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.

Biomedical Applications of Translational Optical Imaging: From Molecules to Humans

Light is a powerful investigational tool in biomedicine, at all levels of structural organization. Its multitude of features (intensity, wavelength, polarization, interference, coherence, timing, non-linear absorption, and even interactions with itself) able to create contrast, and thus images that detail the makeup and functioning of the living state can and should be combined for maximum effect, especially if one seeks simultaneously high spatiotemporal resolution and discrimination ability within a living organism. The resulting high relevance should be directed towards a better understanding, detection of abnormalities, and ultimately cogent, precise, and effective intervention. The new optical methods and their combinations needed to address modern surgery in the operating room of the future, and major diseases such as cancer and neurodegeneration are reviewed here, with emphasis on our own work and highlighting selected applications focusing on quantitation, early detection, treatment assessment, and clinical relevance, and more generally matching the quality of the optical detection approach to the complexity of the disease. This should provide guidance for future advanced theranostics, emphasizing a tighter coupling-spatially and temporally-between detection, diagnosis, and treatment, in the hope that technologic sophistication such as that of a Mars rover can be translationally deployed in the clinic, for saving and improving lives.

Review of high-content screening applications in toxicology

High-content screening (HCS) technology combining automated microscopy and quantitative image analysis can address biological questions in academia and the pharmaceutical industry. Various HCS experimental applications have been utilized in the research field of in vitro toxicology. In this review, we describe several HCS application approaches used for studying the mechanism of compound toxicity, highlight some challenges faced in the toxicological community, and discuss the future directions of HCS in regards to new models, new reagents, data management, and informatics. Many specialized areas of toxicology including developmental toxicity, genotoxicity, developmental neurotoxicity/neurotoxicity, hepatotoxicity, cardiotoxicity, and nephrotoxicity will be examined. In addition, several newly developed cellular assay models including induced pluripotent stem cells (iPSCs), three-dimensional (3D) cell models, and tissues-on-a-chip will be discussed. New genome-editing technologies (e.g., CRISPR/Cas9), data analyzing tools for imaging, and coupling with high-content assays will be reviewed. Finally, the applications of machine learning to image processing will be explored. These new HCS approaches offer a huge step forward in dissecting biological processes, developing drugs, and making toxicology studies easier.

Opportunities and Challenges in Implementation of Multiparameter Single Cell Analysis Platforms for Clinical Translation

The high-content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo. Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care. Since 2013, leading experts representing industry, academia, and government have been brought together as part of the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium to foster the potential of high-content data integration for clinical translation.

Analysis of variability in high throughput screening data: applications to melanoma cell lines and drug responses

High-throughput screening (HTS) strategies and protocols have undergone significant development in the last decade. It is now possible to screen hundreds of thousands of compounds, each exploring multiple biological phenotypes and parameters, against various cell lines or model systems in a single setting. However, given the vast amount of data such studies generate, the fact that they use multiple reagents, and are often technician-intensive, questions have been raised about the variability, reliability and reproducibility of HTS results. Assessments of the impact of the multiple factors in HTS studies could arguably lead to more compelling insights into the robustness of the results of a particular screen, as well as the overall quality of the study. We leveraged classical, yet highly flexible, analysis of variance (ANOVA)-based linear models to explore how different factors contribute to the variation observed in a screening study of four different melanoma cell lines and 120 drugs over nine dosages studied in two independent academic laboratories. We find that factors such as plate effects, appropriate dosing ranges, and to a lesser extent, the laboratory performing the screen, are significant predictors of variation in drug responses across the cell lines. Further, we show that when sources of variation are quantified and controlled for, they contextualize claims of inconsistencies and reveal the overall quality of the HTS studies performed at each participating laboratory. In the context of the broader screening study, we show that our analysis can also elucidate the robust effects of drugs, even those within specific cell lines.

The development of high-content screening (HCS) technology and its importance to drug discovery

INTRODUCTION

High-content screening (HCS) was introduced about twenty years ago as a promising analytical approach to facilitate some critical aspects of drug discovery. Its application has spread progressively within the pharmaceutical industry and academia to the point that it today represents a fundamental tool in supporting drug discovery and development.

