect cell model system.
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Affiliation(s)
- Franziska A Hecker
- University Bielefeld, Proteome and Metabolome Research, Bielefeld, Germany
| | - Bruno Leggio
- R&D Disease Control, Bayer SAS, Crop Science Division, Lyon, France
| | - Tim König
- R&D Image-based Screening Systems, Bayer AG, Pharma Division, Wuppertal, Germany
| | - Vladislav Kim
- R&D Machine Learning Research, Bayer AG, Pharma Division, Berlin, Germany
| | - Marc Osterland
- R&D Machine Learning Research, Bayer AG, Pharma Division, Berlin, Germany
| | - David Gnutt
- R&D Image-based Screening Systems, Bayer AG, Pharma Division, Wuppertal, Germany
| | - Karsten Niehaus
- University Bielefeld, Proteome and Metabolome Research, Bielefeld, Germany
| | - Sven Geibel
- R&D Hit Discovery, Bayer AG, Crop Science Division, Monheim, Germany.
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2
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Odje F, Meijer D, von Coburg E, van der Hooft JJJ, Dunst S, Medema MH, Volkamer A. Unleashing the potential of cell painting assays for compound activities and hazards prediction. FRONTIERS IN TOXICOLOGY 2024; 6:1401036. [PMID: 39086553 PMCID: PMC11288911 DOI: 10.3389/ftox.2024.1401036] [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: 03/14/2024] [Accepted: 06/14/2024] [Indexed: 08/02/2024] Open
Abstract
The cell painting (CP) assay has emerged as a potent imaging-based high-throughput phenotypic profiling (HTPP) tool that provides comprehensive input data for in silico prediction of compound activities and potential hazards in drug discovery and toxicology. CP enables the rapid, multiplexed investigation of various molecular mechanisms for thousands of compounds at the single-cell level. The resulting large volumes of image data provide great opportunities but also pose challenges to image and data analysis routines as well as property prediction models. This review addresses the integration of CP-based phenotypic data together with or in substitute of structural information from compounds into machine (ML) and deep learning (DL) models to predict compound activities for various human-relevant disease endpoints and to identify the underlying modes-of-action (MoA) while avoiding unnecessary animal testing. The successful application of CP in combination with powerful ML/DL models promises further advances in understanding compound responses of cells guiding therapeutic development and risk assessment. Therefore, this review highlights the importance of unlocking the potential of CP assays when combined with molecular fingerprints for compound evaluation and discusses the current challenges that are associated with this approach.
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Affiliation(s)
- Floriane Odje
- Data Driven Drug Design, Center for Bioinformatics, Saarland University, Saarbrücken, Germany
| | - David Meijer
- Bioinformatics Group, Wageningen University, Wageningen, Netherlands
| | - Elena von Coburg
- Department Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R), Berlin, Germany
| | | | - Sebastian Dunst
- Department Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R), Berlin, Germany
| | - Marnix H. Medema
- Bioinformatics Group, Wageningen University, Wageningen, Netherlands
| | - Andrea Volkamer
- Data Driven Drug Design, Center for Bioinformatics, Saarland University, Saarbrücken, Germany
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3
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Henriquez JE, Badwaik VD, Bianchi E, Chen W, Corvaro M, LaRocca J, Lunsman TD, Zu C, Johnson KJ. From Pipeline to Plant Protection Products: Using New Approach Methodologies (NAMs) in Agrochemical Safety Assessment. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:10710-10724. [PMID: 38688008 DOI: 10.1021/acs.jafc.4c00958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
The human population will be approximately 9.7 billion by 2050, and food security has been identified as one of the key issues facing the global population. Agrochemicals are an important tool available to farmers that enable high crop yields and continued access to healthy foods, but the average new agrochemical active ingredient takes more than ten years, 350 million dollars, and 20,000 animals to develop and register. The time, monetary, and animal costs incentivize the use of New Approach Methodologies (NAMs) in early-stage screening to prioritize chemical candidates. This review outlines NAMs that are currently available or can be adapted for use in early-stage screening agrochemical programs. It covers new in vitro screens that are on the horizon in key areas of regulatory concern. Overall, early-stage screening with NAMs enables the prioritization of development for agrochemicals without human and environmental health concerns through a more directed, agile, and iterative development program before animal-based regulatory testing is even considered.
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Affiliation(s)
| | - Vivek D Badwaik
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Enrica Bianchi
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Jessica LaRocca
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Chengli Zu
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Kamin J Johnson
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
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4
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Seal S, Trapotsi MA, Spjuth O, Singh S, Carreras-Puigvert J, Greene N, Bender A, Carpenter AE. A Decade in a Systematic Review: The Evolution and Impact of Cell Painting. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.04.592531. [PMID: 38766203 PMCID: PMC11100607 DOI: 10.1101/2024.05.04.592531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other - omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded Cell Painting's ability to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.
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Affiliation(s)
- Srijit Seal
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom
| | - Maria-Anna Trapotsi
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 1 Francis Crick Avenue, Cambridge, CB2 0AA, United Kingdom
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-75124, Uppsala, Sweden
| | - Shantanu Singh
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 1 Francis Crick Avenue, Cambridge, CB2 0AA, United Kingdom
| | - Jordi Carreras-Puigvert
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-75124, Uppsala, Sweden
| | - Nigel Greene
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA
| | - Andreas Bender
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom
| | - Anne E. Carpenter
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States
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5
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Seal S, Trapotsi MA, Spjuth O, Singh S, Carreras-Puigvert J, Greene N, Bender A, Carpenter AE. A Decade in a Systematic Review: The Evolution and Impact of Cell Painting. ARXIV 2024:arXiv:2405.02767v1. [PMID: 38745696 PMCID: PMC11092692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other -omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded Cell Painting's ability to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.
