Cell painting is a powerful technique in biological research that is transforming how new medicines are discovered. It allows observation and measurement of detailed changes within cells, offering insights into how cells respond to different conditions. This method helps scientists identify potential drug candidates and understand their effects at a cellular level.
What is Cell Painting
Cell painting is a high-throughput, image-based assay that uses fluorescent dyes to label various parts of a cell. This process “paints” different organelles and cellular components, such as the nucleus, mitochondria, cytoskeleton, endoplasmic reticulum, and nucleoli, creating a comprehensive visual representation of the cell’s internal organization.
By staining these components, cell painting generates a unique, multidimensional “fingerprint” or “signature” of a cell’s state. This signature reflects the cell’s morphology and internal organization, revealing how cells respond to various treatments or experimental conditions.
The technique allows researchers to capture a broad overview of cellular morphology and organization, providing a rich dataset of information. This comprehensive view helps in understanding the subtle changes that might occur within cells due to different perturbations. Ultimately, it provides a phenotypic profile that can be used to compare and categorize cell responses.
How Cell Painting Works
The cell painting process begins by growing cells in multi-well plates, often 384-well plates, for high-throughput experiments. Cells are then treated with various chemical compounds or genetic perturbations. After incubation, the cells are fixed to preserve their morphology.
Following fixation, the cells are stained with a specific set of fluorescent dyes:
Hoechst dye labels DNA in the nucleus.
MitoTracker stains the mitochondria.
Phalloidin highlights actin in the cytoskeleton.
Concanavalin A targets the endoplasmic reticulum.
SYTO dyes visualize nucleoli and cytoplasmic RNA.
Once stained, automated high-content microscopy systems are used to acquire images of the “painted” cells across multiple fluorescent channels. This imaging process generates vast datasets of cellular images, capturing the detailed morphology of thousands of cells for subsequent analysis.
Cell Painting’s Role in Drug Discovery
Cell painting plays a significant role in phenotypic screening, where compounds are identified based on desired cellular changes rather than targeting a single protein. This approach allows for the discovery of novel drug candidates by observing how compounds alter the overall cellular state, exploring broader biological effects.
The technique can help elucidate the mechanism of action for compounds, even when the initial target is unknown. By comparing the phenotypic profiles of new compounds to those of compounds with known mechanisms, researchers can infer similar biological pathways or targets. For example, if an unknown compound produces a cellular signature similar to a compound known to affect mitochondrial function, it suggests a shared mechanism.
Cell painting can also reveal off-target effects, which are unintended interactions of a compound. These off-target effects can contribute to a drug’s side effects or toxicity. The comprehensive morphological data generated by cell painting can highlight these unwanted cellular changes early in the discovery process, helping to deselect problematic compounds.
Cell painting facilitates drug repurposing by matching the cellular signatures of existing drugs or compounds with unknown activities to those of known compounds or disease phenotypes. This allows researchers to identify new uses for approved drugs, potentially accelerating their development. The method’s ability to capture subtle cellular changes provides a rich basis for such comparisons.
This method offers advantages over traditional target-based screening, which may miss compounds that act through novel or complex biological pathways. Cell painting provides an unbiased, holistic view of cellular responses, increasing the chances of discovering new biology and innovative therapeutic approaches. It can also be adapted to various cell types, including cancer cell lines or hepatocyte-derived cells.
Insights from Cell Painting Data
Once high-resolution images are acquired, computational tools extract quantitative features from the “painted” organelles. This involves measuring aspects like cell size, shape, texture, and the intensity of the fluorescent dyes within different compartments. Automated image analysis software, including CellProfiler, is commonly used for this.
These extracted numerical features, often thousands per cell, are then subjected to advanced data analysis, leveraging machine learning and artificial intelligence algorithms. These methods identify subtle patterns and relationships within vast datasets, predicting the activity, safety, and toxicity of unknown compounds.
The data analysis can involve clustering compounds with similar effects, predicting compound function, and identifying potential toxicity. By comparing the morphological profiles of treated cells to those of control cells or cells treated with known compounds, researchers can gain deeper insights into how a drug affects cellular processes. This computational interpretation ultimately guides the selection of promising drug candidates for further development.