High-content, high-throughput screening for the identification of cytotoxic compounds based on cell morphology and cell proliferation markers

Unbiased image segmentation assessment toolkit for quantitative differentiation of state-of-the-art algorithms and pipelines

BACKGROUND

Image segmentation pipelines are commonly used in microscopy to identify cellular compartments like nucleus and cytoplasm, but there are few standards for comparing segmentation accuracy across pipelines. The process of selecting a segmentation assessment pipeline can seem daunting to researchers due to the number and variety of metrics available for evaluating segmentation quality.

RESULTS

Here we present automated pipelines to obtain a comprehensive set of 69 metrics to evaluate segmented data and propose a selection methodology for models based on quantitative analysis, dimension reduction or unsupervised classification techniques and informed selection criteria.

CONCLUSION

We show that the metrics used here can often be reduced to a small number of metrics that give a more complete understanding of segmentation accuracy, with different groups of metrics providing sensitivity to different types of segmentation error. These tools are delivered as easy to use python libraries, command line tools, Common Workflow Language Tools, and as Web Image Processing Pipeline interactive plugins to ensure a wide range of users can access and use them. We also present how our evaluation methods can be used to observe the changes in segmentations across modern machine learning/deep learning workflows and use cases.

Tissue-Engineered 3D In Vitro Disease Models for High-Throughput Drug Screening

During high-throughput drug screening, in vitro models are fabricated and the effects of therapeutics on the models evaluated in high throughput-for example, with automated liquid handling systems and microplate reader-based high-throughput screening (HTS) assays. The most frequently-used model systems for HTS, 2D models, do not adequately model the in vivo 3D microenvironment-an important aspect of which is the extracellular matrix-and therefore, 2D models may not be appropriate for drug screening. Instead, tissue-engineered 3D models with extracellular matrix-mimicking components are destined to become the preferred in vitro systems for HTS. However, for 3D models, such as 3D cell-laden hydrogels and scaffolds, cell sheets, and spheroids as well as 3D microfluidic and organ-on-a-chip systems, to replace 2D models in HTS, they must be compatible with high-throughput fabrication schemes and evaluation methods. In this review, we summarize HTS in 2D models and discuss recent studies that have successfully demonstrated HTS-compatible 3D models of high-impact diseases, such as cancers or cardiovascular diseases.

Unveiling hepatotoxicity distinction of coumarin-related compounds from glycosides to aglycones in Fructus Psoraleae by integrating UPLC-Q-TOF-MS and high content analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Fructus Psoraleae (FP), the dried and ripe fruit of Cullen corylifolium (L.) Medik., is widely used due to its various clinical pharmacological effects, but its hepatotoxicity restricts its clinical application. So far, its hepatotoxic components and their underlying mechanism have not been systematically elucidated.

AIM OF THE STUDY

This study was undertaken to reveal the hepatotoxicity distinction of coumarin-related compounds from glycosides to aglycones in FP and elucidate their potential mechanism.

METHODS

Rats were administrated with the aqueous extract of Fructus Psoraleae (AEFP), in which eight coumarin-related compounds were focused. Subsequently, compounds exposed in rats' livers were detected by UPLC-Q-TOF-MS, and the identified hepatotoxic compounds were evaluated to elaborate their possible mechanism by the aid of high content analysis (HCA).

RESULTS

Eight coumarin-related compounds were identified, among which psoralenoside (PO), isopsoralenoside (IPO), psoralen (P), and isopsoralen (IP) were the principally exposed compounds in rats' livers. Furocoumarinic acid glucoside (FAG), (E)-3-(4-(((2S, 3R, 4S, 5S, 6R)-3,4,5-trihydroxy-6-(hydroxymethyl) tetrahydro-2H-pyran-2-yl) oxy) benzofuran-5-yl) acrylic acid (isofurocoumarinic acid glucoside, IFAG), furocoumarinic acid (FA), and (E)-3-(4-hydroxybenzofuran-5-yl) acrylic acid (isofurocoumarinic acid, IFA) were also detected in low abundance. P, IP, FA, and IFA were identified as the hepatotoxic compounds, while their glycosides were almost non-hepatotoxic. The HCA's results showed that hepatotoxic compounds disrupted the balance in reactive oxygen species (ROS), nuclear area, and mitochondrial membrane potential of HepG2 cells, leading to the occurrence of hepatotoxicity.

CONCLUSIONS

P, IP, FA, and IFA were identified as hepatotoxic compounds, from which P and IP were proposed as the important risk components for hepatotoxicity. The conversion from glycosides to aglycones played an essential role in FP-induced hepatotoxicity.

Transcriptional Inhibition of MicroRNA miR-122 by Small Molecules Reduces Hepatitis C Virus Replication in Liver Cells

MicroRNAs (miRNAs) are noncoding RNA molecules of 22-24 nucleotides that are estimated to regulate thousands of genes in humans, and their dysregulation has been implicated in many diseases. MicroRNA-122 (miR-122) is the most abundant miRNA in the liver and has been linked to the development of hepatocellular carcinoma and hepatitis C virus (HCV) infection. Its role in these diseases renders miR-122 a potential target for small-molecule therapeutics. Here, we report the discovery of a new sulfonamide class of small-molecule miR-122 inhibitors from a high-throughput screen using a luciferase-based reporter assay. Structure-activity relationship (SAR) studies and secondary assays led to the development of potent and selective miR-122 inhibitors. Preliminary mechanism-of-action studies suggest a role in the promoter-specific transcriptional inhibition of miR-122 expression through direct binding to the liver-enriched transcription factor hepatocyte nuclear factor 4α. Importantly, the developed inhibitors significantly reduce HCV replication in human liver cells.

