Getting the whole picture: High content screening using three-dimensional cellular model systems and whole animal assays

A novel thin plate spline methodology to model tissue surfaces and quantify tumor cell invasion in organ-on-chip models

Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.

Advances in high throughput cell culture technologies for therapeutic screening and biological discovery applications

Cellular phenotypes and functional responses are modulated by the signals present in their microenvironment, including extracellular matrix (ECM) proteins, tissue mechanical properties, soluble signals and nutrients, and cell-cell interactions. To better recapitulate and analyze these complex signals within the framework of more physiologically relevant culture models, high throughput culture platforms can be transformative. High throughput methodologies enable scientists to extract increasingly robust and broad datasets from individual experiments, screen large numbers of conditions for potential hits, better qualify and predict responses for preclinical applications, and reduce reliance on animal studies. High throughput cell culture systems require uniformity, assay miniaturization, specific target identification, and process simplification. In this review, we detail the various techniques that researchers have used to face these challenges and explore cellular responses in a high throughput manner. We highlight several common approaches including two-dimensional multiwell microplates, microarrays, and microfluidic cell culture systems as well as unencapsulated and encapsulated three-dimensional high throughput cell culture systems, featuring multiwell microplates, micromolds, microwells, microarrays, granular hydrogels, and cell-encapsulated microgels. We also discuss current applications of these high throughput technologies, namely stem cell sourcing, drug discovery and predictive toxicology, and personalized medicine, along with emerging opportunities and future impact areas.

A novel thin plate spline methodology to model tissue surfaces and quantify tumor cell invasion in organ-on-chip models

Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.

Technologies bringing young Zebrafish from a niche field to the limelight

Fundamental life science and pharmaceutical research are continually striving to provide physiologically relevant context for their biological studies. Zebrafish present an opportunity for high-content screening (HCS) to bring a true in vivo model system to screening studies. Zebrafish embryos and young larvae are an economical, human-relevant model organism that are amenable to both genetic engineering and modification, and direct inspection via microscopy. The use of these organisms entails unique challenges that new technologies are overcoming, including artificial intelligence (AI). In this perspective article, we describe the state-of-the-art in terms of automated sample handling, imaging, and data analysis with zebrafish during early developmental stages. We highlight advances in orienting the embryos, including the use of robots, microfluidics, and creative multi-well plate solutions. Analyzing the micrographs in a fast, reliable fashion that maintains the anatomical context of the fluorescently labeled cells is a crucial step. Existing software solutions range from AI-driven commercial solutions to bespoke analysis algorithms. Deep learning appears to be a critical tool that researchers are only beginning to apply, but already facilitates many automated steps in the experimental workflow. Currently, such work has permitted the cellular quantification of multiple cell types in vivo, including stem cell responses to stress and drugs, neuronal myelination and macrophage behavior during inflammation and infection. We evaluate pro and cons of proprietary versus open-source methodologies for combining technologies into fully automated workflows of zebrafish studies. Zebrafish are poised to charge into HCS with ever-greater presence, bringing a new level of physiological context.

Current Trends and Research Topics Regarding Intestinal Organoids: An Overview Based on Bibliometrics

Currently, research on intestinal diseases is mainly based on animal models and cell lines in monolayers. However, these models have drawbacks that limit scientific advances in this field. Three-dimensional (3D) culture systems named organoids are emerging as a reliable research tool for recapitulating the human intestinal epithelium and represent a unique platform for patient-specific drug testing. Intestinal organoids (IOs) are crypt–villus structures that can be derived from adult intestinal stem cells (ISCs), embryonic stem cells (ESCs), or induced pluripotent stem cells (iPSCs) and have the potential to serve as a platform for individualized medicine and research. However, this emerging field has not been bibliometric summarized to date. Here, we performed a bibliometric analysis of the Web of Science Core Collection (WoSCC) database to evaluate 5,379 publications concerning the use of organoids; the studies were divided into four clusters associated with the current situation and future directions for the application of IOs. Based on the results of our bibliometric analysis of IO applications, we systematically summarized the latest advances and analyzed the limitations and prospects.