AREAS COVERED

Here, the authors review some of significant progress in the HCS field in terms of biological models and assay readouts. They highlight the importance of high-content screening in drug discovery, as testified by its numerous applications in a variety of therapeutic areas: oncology, infective diseases, cardiovascular and neurodegenerative diseases. They also dissect the role of HCS technology in different phases of the drug discovery pipeline: target identification, primary compound screening, secondary assays, mechanism of action studies and in vitro toxicology.

EXPERT OPINION

Recent advances in cellular assay technologies, such as the introduction of three-dimensional (3D) cultures, induced pluripotent stem cells (iPSCs) and genome editing technologies (e.g., CRISPR/Cas9), have tremendously expanded the potential of high-content assays to contribute to the drug discovery process. Increasingly predictive cellular models and readouts, together with the development of more sophisticated and affordable HCS readers, will further consolidate the role of HCS technology in drug discovery.

Visualization and Image Analysis of Yeast Cells

When converting real-life data via visualization to numbers and then onto statistics the whole system needs to be considered so that conversion from the analogue to the digital is accurate and repeatable. Here we describe the points to consider when approaching yeast cell analysis visualization, processing, and analysis of a population by screening techniques.

Fluorescent protein biosensors applied to microphysiological systems

This mini-review discusses the evolution of fluorescence as a tool to study living cells and tissues in vitro and the present role of fluorescent protein biosensors (FPBs) in microphysiological systems (MPSs). FPBs allow the measurement of temporal and spatial dynamics of targeted cellular events involved in normal and perturbed cellular assay systems and MPSs in real time. FPBs evolved from fluorescent analog cytochemistry (FAC) that permitted the measurement of the dynamics of purified proteins covalently labeled with environmentally insensitive fluorescent dyes and then incorporated into living cells, as well as a large list of diffusible fluorescent probes engineered to measure environmental changes in living cells. In parallel, a wide range of fluorescence microscopy methods were developed to measure the chemical and molecular activities of the labeled cells, including ratio imaging, fluorescence lifetime, total internal reflection, 3D imaging, including super-resolution, as well as high-content screening. FPBs evolved from FAC by combining environmentally sensitive fluorescent dyes with proteins in order to monitor specific physiological events such as post-translational modifications, production of metabolites, changes in various ion concentrations, and the dynamic interaction of proteins with defined macromolecules in time and space within cells. Original FPBs involved the engineering of fluorescent dyes to sense specific activities when covalently attached to particular domains of the targeted protein. The subsequent development of fluorescent proteins (FPs), such as the green fluorescent protein, dramatically accelerated the adoption of studying living cells, since the genetic "labeling" of proteins became a relatively simple method that permitted the analysis of temporal-spatial dynamics of a wide range of proteins. Investigators subsequently engineered the fluorescence properties of the FPs for environmental sensitivity that, when combined with targeted proteins/peptides, created a new generation of FPBs. Examples of FPBs that are useful in MPS are presented, including the design, testing, and application in a liver MPS.

High-content screening technology for studying drug-induced hepatotoxicity in cell models

High-content screening is the application of automated microscopy and image analysis to both cell biology and drug discovery. Over the last decade, this technique has emerged as a useful technology that allows the simultaneous measurement of different parameters at a single-cell level. Hepatotoxicity is a compelling reason for drug nonapprovals and withdrawals. It is recognized that the safety of a compound cannot be based on a single in vitro assay, and existing methods are not predictive of drug-induced toxicity. However, different HCS assays have been recently demonstrated as being powerful for identifying different mechanisms implicated in drug-induced toxicity with high sensitivity and specificity. These assays integrate the data obtained from different cell function indicators and can be easily incorporated into basic screening processes for the safety evaluation and selection of drug candidates; thus, they contribute greatly to lessen the likelihood of drug failure. Exploring the use of cellular imaging technology in drug-induced liver injury by reviewing the different tests proposed provides evidence that this technology has a strong impact on drug discovery.

RNAi screens for genes involved in Golgi glycosylation

RNAi screening has gained popularity in recent years, due to its usefulness in systematic investigations of biological pathways. Combined with high-content screening and advances in imaging and analysis methods, it can enable detailed genetic characterization of cellular processes such as protein glycosylation, a major function of the Golgi apparatus. Glycosylation concerns about one third of all human proteins and regulates various cellular behaviors. Yet the methods available to study it are limited and not easily accessible. In this chapter, we detail a step-by-step method to systematically and quantitatively investigate glycosylation using fluorescent lectin staining, following high-throughput RNAi-based downregulation of gene activities. We also provide a workflow for downstream analysis of the data generated.