Mayaro Virus: The State-of-the-Art for Antiviral Drug Development

Mayaro virus is an emerging arbovirus that causes nonspecific febrile illness or arthralgia syndromes similar to the Chikungunya virus, a virus closely related from the Togaviridae family. MAYV outbreaks occur more frequently in the northern and central-western states of Brazil; however, in recent years, virus circulation has been spreading to other regions. Due to the undifferentiated initial clinical symptoms between MAYV and other endemic pathogenic arboviruses with geographic overlapping, identification of patients infected by MAYV might be underreported. Additionally, the lack of specific prophylactic approaches or antiviral drugs limits the pharmacological management of patients to treat symptoms like pain and inflammation, as is the case with most pathogenic alphaviruses. In this context, this review aims to present the state-of-the-art regarding the screening and development of compounds/molecules which may present anti-MAYV activity and infection inhibition.

Cell Morphological Profiling Enables High-Throughput Screening for PROteolysis TArgeting Chimera (PROTAC) Phenotypic Signature

PROteolysis TArgeting Chimeras (PROTACs) use the ubiquitin-proteasome system to degrade a protein of interest for therapeutic benefit. Advances made in targeted protein degradation technology have been remarkable, with several molecules having moved into clinical studies. However, robust routes to assess and better understand the safety risks of PROTACs need to be identified, which is an essential step toward delivering efficacious and safe compounds to patients. In this work, we used Cell Painting, an unbiased high-content imaging method, to identify phenotypic signatures of PROTACs. Chemical clustering and model prediction allowed the identification of a mitotoxicity signature that could not be expected by screening the individual PROTAC components. The data highlighted the benefit of unbiased phenotypic methods for identifying toxic signatures and the potential to impact drug design.

Picroscope: low-cost system for simultaneous longitudinal biological imaging

Simultaneous longitudinal imaging across multiple conditions and replicates has been crucial for scientific studies aiming to understand biological processes and disease. Yet, imaging systems capable of accomplishing these tasks are economically unattainable for most academic and teaching laboratories around the world. Here, we propose the Picroscope, which is the first low-cost system for simultaneous longitudinal biological imaging made primarily using off-the-shelf and 3D-printed materials. The Picroscope is compatible with standard 24-well cell culture plates and captures 3D z-stack image data. The Picroscope can be controlled remotely, allowing for automatic imaging with minimal intervention from the investigator. Here, we use this system in a range of applications. We gathered longitudinal whole organism image data for frogs, zebrafish, and planaria worms. We also gathered image data inside an incubator to observe 2D monolayers and 3D mammalian tissue culture models. Using this tool, we can measure the behavior of entire organisms or individual cells over long-time periods.

In-Cell Generation of Anticancer Phenanthridine Through Bioorthogonal Cyclization in Antitumor Prodrug Development

Pharmacological inactivation of antitumor drugs toward healthy cells is a critical factor in prodrug development. Typically, pharmaceutical chemists graft temporary moieties to existing antitumor drugs to reduce their pharmacological activity. Here, we report a platform able to generate the cytotoxic agent by intramolecular cyclization. Using phenanthridines as cytotoxic model compounds, we designed ring-opened biaryl precursors that generated the phenanthridines through bioorthogonal irreversible imination. This reaction was triggered by reactive oxygen species, commonly overproduced in cancer cells, able to convert a vinyl boronate ester function into a ketone that subsequently reacted with a pendant aniline. An inactive precursor was shown to engender a cytotoxic phenanthridine against KB cancer cells. Moreover, the kinetic of cyclization of this prodrug was extremely rapid inside living cells of KB cancer spheroids so as to circumvent drug action.

Lnc GNG12-AS1 knockdown suppresses glioma progression through the AKT/GSK-3β/β-catenin pathway

BACKGROUND

Long non-coding RNAs (lncRNAs) are increasingly being regarded as regulators of glioma development. Notably, some studies report that GNG12-AS1 plays important functions and molecular mechanism in breast cancer, but there are no existing studies in glioma.

OBJECTIVE

To analyze the biological functions and potential mechanisms of GNG12-AS1 in glioma.

METHODS

We detected the expression of GNG12-AS1 in glioma tissues through analyzing TCGA data as well as our clinical samples. We then evaluated cell proliferation through MTT assay and colony formation and cell migration by transwell assay, wound healing assay and single cell tracking assay. After, we analyzed the effects of the AKT/GSK-3β/β-catenin through Western blotting and utilized the β-catenin agonist SKL2001 for the rescue experiment.

RESULTS

GNG12-AS1 was highly expressed in glioma tissues. The silence of GNG12-AS1 inhibited the proliferation, migration and epithelial-mesenchymal transition of glioma cells, and reduced the activity of the AKT/GSK-3β/β-catenin pathway. Notably, SKL2001 could reverse cell migration as well as β-catenin expression in glioma cells with lower GNG12-AS1 expression.

CONCLUSIONS

GNG12-AS1 regulates proliferation and migration of glioma cells through the AKT/GSK-3β/β-catenin signaling and can perhaps be a new target for the treatment of glioma.