Quantitative Confocal Microscopy for Grouping of Dose-Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine

Fluorescent calcium (Ca²⁺) imaging is one of the preferred methods to record cellular activity during in vitro preclinical studies, high-content drug screening, and toxicity analysis. Visualization and analysis for dose-response data obtained using high-resolution imaging remain challenging, due to the inherent heterogeneity present in the Ca²⁺ spiking. To address this challenge, we propose measurement of cytosolic Ca²⁺ ions using spinning-disk confocal microscopy and machine learning-based analytics that is scalable. First, we implemented uniform manifold approximation and projection (UMAP) for visualizing the multivariate time-series dataset in the two-dimensional (2D) plane using Python. The dataset was obtained through live imaging experiments with norepinephrine-induced Ca²⁺ oscillation in HeLa cells for a large range of doses. Second, we demonstrate that the proposed framework can be used to depict the grouping of the spiking pattern for lower and higher drug doses. To the best of our knowledge, this is the first attempt at UMAP visualization of the time-series dose response and identification of the Ca²⁺ signature during lytic death. Such quantitative microscopy can be used as a component of a high-throughput data analysis workflow for toxicity analysis.

High-Throughput Screening of Compound Neurotoxicity Using 3D-Cultured Neural Stem Cells on a 384-Pillar Plate

Assessing the neurotoxicity of test chemicals has typically been performed using two-dimensionally (2D)-cultured neuronal cell monolayers and animal models. The in vitro 2D cell models are simple and straightforward compared to animal models, which have the disadvantage of being relatively low throughput, expensive, and time consuming. Despite their extensive use in this area of neurotoxicology research, both models often do not accurately recapitulate human outcomes. To bridge this gap and attempt to better replicate what happens in vivo, three-dimensionally (3D) cultured neural stem cells (NSCs) encapsulated in hydrogels on a 384-pillar plate have been developed via miniature 3D bioprinting. This technology allows users to print NSCs on a pillar plate for rapid 3D cell culture as well as high-throughput compound screening. For this, the 384-pillar plate with bioprinted NSCs is sandwiched with a standard 384-well plate with growth medium for 3D culture, allowing researchers to expose the cells to test compounds and stain them with various fluorescent dyes for a suite of high-content imaging assays, including assays for DNA damage, mitochondrial impairment, cell membrane integrity, intracellular glutathione levels, and apoptosis. After acquiring cell images from an automated fluorescence microscope and extracting fluorescence intensities, researchers can obtain the IC₅₀ value of each compound to evaluate critical parameters in neurotoxicity. Here, we provide a detailed description of protocols for cell printing on a 384-pillar plate, 3D NSC culture, compound testing, 3D cell staining, and image acquisition and analysis, which altogether will allow researchers to investigate mechanisms of compound neurotoxicity with 3D-cultured NSCs in a high-throughput manner. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Three-dimensional neural stem cell culture on a 384-pillar plate Basic Protocol 2: Compound treatment and cell staining Basic Protocol 3: Image acquisition, processing, and data analysis.

Use of artificial intelligence to enhance phenotypic drug discovery

Research and development (R&D) productivity across the pharmaceutical industry has received close scrutiny over the past two decades, especially taking into consideration reports of attrition rates and the colossal cost for drug development. The respective merits of the two main drug discovery approaches, phenotypic and target based, have divided opinion across the research community, because each hold different advantages for identifying novel molecular entities with a successful path to the market. Nevertheless, both have low translatability in the clinic. Artificial intelligence (AI) and adoption of machine learning (ML) tools offer the promise of revolutionising drug development, and overcoming obstacles in the drug discovery pipeline. Here, we assess the potential of target-driven and phenotypic-based approaches and offer a holistic description of the current state of the field, from both a scientific and industry perspective. With the emerging partnerships between AI/ML and pharma still in their relative infancy, we investigate the potential and current limitations with a particular focus on phenotypic drug discovery. Finally, we emphasise the value of public-private partnerships (PPPs) and cross-disciplinary collaborations to foster innovation and facilitate efficient drug discovery programmes.

