Advances in high content screening for drug discovery

High-content analysis in toxicology: screening substances for human toxicity potential, elucidating subcellular mechanisms and in vivo use as translational safety biomarkers

High-content analysis (HCA) of in vitro biochemical and morphological effects of classic (small molecule) drugs and chemicals is concordant with potential for human toxicity. For hepatotoxicity, concordance is greater for cytotoxic effects assessed by HCA than for conventional cytotoxicity tests and for regulatory animal toxicity studies. Additionally, HCA identifies chronic toxicity potential, and drugs producing idiosyncratic adverse reactions and/or toxic metabolites are also identified by HCA. Mechanistic information on the subcellular basis for the toxicity is frequently identified, including various mitochondrial effects, oxidative stress, calcium dyshomeostasis, phospholipidosis, apoptosis and antiproliferative effects, and a fingerprinting of the sequence and pattern of subcellular events. As these effects are frequently non-specific and affect many cell types, some toxicities may be detected and monitored by HCA of peripheral blood cells, such as for anticancer and anti-infective drugs. Critical methodological and interpretive features are identified that are critical to the effectiveness of the HCA cytotoxicity assessment, including the need for multiple days of exposure of cells to drug, use of a human hepatocyte cell line with metabolic competence, assessment of multiple pre-lethal effects in individual live cells, consideration of hormesis, the need for interpretation of relevance of cytotoxicity concentration compared to efficacy concentration and quality management. Limitations of the HCA include assessment of drugs that act on receptors, transporters or processes not found in hepatocytes. HCA may be used in a) screening lead candidates for potential human toxicity in drug discovery alongside of in vitro assessment of efficacy and pharmacokinetics, b) elucidating mechanisms of toxicity and c) monitoring in vivo toxicity of drugs with known toxicity of known mechanism.

Analysis of cellular events using CellCard™ System in cell-based high-content multiplexed assays

High-content screening technologies utilize assays that monitor and quantify multiple cellular events. These assays are typically performed on a single cell type with automated microscopy and image analysis. However, in order to better understand the selectivity of a compound across multiple cell lines, these types of assay must be run serially, which is time consuming. The CellCard System developed by Vitra Bioscience enables multiple cell types to be assayed within a single microtiter well, thereby enabling the simultaneous determination of cellular responses across ten cell types. This multiplexed approach could address the demand for assay capacity, increase the quality of the biologic data, reduce timelines, and improve cost-effectiveness in hit identification and lead evaluation. The authors have carried out an in-depth evaluation of this technology platform using ten cancer cell lines and a library of compounds that affect cellular growth through different mechanisms. Multiple assays were used to investigate the compound effects on membrane integrity, cell cycle progression and apoptosis. In this technology review, the authors discuss personal experience with assay validation, data analysis, results such as cell type-specific compound effects, and the potential application of the CellCard System in drug discovery.

Visualizing chemical structure-subcellular localization relationships using fluorescent small molecules as probes of cellular transport

Background

To study the chemical determinants of small molecule transport inside cells, it is crucial to visualize relationships between the chemical structure of small molecules and their associated subcellular distribution patterns. For this purpose, we experimented with cells incubated with a synthetic combinatorial library of fluorescent, membrane-permeant small molecule chemical agents. With an automated high content screening instrument, the intracellular distribution patterns of these chemical agents were microscopically captured in image data sets, and analyzed off-line with machine vision and cheminformatics algorithms. Nevertheless, it remained challenging to interpret correlations linking the structure and properties of chemical agents to their subcellular localization patterns in large numbers of cells, captured across large number of images.

Results

To address this challenge, we constructed a Multidimensional Online Virtual Image Display (MOVID) visualization platform using off-the-shelf hardware and software components. For analysis, the image data set acquired from cells incubated with a combinatorial library of fluorescent molecular probes was sorted based on quantitative relationships between the chemical structures, physicochemical properties or predicted subcellular distribution patterns. MOVID enabled visual inspection of the sorted, multidimensional image arrays: Using a multipanel desktop liquid crystal display (LCD) and an avatar as a graphical user interface, the resolution of the images was automatically adjusted to the avatar’s distance, allowing the viewer to rapidly navigate through high resolution image arrays, zooming in and out of the images to inspect and annotate individual cells exhibiting interesting staining patterns. In this manner, MOVID facilitated visualization and interpretation of quantitative structure-localization relationship studies. MOVID also facilitated direct, intuitive exploration of the relationship between the chemical structures of the probes and their microscopic, subcellular staining patterns.

