Live-Cell High Content Screening in Drug Development

"Keep on ROCKIn": Repurposed ROCK inhibitors to boost corneal endothelial regeneration

The global shortage of corneal endothelial graft tissue necessitates the exploration of alternative therapeutic strategies. Rho-associated protein kinase inhibitors (ROCKi), recognized for their regenerative potential in cardiology, oncology, and neurology, have shown promise in corneal endothelial regeneration. This study investigates the repurposing potential of additional ROCKi compounds. Through screening a self-assembled library of ROCKi on B4G12 corneal endothelial cells, we evaluated their dose-dependent effects on proliferation, migration, and toxicity using live-cell imaging. Nine ROCKi candidates significantly enhanced B4G12 proliferation compared to the basal growth rate. These candidates were further assessed for their potential to accelerate wound closure as another indicator for tissue regeneration capacity, with most demonstrating notable efficacy. To assess the potential impact of candidate ROCKi on key corneal endothelial cell markers related to cell proliferation, leaky tight junctions and ion efflux capacity, we analyzed the protein expression of cyclin E1, CDK2, p16, ZO-1 and Na+/K+-ATPase, respectively. Immunocytochemistry and western blot analysis confirmed the preservation of corneal endothelial markers post-treatment with ROCKi hits. However, notable cytoplasm enlargement and nuclear fragmentation were detected after the treatment with SR-3677 and Thiazovivin, indicating possible cellular stress. In compared parameters, Chroman-1 at a concentration of 10 nM outperformed other ROCKi, requiring significantly 1000-fold lower effective concentration than established ROCKi Y-27632 and Fasudil. Altogether, this study underscores the potential of repurposing ROCKi for treating corneal endothelial dysfunctions, offering a viable alternative to conventional grafting methods, and highlights Chroman-1 as a promising candidate structure for hit-to-lead development.

hcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells

Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

Automated high-content imaging in iPSC-derived neuronal progenitors

Induced pluripotent stem cells (iPSCs) have great potential as physiological disease models for human disorders where access to primary cells is difficult, such as neurons. In recent years, many protocols have been developed for the generation of iPSCs and the differentiation into specialised cell subtypes of interest. More recently, these models have been modified to allow large-scale phenotyping and high-content screening of small molecule compounds in iPSC-derived neuronal cells. Here, we describe the automated seeding of day 11 ventral midbrain progenitor cells into 96-well plates, administration of compounds, automated staining for immunofluorescence, the acquisition of images on a high-content screening platform and workflows for image analysis.

High-throughput imaging of mRNA at the single-cell level in human primary immune cells

Measurement of gene expression at the single-cell level has advanced the study of transcriptional regulation programs in healthy and disease states. In particular, single-cell approaches have shed light on the high level of transcriptional heterogeneity of individual cells, both at baseline and in response to experimental or environmental perturbations. We have developed a method for high-content imaging (HCI)-based quantification of relative changes in transcript abundance at the single-cell level in human primary immune cells and have validated its performance under multiple experimental conditions to demonstrate its general applicability. This method, named hcHCR, combines the sensitivity of the hybridization chain reaction (HCR) for the visualization of RNA in single cells, with the speed, scalability, and reproducibility of HCI. We first tested eight cell attachment substrates for short-term culture of primary human B cells, T cells, monocytes, or neutrophils. We then miniaturized HCR in 384-well format and documented the ability of the method to detect changes in transcript abundance at the single-cell level in thousands of cells for each experimental condition by HCI. Furthermore, we demonstrated the feasibility of multiplexing gene expression measurements by simultaneously assaying the abundance of three transcripts per cell at baseline and in response to an experimental stimulus. Finally, we tested the robustness of the assay to technical and biological variation. We anticipate that hcHCR will be suitable for low- to medium-throughput chemical or functional genomics screens in primary human cells, with the possibility of performing screens on cells obtained from patients with a specific disease.

Live-cell microscopy or fluorescence anisotropy with budded baculoviruses-which way to go with measuring ligand binding to M4 muscarinic receptors?