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Affiliation(s)
- Srijit Seal
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom
| | - Maria-Anna Trapotsi
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 1 Francis Crick Avenue, Cambridge, CB2 0AA, United Kingdom
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-75124, Uppsala, Sweden
| | - Shantanu Singh
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 1 Francis Crick Avenue, Cambridge, CB2 0AA, United Kingdom
| | - Jordi Carreras-Puigvert
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-75124, Uppsala, Sweden
| | - Nigel Greene
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA
| | - Andreas Bender
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom
| | - Anne E. Carpenter
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States
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6
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Tapaswi A, Cemalovic N, Polemi KM, Sexton JZ, Colacino JA. Applying Cell Painting in Non-Tumorigenic Breast Cells to Understand Impacts of Common Chemical Exposures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.30.591893. [PMID: 38746407 PMCID: PMC11092634 DOI: 10.1101/2024.04.30.591893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
There are a substantial number of chemicals to which individuals in the general population are exposed which have putative, but still poorly understood, links to breast cancer. Cell Painting is a high-content imaging-based in vitro assay that allows for rapid and unbiased measurements of the concentration-dependent effects of chemical exposures on cellular morphology. We optimized the Cell Painting assay and measured the effect of exposure to 16 human exposure relevant chemicals, along with 21 small molecules with known mechanisms of action, for 48 hours in non-tumorigenic mammary epithelial cells, the MCF10A cell line. Through unbiased imaging analyses using CellProfiler, we quantified 3042 morphological features across approximately 1.2 million cells. We used benchmark concentration modeling to quantify significance and dose-dependent directionality to identify morphological features conserved across chemicals and find features that differentiate the effects of toxicants from one another. Benchmark concentrations were compared to chemical exposure biomarker concentration measurements from the National Health and Nutrition Examination Survey to assess which chemicals induce morphological alterations at human-relevant concentrations. Morphometric fingerprint analysis revealed similar phenotypes between small molecules and prioritized NHANES-toxicants guiding further investigation. A comparison of feature fingerprints via hypergeometric analysis revealed significant feature overlaps between chemicals when stratified by compartment and stain. One such example was the similarities between a metabolite of the organochlorine pesticide DDT (p,p'-DDE) and an activator of canonical Wnt signaling CHIR99201. As CHIR99201 is a known Wnt pathway activator and its role in β-catenin translocation is well studied, we studied the translocation of β-catenin following p'-p' DDE exposure in an orthogonal high-content imaging assay. Consistent with activation of Wnt signaling, low dose p',p'-DDE (25nM) significantly enhances the nuclear translocation of β-catenin. Overall, these findings highlight the ability of Cell Painting to enhance mode-of-action studies for toxicants which are common exposures in our environment but have previously been incompletely characterized with respect to breast cancer risk.
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Affiliation(s)
- Anagha Tapaswi
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Cemalovic
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA
| | - Katelyn M Polemi
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA
| | - Jonathan Z Sexton
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Medicinal Chemistry, University of Michigan School of Pharmacy, Ann Arbor, MI, USA
| | - Justin A Colacino
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA
- Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI, USA
- Program in the Environment, University of Michigan, Ann Arbor MI, USA
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7
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Franks SN, Heon-Roberts R, Ryan BJ. CRISPRi: a way to integrate iPSC-derived neuronal models. Biochem Soc Trans 2024; 52:539-551. [PMID: 38526223 PMCID: PMC11088925 DOI: 10.1042/bst20230190] [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: 09/07/2023] [Revised: 02/28/2024] [Accepted: 03/13/2024] [Indexed: 03/26/2024]
Abstract
The genetic landscape of neurodegenerative diseases encompasses genes affecting multiple cellular pathways which exert effects in an array of neuronal and glial cell-types. Deconvolution of the roles of genes implicated in disease and the effects of disease-associated variants remains a vital step in the understanding of neurodegeneration and the development of therapeutics. Disease modelling using patient induced pluripotent stem cells (iPSCs) has enabled the generation of key cell-types associated with disease whilst maintaining the genomic variants that predispose to neurodegeneration. The use of CRISPR interference (CRISPRi), alongside other CRISPR-perturbations, allows the modelling of the effects of these disease-associated variants or identifying genes which modify disease phenotypes. This review summarises the current applications of CRISPRi in iPSC-derived neuronal models, such as fluorescence-activated cell sorting (FACS)-based screens, and discusses the future opportunities for disease modelling, identification of disease risk modifiers and target/drug discovery in neurodegeneration.
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Affiliation(s)
- Sarah N.J. Franks
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
| | - Rachel Heon-Roberts
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
| | - Brent J. Ryan
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
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8
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Ostovich E, Klaper R. Using a Novel Multiplexed Algal Cytological Imaging (MACI) Assay and Machine Learning as a Way to Characterize Complex Phenotypes in Plant-Type Organisms. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:4894-4903. [PMID: 38446593 DOI: 10.1021/acs.est.3c07733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
High-throughput phenotypic profiling assays, popular for their ability to characterize alternations in single-cell morphological feature data, have been useful in recent years for predicting cellular targets and mechanisms of action (MoAs) for different chemicals and novel drugs. However, this approach has not been extensively used in environmental toxicology due to the lack of studies and established methods for performing this kind of assay in environmentally relevant species. Here, we developed a multiplexed algal cytological imaging (MACI) assay, based on the subcellular structures of the unicellular microalgae, Raphidocelis subcapitata, a toxicology and ecological model species. Several different herbicides and antibiotics with unique MoAs were exposed to R. subcapitata cells, and MACI was used to characterize cellular impacts by measuring subtle changes in their morphological features, including metrics of area, shape, quantity, fluorescence intensity, and granularity of individual subcellular components. This study demonstrates that MACI offers a quick and effective framework for characterizing complex phenotypic responses to environmental chemicals that can be used for determining their MoAs and identifying their cellular targets in plant-type organisms.
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Affiliation(s)
- Eric Ostovich
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53204, United States
| | - Rebecca Klaper
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53204, United States
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9
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Addis P, Bali U, Baron F, Campbell A, Harborne S, Jagger L, Milne G, Pearce M, Rosethorne EM, Satchell R, Swift D, Young B, Unitt JF. Key aspects of modern GPCR drug discovery. SLAS DISCOVERY : ADVANCING LIFE SCIENCES R & D 2024; 29:1-22. [PMID: 37625784 DOI: 10.1016/j.slasd.2023.08.007] [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: 04/13/2023] [Revised: 08/07/2023] [Accepted: 08/22/2023] [Indexed: 08/27/2023]
Abstract
G-protein-coupled receptors (GPCRs) are the largest and most versatile cell surface receptor family with a broad repertoire of ligands and functions. We've learned an enormous amount about discovering drugs of this receptor class since the first GPCR was cloned and expressed in 1986, such that it's now well-recognized that GPCRs are the most successful target class for approved drugs. Here we take the reader through a GPCR drug discovery journey from target to the clinic, highlighting the key learnings, best practices, challenges, trends and insights on discovering drugs that ultimately modulate GPCR function therapeutically in patients. The future of GPCR drug discovery is inspiring, with more desirable drug mechanisms and new technologies enabling the delivery of better and more successful drugs.
