Cell Painting: a decade of discovery and innovation in cellular imaging.

Modern quantitative image analysis techniques have enabled high-throughput, high-content imaging experiments. Image-based profiling leverages the rich information in images to identify similarities or differences among biological samples, rather than measuring a few features, as in high-content screening. Here, we review a decade of advancements and applications of Cell Painting, a microscopy-based cell-labeling assay aiming to capture a cell's state, introduced in 2013 to optimize and standardize image-based profiling.

Discovery of a novel inhibitor of macropinocytosis with antiviral activity.

Several viruses hijack various forms of endocytosis in order to infect host cells. Here, we report the discovery of a molecule with antiviral properties that we named virapinib, which limits viral entry by macropinocytosis. The identification of virapinib derives from a chemical screen using high-throughput microscopy, where we identified chemical entities capable of preventing infection with a pseudotype virus expressing the spike (S) protein from SARS-CoV-2.

Artificial intelligence for high content imaging in drug discovery.

Artificial intelligence (AI) and high-content imaging (HCI) are contributing to advancements in drug discovery, propelled by the recent progress in deep neural networks. This review highlights AI's role in analysis of HCI data from fixed and live-cell imaging, enabling novel label-free and multi-channel fluorescent screening methods, and improving compound profiling. HCI experiments are rapid and cost-effective, facilitating large data set accumulation for AI model training.

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction.

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction.

Corrigendum: Development of new approach methods for the identification and characterization of endocrine metabolic disruptors-a PARC project.

[This corrects the article DOI: 10.3389/ftox.2023.

From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability.

Cell Painting assays generate morphological profiles that are versatile descriptors of biological systems and have been used to predict in vitro and in vivo drug effects. However, Cell Painting features extracted from classical software such as CellProfiler are based on statistical calculations and often not readily biologically interpretable. In this study, we propose a new feature space, which we call BioMorph, that maps these Cell Painting features with readouts from comprehensive Cell Health assays.

Evaluating the utility of brightfield image data for mechanism of action prediction.

Fluorescence staining techniques, such as Cell Painting, together with fluorescence microscopy have proven invaluable for visualizing and quantifying the effects that drugs and other perturbations have on cultured cells. However, fluorescence microscopy is expensive, time-consuming, labor-intensive, and the stains applied can be cytotoxic, interfering with the activity under study. The simplest form of microscopy, brightfield microscopy, lacks these downsides, but the images produced have low contrast and the cellular compartments are difficult to discern.

Development of new approach methods for the identification and characterization of endocrine metabolic disruptors-a PARC project.

In past times, the analysis of endocrine disrupting properties of chemicals has mainly been focused on (anti-)estrogenic or (anti-)androgenic properties, as well as on aspects of steroidogenesis and the modulation of thyroid signaling. More recently, disruption of energy metabolism and related signaling pathways by exogenous substances, so-called metabolism-disrupting chemicals (MDCs) have come into focus. While general effects such as body and organ weight changes are routinely monitored in animal studies, there is a clear lack of mechanistic test systems to determine and characterize the metabolism-disrupting potential of chemicals.

Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data.

The applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. In this work, we developed similarity-based merger models which combined the outputs of individual models trained on cell morphology (based on Cell Painting) and chemical structure (based on chemical fingerprints) and the structural and morphological similarities of the compounds in the test dataset to compounds in the training dataset. We applied these similarity-based merger models using logistic regression models on the predictions and similarities as features and predicted assay hit calls of 177 assays from ChEMBL, PubChem and the Broad Institute (where the required Cell Painting annotations were available).

New regulators of the tetracycline-inducible gene expression system identified by chemical and genetic screens.

The tetracycline repressor (tetR)-regulated system is a widely used tool to specifically control gene expression in mammalian cells. Based on this system, we generated a human osteosarcoma cell line, which allows for the inducible expression of an EGFP fusion of the TAR DNA-binding protein 43 (TDP-43), which has been linked to neurodegenerative diseases. Consistent with previous findings, TDP-43 overexpression led to the accumulation of aggregates and limited the viability of U2OS.

Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection.

Mitochondrial toxicity is an important safety endpoint in drug discovery. Models based solely on chemical structure for predicting mitochondrial toxicity are currently limited in accuracy and applicability domain to the chemical space of the training compounds. In this work, we aimed to utilize both -omics and chemical data to push beyond the state-of-the-art.

Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects.

Environmental chemicals are commonly studied one at a time, and there is a need to advance our understanding of the effect of exposure to their combinations. Here we apply high-content microscopy imaging of cells stained with multiplexed dyes (Cell Painting) to profile the effects of Cetyltrimethylammonium bromide (CTAB), Bisphenol A (BPA), and Dibutyltin dilaurate (DBTDL) exposure on four human cell lines; both individually and in all combinations. We show that morphological features can be used with multivariate data analysis to discern between exposures from individual compounds, concentrations, and combinations.