Conclusion

MOVID can provide a practical, graphical user interface and computer-assisted image data visualization platform to facilitate bioimage data mining and cheminformatics analysis of high content, phenotypic screening experiments.

Discovery and biological activity of new chondramides from Chondromyces sp

Myxobacteria have proven to be highly valuable sources of natural products, as they produce a variety of secondary metabolites with unique structures and often new modes of action. In this study, high-content screening is demonstrated to be a convenient tool for bioactivity-guided isolation of natural products from crude bacterial extracts. By the application of focused, image-based screens we were able to identify over 30 novel chondramide derivatives from Chondromyces sp. MSr9030, some of which were present in only minute amounts. These cyclic depsipeptides were shown to target actin filaments with a similar binding mode to that of the mushroom toxin phalloidin. Fermentations of the myxobacterial strain were carried out under improved cultivation conditions, and supplementation of the culture broth with potassium bromide afforded the production of brominated analogues that are superior (in terms of biological activity) to all chondramides described to date. Initial biological profiling of 11 new derivatives in comparison to the reference compounds (chondramides A-C) showed that bromo-chondramide C3 and propionyl-bromo-chondramide C3 are the most active in cell-based studies, with GI₅₀ values on human cancer cell lines in the low nanomolar range. Given that these brominated C3 analogues were also less potent on noncancerous human cells (by a factor of 2 to 4 in comparison to cancer cell lines), our results can aid further structure-activity relationship-guided development of chondramides, either as molecular probes or pharmaceutical agents.

Drug target inference through pathway analysis of genomics data

Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues in this field, covering methodological developments, their pros and cons, as well as future research directions.

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially.

Update on in vitro cytotoxicity assays for drug development

BACKGROUND

in vitro cytotoxicity testing provides a crucial means of ranking compounds for consideration in drug discovery. The choice of using a particular viability or cytotoxicity assay technology may be influenced by specific research goals.

OBJECTIVE

Although the high-throughput screening (HTS) utility is typically dependent upon sensitivity and scalability, it is also impacted by signal robustness and resiliency to assay interferences. Further consideration should be given to data quality, ease-of-use, reagent stability, and matters of cost-effectiveness.

METHODS

Here we focus on three main classes of assays that are at present the most popular, useful, and practical for HTS drug discovery efforts. These methods measure: i) viability by metabolism reductase activities; ii) viability by bioluminescent ATP assays; or iii) cytotoxicity by enzymes 'released' into culture medium. Multi-parametric technologies are also briefly discussed.

RESULTS/CONCLUSION

Each of these methods has its relative merits and detractions; however multi-parametric methods using both viability and cytotoxicity markers may mitigate the inherent shortcomings of single parameter measures.

Functional interrogation of breast cancer: from models to drugs

Functional genomics allows for the activity of the whole genome to be surveyed at once. Using this technology for the identification of novel targets and their validation in disease-specific contexts has profound implications for the future of drug discovery. Now researchers have the technological means to gather comprehensive data on basic biological phenomena and disease mechanisms, while monitoring the effect of drug candidates on a molecular level. Pathway analysis can facilitate the genetic profiling of patients and, in turn, predict individual responses to treatment regimes. Functional interrogation of a disease-specific phenotype at a whole genome level (through, for example, the use of whole genome RNAi libraries) allows for the identification of critical regulators in complex biological systems, and the detection of putative targets for future therapeutic intervention. The authors describe the applications of functional genomics in models of breast cancer and the integration of these disparate technologies, specifically in the context of the search for novel therapeutic targets.

The future of microfluidic assays in drug development

BACKGROUND

Microfluidic technology emerges as a convenient route to applying automated and reliable assays in a high-throughput manner with low cost.

OBJECTIVE

This review aims to answer questions related to the capabilities and potential applications of microfluidic assays that can benefit the drug development process and extends an outlook on its future trends.

METHODS

This article reviews recent publications in the field of microfluidics, with an emphasis on novel applications for drug development.

RESULTS/CONCLUSION

Microfluidics affords unique capabilities in sample preparation and separation, combinatorial synthesis and array formation, and incorporating nanotechnology for more functionalities. The pharmaceutical industry, facing challenges from limited productivity and accelerated competition, can thus greatly benefit from applying new microfluidic assays in various drug development stages, from target screening and lead optimization to absorption distribution metabolism elimination and toxicity studies in preclinical evaluations, diagnostics in clinical trials and drug formulation and manufacturing process optimization.