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Affiliation(s)
- Phil Addis
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Utsav Bali
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Frank Baron
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Adrian Campbell
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Steven Harborne
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Liz Jagger
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Gavin Milne
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Martin Pearce
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Elizabeth M Rosethorne
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Rupert Satchell
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Denise Swift
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - Barbara Young
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK
| | - John F Unitt
- Bioscience, Medicinal Chemistry, Pharmacology and Protein Science Departments, Sygnature Discovery Ltd, BioCity, Pennyfoot Street, Nottingham NG1 1GR, UK.
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10
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Ortiz-Perez A, Zhang M, Fitzpatrick LW, Izquierdo-Lozano C, Albertazzi L. Advanced optical imaging for the rational design of nanomedicines. Adv Drug Deliv Rev 2024; 204:115138. [PMID: 37980951 DOI: 10.1016/j.addr.2023.115138] [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: 06/09/2023] [Revised: 11/06/2023] [Accepted: 11/08/2023] [Indexed: 11/21/2023]
Abstract
Despite the enormous potential of nanomedicines to shape the future of medicine, their clinical translation remains suboptimal. Translational challenges are present in every step of the development pipeline, from a lack of understanding of patient heterogeneity to insufficient insights on nanoparticle properties and their impact on material-cell interactions. Here, we discuss how the adoption of advanced optical microscopy techniques, such as super-resolution optical microscopies, correlative techniques, and high-content modalities, could aid the rational design of nanocarriers, by characterizing the cell, the nanomaterial, and their interaction with unprecedented spatial and/or temporal detail. In this nanomedicine arena, we will discuss how the implementation of these techniques, with their versatility and specificity, can yield high volumes of multi-parametric data; and how machine learning can aid the rapid advances in microscopy: from image acquisition to data interpretation.
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Affiliation(s)
- Ana Ortiz-Perez
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Miao Zhang
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Laurence W Fitzpatrick
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Cristina Izquierdo-Lozano
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Lorenzo Albertazzi
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.
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11
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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] [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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12
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Lejal V, Cerisier N, Rouquié D, Taboureau O. Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis. Chem Res Toxicol 2023; 36:1456-1470. [PMID: 37652439 PMCID: PMC10523580 DOI: 10.1021/acs.chemrestox.2c00381] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Indexed: 09/02/2023]
Abstract
Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, ...) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.
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Affiliation(s)
- Vanille Lejal
- Université
Paris Cité, Inserm U1133, CNRS
UMR 8251, 75013, Paris, France
| | - Natacha Cerisier
- Université
Paris Cité, Inserm U1133, CNRS
UMR 8251, 75013, Paris, France
| | - David Rouquié
- Bayer
SAS, Bayer Crop Science, 355 rue Dostoïevski, CS 90153, 06906 Valbonne, Sophia-Antipolis, France
- Université
Côte d’Azur 3IA Interdisciplinary Institute in Artificial Intelligence, 06103 Nice Cedex, France
| | - Olivier Taboureau
- Université
Paris Cité, Inserm U1133, CNRS
UMR 8251, 75013, Paris, France
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13
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Trastulla L, Savino A, Beltrao P, Ciriano IC, Fenici P, Garnett MJ, Guerini I, Bigas NL, Mattaj I, Petsalaki E, Riva L, Tape CJ, Leeuwen JV, Sharma S, Vazquez F, Iorio F. Highlights from the 1st European cancer dependency map symposium and workshop. FEBS Lett 2023; 597:1921-1927. [PMID: 37487655 DOI: 10.1002/1873-3468.14699] [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: 07/06/2023] [Revised: 07/10/2023] [Accepted: 07/13/2023] [Indexed: 07/26/2023]
Abstract
The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap. The symposium aimed to facilitate interactions among participants across Europe, encourage idea exchange with leading experts, and present their work and future projects. Importantly, it sparked discussions on future endeavours, such as screening more complex cancer models and accounting for tumour evolution.
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Affiliation(s)
| | | | - Pedro Beltrao
- Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | | | | | | | | | | | | | | | | | | | | | | | - Francisca Vazquez
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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14
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McMahon CL, Esqueda M, Yu JJ, Wall G, Romo JA, Vila T, Chaturvedi A, Lopez-Ribot JL, Wormley F, Hung CY. Development of an Imaging Flow Cytometry Method for Fungal Cytological Profiling and Its Potential Application in Antifungal Drug Development. J Fungi (Basel) 2023; 9:722. [PMID: 37504711 PMCID: PMC10381375 DOI: 10.3390/jof9070722] [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: 10/13/2022] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 07/29/2023] Open
Abstract
Automated imaging techniques have been in increasing demand for the more advanced analysis and efficient characterization of cellular phenotypes. The success of the image-based profiling method hinges on assays that can rapidly and simultaneously capture a wide range of phenotypic features. We have developed an automated image acquisition method for fungal cytological profiling (FCP) using an imaging flow cytometer that can objectively measure over 250 features of a single fungal cell. Fungal cells were labeled with calcofluor white and FM4-64FX, which bind to the cell wall and lipophilic membrane, respectively. Images of single cells were analyzed using IDEAS® software. We first acquired FCPs of fungal cells treated with fluconazole, amphotericin B, and caspofungin, each with a distinct mode of action, to establish FCP databases of profiles associated with specific antifungal treatment. Once fully established, we investigated the potential application of this technique as a screening methodology to identify compounds with novel antifungal activity against Candida albicans and Cryptococcus neoformans. Altogether, we have developed a rapid, powerful, and novel image-profiling method for the phenotypic characterization of fungal cells, also with potential applications in antifungal drug development.
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Affiliation(s)
- Courtney L McMahon
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Marisol Esqueda
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Jieh-Juen Yu
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Gina Wall
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Jesus A Romo
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Taissa Vila
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Ashok Chaturvedi
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Jose L Lopez-Ribot
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Floyd Wormley
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Chiung-Yu Hung
- Department of Molecular Microbiology and Immunology and South Texas Center for Emerging Infectious Diseases, The University of Texas at San Antonio, San Antonio, TX 78249, USA
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15
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Pruteanu LL, Bender A. Using Transcriptomics and Cell Morphology Data in Drug Discovery: The Long Road to Practice. ACS Med Chem Lett 2023; 14:386-395. [PMID: 37077392 PMCID: PMC10107910 DOI: 10.1021/acsmedchemlett.3c00015] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/10/2023] [Indexed: 04/21/2023] Open
Abstract
Gene expression and cell morphology data are high-dimensional biological readouts of much recent interest for drug discovery. They are able to describe biological systems in different states (e.g., healthy and diseased), as well as biological systems before and after compound treatment, and they are hence useful for matching both spaces (e.g., for drug repurposing) as well as for characterizing compounds with respect to efficacy and safety endpoints. This Microperspective describes recent advances in this direction with a focus on applied drug discovery and drug repurposing, as well as outlining what else is needed to advance further, with a particular focus on better understanding the applicability domain of readouts and their relevance for decision making, which is currently often still unclear.