NOX4 regulates TGFβ-induced proliferation and self-renewal in glioblastoma stem cells.

Glioblastoma (GBM) is the most aggressive and common glioma subtype, with a median survival of 15 months after diagnosis. Current treatments have limited therapeutic efficacy; thus, more effective approaches are needed. The glioblastoma tumoural mass is characterised by a small cellular subpopulation - glioblastoma stem cells (GSCs) - that has been held responsible for glioblastoma initiation, cell invasion, proliferation, relapse and resistance to chemo- and radiotherapy.

An Open-Source Modular Framework for Automated Pipetting and Imaging Applications.

The number of samples in biological experiments is continuously increasing, but complex protocols and human error in many cases lead to suboptimal data quality and hence difficulties in reproducing scientific findings. Laboratory automation can alleviate many of these problems by precisely reproducing machine-readable protocols. These instruments generally require high up-front investments, and due to the lack of open application programming interfaces (APIs), they are notoriously difficult for scientists to customize and control outside of the vendor-supplied software.

Prolonged estrogen deprivation triggers a broad immunosuppressive phenotype in breast cancer cells.

Among others, expression levels of programmed cell death 1 ligand 1 (PD-L1) have been explored as biomarkers of the response to immune checkpoint inhibitors in cancer therapy. Here, we present the results of a chemical screen that interrogated how medically approved drugs influence PD-L1 expression. As expected, corticosteroids and inhibitors of Janus kinases were among the top PD-L1 downregulators.

A phenomics approach for antiviral drug discovery.

Background: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates.

A chemical screen for modulators of mRNA translation identifies a distinct mechanism of toxicity for sphingosine kinase inhibitors.

We here conducted an image-based chemical screen to evaluate how medically approved drugs, as well as drugs that are currently under development, influence overall translation levels. None of the compounds up-regulated translation, which could be due to the screen being performed in cancer cells grown in full media where translation is already present at very high levels. Regarding translation down-regulators, and consistent with current knowledge, inhibitors of the mechanistic target of rapamycin (mTOR) signaling pathway were the most represented class.

High content drug screening for Fanconi anemia therapeutics.

Background: Fanconi anemia is a rare disease clinically characterized by malformations, bone marrow failure and an increased risk of solid tumors and hematologic malignancies. The only therapies available are hematopoietic stem cell transplantation for bone marrow failure or leukemia, and surgical resection for solid tumors. Therefore, there is still an urgent need for new therapeutic options.

Gefitinib and Afatinib Show Potential Efficacy for Fanconi Anemia-Related Head and Neck Cancer.

Purpose: Fanconi anemia rare disease is characterized by bone marrow failure and a high predisposition to solid tumors, especially head and neck squamous cell carcinoma (HNSCC). Patients with Fanconi anemia with HNSCC are not eligible for conventional therapies due to high toxicity in healthy cells, predominantly hematotoxicity, and the only treatment currently available is surgical resection. In this work, we searched and validated two already approved drugs as new potential therapies for HNSCC in patients with Fanconi anemia.

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of its autophagy-inhibitory activity.

Pharmacological inhibition of ribosome biogenesis is a promising avenue for cancer therapy. Herein, we report a novel activity of the FDA-approved antimalarial drug amodiaquine which inhibits rRNA transcription, a rate-limiting step for ribosome biogenesis, in a dose-dependent manner. Amodiaquine triggers degradation of the catalytic subunit of RNA polymerase I (Pol I), with ensuing RPL5/RPL11-dependent stabilization of p53.

A Chemical Screen Identifies Compounds Limiting the Toxicity of C9ORF72 Dipeptide Repeats.

The expansion of GGGGCC repeats within the first intron of C9ORF72 constitutes the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Through repeat-associated non-ATG translation, these expansions are translated into dipeptide repeats (DPRs), some of which accumulate at nucleoli and lead to cell death. We here performed a chemical screen to identify compounds reducing the toxicity of ALS-related poly(PR) peptides.

Human NUDT22 Is a UDP-Glucose/Galactose Hydrolase Exhibiting a Unique Structural Fold.

Human NUDT22 belongs to the diverse NUDIX family of proteins, but has, until now, remained uncharacterized. Here we show that human NUDT22 is a Mg-dependent UDP-glucose and UDP-galactose hydrolase, producing UMP and glucose 1-phosphate or galactose 1-phosphate. We present the structure of human NUDT22 alone and in a complex with the substrate UDP-glucose.