Antitags: SERS-encoded nanoparticle assemblies that enable single-spot multiplex protein detection

Simultaneous detection of multiple proteins on a single spot can be efficiently achieved by using multiplexed surface-enhanced Raman spectroscopy (SERS)-encoded nanoparticle 'antitags' consisting of poly(ethylene glycol) (PEG)-protected silver dimers (and higher aggregates) and antibody-tagging entities. The effective SERS-based multivariate deconvolution approach guarantees an accurate and successful distinguishable identification of single and multiple proteins in complex samples. Their potential application in multiplexed SERS bioimaging technology can be easily envisaged.

Fluorescent biosensors for high throughput screening of protein kinase inhibitors

High throughput screening assays aim to identify small molecules that interfere with protein function, activity, or conformation, which can serve as effective tools for chemical biology studies of targets involved in physiological processes or pathways of interest or disease models, as well as templates for development of therapeutics in medicinal chemistry. Fluorescent biosensors constitute attractive and powerful tools for drug discovery programs, from high throughput screening assays, to postscreen characterization of hits, optimization of lead compounds, and preclinical evaluation of candidate drugs. They provide a means of screening for inhibitors that selectively target enzymatic activity, conformation, and/or function in vitro. Moreover, fluorescent biosensors constitute useful tools for cell- and image-based, multiplex and multiparametric, high-content screening. Application of fluorescence-based sensors to screen large and complex libraries of compounds in vitro, in cell-based formats or whole organisms requires several levels of optimization to establish robust and reproducible assays. In this review, we describe the different fluorescent biosensor technologies which have been applied to high throughput screens, and discuss the prerequisite criteria underlying their successful application. Special emphasis is placed on protein kinase biosensors, since these enzymes constitute one of the most important classes of therapeutic targets in drug discovery.

Genotoxicity evaluation of individual cigarette smoke toxicants using the in vitro γH2AX assay by high content screening

Cigarette smoke is a complex mixture consisting of more than 5600 identified chemical constituents of which approximately 150 have been identified so far as "tobacco smoke toxicants". Proposals made by the World Health Organisation Framework Convention on Tobacco Control mandate the lowering of nine tobacco smoke priority toxicants, including 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), N-nitrosonornicotine (NNN), and benzo[a]pyrene (B[a]P) and monitoring the levels of a further nine including cadmium. Here, we evaluated the genotoxic potential in human bronchial epithelial BEAS-2B cells of four cigarette smoke toxicants; NNK, NNN, B[a]P and cadmium using the novel in vitro γH2AX assay by High Content Screening (HCS). We also examined the genotoxicity of binary mixtures of NNK and NNN reporting their relative contribution to the genotoxic end-point. The results of this preliminary assessment showed that the in vitro γH2AX assay by HCS could be used as a pre-screening tool to detect and quantify the genotoxicity effect of cigarette smoke toxicants individually and in binary mixture. Moreover, the data produced could contribute to the prioritisation of toxicant reduction research in modified tobacco products.

Assessment of the in vitro γH2AX assay by High Content Screening as a novel genotoxicity test

The γH2AX assay is widely used as a marker of DNA damage in multiple scientific fields such as cancer biomarker, clinical studies and radiation biology. In particular, the in vitro γH2AX assay has been suggested as a novel in vitro genotoxicity test with potential as a pre-screening tool. However, to date, limited assessments have been carried out to evaluate the sensitivity, specificity and accuracy of the in vitro γH2AX assay. In this study, the microscopy-based system combining automated cellular image acquisition with software quantification for High Content Screening (HCS) has been used for the first time to evaluate the in vitro γH2AX assay. A panel of well-characterised genotoxic and non-genotoxic compounds was selected to assess the performance of the in vitro γH2AX assay in the human bronchial epithelial cell line BEAS-2B. The results obtained during this preliminary assessment indicate that the in vitro γH2AX assay has a high accuracy (86%) as a result of high sensitivity and specificity (86-92% and 80-88% respectively). Our data highlight the potential for γH2AX detection in HCS as a complement to the current regulatory genotoxicity battery of in vitro assays. We therefore recommend more comprehensive assessments to confirm the performance of the in vitro γH2AX assay by HCS with a more extensive set of compounds.

Chapter 17: bioimage informatics for systems pharmacology

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies.