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Affiliation(s)
- Lavinia-Lorena Pruteanu
- Department
of Chemistry and Biology, North University
Center at Baia Mare, Technical University of Cluj-Napoca, Victoriei 76, 430122 Baia Mare, Romania
- Research
Center for Functional Genomics, Biomedicine, and Translational Medicine, “Iuliu Haţieganu” University
of Medicine and Pharmacy, 400337 Cluj-Napoca, Romania
| | - Andreas Bender
- Centre
for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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16
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Pognan F, Beilmann M, Boonen HCM, Czich A, Dear G, Hewitt P, Mow T, Oinonen T, Roth A, Steger-Hartmann T, Valentin JP, Van Goethem F, Weaver RJ, Newham P. The evolving role of investigative toxicology in the pharmaceutical industry. Nat Rev Drug Discov 2023; 22:317-335. [PMID: 36781957 PMCID: PMC9924869 DOI: 10.1038/s41573-022-00633-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/16/2022] [Indexed: 02/15/2023]
Abstract
For decades, preclinical toxicology was essentially a descriptive discipline in which treatment-related effects were carefully reported and used as a basis to calculate safety margins for drug candidates. In recent years, however, technological advances have increasingly enabled researchers to gain insights into toxicity mechanisms, supporting greater understanding of species relevance and translatability to humans, prediction of safety events, mitigation of side effects and development of safety biomarkers. Consequently, investigative (or mechanistic) toxicology has been gaining momentum and is now a key capability in the pharmaceutical industry. Here, we provide an overview of the current status of the field using case studies and discuss the potential impact of ongoing technological developments, based on a survey of investigative toxicologists from 14 European-based medium-sized to large pharmaceutical companies.
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Affiliation(s)
- Francois Pognan
- Discovery and Investigative Safety, Novartis Pharma AG, Basel, Switzerland.
| | - Mario Beilmann
- Nonclinical Drug Safety Germany, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Harrie C M Boonen
- Drug Safety, Dept of Exploratory Toxicology, Lundbeck A/S, Valby, Denmark
| | | | - Gordon Dear
- In Vitro In Vivo Translation, GlaxoSmithKline David Jack Centre for Research, Ware, UK
| | - Philip Hewitt
- Chemical and Preclinical Safety, Merck Healthcare KGaA, Darmstadt, Germany
| | - Tomas Mow
- Safety Pharmacology and Early Toxicology, Novo Nordisk A/S, Maaloev, Denmark
| | - Teija Oinonen
- Preclinical Safety, Orion Corporation, Espoo, Finland
| | - Adrian Roth
- Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland
| | | | | | - Freddy Van Goethem
- Predictive, Investigative & Translational Toxicology, Nonclinical Safety, Janssen Research & Development, Beerse, Belgium
| | - Richard J Weaver
- Innovation Life Cycle Management, Institut de Recherches Internationales Servier, Suresnes, France
| | - Peter Newham
- Clinical Pharmacology and Safety Sciences, AstraZeneca R&D, Cambridge, UK.
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17
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Dahlin JL, Hua BK, Zucconi BE, Nelson SD, Singh S, Carpenter AE, Shrimp JH, Lima-Fernandes E, Wawer MJ, Chung LPW, Agrawal A, O'Reilly M, Barsyte-Lovejoy D, Szewczyk M, Li F, Lak P, Cuellar M, Cole PA, Meier JL, Thomas T, Baell JB, Brown PJ, Walters MA, Clemons PA, Schreiber SL, Wagner BK. Reference compounds for characterizing cellular injury in high-content cellular morphology assays. Nat Commun 2023; 14:1364. [PMID: 36914634 PMCID: PMC10011410 DOI: 10.1038/s41467-023-36829-x] [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: 08/01/2022] [Accepted: 02/20/2023] [Indexed: 03/16/2023] Open
Abstract
Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.
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Grants
- R35 GM127045 NIGMS NIH HHS
- U01 CA272612 NCI NIH HHS
- T32 HL007627 NHLBI NIH HHS
- R37 GM062437 NIGMS NIH HHS
- S10 OD026839 NIH HHS
- R35 GM122481 NIGMS NIH HHS
- U01 DK123717 NIDDK NIH HHS
- Wellcome Trust
- R35 GM122547 NIGMS NIH HHS
- U01 CA217848 NCI NIH HHS
- K99 GM124357 NIGMS NIH HHS
- R35 GM149229 NIGMS NIH HHS
- This study was supported by the Ono Pharma Breakthrough Science Initiative Award (to BKW). Authors acknowledge the following financial support: JLD (NIH NHLBI, T32-HL007627); BKH (National Science Foundation, DGE1144152 and DGE1745303); BEZ (NIH NIGMS, K99-GM124357); SDN (Harvard University’s Graduate Prize Fellowship, Eli Lilly Graduate Fellowship in Chemistry); PA Cole (NIH NIGMS, R37-GM62437); SLS (NIGMS, R35-GM127045); BKW (Ono Pharma Foundation; NIH NIDDK, U01-DK123717); SS (NIH NIGMS, R35-GM122547). The authors gratefully acknowledge the use of the Opera Phenix High-Content/High-Throughput imaging system at the Broad Institute, funded by the NIH S10 grant OD026839. This research was supported in part by the Intramural/Extramural research program of the NCATS, NIH.
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Affiliation(s)
- Jayme L Dahlin
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA.