Comparison of Cellular Morphological Descriptors and Molecular Fingerprints for the Prediction of Cytotoxicity- and Proliferation-Related Assays

Cell morphology features, such as those from the Cell Painting assay, can be generated at relatively low costs and represent versatile biological descriptors of a system and thereby compound response. In this study, we explored cell morphology descriptors and molecular fingerprints, separately and in combination, for the prediction of cytotoxicity- and proliferation-related in vitro assay endpoints. We selected 135 compounds from the MoleculeNet ToxCast benchmark data set which were annotated with Cell Painting readouts, where the relatively small size of the data set is due to the overlap of required annotations. We trained Random Forest classification models using nested cross-validation and Cell Painting descriptors, Morgan and ErG fingerprints, and their combinations. While using leave-one-cluster-out cross-validation (with clusters based on physicochemical descriptors), models using Cell Painting descriptors achieved higher average performance over all assays (Balanced Accuracy of 0.65, Matthews Correlation Coefficient of 0.28, and AUC-ROC of 0.71) compared to models using ErG fingerprints (BA 0.55, MCC 0.09, and AUC-ROC 0.60) and Morgan fingerprints alone (BA 0.54, MCC 0.06, and AUC-ROC 0.56). While using random shuffle splits, the combination of Cell Painting descriptors with ErG and Morgan fingerprints further improved balanced accuracy on average by 8.9% (in 9 out of 12 assays) and 23.4% (in 8 out of 12 assays) compared to using only ErG and Morgan fingerprints, respectively. Regarding feature importance, Cell Painting descriptors related to nuclei texture, granularity of cells, and cytoplasm as well as cell neighbors and radial distributions were identified to be most contributing, which is plausible given the endpoint considered. We conclude that cell morphological descriptors contain complementary information to molecular fingerprints which can be used to improve the performance of predictive cytotoxicity models, in particular in areas of novel structural space.

Application of high-content screening for the study of hepatotoxicity: Focus on food toxicology

Safety evaluation of thousands of chemicals that are directly added to or come in contact with food is needed. Due to the central role of the liver in intermediary and energy metabolism and in the biotransformation of foreign compounds, the hepatotoxicity assessment is essential. New approach methodologies have been proposed for the safety evaluation of compounds with the idea of rapidly gaining insight into effects on biochemical mechanisms and cellular processes and screening large number of compounds. In this sense, high-content screening (HCS) is the application of automated microscopy and image analysis for better understanding of complex biological functions and mechanisms of toxicity. HCS multiparametric measurements have been shown to be a useful tool in early toxicity testing during drug development, but also in assessing the impact from food chemicals and environmental toxicants. Reviewing the use of cellular imaging technology in the safety evaluation of food-relevant chemicals offers evidence about the impact of this technology in safety assessment.

Models of Idiosyncratic Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a leading cause of attrition during the early and late stages of drug development and after a drug is marketed. DILI is generally classified as either intrinsic or idiosyncratic. Intrinsic DILI is dose dependent and predictable (e.g., acetaminophen toxicity). However, predicting the occurrence of idiosyncratic DILI, which has a very low incidence and is associated with severe liver damage, is difficult because of its complex nature and the poor understanding of its mechanism. Considering drug metabolism and pharmacokinetics, we established experimental animal models of DILI for 14 clinical drugs that cause idiosyncratic DILI in humans, which is characterized by the formation of reactive metabolites and the involvement of both innate and adaptive immunity. On the basis of the biomarker data obtained from the animal models, we developed a cell-based assay system that predicts the potential risks of drugs for inducing DILI. These findings increase our understanding of the mechanisms of DILI and may help predict and prevent idiosyncratic DILI due to certain drugs.

Validation of in-vitro bioassay methods: Application in herbal drug research

This present review described the validation method of in-vitro bioassay for its application in herbal drug research. Seven sequencing steps that can be taken for performing a valid bioassay include: literature survey, sample stability evaluation, Biosystem performance testing, Sample performance evaluation, determination of 50% effective concentration or cytotoxic concentrations, selective index evaluation, and determination of accurate relative potency of sample. Detailed methods and acceptance criteria for each step are described herein. Method calculations of the relative potency of sample using European Pharmacopeia 10.0, 5.3 (2020) were recommended instead of using United States Pharmacopeia 42 (2019). For having reliable data and conclusions, all methods (chemical and bioassay) need to be first validated before any data collection. Absence of any validation method may results in incorrect conclusions and bias.

The EZMTT cell proliferation assay provides precise measurement for drug combinations and better correlation between in vitro and in vivo efficacy

The rate of drug-induced proliferation (DIP) has been proposed as an unbiased alternative drug effect metric. However, current assays are not easy and precise enough to track minor changes in cell growth. Here, we report the optimized EZMTT based detection method which can continuously measure time-dependent growth after drug treatment and reliably detect partial drug resistance for cancer cells. Importantly, tracking time-dependent growth after drug treatment demonstrated that a KGA allosteric inhibitor alone failed to completely inhibit cancer cell growth, but a drug combination was able to provide complete inhibition in cell-based assays that translated well in in vivo animal experiments. In conclusion, this simple EZMTT method provided precise measurement of loss of susceptibility after drug treatment and has great potential to be developed for drug efficacy and drug combination studies to solve the unmet medical need.