Moving to the core: spatiotemporal analysis of Forkhead box O (FOXO) and nuclear factor-κB (NF-κB) nuclear translocation

Nuclear translocation of proteins is an essential aspect of normal cell function, and defects in this process have been detected in many disease-associated conditions. The detection and quantification of nuclear translocation was significantly boosted by the association of robotized microscopy with automated image analysis, a technology designated as high-content screening. Image-based high-content screening and analysis provides the means to systematically observe cellular translocation events in time and space in response to chemical or genetic perturbation at large scale. This approach yields powerful insights into the regulation of complex signaling networks independently of preconceived notions of mechanistic relationships. In this review, we briefly overview the different mechanisms involved in nucleocytoplasmic protein trafficking. In addition, we discuss high-content approaches used to interrogate the mechanistic and spatiotemporal dynamics of cellular signaling events using Forkhead box O (FOXO) proteins and the nuclear factor-κB (NF-κB) as important and clinically relevant examples.

High-content screening and analysis of the Golgi complex

High-content screening (HCS) as a methodological tool has evolved relatively recently, largely driven by the demand for in depth spatial and temporal information from intact cells exposed to a range of chemical and/or genomic perturbations. The technology is based around automated fluorescence microscopy in combination with advanced imaging processing and analysis tools, which together can provide quantitative information as a first-level description of complex cellular events. HCS and high-content analysis are particularly powerful when combined with perturbation techniques such as RNA interference (RNAi), as this allows large families of genes to be interrogated with respect to a biological pathway or process of interest. In this methodology chapter, we describe an approach by which HCS can be applied to study the morphological state of the Golgi complex in cultured mammalian cells. We provide a detailed protocol for the highly parallel downregulation of gene activity using RNAi in 384-well plates and describe an automated image analysis routine that could be used to quantify Golgi complex in a genome-wide RNAi context.

Multiplex optical sensing with surface-enhanced Raman scattering: a critical review

Multiplex analysis permits the detection of several analytical targets at the same time. This approach may permit to draw a rapid and accurate diagnostic about the health of an individual or an environment. Among the analytical techniques with potential for multiplexing surface-enhanced Raman scattering (SERS) offer unique advantages such as ultrasensitive detection down low the deconvolution times, a unique signature containing all the vibrational information of the target molecules, and the possibility of performing the experiments even in very demanding environments such as natural or biological fluids. Here we review the late advances in multiplex SERS including the direct methods, those aided by the surface functionalization of the plasmonic nanoparticles and the use of SERS encoded particles.

Designs and concept reliance of a fully automated high-content screening platform

High-content screening (HCS) is becoming an accepted platform in academic and industry screening labs and does require slightly different logistics for execution. To automate our stand-alone HCS microscopes, namely, an alpha IN Cell Analyzer 3000 (INCA3000), originally a Praelux unit hooked to a Hudson Plate Crane with a maximum capacity of 50 plates per run, and the IN Cell Analyzer 2000 (INCA2000), in which up to 320 plates could be fed per run using the Thermo Fisher Scientific Orbitor, we opted for a 4 m linear track system harboring both microscopes, plate washer, bulk dispensers, and a high-capacity incubator allowing us to perform both live and fixed cell-based assays while accessing both microscopes on deck. Considerations in design were given to the integration of the alpha INCA3000, a new gripper concept to access the onboard nest, and peripheral locations on deck to ensure a self-reliant system capable of achieving higher throughput. The resulting system, referred to as Hestia, has been fully operational since the new year, has an onboard capacity of 504 plates, and harbors the only fully automated alpha INCA3000 unit in the world.

The use of integrated and intelligent testing strategies in the prediction of toxic hazard and in risk assessment

There is increasing concern that insurmountable differences between humans and laboratory animals limit the relevance and reliability for hazard identification and risk assessment purposes of animal data produced by traditional toxicity test procedures. A way forward is offered by the emerging new technologies, which can be directly applied to human material or even to human beings themselves. This promises to revolutionise the evaluation of the safety of chemicals and chemical products of various kinds and, in particular, pharmaceuticals. The available and developing technologies are summarised and it is emphasised that they will need to be used selectively, in integrated and intelligent testing strategies, which, in addition to being scientifically sound, must be manageable and affordable. Examples are given of proposed testing strategies for general chemicals, cosmetic ingredients, candidate pharmaceuticals, inhaled substances, nanoparticles and neurotoxicity.