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA.
| | - Bruce K Hua
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Beth E Zucconi
- Division of Genetics, Departments of Medicine and Biological Chemistry and Molecular Pharmacology, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | | | | | | | - Jonathan H Shrimp
- Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | | | - Mathias J Wawer
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Lawrence P W Chung
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Ayushi Agrawal
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | | | | | - Magdalena Szewczyk
- Structural Genomics Consortium, University of Toronto, Toronto, ON, Canada
| | - Fengling Li
- Structural Genomics Consortium, University of Toronto, Toronto, ON, Canada
| | - Parnian Lak
- Department of Pharmaceutical Chemistry and Quantitative Biology Institute, University of California San Francisco, San Francisco, CA, USA
| | - Matthew Cuellar
- Institute for Therapeutics Discovery and Development, University of Minnesota, Minneapolis, MN, USA
| | - Philip A Cole
- Division of Genetics, Departments of Medicine and Biological Chemistry and Molecular Pharmacology, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | - Jordan L Meier
- Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - Tim Thomas
- Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia
| | - Jonathan B Baell
- Medicinal Chemistry Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
| | - Peter J Brown
- Structural Genomics Consortium, University of Toronto, Toronto, ON, Canada
| | - Michael A Walters
- Institute for Therapeutics Discovery and Development, University of Minnesota, Minneapolis, MN, USA
| | - Paul A Clemons
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Stuart L Schreiber
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Bridget K Wagner
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA.
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18
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Hutter V, Hopper S, Skamarauskas J, Hoffman E. High content analysis of in vitro alveolar macrophage responses can provide mechanistic insight for inhaled product safety assessment. Toxicol In Vitro 2023; 86:105506. [PMID: 36330929 DOI: 10.1016/j.tiv.2022.105506] [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: 06/06/2022] [Revised: 10/11/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
Assessing the safety of inhaled substances in the alveolar region of the lung requires an understanding of how the respired material interacts with both physical and immunological barriers. Human alveolar-like macrophages in vitro provide a platform to assess the immunological response in the airways and may better inform the understanding of a response to an inhaled challenge being adaptive or adverse. The aim of this study was to determine if a morphometric phenotyping approach could discriminate between different inhaled nicotine products and indicate the potential mechanism of toxicity of a substance. Cigarette smoke (CS) and e-liquids extracted into cell culture medium were applied to human alveolar-like macrophages in mono-culture (ImmuONE™) and co-culture (ImmuLUNG™) to test the hypothesis. Phenotype profiling of cell responses was highly reproducible and clearly distinguished the different responses to CS and e-liquids. Whilst the phenotypes of untreated macrophages were similar regardless of culture condition, macrophages cultured in the presence of epithelial cells were more sensitive to CS-induced changes related to cell size and vacuolation processes. This technique demonstrated phenotypical observations typical for CS exposure and indicative of the established mechanisms of toxicity. The technique provides a rapid screening approach to determine detailed immunological responses in the airways which can be linked to potentially adverse pathways and support inhalation safety assessment.
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Affiliation(s)
- V Hutter
- ImmuONE Ltd, Science Building, College Lane, Hatfield, Herts AL10 9AB, UK; Centre for Topical Drug Delivery and Toxicology, University of Hertfordshire, College Lane Campus, Hatfield, Herts AL10 9AB, UK.
| | - S Hopper
- Thornton & Ross Ltd, Linthwaite, Huddersfield HD7 5QH, UK; School of Clinical and Applied Sciences, Leeds Becket University, City Campus, Woodhouse Lane, Leeds LS1 3HE, UK
| | - J Skamarauskas
- Centre for Topical Drug Delivery and Toxicology, University of Hertfordshire, College Lane Campus, Hatfield, Herts AL10 9AB, UK
| | - E Hoffman
- ImmuONE Ltd, Science Building, College Lane, Hatfield, Herts AL10 9AB, UK
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19
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Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection. Commun Biol 2022; 5:858. [PMID: 35999457 PMCID: PMC9399120 DOI: 10.1038/s42003-022-03763-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/25/2022] [Indexed: 12/05/2022] Open
Abstract
Mitochondrial toxicity is an important safety endpoint in drug discovery. Models based solely on chemical structure for predicting mitochondrial toxicity are currently limited in accuracy and applicability domain to the chemical space of the training compounds. In this work, we aimed to utilize both -omics and chemical data to push beyond the state-of-the-art. We combined Cell Painting and Gene Expression data with chemical structural information from Morgan fingerprints for 382 chemical perturbants tested in the Tox21 mitochondrial membrane depolarization assay. We observed that mitochondrial toxicants differ from non-toxic compounds in morphological space and identified compound clusters having similar mechanisms of mitochondrial toxicity, thereby indicating that morphological space provides biological insights related to mechanisms of action of this endpoint. We further showed that models combining Cell Painting, Gene Expression features and Morgan fingerprints improved model performance on an external test set of 244 compounds by 60% (in terms of F1 score) and improved extrapolation to new chemical space. The performance of our combined models was comparable with dedicated in vitro assays for mitochondrial toxicity. Our results suggest that combining chemical descriptors with biological readouts enhances the detection of mitochondrial toxicants, with practical implications in drug discovery. Cell Painting, gene expression, and chemical structural data are used to examine the differences between mitochondrial toxicants and non-toxicants and enhance the detection of mitotoxic compounds for future drug discovery.
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20
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Rietdijk J, Aggarwal T, Georgieva P, Lapins M, Carreras-Puigvert J, Spjuth O. Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 832:155058. [PMID: 35390365 DOI: 10.1016/j.scitotenv.2022.155058] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/01/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
Environmental chemicals are commonly studied one at a time, and there is a need to advance our understanding of the effect of exposure to their combinations. Here we apply high-content microscopy imaging of cells stained with multiplexed dyes (Cell Painting) to profile the effects of Cetyltrimethylammonium bromide (CTAB), Bisphenol A (BPA), and Dibutyltin dilaurate (DBTDL) exposure on four human cell lines; both individually and in all combinations. We show that morphological features can be used with multivariate data analysis to discern between exposures from individual compounds, concentrations, and combinations. CTAB and DBTDL induced concentration-dependent morphological changes across the four cell lines, and BPA exacerbated morphological effects when combined with CTAB and DBTDL. Combined exposure to CTAB and BPA induced changes in the ER, Golgi apparatus, nucleoli and cytoplasmic RNA in one of the cell lines. Different responses between cell lines indicate that multiple cell types are needed when assessing combination effects. The rapid and relatively low-cost experiments combined with high information content make Cell Painting an attractive methodology for future studies of combination effects. All data in the study is made publicly available on Figshare.
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Affiliation(s)
- Jonne Rietdijk
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Tanya Aggarwal
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Polina Georgieva
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Maris Lapins
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Jordi Carreras-Puigvert
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden.
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden.