Identifying Metabolic Inhibitors to Reduce Bacterial Persistence

Bacterial persisters are rare phenotypic variants that are temporarily tolerant to high concentrations of antibiotics. We have previously discovered that stationary-phase-cell subpopulations exhibiting high redox activities were less capable of producing proteins and resuming growth upon their dilution into fresh media. The redox activities of these cells were maintained by endogenous protein and RNA degradation, resulting in self-inflicted damage that transiently repressed the cellular functions targeted by antibiotics. Here, we showed that pretreatment of stationary-phase cells with an ATP synthase inhibitor, chlorpromazine hydrochloride (CPZ), significantly reduced stationary-phase-redox activities and protein degradation, and yielded cells that were more susceptible to cell death when exposed to antibiotics in fresh media. Leveraging this knowledge, we developed an assay integrating a degradable fluorescent protein system and a small library, containing FDA-approved drugs and antibiotics, to detect medically relevant drugs that potentially target persister metabolism. We identified a subset of chemical inhibitors, including polymyxin B, poly-L-lysine and phenothiazine anti-psychotic drugs, that were able to reduce the persistence phenotype in Escherichia coli. These chemical inhibitors also reduced Pseudomonas aeruginosa persistence, potentially verifying the existence of similar mechanisms in a medically relevant organism.

High-Content Image-Based Single-Cell Phenotypic Analysis for the Testicular Toxicity Prediction Induced by Bisphenol A and Its Analogs Bisphenol S, Bisphenol AF, and Tetrabromobisphenol A in a Three-Dimensional Testicular Cell Co-culture Model

Emerging data indicate that structural analogs of bisphenol A (BPA) such as bisphenol S (BPS), tetrabromobisphenol A (TBBPA), and bisphenol AF (BPAF) have been introduced into the market as substitutes for BPA. Our previous study compared in vitro testicular toxicity using murine C18-4 spermatogonial cells and found that BPAF and TBBPA exhibited higher spermatogonial toxicities as compared with BPA and BPS. Recently, we developed a novel in vitro three-dimensional (3D) testicular cell co-culture model, enabling the classification of reproductive toxic substances. In this study, we applied the testicular cell co-culture model and employed a high-content image (HCA)-based single-cell analysis to further compare the testicular toxicities of BPA and its analogs. We also developed a machine learning (ML)-based HCA pipeline to examine the complex phenotypic changes associated with testicular toxicities. We found dose- and time-dependent changes in a wide spectrum of adverse endpoints, including nuclear morphology, DNA synthesis, DNA damage, and cytoskeletal structure in a single-cell-based analysis. The co-cultured testicular cells were more sensitive than the C18 spermatogonial cells in response to BPA and its analogs. Unlike conventional population-averaged assays, single-cell-based assays not only showed the levels of the averaged population, but also revealed changes in the sub-population. Machine learning-based phenotypic analysis revealed that treatment of BPA and its analogs resulted in the loss of spatial cytoskeletal structure, and an accumulation of M phase cells in a dose- and time-dependent manner. Furthermore, treatment of BPAF-induced multinucleated cells, which were associated with altered DNA damage response and impaired cellular F-actin filaments. Overall, we demonstrated a new and effective means to evaluate multiple toxic endpoints in the testicular co-culture model through the combination of ML and high-content image-based single-cell analysis. This approach provided an in-depth analysis of the multi-dimensional HCA data and provided an unbiased quantitative analysis of the phenotypes of interest.

Circulating Tumor Cell Clustering Shapes DNA Methylation to Enable Metastasis Seeding

The ability of circulating tumor cells (CTCs) to form clusters has been linked to increased metastatic potential. Yet biological features and vulnerabilities of CTC clusters remain largely unknown. Here, we profile the DNA methylation landscape of single CTCs and CTC clusters from breast cancer patients and mouse models on a genome-wide scale. We find that binding sites for stemness- and proliferation-associated transcription factors are specifically hypomethylated in CTC clusters, including binding sites for OCT4, NANOG, SOX2, and SIN3A, paralleling embryonic stem cell biology. Among 2,486 FDA-approved compounds, we identify Na⁺/K⁺ ATPase inhibitors that enable the dissociation of CTC clusters into single cells, leading to DNA methylation remodeling at critical sites and metastasis suppression. Thus, our results link CTC clustering to specific changes in DNA methylation that promote stemness and metastasis and point to cluster-targeting compounds to suppress the spread of cancer.

TiO2 particles induce ER stress and apoptosis in human hepatoma cells, HepG2, in a particle size-dependent manner

The cytotoxicity of TiO₂ nanoparticles are well-known, but the particle size-dependent induction of ER stress and apoptosis by TiO₂ in hepatocytes has not been elucidated clearly. In the present study, we investigated whether a fine TiO₂ particle and two types of TiO₂ nanoparticles induce ER stress and apoptosis differently in HepG2 cells. A particle size-dependent decrease in cell viability was observed after exposure to the TiO₂ particles. The levels of ER stress-related proteins (BiP, CHOP, ATF6α, and p-PERK) were increased with decreasing particle size. TiO₂ particles induced ER stress-mediated apoptosis in a particle size-dependent manner as seen by a decrease in the expression of Bcl-2, and increases in the expression of Bax, caspase-12, and cleaved caspase-3. These results indicated that the cytotoxicity produced by TiO₂ particles was related to particle size, with smaller TiO₂ nanoparticles producing greater toxic effects involving ER stress and apoptosis in the HepG2 cells.

The isolation and characterization of a new snake venom cysteine-rich secretory protein (svCRiSP) from the venom of the Southern Pacific rattlesnake and its effect on vascular permeability

A novel snake venom cysteine-rich secretory protein (svCRiSP), Hellerin, was purified from C. o. helleri venom using sequential reverse phase and cation-exchange chromatography. Gel electrophoresis, N-terminal sequencing, and LC-MS/MS sequencing identified a single protein with a molecular mass of approximately 24.8 kDa and confirmed its identity as a svCRiSP. Hellerin had cytotoxic effects on human umbilical vein endothelial cells (HUVECs) in a dose-dependent manner but not in human dermal lymphatic endothelial cells (HDLECs) and human dermal blood endothelial cells (HDBECs). Hellerin produced a dramatic increase in both blood vascular permeability in vivo, and in the trans-epithelial permeability of cultured HDLEC and HDBEC cells. This is the first study that describes the effect of a svCRiSP on vascular, blood and lymphatic permeability.