M4 muscarinic acetylcholine receptor is a G protein-coupled receptor (GPCR) that has been associated with alcohol and cocaine abuse, Alzheimer's disease, and schizophrenia which makes it an interesting drug target. For many GPCRs, the high-affinity fluorescence ligands have expanded the options for high-throughput screening of drug candidates and serve as useful tools in fundamental receptor research. Here, we explored two TAMRA-labelled fluorescence ligands, UR-MK342 and UR-CG072, for development of assays for studying ligand-binding properties to M4 receptor. Using budded baculovirus particles as M4 receptor preparation and fluorescence anisotropy method, we measured the affinities and binding kinetics of both fluorescence ligands. Using the fluorescence ligands as reporter probes, the binding affinities of unlabelled ligands could be determined. Based on these results, we took a step towards a more natural system and developed a method using live CHO-K1-hM4R cells and automated fluorescence microscopy suitable for the routine determination of unlabelled ligand affinities. For quantitative image analysis, we developed random forest and deep learning-based pipelines for cell segmentation. The pipelines were integrated into the user-friendly open-source Aparecium software. Both image analysis methods were suitable for measuring fluorescence ligand saturation binding and kinetics as well as for screening binding affinities of unlabelled ligands.

Capturing the third dimension in drug discovery: Spatially-resolved tools for interrogation of complex 3D cell models

Advanced three-dimensional (3D) cell models have proven to be capable of depicting architectural and microenvironmental features of several tissues. By providing data of higher physiological and pathophysiological relevance, 3D cell models have been contributing to a better understanding of human development, pathology onset and progression mechanisms, as well as for 3D cell-based assays for drug discovery. Nonetheless, the characterization and interrogation of these tissue-like structures pose major challenges on the conventional analytical methods, pushing the development of spatially-resolved technologies. Herein, we review recent advances and pioneering technologies suitable for the interrogation of multicellular 3D models, while capable of retaining biological spatial information. We focused on imaging technologies and omics tools, namely transcriptomics, proteomics and metabolomics. The advantages and shortcomings of these novel methodologies are discussed, alongside the opportunities to intertwine data from the different tools.

Neural network fast-classifies biological images through features selecting to power automated microscopy

Artificial intelligence is nowadays used for cell detection and classification in optical microscopy during post-acquisition analysis. The microscopes are now fully automated and next expected to be smart by making acquisition decisions based on the images. It calls for analysing them on the fly. Biology further imposes training on a reduced data set due to cost and time to prepare the samples and have the data sets annotated by experts. We propose a real-time image processing compliant with these specifications by balancing accurate detection and execution performance. We characterised the images using a generic, high-dimensional feature extractor. We then classified the images using machine learning to understand the contribution of each feature in decision and execution time. We found that the non-linear-classifier random forests outperformed Fisher's linear discriminant. More importantly, the most discriminant and time-consuming features could be excluded without significant accuracy loss, offering a substantial gain in execution time. It suggests a feature-group redundancy likely related to the biology of the observed cells. We offer a method to select fast and discriminant features. In our assay, a 79.6 ± 2.4% accurate classification of a cell took 68.7 ± 3.5 ms (mean ± SD, 5-fold cross-validation nested in 10 bootstrap repeats), corresponding to 14 cells per second, dispatched into eight phases of the cell cycle, using 12 feature groups and operating a consumer market ARM-based embedded system. A simple neural network offered similar performances paving the way to faster training and classification, using parallel execution on a general-purpose graphic processing unit. Finally, this strategy is also usable for deep neural networks paving the way to optimizing these algorithms for smart microscopy.

Automated Functional Screening for Modulators of Optogenetically Activated Neural Responses in Living Organisms

All-optical methods of probing in vivo brain function are advantageous for their compatibility with automated microscopy and fast spatial targeting of neural circuit excitation and response. Recent advances in optogenetic technologies allow simultaneous light activation of specific neurons and optical readout of neural activity via fluorescent calcium reporters, providing an attractive opportunity for high-throughput screening assays that directly assess dynamic neural function in vivo. Here we describe a method to automatically record optogenetically activated neural responses in living, hydrogel-embedded organisms over many hours in a multiwell plate format. This method is suitable for screening the neural effects of hundreds of chemical compounds and assessing the time course of bioactivity over 12 h or more. As examples, we show the suppression of neural responses over time with various concentrations of two voltage-gated calcium channel blockers and a full-plate screen of 320 chemicals with positive and negative controls in a single experiment.