1Click1View: interactive visualization methodology for RNAi cell-based microscopic screening

Technological advancements are constantly increasing the size and complexity of data resulting from large-scale RNA interference screens. This fact has led biologists to ask complex questions, which the existing, fully automated analyses are often not adequate to answer. We present a concept of 1Click1View (1C1V) as a methodology for interactive analytic software tools. 1C1V can be applied for two-dimensional visualization of image-based screening data sets from High Content Screening (HCS). Through an easy-to-use interface, one-click, one-view concept, and workflow based architecture, visualization method facilitates the linking of image data with numeric data. Such method utilizes state-of-the-art interactive visualization tools optimized for fast visualization of large scale image data sets. We demonstrate our method on an HCS dataset consisting of multiple cell features from two screening assays.

A high-content screening assay in transgenic zebrafish identifies two novel activators of fgf signaling

Zebrafish have become an invaluable vertebrate animal model to interrogate small molecule libraries for modulators of complex biological pathways and phenotypes. We have recently described the implementation of a quantitative, high-content imaging assay in multi-well plates to analyze the effects of small molecules on Fibroblast Growth Factor (FGF) signaling in vivo. Here we have evaluated the capability of the assay to identify compounds that hyperactivate FGF signaling from a test cassette of agents with known biological activities. Using a transgenic zebrafish reporter line for FGF activity, we screened 1040 compounds from an annotated library of known bioactive agents, including FDA-approved drugs. The assay identified two molecules, 8-hydroxyquinoline sulfate and pyrithione zinc, that enhanced FGF signaling in specific areas of the brain. Subsequent studies revealed that both compounds specifically expanded FGF target gene expression. Furthermore, treatment of early stage embryos with either compound resulted in dorsalized phenotypes characteristic of hyperactivation of FGF signaling in early development. Documented activities for both agents included activation of extracellular signal-related kinase (ERK), consistent with FGF hyperactivation. To conclude, we demonstrate the power of automated quantitative high-content imaging to identify small molecule modulators of FGF.

Intracellular protein trafficking kinetics in chronic myeloid leukemia stem cells using a microfluidic platform

The oncogenic fusion protein BCR-ABL is produced by chronic myeloid leukemia (CML) cells and functions as an abnormal, constitutively active tyrosine kinase that interferes with normal migratory and apoptotic behaviour of cells. Small molecule tyrosine kinase inhibitors (TKIs), such as dasatinib, eliminate CML progenitor cells, but fail to target the stem cell fraction resulting in persistent disease. In order to achieve a cure for CML in the majority of patients, we need an improved understanding of intracellular signalling dynamics, including the shuttling of BCR-ABL between cytosolic and nuclear compartments. In the past, the instability of BCR-ABL in assays using conventional immunohistochemical techniques has made this difficult and has not allowed for reliable analysis at the single cell level. Here we show how the utilization of rapid on-chip cell fixation within a microfluidic platform provides a means to immunofluorescently analyze the spatiotemporal localization of both BCR-ABL and c-ABL, as well as the linked apoptosis mediator, BCL-XL, in arrays of single CD34+ CML stem/progenitor cells, without cell loss. We demonstrate this proceeds up to 4 times faster than benchtop methods. Our results indicate that whilst both BCR-ABL and c-ABL shuttle from the cytoplasm to the nucleus following dasatinib treatment, the temporal dynamics are not synchronized. The microfluidic platform has the potential to provide insights into the intracellular signalling events in single cells. The ability to examine signalling events and assess BCR-ABL expression/activity in isolated cells in "real-time" may help elucidate the characteristics of rare CML stem cell events, which lead to the resistance of CML stem cells to TKIs.

New concepts for building vocabulary for cell image ontologies

Background

There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within ontologies, queries would be possible through shared terms. One approach to achieving this is to strictly control the terms used in ontologies in the form of a pre-defined schema, but this approach limits the individual researcher's ability to create new terms when needed to describe new experiments.

