Image-Based Profiling in Live Cells Using Live Cell Painting
High-content analysis (HCA) is a powerful image-based approach for phenotypic profiling and drug discovery, enabling the extraction of multiparametric data from individual cells. Traditional HCA protocols often rely on fixed-cell imaging, with assays like cell painting widely adopted as standard. While these methods provide rich morphological information, the integration of live-cell imaging expands analytical capabilities by enabling the study of dynamic biological processes and real-time cellular responses. This protocol presents a simple, cost-effective, and scalable method for live-cell HCA using acridine orange (AO), a metachromatic fluorescent dye that highlights cellular organization by staining nucleic acids and acidic compartments. The assay provides visualization of distinct subcellular structures, including nuclei and cytoplasmic organelles, using a two-channel fluorescence readout. Compatible with high-throughput microscopy and computational analysis, the method supports diverse applications such as phenotypic screening, cytotoxicity assessment, and morphological profiling. By preserving cell viability and enabling dynamic, real-time measurements, this live-cell imaging approach complements existing fixed-cell assays and offers a versatile platform for uncovering complex cellular phenotypes. Key features • Builds upon Garcia-Fossa et al. [1], providing an accessible workflow for image-based profiling in live cells. • Enables phenotypic profiling and dose-response analysis of diverse perturbants, including small molecules, oligonucleotides, and nanoparticles. • Provides a live-cell framework to detect subtle, sublethal phenotypic changes, overcoming fixation assay limitations in toxicology and drug discovery. • Includes a streamlined analysis pipeline supporting efficient and reproducible interpretation of image-based data.
Authors
- Shantanu Singh (ORCID: https://orcid.org/0000-0003-3150-3025)
- Thaís Moraes-Lacerda (ORCID: https://orcid.org/0000-0002-9529-3349)
- Mariana Rodrigues-da-Silva
- Marcelo De Jesus (ORCID: https://orcid.org/0000-0003-0812-1491)
Institutions
- Broad Institute (US)
- Universidade Estadual de Campinas (UNICAMP) (BR)
Publication Details
- Journal
- BIO-PROTOCOL
- Published
- 2025-01-01
- DOI
- https://doi.org/10.21769/bioprotoc.5464
- Citations
- 2
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.27