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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Image-Based Profiling in Live Cells Using Live Cell Painting

Shantanu Singh, Thaís Moraes-Lacerda, Mariana Rodrigues-da-Silva, Marcelo De Jesus
2 citations
BIO-PROTOCOL
Cell Image Analysis Techniques
3.27
article

Image-Based Profiling in Live Cells Using Live Cell Painting

Shantanu Singh, Thaís Moraes-Lacerda, Mariana Rodrigues-da-Silva, Marcelo De Jesus
article en
2 citations

Abstract

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.

BIO-PROTOCOLVol. 15(1381)
Broad Institute (US), Universidade Estadual de Campinas (UNICAMP) (BR)
Openalex Percentile: Top 7%
Cell Image Analysis Techniques
3.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.