High-content analysis of larval phenotypes for the screening of xenobiotic toxicity using Phallusia mammillata embryos

In recent years, pollution of surface waters with xenobiotic compounds became an issue of concern in society and has been the object of numerous studies. Most of these xenobiotic compounds are man-made molecules and some of them are qualified as endocrine disrupting chemicals (EDCs) when they interfere with hormones actions. Several studies have investigated the teratogenic impacts of EDCs in vertebrates (including marine vertebrates). However, the impact of such EDCs on marine invertebrates is much debated and still largely obscure. In addition, DNA-altering genotoxicants can induce embryonic malformations. The goal of this study is to develop a reliable and effective test for assessing toxicity of chemicals using embryos of the ascidian (Phallusia mammillata) in order to find phenotypic signatures associated with xenobiotics. We evaluated embryonic malformations with high-content analysis of larval phenotypes by scoring several quantitative and qualitative morphometric endpoints on a single image of Phallusia tadpole larvae with semi-automated image analysis. Using this approach we screened different classes of toxicants including genotoxicants, known or suspected EDCs and nuclear receptors (NRs) ligands. The screen presented here reveals a specific phenotypic signature for ligands of retinoic acid receptor/retinoid X receptor. Analysis of larval morphology combined with DNA staining revealed that embryos with DNA aberrations displayed severe malformations affecting multiple aspects of embryonic development. In contrast EDCs exposure induced no or little DNA aberrations and affected mainly neural development. Therefore the ascidian embryo/larval assay presented here can allow to distinguish the type of teratogenicity induced by different classes of toxicants.

Optimizing skin pharmacotherapy for older patients: the future is at hand but are we ready for it?

Age-related changes affect both the local pharmacotherapy of skin diseases and the transdermal administration of drugs. The development of aged skin models disregards the highly individual process of aging, facilitating general conclusions for older patients. Nevertheless, 'omics technology, high-content screening, and non-invasive imaging, as well as bioprinting, CRISPR-Cas, and, patients-on-a-chip, can retrieve personalized information for the generation of in vitro models. Herein, we suggest a strategy to optimize pharmacotherapy for older patients. The technology for relevant human cell-based models is at hand and the consideration of patient heterogeneity is required to unlock their full potential.

Development of a 3-D Organoid System Using Human Induced Pluripotent Stem Cells to Model Idiopathic Autism

Autism spectrum condition (ASC) is a complex set of behavioral and neurological responses reflecting a likely interaction between autism susceptibility genes and the environment. Autism represents a spectrum in which heterogeneous genetic backgrounds are expressed with similar heterogeneity in the affected domains of communication, social interaction, and behavior. The impact of gene-environment interactions may also account for differences in underlying neurology and wide variation in observed behaviors. For these reasons, it has been difficult for geneticists and neuroscientists to build adequate systems to model the complex neurobiology causes of autism. In addition, the development of therapeutics for individuals with autism has been painstakingly slow, with most treatment options reduced to repurposed medications developed for other neurological diseases. Adequately developing therapeutics that are sensitive to the genetic and neurobiological diversity of individuals with autism necessitates personalized models of ASC that can capture some common pathways that reflect the neurophysiological and genetic backgrounds of varying individuals. Testing cohorts of individuals with and without autism for these potentially convergent pathways on a scalable platform for therapeutic development requires large numbers of samples from a diverse population. To date, human induced pluripotent stem cells (iPSCs) represent one of the best systems for conducting these types of assays in a clinically relevant and scalable way. The discovery of the four Yamanaka transcription factors (OCT3/4, SOX2, c-Myc, and KLF4) [1] allows for the induction of iPSCs from fibroblasts [2], peripheral blood mononuclear cells (PBMCs, i.e. lymphocytes and monocytes) [3, 4], or dental pulp cells [5] that retain the original genetics of the individual from which they were derived [6], making iPSCs a powerful tool to model neurophysiological conditions. iPSCs are a readily renewable cell type that can be developed on a small scale for boutique-style proof-of-principle phenotypic studies and scaled to an industrial level for drug screening and other high-content assays. This flexibility, along with the ability to represent the true genetic diversity of autism, underscores the importance of using iPSCs to model neurophysiological aspects of ASC.

The Promises and Challenges of Toxico-Epigenomics: Environmental Chemicals and Their Impacts on the Epigenome

BACKGROUND

It has been estimated that a substantial portion of chronic and noncommunicable diseases can be caused or exacerbated by exposure to environmental chemicals. Multiple lines of evidence indicate that early life exposure to environmental chemicals at relatively low concentrations could have lasting effects on individual and population health. Although the potential adverse effects of environmental chemicals are known to the scientific community, regulatory agencies, and the public, little is known about the mechanistic basis by which these chemicals can induce long-term or transgenerational effects. To address this question, epigenetic mechanisms have emerged as the potential link between genetic and environmental factors of health and disease.