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21
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Label-free prediction of cell painting from brightfield images. Sci Rep 2022; 12:10001. [PMID: 35705591 PMCID: PMC9200748 DOI: 10.1038/s41598-022-12914-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 05/18/2022] [Indexed: 11/08/2022] Open
Abstract
Cell Painting is a high-content image-based assay applied in drug discovery to predict bioactivity, assess toxicity and understand mechanisms of action of chemical and genetic perturbations. We investigate label-free Cell Painting by predicting the five fluorescent Cell Painting channels from brightfield input. We train and validate two deep learning models with a dataset representing 17 batches, and we evaluate on batches treated with compounds from a phenotypic set. The mean Pearson correlation coefficient of the predicted images across all channels is 0.84. Without incorporating features into the model training, we achieved a mean correlation of 0.45 with ground truth features extracted using a segmentation-based feature extraction pipeline. Additionally, we identified 30 features which correlated greater than 0.8 to the ground truth. Toxicity analysis on the label-free Cell Painting resulted a sensitivity of 62.5% and specificity of 99.3% on images from unseen batches. We provide a breakdown of the feature profiles by channel and feature type to understand the potential and limitations of label-free morphological profiling. We demonstrate that label-free Cell Painting has the potential to be used for downstream analyses and could allow for repurposing imaging channels for other non-generic fluorescent stains of more targeted biological interest.
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22
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Nyffeler J, Willis C, Harris FR, Taylor LW, Judson R, Everett LJ, Harrill JA. Combining phenotypic profiling and targeted RNA-Seq reveals linkages between transcriptional perturbations and chemical effects on cell morphology: Retinoic acid as an example. Toxicol Appl Pharmacol 2022; 444:116032. [PMID: 35483669 PMCID: PMC10894461 DOI: 10.1016/j.taap.2022.116032] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 10/18/2022]
Abstract
The United States Environmental Protection Agency has proposed a tiered testing strategy for chemical hazard evaluation based on new approach methods (NAMs). The first tier includes in vitro profiling assays applicable to many (human) cell types, such as high-throughput transcriptomics (HTTr) and high-throughput phenotypic profiling (HTPP). The goals of this study were to: (1) harmonize the seeding density of U-2 OS human osteosarcoma cells for use in both assays; (2) compare HTTr- versus HTPP-derived potency estimates for 11 mechanistically diverse chemicals; (3) identify candidate reference chemicals for monitoring assay performance in future screens; and (4) characterize the transcriptional and phenotypic changes in detail for all-trans retinoic acid (ATRA) as a model compound known for its adverse effects on osteoblast differentiation. The results of this evaluation showed that (1) HTPP conducted at low (400 cells/well) and high (3000 cells/well) seeding densities yielded comparable potency estimates and similar phenotypic profiles for the tested chemicals; (2) HTPP and HTTr resulted in comparable potency estimates for changes in cellular morphology and gene expression, respectively; (3) three test chemicals (etoposide, ATRA, dexamethasone) produced concentration-dependent effects on cellular morphology and gene expression that were consistent with known modes-of-action, demonstrating their suitability for use as reference chemicals for monitoring assay performance; and (4) ATRA produced phenotypic changes that were highly similar to other retinoic acid receptor activators (AM580, arotinoid acid) and some retinoid X receptor activators (bexarotene, methoprene acid). This phenotype was observed concurrently with autoregulation of the RARB gene. Both effects were prevented by pre-treating U-2 OS cells with pharmacological antagonists of their respective receptors. Thus, the observed phenotype could be considered characteristic of retinoic acid pathway activation in U-2 OS cells. These findings lay the groundwork for combinatorial screening of chemicals using HTTr and HTPP to generate complementary information for the first tier of a NAM-based chemical hazard evaluation strategy.
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Affiliation(s)
- Johanna Nyffeler
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America; Oak Ridge Institute for Science and Education (ORISE) Postdoctoral Fellow, Oak Ridge, TN 37831, United States of America
| | - Clinton Willis
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Felix R Harris
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America; Oak Ridge Associated Universities (ORAU) National Student Services Contractor, Oak Ridge, TN 37831, United States of America
| | - Laura W Taylor
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Richard Judson
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Logan J Everett
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Joshua A Harrill
- Center for Computational Toxicology & Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America.
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Alijagic A, Engwall M, Särndahl E, Karlsson H, Hedbrant A, Andersson L, Karlsson P, Dalemo M, Scherbak N, Färnlund K, Larsson M, Persson A. Particle Safety Assessment in Additive Manufacturing: From Exposure Risks to Advanced Toxicology Testing. FRONTIERS IN TOXICOLOGY 2022; 4:836447. [PMID: 35548681 PMCID: PMC9081788 DOI: 10.3389/ftox.2022.836447] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
Additive manufacturing (AM) or industrial three-dimensional (3D) printing drives a new spectrum of design and production possibilities; pushing the boundaries both in the application by production of sophisticated products as well as the development of next-generation materials. AM technologies apply a diversity of feedstocks, including plastic, metallic, and ceramic particle powders with distinct size, shape, and surface chemistry. In addition, powders are often reused, which may change the particles' physicochemical properties and by that alter their toxic potential. The AM production technology commonly relies on a laser or electron beam to selectively melt or sinter particle powders. Large energy input on feedstock powders generates several byproducts, including varying amounts of virgin microparticles, nanoparticles, spatter, and volatile chemicals that are emitted in the working environment; throughout the production and processing phases. The micro and nanoscale size may enable particles to interact with and to cross biological barriers, which could, in turn, give rise to unexpected adverse outcomes, including inflammation, oxidative stress, activation of signaling pathways, genotoxicity, and carcinogenicity. Another important aspect of AM-associated risks is emission/leakage of mono- and oligomers due to polymer breakdown and high temperature transformation of chemicals from polymeric particles, both during production, use, and in vivo, including in target cells. These chemicals are potential inducers of direct toxicity, genotoxicity, and endocrine disruption. Nevertheless, understanding whether AM particle powders and their byproducts may exert adverse effects in humans is largely lacking and urges comprehensive safety assessment across the entire AM lifecycle-spanning from virgin and reused to airborne particles. Therefore, this review will detail: 1) brief overview of the AM feedstock powders, impact of reuse on particle physicochemical properties, main exposure pathways and protective measures in AM industry, 2) role of particle biological identity and key toxicological endpoints in the particle safety assessment, and 3) next-generation toxicology approaches in nanosafety for safety assessment in AM. Altogether, the proposed testing approach will enable a deeper understanding of existing and emerging particle and chemical safety challenges and provide a strategy for the development of cutting-edge methodologies for hazard identification and risk assessment in the AM industry.