Imaging microphysiological systems: a review

Microphysiological systems (MPS), often referred to as "organ-on-chips," are microfluidic-based in vitro models that aim to recapitulate the dynamic chemical and mechanical microenvironment of living organs. MPS promise to bridge the gap between in vitro and in vivo models and ultimately improve the translation from preclinical animal studies to clinical trials. However, despite the explosion of interest in this area in recent years, and the obvious rewards for such models that could improve R&D efficiency and reduce drug attrition in the clinic, the pharmaceutical industry has been slow to fully adopt this technology. The ability to extract robust, quantitative information from MPS at scale is a key requirement if these models are to impact drug discovery and the subsequent drug development process. Microscopy imaging remains a core technology that enables the capture of information at the single-cell level and with subcellular resolution. Furthermore, such imaging techniques can be automated, increasing throughput and enabling compound screening. In this review, we discuss a range of imaging techniques that have been applied to MPS of varying focus, such as organoids and organ-chip-type models. We outline the opportunities these technologies can bring in terms of understanding mechanistic biology, but also how they could be used in higher-throughput screens, widening the scope of their impact in drug discovery. We discuss the associated challenges of imaging these complex models and the steps required to enable full exploitation. Finally, we discuss the requirements for MPS, if they are to be applied at a scale necessary to support drug discovery projects.

High-content imaging of 3D-cultured neural stem cells on a 384-pillar plate for the assessment of cytotoxicity

The assessment of neurotoxicity has been performed traditionally with animals. However, in vivo studies are highly expensive and time-consuming, and often do not correlate to human outcomes. Thus, there is a need for cost-effective, high-throughput, highly predictive alternative in vitro test methods based on early markers of mechanisms of toxicity. High-content imaging (HCI) assays performed on three-dimensionally (3D) cultured cells could provide better understanding of the mechanism of toxicity needed to predict neurotoxicity in humans. However, current 3D cell culture systems lack the throughput required for screening neurotoxicity against a large number of chemicals. Therefore, we have developed miniature 3D neural stem cell (NSC) culture on a unique 384-pillar plate, which is complementary to conventional 384-well plates. Mitochondrial membrane impairment, intracellular glutathione level, cell membrane integrity, DNA damage, and apoptosis have been tested against 3D-cultured ReNcell VM on the 384-pillar plate with four model compounds rotenone, 4-aminopyridine, digoxin, and topotecan. The HCI assays performed in 3D-cultured ReNcell VM on the 384-pillar plates were highly robust and reproducible as indicated by the average Z' factor of 0.6 and CV values around 12%. From concentration-response curves and IC₅₀ values, mitochondrial membrane impairment appears to be the early stage marker of cell death by the compounds.

Simultaneous in situ visualization and quantitation of dual antigens adsorbed on adjuvants using high content analysis

Aim: Traditional antigenicity assay requires antigen recovery from the particulate adjuvants prior to analysis. An in situ method was developed for interrogating vaccine antigens with monoclonal antibodies while being adsorbed on adjuvants. Materials & methods: The fluorescence imaging-based high content analysis was used to visualize the antigen distribution on adjuvant agglomerates and to analyze the antigenicity for adsorbed antigens. Results: Simultaneous visualization and quantitation were achieved for dual antigens in a bivalent human papillomavirus vaccine with uniquely labeled antibodies. Good agreement was observed between the in situ multiplexed assays with well-established sandwich enzyme-linked immunosorbent assays. Conclusion: The streamlined procedures and the amenability for multiplexing make the in situ antigenicity analysis a favorable choice for in vitro functional assessment of bionanoparticles as vaccine antigens.

Models used to screen for the treatment of multidrug resistant cancer facilitated by transporter-based efflux

PURPOSE

Efflux transporters of the adenosine triphosphate-binding cassette (ABC)-superfamily play an important role in the development of multidrug resistance (multidrug resistant; MDR) in cancer. The overexpression of these transporters can directly contribute to the failure of chemotherapeutic drugs. Several in vitro and in vivo models exist to screen for the efficacy of chemotherapeutic drugs against MDR cancer, specifically facilitated by efflux transporters.

RESULTS

This article reviews a range of efflux transporter-based MDR models used to test the efficacy of compounds to overcome MDR in cancer. These models are classified as either in vitro or in vivo and are further categorised as the most basic, conventional models or more complex and advanced systems. Each model's origin, advantages and limitations, as well as specific efflux transporter-based MDR applications are discussed. Accordingly, future modifications to existing models or new research approaches are suggested to develop prototypes that closely resemble the true nature of multidrug resistant cancer in the human body.