Results

Here, we propose the use of a limited number of highly reusable common root terms, and rules for an experimentalist to locally expand terms by adding more specific terms under more general root terms to form specific new vocabulary hierarchies that can be used to build ontologies. We illustrate the application of the method to build vocabularies and a prototype database for cell images that uses a visual data-tree of terms to facilitate sophisticated queries based on a experimental parameters. We demonstrate how the terminology might be extended by adding new vocabulary terms into the hierarchy of terms in an evolving process. In this approach, image data and metadata are handled separately, so we also describe a robust file-naming scheme to unambiguously identify image and other files associated with each metadata value. The prototype database http://sbd.nist.gov/ consists of more than 2000 images of cells and benchmark materials, and 163 metadata terms that describe experimental details, including many details about cell culture and handling. Image files of interest can be retrieved, and their data can be compared, by choosing one or more relevant metadata values as search terms. Metadata values for any dataset can be compared with corresponding values of another dataset through logical operations.

Conclusions

Organizing metadata for cell imaging experiments under a framework of rules that include highly reused root terms will facilitate the addition of new terms into a vocabulary hierarchy and encourage the reuse of terms. These vocabulary hierarchies can be converted into XML schema or RDF graphs for displaying and querying, but this is not necessary for using it to annotate cell images. Vocabulary data trees from multiple experiments or laboratories can be aligned at the root terms to facilitate query development. This approach of developing vocabularies is compatible with the major advances in database technology and could be used for building the Semantic Web.

Genetic and proteomic approaches to identify cancer drug targets

While target-based small-molecule discovery has taken centre-stage in the pharmaceutical industry, there are many cancer-promoting proteins not easily addressed with a traditional target-based screening approach. In order to address this problem, as well as to identify modulators of biological states in the absence of knowing the protein target of the state switch, alternative phenotypic screening approaches, such as gene expression-based and high-content imaging, have been developed. With this renewed interest in phenotypic screening, however, comes the challenge of identifying the binding protein target(s) of small-molecule hits. Emerging technologies have the potential to improve the process of target identification. In this review, we discuss the application of genomic (gene expression-based), genetic (short hairpin RNA and open reading frame screening), and proteomic approaches to protein target identification.

A high content drug screen identifies ursolic acid as an inhibitor of amyloid beta protein interactions with its receptor CD36

A pathological hallmark of Alzheimer disease (AD) is deposition of amyloid β (Aβ) in the brain. Aβ binds to microglia via a receptor complex that includes CD36 leading to production of proinflammatory cytokines and neurotoxic reactive oxygen species and subsequent neurodegeneration. Interruption of Aβ binding to CD36 is a potential therapeutic strategy for AD. To identify pharmacologic inhibitors of Aβ binding to CD36, we developed a 384-well plate assay for binding of fluorescently labeled Aβ to Chinese hamster ovary cells stably expressing human CD36 (CHO-CD36) and screened an Food and Drug Administration-approved compound library. The assay was optimized based on the cells' tolerance to dimethyl sulfoxide, Aβ concentration, time required for Aβ binding, reproducibility, and signal-to-background ratio. Using this assay, we identified four compounds as potential inhibitors of Aβ binding to CD36. These compounds were ursolic acid, ellipticine, zoxazolamine, and homomoschatoline. Of these compounds, only ursolic acid, a naturally occurring pentacyclic triterpenoid, successfully inhibited binding of Aβ to CHO-CD36 cells in a dose-dependent manner. The ursolic acid effect reached a plateau at ~20 μm, with a maximal inhibition of 64%. Ursolic acid also blocked binding of Aβ to microglial cells and subsequent ROS production. Our data indicate that cell-based high-content screening of small molecule libraries for their ability to block binding of Aβ to its receptors is a useful tool to identify novel inhibitors of receptors involved in AD pathogenesis. Our data also suggest that ursolic acid is a potential therapeutic agent for AD via its ability to block Aβ-CD36 interactions.

Screening of siRNA nanoparticles for delivery to airway epithelial cells using high-content analysis

Aims: Delivery of siRNA to the lungs via inhalation offers a unique opportunity to develop a new treatment paradigm for a range of respiratory conditions. However, progress has been greatly hindered by safety and delivery issues. This study developed a high-throughput method for screening novel nanotechnologies for pulmonary siRNA delivery. Methodology: Following physicochemical analysis, the ability of PEI–PEG–siRNA nanoparticles to facilitate siRNA delivery was determined using high-content analysis (HCA) in Calu-3 cells. Results obtained from HCA were validated using confocal microscopy. Finally, cytotoxicity of the PEI–PEG–siRNA particles was analyzed by HCA using the Cellomics® multiparameter cytotoxicity assay. Conclusion: PEI–PEG–siRNA nanoparticles facilitated increased siRNA uptake and luciferase knockdown in Calu-3 cells compared with PEI–siRNA.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