Comparisons between in vitro whole cell imaging and in vivo zebrafish-based approaches for identifying potential human hepatotoxicants earlier in pharmaceutical development

Drug-induced liver injury (DILI) is a major cause of attrition during both the early and later stages of the drug development and marketing process. Reducing or eliminating drug-induced severe liver injury, especially those that lead to liver transplants or death, would be tremendously beneficial for patients. Therefore, developing new pharmaceuticals that have the highest margins and attributes of hepatic safety would be a great accomplishment. Given the current low productivity of pharmaceutical companies and the high costs of bringing new medicines to market, any early screening assay(s) to identify and eliminate pharmaceuticals with the potential to cause severe liver injury in humans would be of economic value as well. The present review discusses the background, proof-of-concept, and validation studies associated with high-content screening (HCS) by two major pharmaceutical companies (Pfizer Inc and Jansen Pharmaceutical Companies of Johnson & Johnson) for detecting compounds with the potential to cause human DILI. These HCS assays use fluorescent-based markers of cell injury in either human hepatocytes or HepG2 cells. In collaboration with Evotec, an independent contract lab, these two companies also independently evaluated larval zebrafish as an early-stage in vivo screen for hepatotoxicity in independently conducted, blinded assessments. Details about this model species, the need for bioanalysis, and, specifically, the outcome of the phenotypic-based zebrafish screens are presented. Comparing outcomes in zebrafish against both HCS assays suggests an enhanced detection for hepatotoxicants of most DILI concern when used in combination with each other, based on the U.S. Food and Drug Administration DILI classification list.

High-content screening data management for drug discovery in a small- to medium-size laboratory: results of a collaborative pilot study focused on user expectations as indicators of effectiveness

High-content screening (HCS) technology provides a powerful vantage point to approach biological problems; it allows analysis of cell parameters, including changes in cell or protein movement, shape, or texture. As part of a collaborative pilot research project to improve bioscience research data integration, we identified HCS data management as an area ripe for advancement. A primary goal was to develop an integrated data management and analysis system suitable for small- to medium-size HCS programs that would improve research productivity and increase work satisfaction. A system was developed that uses Labmatrix, a Web-based research data management platform, to integrate and query data derived from a Cellomics STORE database. Focusing on user expectations, several barriers to HCS productivity were identified and reduced or eliminated. The impact of the project on HCS research productivity was tested through a series of 18 lab-requested integrated data queries, 7 of which were fully enabled, 7 partially enabled, and 4 enabled through data export to standalone data analysis tools. The results are limited to one laboratory, but this pilot suggests that through an "implementation research" approach, a network of small- to medium-size laboratories involved in HCS projects could achieve greater productivity and satisfaction in drug discovery research.

Protein localization in disease and therapy

The eukaryotic cell is organized into membrane-covered compartments that are characterized by specific sets of proteins and biochemically distinct cellular processes. The appropriate subcellular localization of proteins is crucial because it provides the physiological context for their function. In this Commentary, we give a brief overview of the different mechanisms that are involved in protein trafficking and describe how aberrant localization of proteins contributes to the pathogenesis of many human diseases, such as metabolic, cardiovascular and neurodegenerative diseases, as well as cancer. Accordingly, modifying the disease-related subcellular mislocalization of proteins might be an attractive means of therapeutic intervention. In particular, cellular processes that link protein folding and cell signaling, as well as nuclear import and export, to the subcellular localization of proteins have been proposed as targets for therapeutic intervention. We discuss the concepts involved in the therapeutic restoration of disrupted physiological protein localization and therapeutic mislocalization as a strategy to inactivate disease-causing proteins.

Phaedra, a Protocol-Driven System for Analysis and Validation of High-Content Imaging and Flow Cytometry

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community. After review of existing applications, we realized the possibility of adding innovative new analysis options. Phaedra was developed to support workflows for drug screening and target discovery, interact with several laboratory information management systems, and process data generated by a range of techniques including high-content imaging, multicolor flow cytometry, and traditional high-throughput screening assays. The application is modular and flexible, with an interface that can be tuned to specific user roles. It offers user-friendly data visualization and reduction tools for HCS but also integrates Matlab for custom image analysis and the Konstanz Information Miner (KNIME) framework for data mining. Phaedra features efficient JPEG2000 compression and full drill-down functionality from dose-response curves down to individual cells, with exclusion and annotation options, cell classification, statistical quality controls, and reporting.