CONCLUSIONS

It is evident from this review that a combination of both in vitro and in vivo preclinical models can provide a better understanding of cancer itself, than using a single model only. However, there is still a clear lack of progression of these models from basic research to high-throughput clinical practice.

Microfluidic-Printed Microcarrier for In Vitro Expansion of Adherent Stem Cells in 3D Culture Platform

Microcarrier-based stem cell expansion cultures can increase the dimensions of in vitro stem cell cultures from 2D to 3D. The culture handling process then becomes more efficient compared with conventional 2D cultures. However, the use of spherical plastic microcarriers complicates the monitoring of cell culture. To facilitate monitoring, transparent disc-shaped microcarriers are manufactured using a light-initiated microfluidic printing system and the obtained microcarriers are named as 2.5D microcarrier. The 2.5D microcarriers (diameter/height ≈ 5) enable us to use conventional monitoring tools in 2D-based platform during the in vitro expansion on a 3D culture platform. Surface modification via a 1 h-long poly-dopamine (PDA) reaction can maintain the transparent nature of the microcarriers while optimizing the cell attachment. The surface marker expression and differentiation potential of the 2.5D microcarrier-expanded stem cells reveal that the characteristics and functionalities preserved during expansion. The 2.5D microcarrier is readily integrated into an on-bead assay to conserve reagents and permit a high number (n = 9) of repeated measurements with reliable results. These results demonstrate that the 2.5D microcarrier-based scale-up culture provides a valuable tool for the in vitro expansion of adherent stem cells, especially if repetitive monitoring is required.

High content screening for drug discovery from traditional Chinese medicine

Traditional Chinese medicine (TCM) represents the crystallization of Chinese wisdom and civilization. It has been valued as the renewable source for the discovery of novel drugs, owing to its long-term proved efficacy in human diseases and abundant biologically active components pools. To dissect the mystery of TCM, modern technologies such as omics approaches (proteomics, genomics, metabolomics) and drug screening technologies (high through-put screening, high content screening and virtual screening) have been widely applied to either identify the drug target of TCM or identify the active component with certain bio-activity. The advent of high content screening technology has absolutely contributed to a breakthrough in compounds discovery and influenced the evolution of technology in screening field. The review introduces the concept and principle of high content screening, lists and compares the currently used HCS instruments, and summarizes the examples from ours and others research work which applied HCS in TCM-derived compounds screening. Meanwhile, this article also discusses the advantages and limitations of HSC technology in drug discovery from TCM libraries.

Using stem cell-derived neurons in drug screening for neurological diseases

Induced pluripotent stem cells and their derivatives have become an important tool for researching disease mechanisms. It is hoped that they could be used to discover new therapies by providing the most reliable and relevant human in vitro disease models for drug discovery. This review will summarize recent efforts to use stem cell-derived neurons for drug screening. We also explain the current hurdles to using these cells for high-throughput pharmaceutical screening and developments that may help overcome these hurdles. Finally, we critically discuss whether induced pluripotent stem cell-derived neurons will come to fruition as a model that is regularly used to screen for drugs to treat neurological diseases.

A single cell high content assay detects mitochondrial dysfunction in iPSC-derived neurons with mutations in SNCA

Mitochondrial dysfunction is implicated in many neurodegenerative diseases including Parkinson's disease (PD). Induced pluripotent stem cells (iPSCs) provide a unique cell model for studying neurological diseases. We have established a high-content assay that can simultaneously measure mitochondrial function, morphology and cell viability in iPSC-derived dopaminergic neurons. iPSCs from PD patients with mutations in SNCA and unaffected controls were differentiated into dopaminergic neurons, seeded in 384-well plates and stained with the mitochondrial membrane potential dependent dye TMRM, alongside Hoechst-33342 and Calcein-AM. Images were acquired using an automated confocal screening microscope and single cells were analysed using automated image analysis software. PD neurons displayed reduced mitochondrial membrane potential and altered mitochondrial morphology compared to control neurons. This assay demonstrates that high content screening techniques can be applied to the analysis of mitochondria in iPSC-derived neurons. This technique could form part of a drug discovery platform to test potential new therapeutics for PD and other neurodegenerative diseases.

Cell and small animal models for phenotypic drug discovery

The phenotype-based drug discovery (PDD) approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s) or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery.