Cell Painting Assay2022-07-14T09:02:32-05:00
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What is Cell Painting?

Throughout history, humans have been attempting to tackle human disease from all sorts of perspectives using a variety of tools to help identify root causes. As our knowledge of medicine has evolved and advances in technology helping to bridge gaps, we’ve been able to look deeper and deeper into the body to help paint an increasingly representative image of what is taking place at the cellular level. One such sophisticated, advanced technique in the field of microscopy is Cell Painting. In a nutshell, cell painting is a high-content, multiplexed image-based assay that is utilized for cytological profiling where several compartments of the cell are “painted” with a variety of organelle specific stains. When performed, phenotypic examination of physiological, metabolic, or epigenetic perturbations in different cellular compartments can be visualized. The resulting data can be analyzed using hundreds to thousands of parameters, in which phenotypic clustering will be independent of a known target. This ability to analyze large amounts of data and generate inferences in a “cast a wide net” approach, allows the assay to develop mechanical explanations as to how a particular drug is operating and affecting samples. 

Scientists at Visikol used this cell painting technique to elucidate the effects of a small molecule anti-proliferative therapeutic and cytochalasin B in cancer cells. The small molecule therapeutic used in this study  is a potent anti-neoplastic and anti-mitotic taxane drug, which binds to the N-terminus of β-tubulin and stabilizes microtubules arresting the cell cycle at the G2/M phase. Cytochalasin B is a cell-permeable mycotoxin. It strongly inhibits network formation by actin filaments. Below, a simplified representation of the assay’s workflow can be visualized.

Cell Painting Chart

Cell Painting Results

A549cells

A549 cells (lung adenocarcinoma cells) treated with different concentrations of anti-proliferation small molecule. (A) Merged images show nucleus (stained by Hoechst), cytoskeleton (stained by phalloidin), and  ER (stained by concanavalin A). (B) Merged images show nucleus (stained by Hoechst), cytoskeleton (stained by phalloidin), and  mitochondria (stained by Mito Tracker). The effect of the anti-proliferation small molecule on ER network can be seen from 2µM onwards. At 50µm the ER network formation and cytoskeleton is inhibited, and induces disintegration of mitochondria.

A549 cells treated with different concentrations of cytochalasin B.  (A) Merged images show nucleus (stained by Hoechst), cytoskeleton (stained by phalloidin), and  mitochondria (stained by Mito Tracker). (B) Merged images show nucleus (stained by Hoechst), cytoskeleton (stained by phalloidin), and  nucleoli (stained by SYTO14).  The effect of cytochalasin B on mitochondria can be seen from 0.2µM onwards. At 5µm, cytochalasin B inhibits cytoskeleton formation and disintegrates mitochondria and nucleoli.

A549-cells-treated

Significance of Variables 

Cell Painting Variables

Significance * Effect of Variables

Cell Painting Variables Chart

Control, Mitotracker, texture “low”

Mitrotracker Cell Painting

Anti-proliferation small molecule, 250uM, texture “high”

paclitaxel Cell Painting

Control, ER, median intensity “low”

Control Median Intensity

Anti-proliferation small molecule, 250uM, ER (concanavalin) median intensity “high”

Paclitaxel median intensity

Principal Component Analysis

Principal component Analysis

Volcano Plot

Volcano Plot

Fail Faster

Visikol’s future perspectives include incorporating high-throughput robotics and automation to seed cells and deliver compounds to microplates, improving high throughput technology in imaging and its computational image processing pipeline by integrating the data generated with AI and machine learning tools. Our approach aids pharmaceutical research in solving drug discovery problems with high specificity and sensitivity with high temporal and spatial resolutions. The idea at Visikol is to help the drug discovery process to “fail faster”. By being able to visualize tangible changes at the cellular level, researchers can more quickly discern whether a drug is performing effectively or not.

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