OBJECTIVES

We present an overview of epigenetic regulation and a summary of reported evidence of environmental toxicants as epigenetic disruptors. We also discuss the advantages and challenges of using epigenetic biomarkers as an indicator of toxicant exposure, using measures that can be taken to improve risk assessment, and our perspectives on the future role of epigenetics in toxicology.

DISCUSSION

Until recently, efforts to apply epigenomic data in toxicology and risk assessment were restricted by an incomplete understanding of epigenomic variability across tissue types and populations. This is poised to change with the development of new tools and concerted efforts by researchers across disciplines that have led to a better understanding of epigenetic mechanisms and comprehensive maps of epigenomic variation. With the foundations now in place, we foresee that unprecedented advancements will take place in the field in the coming years. https://doi.org/10.1289/EHP6104.

A Smart Imaging Workflow for Organ-Specific Screening in a Cystic Kidney Zebrafish Disease Model

The zebrafish is being increasingly used in biomedical research and drug discovery to conduct large-scale compound screening. However, there is a lack of accessible methodologies to enable automated imaging and scoring of tissue-specific phenotypes at enhanced resolution. Here, we present the development of an automated imaging pipeline to identify chemical modifiers of glomerular cyst formation in a zebrafish model for human cystic kidney disease. Morpholino-mediated knockdown of intraflagellar transport protein Ift172 in Tg(wt1b:EGFP) embryos was used to induce large glomerular cysts representing a robustly scorable phenotypic readout. Compound-treated embryos were consistently aligned within the cavities of agarose-filled microplates. By interfacing feature detection algorithms with automated microscopy, a smart imaging workflow for detection, centring and zooming in on regions of interests was established, which enabled the automated capturing of standardised higher resolution datasets of pronephric areas. High-content screening datasets were processed and analysed using custom-developed heuristic algorithms implemented in common open-source image analysis software. The workflow enables highly efficient profiling of entire compound libraries and scoring of kidney-specific morphological phenotypes in thousands of zebrafish embryos. The demonstrated toolset covers all the aspects of a complex whole organism screening assay and can be adapted to other organs, specimens or applications.

Live Cell Imaging and Analysis to Capture T-Cell Motility in Real-Time

T-lymphocytes are the principle coordinators of the immune defense system and play a major role in the protection of our body against infections, intruders of non-self, and malignancies. To mount an immune response, T-cells need to be effectively employed to tissue sites of infection or inflammation and establish contacts with antigen-presenting cells (APCs) or malignant cells. Understanding how T-cells navigate toward their recruitment sites would offer new therapeutic opportunities. Advancement in the hardware and software upgrades of microscopy technology has created several efficient and easy-to-operate live cell imaging platforms. In this protocol, we present a generalized and simple-to-follow protocol for live cell imaging of migrating T-cells, which can also be adopted to visualize real-time tracking of intracellular signaling events.

Establishing a Cell-Based High-Content Screening Assay for TCM Compounds with Anti-Renal Fibrosis Effects

Renal fibrosis is thought to be the final common pathway leading to chronic kidney disease (CKD) and end-stage renal failure. Except for renal replacement therapy, no adequate treatment regimen is available; therefore studies on the treatment of renal fibrosis have attracted significant interest. In recent years, studies have shown that traditional Chinese medicine (TCM) may represent an attractive source to produce drugs with antifibrosis effects. The aim of this study was to establish a robust cell-based high-content screening (HCS) approach to identify TCM compounds with antifibrosis effects in NRK49F cells following TGF-β1 exposure. When designing the model, one of the most important steps involved the stability and reproducibility of this cell-based model. Therefore, we initially optimized the experimental parameters. Then, our HCS model was validated using SB525334, an inhibitor of the TGF-β1 receptor, and curcumin and emodin, two TCM compounds with well-documented anti-renal fibrosis activity. Subsequently, the proven reliable HCS model was used to screen a standard TCM compound library, which included 344 TCM molecules. Based on our HCS algorithm, a total of 16 compounds were identified to have prospective inhibitory activity. These compounds were further validated by verification experiments. Strikingly, eight compounds have been shown to inhibit renal fibrosis; six of them had rarely been described in the literature, namely, Ligustrazine, Glycyrrhizic acid, Astragaloside iv, Hydroxysafflor Yellow A, Crocin, and Gypenosides. To the best of our knowledge, this is the first study in which a HCS assay was performed to identify TCM compounds with anti-renal fibrosis effects. The HCS approach was successfully applied to screen active compounds and will be propitious to further anti-renal fibrosis drugs discovery research. Meanwhile, it may offer possibilities for identifying lead compounds for treating other diseases from registered Chinese herbal medicines.