Whole-Cell Multiparameter Assay for Ricin and Abrin Activity-Based Digital Holographic Microscopy

Ricin and abrin are ribosome-inactivating proteins leading to inhibition of protein synthesis and cell death. These toxins are considered some of the most potent and lethal toxins against which there is no available antidote. Digital holographic microscopy (DHM) is a time-lapse, label-free, and noninvasive imaging technique that can provide phase information on morphological features of cells. In this study, we employed DHM to evaluate the morphological changes of cell lines during ricin and abrin intoxication. We showed that the effect of these toxins is characterized by a decrease in cell confluence and changes in morphological parameters such as cell area, perimeter, irregularity, and roughness. In addition, changes in optical parameters such as phase-shift, optical thickness, and effective-calculated volume were observed. These effects were completely inhibited by specific neutralizing antibodies. An enhanced intoxication effect was observed for preadherent compared to adherent cells, as was detected in early morphology changes and confirmed by annexin V/propidium iodide (PI) apoptosis assay. Detection of the dynamic changes in cell morphology at initial stages of cell intoxication by DHM emphasizes the highly sensitive and rapid nature of this method, allowing the early detection of active toxins.

A scalable filtration method for high throughput screening based on cell deformability

Cell deformability is a label-free biomarker of cell state in physiological and disease contexts ranging from stem cell differentiation to cancer progression. Harnessing deformability as a phenotype for screening applications requires a method that can simultaneously measure the deformability of hundreds of cell samples and can interface with existing high throughput facilities. Here we present a scalable cell filtration device, which relies on the pressure-driven deformation of cells through a series of pillars that are separated by micron-scale gaps on the timescale of seconds: less deformable cells occlude the gaps more readily than more deformable cells, resulting in decreased filtrate volume which is measured using a plate reader. The key innovation in this method is that we design customized arrays of individual filtration devices in a standard 96-well format using soft lithography, which enables multiwell input samples and filtrate outputs to be processed with higher throughput using automated pipette arrays and plate readers. To validate high throughput filtration to detect changes in cell deformability, we show the differential filtration of human ovarian cancer cells that have acquired cisplatin-resistance, which is corroborated with cell stiffness measurements using quantitative deformability cytometry. We also demonstrate differences in the filtration of human cancer cell lines, including ovarian cancer cells that overexpress transcription factors (Snail, Slug), which are implicated in epithelial-to-mesenchymal transition; breast cancer cells (malignant versus benign); and prostate cancer cells (highly versus weekly metastatic). We additionally show how the filtration of ovarian cancer cells is affected by treatment with drugs known to perturb the cytoskeleton and the nucleus. Our results across multiple cancer cell types with both genetic and pharmacologic manipulations demonstrate the potential of this scalable filtration device to screen cells based on their deformability.

Tox_(R)CNN: Deep learning-based nuclei profiling tool for drug toxicity screening

Toxicity is an important factor in failed drug development, and its efficient identification and prediction is a major challenge in drug discovery. We have explored the potential of microscopy images of fluorescently labeled nuclei for the prediction of toxicity based on nucleus pattern recognition. Deep learning algorithms obtain abstract representations of images through an automated process, allowing them to efficiently classify complex patterns, and have become the state-of-the art in machine learning for computer vision. Here, deep convolutional neural networks (CNN) were trained to predict toxicity from images of DAPI-stained cells pre-treated with a set of drugs with differing toxicity mechanisms. Different cropping strategies were used for training CNN models, the nuclei-cropping-based Tox_CNN model outperformed other models classifying cells according to health status. Tox_CNN allowed automated extraction of feature maps that clustered compounds according to mechanism of action. Moreover, fully automated region-based CNNs (RCNN) were implemented to detect and classify nuclei, providing per-cell toxicity prediction from raw screening images. We validated both Tox_(R)CNN models for detection of pre-lethal toxicity from nuclei images, which proved to be more sensitive and have broader specificity than established toxicity readouts. These models predicted toxicity of drugs with mechanisms of action other than those they had been trained for and were successfully transferred to other cell assays. The Tox_(R)CNN models thus provide robust, sensitive, and cost-effective tools for in vitro screening of drug-induced toxicity. These models can be adopted for compound prioritization in drug screening campaigns, and could thereby increase the efficiency of drug discovery.

Quantitative Algorithm-Based Paired Imaging Measurement for Antibody-Triggered Endocytosis in Cultured Cells

Antibody-triggered endocytosis (ATE) is a biological mechanism on which many therapeutic strategies are grounded, such as delivery of antibody-drug conjugates (ADCs). Current methods monitoring ATE include confocal Z-stack analysis, acid wash, antibody quenching, and pH-sensitive dye labeling. However, those generate less quantifiable results with low throughput. Here we report a new method referred to as "paired imaging measurement" to analyze ATE using a quantitative algorithm in conjunction with high-content imaging. With two sequential measurements of cell surface antibody employing live cell staining and total antibody by immunostaining before and after cell permeabilization, intracellular antibody undergoing endocytosis can be quantified indirectly. Antibodies against CD98 and transferrin receptor were tested on hCMEC/D3 and hiPSC-derived endothelial cells. The maximal response and potency of endocytosed antibodies were generated with good assay robustness (Z' > 0.6) and >5-fold signal/background ratio. Antibody endocytosis response ranking is consistent between batches ( R² > 0.9). The obtained results were confirmed by other traditional methods. In conclusion, we have developed a novel method using a quantitative imaging algorithm in conjunction with live cell staining for high-throughput investigation of ATE.