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Affiliation(s)
- Andi Alijagic
- Man-Technology-Environment Research Center (MTM), Örebro University, Örebro, Sweden
- Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Magnus Engwall
- Man-Technology-Environment Research Center (MTM), Örebro University, Örebro, Sweden
| | - Eva Särndahl
- Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Helen Karlsson
- Department of Health, Medicine and Caring Sciences, Occupational and Environmental Medicine Center in Linköping, Linköping University, Linköping, Sweden
| | - Alexander Hedbrant
- Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Lena Andersson
- Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Occupational and Environmental Medicine, Örebro University, Örebro, Sweden
| | - Patrik Karlsson
- Department of Mechanical Engineering, Örebro University, Örebro, Sweden
| | | | - Nikolai Scherbak
- Man-Technology-Environment Research Center (MTM), Örebro University, Örebro, Sweden
| | | | - Maria Larsson
- Man-Technology-Environment Research Center (MTM), Örebro University, Örebro, Sweden
| | - Alexander Persson
- Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
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24
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Culbreth M, Nyffeler J, Willis C, Harrill JA. Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening. FRONTIERS IN TOXICOLOGY 2022; 3:803987. [PMID: 35295155 PMCID: PMC8915842 DOI: 10.3389/ftox.2021.803987] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Studies in in vivo rodent models have been the accepted approach by regulatory agencies to evaluate potential developmental neurotoxicity (DNT) of chemicals for decades. These studies, however, are inefficient and cannot meet the demand for the thousands of chemicals that need to be assessed for DNT hazard. As such, several in vitro new approach methods (NAMs) have been developed to circumvent limitations of these traditional studies. The DNT NAMs, some of which utilize human-derived cell models, are intended to be employed in a testing battery approach, each focused on a specific neurodevelopmental process. The need for multiple assays, however, to evaluate each process can prolong testing and prioritization of chemicals for more in depth assessments. Therefore, a multi-endpoint higher-throughput approach to assess DNT hazard potential would be of value. Accordingly, we have adapted a high-throughput phenotypic profiling (HTPP) approach for use with human-derived neural progenitor (hNP1) cells. HTPP is a fluorescence-based assay that quantitatively measures alterations in cellular morphology. This approach, however, required optimization of several laboratory procedures prior to chemical screening. First, we had to determine an appropriate cell plating density in 384-well plates. We then had to identify the minimum laminin concentration required for optimal cell growth and attachment. And finally, we had to evaluate whether addition of antibiotics to the culture medium would alter cellular morphology. We selected 6,000 cells/well as an appropriate plating density, 20 µg/ml laminin for optimal cell growth and attachment, and antibiotic addition in the culture medium. After optimizing hNP1 cell culture conditions for HTPP, it was then necessary to select appropriate in-plate assay controls from a reference chemical set. These reference chemicals were previously demonstrated to elicit unique phenotypic profiles in various other cell types. Aphidicolin, bafilomycin A1, berberine chloride, and cucurbitacin I induced robust phenotypic profiles as compared to dimethyl sulfoxide vehicle control in the hNP1 cells, and thus can be employed as in-plate assay controls for subsequent chemical screens. We have optimized HTPP for hNP1 cells, and consequently this approach can now be assessed as a potential NAM for DNT hazard evaluation and results compared to previously developed DNT assays.
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Affiliation(s)
- Megan Culbreth
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, United States
| | - Johanna Nyffeler
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, United States
- Oak Ridge Institute for Science and Education (ORISE) Postdoctoral Fellow, Oak Ridge, TN, United States
| | - Clinton Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, United States
| | - Joshua A. Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC, United States
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25
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Rietdijk J, Tampere M, Pettke A, Georgiev P, Lapins M, Warpman-Berglund U, Spjuth O, Puumalainen MR, Carreras-Puigvert J. A phenomics approach for antiviral drug discovery. BMC Biol 2021; 19:156. [PMID: 34334126 PMCID: PMC8325993 DOI: 10.1186/s12915-021-01086-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 07/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. RESULTS We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. CONCLUSIONS The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery.
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Affiliation(s)
- Jonne Rietdijk
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24, Uppsala, Sweden
| | - Marianna Tampere
- Department of Oncology and Pathology and Science for Life Laboratory, Karolinska Institutet, SE-171 76, Stockholm, Sweden
- National Veterinary Institute, SE-756 51, Uppsala, Sweden
| | - Aleksandra Pettke
- Department of Oncology and Pathology and Science for Life Laboratory, Karolinska Institutet, SE-171 76, Stockholm, Sweden
| | - Polina Georgiev
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24, Uppsala, Sweden
| | - Maris Lapins
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24, Uppsala, Sweden
| | - Ulrika Warpman-Berglund
- Department of Oncology and Pathology and Science for Life Laboratory, Karolinska Institutet, SE-171 76, Stockholm, Sweden
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24, Uppsala, Sweden
| | - Marjo-Riitta Puumalainen
- Department of Oncology and Pathology and Science for Life Laboratory, Karolinska Institutet, SE-171 76, Stockholm, Sweden
| | - Jordi Carreras-Puigvert
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24, Uppsala, Sweden.
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26
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Fennell M, Johnston PA. High-Content Imaging and Informatics: A Joint Special Issue with Society for Biomolecular Imaging and Informatics and SLAS. SLAS DISCOVERY 2021; 25:668-671. [PMID: 32687017 DOI: 10.1177/2472555220937652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
| | - Paul A Johnston
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, UPMC Hillman Cancer Center, Pittsburgh, PA, USA
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27
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Hughes RE, Elliott RJR, Dawson JC, Carragher NO. High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need. Cell Chem Biol 2021; 28:338-355. [PMID: 33740435 DOI: 10.1016/j.chembiol.2021.02.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/10/2020] [Accepted: 02/18/2021] [Indexed: 02/07/2023]
Abstract
Conventional thinking in modern drug discovery postulates that the design of highly selective molecules which act on a single disease-associated target will yield safer and more effective drugs. However, high clinical attrition rates and the lack of progress in developing new effective treatments for many important diseases of unmet therapeutic need challenge this hypothesis. This assumption also impinges upon the efficiency of target agnostic phenotypic drug discovery strategies, where early target deconvolution is seen as a critical step to progress phenotypic hits. In this review we provide an overview of how emerging phenotypic and pathway-profiling technologies integrate to deconvolute the mechanism-of-action of phenotypic hits. We propose that such in-depth mechanistic profiling may support more efficient phenotypic drug discovery strategies that are designed to more appropriately address complex heterogeneous diseases of unmet need.
