Best Practices for Cell Painting Morphologic Profiling – Every Cell in Focus

Abstract This study details best practices for high-content screening (HCS) using the cell painting (CP) technique to enhance drug discovery and biomedical research. HCS, an automated fluorescence microscopy method, offers a detailed analysis of cellular responses by capturing multidimensional data on cellular morphology, protein expression, localization, and function. The CP technique involves staining cells with specific fluorescent dyes and analyzing them with high-resolution fluorescence microscopy. It is particularly effective in generating drug-specific phenotypic fingerprints or “phenoprints,” providing deeper insights into drug mechanisms. Strategies to enhance CP performance include using water immersion and high NA (numerical aperture) objective lenses, large sCMOS detectors, and confocal imaging with maximum intensity projection (MIP) imaging. These strategies are pivotal for producing high-quality images for accurate morphological analysis. This study addresses some of the challenges in standardizing image and data acquisition in CP and identifies optimal acquisition parameters using the Yokogawa CellVoyager CV8000. The results emphasize the critical role of optimizing the signal-to-background ratio in fluorescence imaging by adjusting laser power and camera exposure time. This optimization is essential for enhancing signal detection, reducing background noise and photobleaching, and improving image analysis and reproducibility from experiment to experiment. By refining data acquisition practices and utilizing sophisticated imaging technologies, one can achieve superior cellular feature data, leading to more precise and reliable analyses in drug discovery and disease modeling.

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Publication Details

Journal
Microscopy Today
Published
2024-11-01
DOI
https://doi.org/10.1093/mictod/qaae099
Primary Topic
Cell Image Analysis Techniques
Type
article
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Best Practices for Cell Painting Morphologic Profiling – Every Cell in Focus

Jonathan Z. Sexton, Sophia R. Meyer, Mai Hagimoto, Mahomi Suzuki et al.
Microscopy Today
Cell Image Analysis Techniques
article

Best Practices for Cell Painting Morphologic Profiling – Every Cell in Focus

Jonathan Z. Sexton, Sophia R. Meyer, Mai Hagimoto, Mahomi Suzuki, Kevin Jan
article en

Abstract

Abstract This study details best practices for high-content screening (HCS) using the cell painting (CP) technique to enhance drug discovery and biomedical research. HCS, an automated fluorescence microscopy method, offers a detailed analysis of cellular responses by capturing multidimensional data on cellular morphology, protein expression, localization, and function. The CP technique involves staining cells with specific fluorescent dyes and analyzing them with high-resolution fluorescence microscopy. It is particularly effective in generating drug-specific phenotypic fingerprints or “phenoprints,” providing deeper insights into drug mechanisms. Strategies to enhance CP performance include using water immersion and high NA (numerical aperture) objective lenses, large sCMOS detectors, and confocal imaging with maximum intensity projection (MIP) imaging. These strategies are pivotal for producing high-quality images for accurate morphological analysis. This study addresses some of the challenges in standardizing image and data acquisition in CP and identifies optimal acquisition parameters using the Yokogawa CellVoyager CV8000. The results emphasize the critical role of optimizing the signal-to-background ratio in fluorescence imaging by adjusting laser power and camera exposure time. This optimization is essential for enhancing signal detection, reducing background noise and photobleaching, and improving image analysis and reproducibility from experiment to experiment. By refining data acquisition practices and utilizing sophisticated imaging technologies, one can achieve superior cellular feature data, leading to more precise and reliable analyses in drug discovery and disease modeling.

Microscopy TodayVol. 32(6)
University of Michigan (US), Michigan Medicine (US), Michigan Center for Translational Pathology (US), Yokogawa Electric (Japan) (JP)
Good health and well-being
Openalex Percentile: Top 85%
Cell Image Analysis Techniques
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