A High-Content Live-Cell Viability Assay and Its Validation on a Diverse 12K Compound Screen

We have developed a new high-content cytotoxicity assay using live cells, called “ImageTOX.” We used a high-throughput fluorescence microscope system, image segmentation software, and the combination of Hoechst 33342 and SYTO 17 to simultaneously score the relative size and the intensity of the nuclei, the nuclear membrane permeability, and the cell number in a 384-well microplate format. We then performed a screen of 12,668 diverse compounds and compared the results to a standard cytotoxicity assay. The ImageTOX assay identified similar sets of compounds to the standard cytotoxicity assay, while identifying more compounds having adverse effects on cell structure, earlier in treatment time. The ImageTOX assay uses inexpensive commercially available reagents and facilitates the use of live cells in toxicity screens. Furthermore, we show that we can measure the kinetic profile of compound toxicity in a high-content, high-throughput format, following the same set of cells over an extended period of time.

Comparison of the Acute Immunotoxicity of Nonfractionated and Fractionated Oil Sands Process-Affected Water Using Mammalian Macrophages

OSPW is a complex mixture of inorganic and organic substances and its principal toxic components have yet to be fully characterized. Previously, we showed in vitro that the oil sands process-affected water (OSPW) organic fraction (OF) caused a concentration-dependent immunotoxicity in mammals. In the present study we further explore the immunotoxicological properties of OSPW in mammals using a series of in vitro bioassays. Specifically, using the RAW 264.7 mouse macrophage cell line we show that whole OSPW containing naphthenic acid (NA) concentrations ranging from 12 to 18 mg/L, significantly inhibited cell proliferation, reduced cell viability, and was directly cytotoxic, whereas the exposure of cells to equivalent doses of the OSPW-OF had no measurable effects. Whole OSPW exposures also caused morphological changes in RAW 264.7 cells, and at sublethal doses (i.e., 10 mg/L) it induced the early expression of the stress genes hmox1 and gadd45. In addition, at NA concentrations of 10 mg/L, whole OSPW but not the OSPW-OF had significant effects on pro-inflammatory cytokine mRNA levels and cytokine protein secretion activities. Finally, whole OSPW also impaired the ability of RAW 264.7 cells to perform phagocytosis. Overall, we demonstrate that exposure to whole OSPW (at NA doses ranging from 10 to 20 mg/L), but not the OSPW-OF caused both cytotoxic and immunomodulatory changes in mouse macrophages. This suggests that the complex mixture of inorganic and organic components found in whole OSPW are acutely toxic at much lower doses than we previously reported for the OSPW-OF (i.e., 50 mg/L) due to unknown additive and/or synergistic interactions that likely occur between the various components present in whole OSPW.

A new approach for the assessment of the toxicity of polyphenol-rich compounds with the use of high content screening analysis

The toxicity of in vitro tested compounds is usually evaluated based on AC₅₀ values calculated from dose-response curves. However, there is a large group of compounds for which a standard four-parametric sigmoid curve fitting may be inappropriate for estimating AC₅₀. In the present study, 22 polyphenol-rich compounds were prioritized from the least to the most toxic based on the total area under and over the dose-response curves (AUOC) in relation to baselines. The studied compounds were ranked across three key cell indicators (mitochondrial membrane potential, cell membrane integrity and nuclear size) in a panel of five cell lines (HepG2, Caco-2, A549, HMEC-1, and 3T3), using a high-content screening (HCS) assay. Regarding AUOC score values, naringin (negative control) was the least toxic phenolic compound. Aronox, spent hop extract and kale leaf extract had very low cytotoxicity with regard to mitochondrial membrane potential and cell membrane integrity, as well as nuclear morphology (nuclear area). Kaempferol (positive control) exerted strong cytotoxic effects on the mitochondrial and nuclear compartments. Extracts from buckthorn bark, walnut husk and hollyhock flower were highly cytotoxic with regard to the mitochondrion and cell membrane, but not the nucleus. We propose an alternative algorithm for the screening of a large number of agents and for identifying those with adverse cellular effects at an early stage of drug discovery, using high content screening analysis. This approach should be recommended for series of compounds producing a non-sigmoidal cell response, and for agents with unknown toxicity or mechanisms of action.

Anti-proliferative and anti-metastasis effects of ten oligostilbenes from the seeds of Paeonia suffruticosa on human cancer cells

Paeonia suffruticosa from the section Moutan of the genus Paeonia is an important Chinese medicinal herb. In our previous study, 10 oligostilbenes from the seeds of P. suffruticosa, including trans-resveratrol and its dimers and trimers, were isolated and identified. In the present study, the anti-proliferative effects of these 10 oligostilbenes were systemically evaluated in a panel of human lung, breast and bone cancer cell lines, and their apoptotic effects were analyzed using a high-content multiplex apoptosis assay and a fluorescent caspase-3/7 assay. Furthermore, their anti-metastasis effects were examined in an invasive breast cancer cell line. Among the ten compounds, two resveratrol dimers, trans- and cis-gnetin H, showed the most potent anti-proliferative and anti-metastasis effects. All trans-oligostilbenes were more effective than their cis-forms, and trimers of resveratrol were more effective than dimers and the resveratrol isomer. The structure-activity relationships revealed that the polymerization degree, the double bond in the stilbene skeleton, and the steric arrangement and conformation of oligostilbenes obviously affected their antitumor potential. The results from this study provide valuable information for future semi-synthesis of resveratrol derivatives to develop novel cancer chemopreventive agents.