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Affiliation(s)
- Rebecca E Hughes
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, UK
| | - Richard J R Elliott
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, UK
| | - John C Dawson
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, UK
| | - Neil O Carragher
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, UK.
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28
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Dahlin JL, Auld DS, Rothenaigner I, Haney S, Sexton JZ, Nissink JWM, Walsh J, Lee JA, Strelow JM, Willard FS, Ferrins L, Baell JB, Walters MA, Hua BK, Hadian K, Wagner BK. Nuisance compounds in cellular assays. Cell Chem Biol 2021; 28:356-370. [PMID: 33592188 PMCID: PMC7979533 DOI: 10.1016/j.chembiol.2021.01.021] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 01/02/2021] [Accepted: 01/27/2021] [Indexed: 12/17/2022]
Abstract
Compounds that exhibit assay interference or undesirable mechanisms of bioactivity ("nuisance compounds") are routinely encountered in cellular assays, including phenotypic and high-content screening assays. Much is known regarding compound-dependent assay interferences in cell-free assays. However, despite the essential role of cellular assays in chemical biology and drug discovery, there is considerably less known about nuisance compounds in more complex cell-based assays. In our view, a major obstacle to realizing the full potential of chemical biology will not just be difficult-to-drug targets or even the sheer number of targets, but rather nuisance compounds, due to their ability to waste significant resources and erode scientific trust. In this review, we summarize our collective academic, government, and industry experiences regarding cellular nuisance compounds. We describe assay design strategies to mitigate the impact of nuisance compounds and suggest best practices to efficiently address these compounds in complex biological settings.
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Affiliation(s)
- Jayme L Dahlin
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD 20850, USA.
| | - Douglas S Auld
- Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA
| | - Ina Rothenaigner
- Assay Development and Screening Platform, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany
| | - Steve Haney
- Indiana Biosciences Research Institute, Indianapolis, IN 46202, USA
| | - Jonathan Z Sexton
- Department of Internal Medicine, Gastroenterology, Michigan Medicine at the University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Jarrod Walsh
- Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Alderley Park SK10 4TG, UK
| | | | | | | | - Lori Ferrins
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
| | - Jonathan B Baell
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, People's Republic of China
| | - Michael A Walters
- Institute for Therapeutics Discovery and Development, University of Minnesota, Minneapolis, MN 55414, USA
| | - Bruce K Hua
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02140, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02140, USA
| | - Kamyar Hadian
- Assay Development and Screening Platform, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany
| | - Bridget K Wagner
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02140, USA
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29
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Ziegler S, Sievers S, Waldmann H. Morphological profiling of small molecules. Cell Chem Biol 2021; 28:300-319. [PMID: 33740434 DOI: 10.1016/j.chembiol.2021.02.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/22/2021] [Accepted: 02/17/2021] [Indexed: 12/30/2022]
Abstract
Profiling approaches such as gene expression or proteome profiling generate small-molecule bioactivity profiles that describe a perturbed cellular state in a rather unbiased manner and have become indispensable tools in the evaluation of bioactive small molecules. Automated imaging and image analysis can record morphological alterations that are induced by small molecules through the detection of hundreds of morphological features in high-throughput experiments. Thus, morphological profiling has gained growing attention in academia and the pharmaceutical industry as it enables detection of bioactivity in compound collections in a broader biological context in the early stages of compound development and the drug-discovery process. Profiling may be used successfully to predict mode of action or targets of unexplored compounds and to uncover unanticipated activity for already characterized small molecules. Here, we review the reported approaches to morphological profiling and the kind of bioactivity that can be detected so far and, thus, predicted.
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Affiliation(s)
- Slava Ziegler
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.
| | - Sonja Sievers
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany
| | - Herbert Waldmann
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany; Technical University Dortmund, Faculty of Chemistry and Chemical Biology, Otto-Hahn-Strasse 6, 44227 Dortmund, Germany.
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30
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Seal S, Yang H, Vollmers L, Bender A. Comparison of Cellular Morphological Descriptors and Molecular Fingerprints for the Prediction of Cytotoxicity- and Proliferation-Related Assays. Chem Res Toxicol 2021; 34:422-437. [PMID: 33522793 DOI: 10.1021/acs.chemrestox.0c00303] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Cell morphology features, such as those from the Cell Painting assay, can be generated at relatively low costs and represent versatile biological descriptors of a system and thereby compound response. In this study, we explored cell morphology descriptors and molecular fingerprints, separately and in combination, for the prediction of cytotoxicity- and proliferation-related in vitro assay endpoints. We selected 135 compounds from the MoleculeNet ToxCast benchmark data set which were annotated with Cell Painting readouts, where the relatively small size of the data set is due to the overlap of required annotations. We trained Random Forest classification models using nested cross-validation and Cell Painting descriptors, Morgan and ErG fingerprints, and their combinations. While using leave-one-cluster-out cross-validation (with clusters based on physicochemical descriptors), models using Cell Painting descriptors achieved higher average performance over all assays (Balanced Accuracy of 0.65, Matthews Correlation Coefficient of 0.28, and AUC-ROC of 0.71) compared to models using ErG fingerprints (BA 0.55, MCC 0.09, and AUC-ROC 0.60) and Morgan fingerprints alone (BA 0.54, MCC 0.06, and AUC-ROC 0.56). While using random shuffle splits, the combination of Cell Painting descriptors with ErG and Morgan fingerprints further improved balanced accuracy on average by 8.9% (in 9 out of 12 assays) and 23.4% (in 8 out of 12 assays) compared to using only ErG and Morgan fingerprints, respectively. Regarding feature importance, Cell Painting descriptors related to nuclei texture, granularity of cells, and cytoplasm as well as cell neighbors and radial distributions were identified to be most contributing, which is plausible given the endpoint considered. We conclude that cell morphological descriptors contain complementary information to molecular fingerprints which can be used to improve the performance of predictive cytotoxicity models, in particular in areas of novel structural space.
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Affiliation(s)
- Srijit Seal
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Hongbin Yang
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Luis Vollmers
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Andreas Bender
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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31
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Nyffeler J, Haggard DE, Willis C, Setzer RW, Judson R, Paul-Friedman K, Everett LJ, Harrill JA. Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data. SLAS DISCOVERY 2020; 26:292-308. [PMID: 32862757 DOI: 10.1177/2472555220950245] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.
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Affiliation(s)
- Johanna Nyffeler
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Clinton Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Associated Universities (ORAU), Oak Ridge, TN, USA
| | - R Woodrow Setzer
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Richard Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Katie Paul-Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
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