A covalently bound inhibitor triggers EZH2 degradation through CHIP-mediated ubiquitination

Enhancer of zeste homolog 2 (EZH2) has been characterized as a critical oncogene and a promising drug target in human malignant tumors. The current EZH2 inhibitors strongly suppress the enhanced enzymatic function of mutant EZH2 in some lymphomas. However, the recent identification of a PRC2- and methyltransferase-independent role of EZH2 indicates that a complete suppression of all oncogenic functions of EZH2 is needed. Here, we report a unique EZH2-targeting strategy by identifying a gambogenic acid (GNA) derivative as a novel agent that specifically and covalently bound to Cys668 within the EZH2-SET domain, triggering EZH2 degradation through COOH terminus of Hsp70-interacting protein (CHIP)-mediated ubiquitination. This class of inhibitors significantly suppressed H3K27Me3 and effectively reactivated polycomb repressor complex 2 (PRC2)-silenced tumor suppressor genes. Moreover, the novel inhibitors significantly suppressed tumor growth in an EZH2-dependent manner, and tumors bearing a non-GNA-interacting C668S-EZH2 mutation exhibited resistance to the inhibitors. Together, our results identify the inhibition of the signaling pathway that governs GNA-mediated destruction of EZH2 as a promising anti-cancer strategy.

Image-Based High Content Screening: Automating the Quantification Process for DNA Damage-Induced Foci

Visual inspection of cellular activities based on conventional fluorescence microscope is a fundamental tool to study the role of DNA damage response (DDR). In the context of drug discovery where the capture of thousands of images is required across parallel experiments, this presents a challenge to data collection and analysis. Manual scoring is laborious and often reliant on trained personnel to intuit biological meaning through visual reasoning. On the other hand, high content screening combines the automation of microscopy image acquisition and analysis in a single platform to quantify cellular events of interests. The data generated is rapid and accurate, lessening the bias of human interpretation. Herein, this chapter will describe an image-based high content screen approach and the data analysis of Ataxia-Telangiectasia Mutated (ATM) DNA damage-induced foci.

High-Content Analysis Provides Mechanistic Insights into the Testicular Toxicity of Bisphenol A and Selected Analogues in Mouse Spermatogonial Cells

Bisphenol A (BPA), an endocrine-disrupting compound, was found to be a testicular toxicant in animal models. Bisphenol S (BPS), bisphenol AF (BPAF), and tetrabromobisphenol A (TBBPA) were recently introduced to the market as alternatives to BPA. However, toxicological data of these compounds in the male reproductive system are still limited so far. This study developed and validated an automated multi-parametric high-content analysis (HCA) using the C18-4 spermatogonial cell line as a model. We applied these validated HCA, including nuclear morphology, DNA content, cell cycle progression, DNA synthesis, cytoskeleton integrity, and DNA damage responses, to characterize and compare the testicular toxicities of BPA and 3 selected commercial available BPA analogues, BPS, BPAF, and TBBPA. HCA revealed BPAF and TBBPA exhibited higher spermatogonial toxicities as compared with BPA and BPS, including dose- and time-dependent alterations in nuclear morphology, cell cycle, DNA damage responses, and perturbation of the cytoskeleton. Our results demonstrated that this specific culture model together with HCA can be utilized for quantitative screening and discriminating of chemical-specific testicular toxicity in spermatogonial cells. It also provides a fast and cost-effective approach for the identification of environmental chemicals that could have detrimental effects on reproduction.

An isoflavonoid-enriched extract from Pueraria lobata (kudzu) root protects human umbilical vein endothelial cells against oxidative stress induced apoptosis

ETHNOPHARMACOLOGICAL RELEVANCE

Reactive oxygen species (ROS) mediate vascular cell dysfunction and lead to atherosclerosis and other chronic cardiovascular diseases. The root of Pueraria lobata (Willd.) Ohwi, also known as kudzu or Gegen (Chinese name), is one of the most important herbs in traditional Chinese medicine and has been widely used in the treatment of cardiovascular diseases, diabetes, osteonecrosis and neurodegradation diseases. In this study, an ethanol extract from kudzu root was prepared and the in vitro protective effect of the kudzu root extract (KUD) on human umbilical vein endothelial cells (HUVECs) was investigated.

MATERIAL AND METHODS

An ethanol extract of dried kudzu root was purified with an AB-8 resin column, and the concentrations of puerarin, daidzin and daidzein in the KUD were determined using UV spectroscopy. HUVECs were pretreated with various concentrations of the KUD with or without rotenone and the viability was assessed by AlamarBlue cell viability assay. Next, HUVECs were pretreated with the KUD and then treated with rotenone, and the levels of ROS generation, apoptosis, and changes of the mitochondrial membrane potential (ΔΨm) in HUVECs were measured using fluorescent staining assay and high-content analysis.

RESULTS

The contents of three major isoflavonoids (puerarin, daidzin and daidzein) were enriched by 7.75-27.51 fold in the extract. The KUD enhanced the proliferation of HUVECs, and protected HUVECs against rotenone-induced oxidative stress and apoptosis. Additionally, the KUD prevented the loss of ΔΨm in HUVECs stimulated by oxidative stress.

CONCLUSION

We demonstrated that an isoflavonoid-rich extract prepared from kudzu root has the potential to act as a protector for vascular endothelial cells against intracellular ROS mediated apoptosis and mitochondrial damage.

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the "gas of near circles" active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts.

[Establishment of animal models of drug-induced liver injury and analysis of possible mechanisms]

Drug-induced liver injury (DILI) is one of leading causes of attrition during both early and late stages of drug development and postmarketing. DILI is generally classified into the intrinsic and idiosyncratic types. Intrinsic DILI is dose dependent and predictable as exemplified by acetaminophen toxicity. However, the occurrence of idiosyncratic DILI with very low incidence and severe liver damage is difficult to predict because of the complex nature of DILI and poor understanding of its mechanism. In this review, we summarize current knowledge and our accumulated experimental findings on the pathogenic mechanisms of DILI focusing on the reactive metabolites of drugs formed by drug-metabolizing enzymes and immune- and inflammation-related responses. Considering drug metabolism and pharmacokinetics, we have established nonclinical animal models of DILI for 10 types of clinical drug known to cause idiosyncratic DILI in humans. Using animal models, it has been shown that the formation of reactive metabolites and both innate and adaptive immunity are involved in the pathogenesis of drug hepatotoxicity. Based on information on biomarkers obtained from animal models, we developed a cell-based system that predicts the potential DILI risks of drugs. The results of these studies increased our understanding of the mechanisms of DILI and help to predict and prevent idiosyncratic DILI caused by drug candidates.

Convergence of Highly Resolved and Rapid Screening Platforms with Dynamically Engineered, Cell Phenotype-Prescriptive Biomaterials

Biophysical and biochemical cues from the cellular microenvironment initiate intracellular signaling through cellular membrane receptors and trigger specific cell developmental programs. Extracellular substrates and matrix scaffolds engineered to mimic cell's native physiological environment must incorporate the multifactorial parameters (composition, micro and nanoscale organization and topography) of the extracellular matrix as well as the dynamic nature of the matrix. The design of such engineered biomaterials is challenged by the inherent complexity and dynamic nature of the cell-extracellular matrix reciprocity, while the validation of robust microenvironments requires a deeper, higher content phenotypic resolution of cell-matrix interactions alongside a rapid screening capability. To this end, high-throughput platforms are integral to facilitating the screening and optimization of complex engineered microenvironments for directing desired cell developmental pathway. This review highlights the recent advances in biomaterial platforms that present dynamic cues and enable high throughput screening of cell's response to a combination of micro-environmental factors. We also address some newer techniques involving high content image informatics to elucidate emergent cellular behaviors with a focus on stem cell regenerative endpoints.

High Content Imaging (HCI) on Miniaturized Three-Dimensional (3D) Cell Cultures

High content imaging (HCI) is a multiplexed cell staining assay developed for better understanding of complex biological functions and mechanisms of drug action, and it has become an important tool for toxicity and efficacy screening of drug candidates. Conventional HCI assays have been carried out on two-dimensional (2D) cell monolayer cultures, which in turn limit predictability of drug toxicity/efficacy in vivo; thus, there has been an urgent need to perform HCI assays on three-dimensional (3D) cell cultures. Although 3D cell cultures better mimic in vivo microenvironments of human tissues and provide an in-depth understanding of the morphological and functional features of tissues, they are also limited by having relatively low throughput and thus are not amenable to high-throughput screening (HTS). One attempt of making 3D cell culture amenable for HTS is to utilize miniaturized cell culture platforms. This review aims to highlight miniaturized 3D cell culture platforms compatible with current HCI technology.

Multiparametric Cell Cycle Analysis Using the Operetta High-Content Imager and Harmony Software with PhenoLOGIC

High-content imaging is a powerful tool for determining cell phenotypes at the single cell level. Characterising the effect of small molecules on cell cycle distribution is important for understanding their mechanism of action especially in oncology drug discovery but also for understanding potential toxicology liabilities. Here, a high-throughput phenotypic assay utilising the PerkinElmer Operetta high-content imager and Harmony software to determine cell cycle distribution is described. PhenoLOGIC, a machine learning algorithm within Harmony software was employed to robustly separate single cells from cell clumps. DNA content, EdU incorporation and pHH3 (S10) expression levels were subsequently utilised to separate cells into the various phases of the cell cycle. The assay is amenable to multiplexing with an additional pharmacodynamic marker to assess cell cycle changes within a specific cellular sub-population. Using this approach, the cell cycle distribution of γH2AX positive nuclei was determined following treatment with DNA damaging agents. Likewise, the assay can be multiplexed with Ki67 to determine the fraction of quiescent cells and with BrdU dual labelling to determine S-phase duration. This methodology therefore provides a relatively cheap, quick and high-throughput phenotypic method for determining accurate cell cycle distribution for small molecule mechanism of action and drug toxicity studies.

Safety evaluation of chinese medicine injections with a cell imaging-based multiparametric assay revealed a critical involvement of mitochondrial function in hepatotoxicity

The safety of herbal medicine products has been a widespread concern due to their complex chemical nature and lack of proper evaluation methods. We have adapted a sensitive and reproducible multiparametric cell-based high-content analysis assay to evaluate the hepatic-safety of four Chinese medicine injections and validated it with classical animal-based toxicity assays. Our results suggested that the reported hepatotoxicity by one of the drugs, Fufangkushen injection, could be attributed at least in part to the interference of mitochondrial function in human HepG2 cells by some of its constituents. This method should be useful for both preclinical screen in a drug discovery program and postclinical evaluation of herbal medicine preparations.