Comparison of segmentation algorithms for fluorescence microscopy images of cells

The analysis of fluorescence microscopy of cells often requires the determination of cell edges. This is typically done using segmentation techniques that separate the cell objects in an image from the surrounding background. This study compares segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions. Significant variability in the results of segmentation was observed that was due solely to differences in imaging conditions or applications of different algorithms. We quantified and compared the results with a novel bivariate similarity index metric that evaluates the degree of underestimating or overestimating a cell object. The results show that commonly used threshold-based segmentation techniques are less accurate than k-means clustering with multiple clusters. Segmentation accuracy varies with imaging conditions that determine the sharpness of cell edges and with geometric features of a cell. Based on this observation, we propose a method that quantifies cell edge character to provide an estimate of how accurately an algorithm will perform. The results of this study will assist the development of criteria for evaluating interlaboratory comparability.

A quantitative, facile, and high-throughput image-based cell migration method is a robust alternative to the scratch assay

Cell migration is a key phenotype for a number of therapeutically important biological responses, including angiogenesis. A commonly used method to assess cell migration is the scratch assay, which measures the movement of cells into a wound made by physically scoring a confluent cell monolayer to create an area devoid of cells. Although this method has been adequate for qualitative characterization of migration inhibitors, it does not provide the highly reproducible results required for quantitative compound structure-activity relationship evaluation because of the inconsistent size and placement of the wound area within the microplate well. The Oris™ Cell Migration Assay presents a superior alternative to the scratch assay, permitting formation of precisely placed and homogeneously sized cell-free areas into which migration can occur without releasing factors from wounded or dead cells or damaging the underlying extracellular matrix. Herein the authors compare results from the scratch and Oris™ cell migration assays using an endothelial progenitor cell line and the Src kinase inhibitor dasatinib. They find that using the Acumen™ Explorer laser microplate cytometer in combination with the Oris™ Cell Migration Assay plate provides a robust, efficient, and cost-effective cell migration assay exhibiting excellent signal to noise, plate uniformity, and statistical validation metrics.

Cell migration and invasion assays as tools for drug discovery

Cell migration and invasion are processes that offer rich targets for intervention in key physiologic and pathologic phenomena such as wound healing and cancer metastasis. With the advent of high-throughput and high content imaging systems, there has been a movement towards the use of physiologically relevant cell-based assays earlier in the testing paradigm. This allows more effective identification of lead compounds and recognition of undesirable effects sooner in the drug discovery screening process. This article will review the effective use of several principle formats for studying cell motility: scratch assays, transmembrane assays, microfluidic devices and cell exclusion zone assays.

Sequential array cytometry: multi-parameter imaging with a single fluorescent channel

Heterogeneity within the human population and within diseased tissues necessitates a personalized medicine approach to diagnostics and the treatment of diseases. Functional assays at the single-cell level can contribute to uncovering heterogeneity and ultimately assist in improved treatment decisions based on the presence of outlier cells. We aim to develop a platform for high-throughput, single-cell-based assays using well-characterized hydrodynamic cell isolation arrays which allow for precise cell and fluid handling. Here, we demonstrate the ability to extract spatial and temporal information about several intracellular components using a single fluorescent channel, eliminating the problem of overlapping fluorescence emission spectra. Integrated with imaging technologies such as wide field-of-view lens-free fluorescent imaging, fiber-optic array scanning technology, and microlens arrays, use of a single fluorescent channel will reduce the cost of reagents and optical components. Specifically, we sequentially stain hydrodynamically trapped cells with three biochemical labels all sharing the same fluorescence excitation and emission spectrum. These markers allow us to analyze the amount of DNA, and compare nucleus-to-cytoplasm ratio, as well as glycosylation of surface proteins. By imaging cells in real-time we enable measurements of temporal localization of cellular components and intracellular reaction kinetics, the latter is used as a measurement of multi-drug resistance. Demonstrating the efficacy of this single-cell analysis platform is the first step in designing and implementing more complete assays, aimed toward improving diagnosis and personalized treatments to complex diseases.

A Personal Perspective on High-Content Screening (HCS)

High-content screening (HCS) was introduced in 1997 based on light microscope imaging technologies to address the need for an automated platform that could analyze large numbers of individual cells with subcellular resolution using standard microplates. Molecular specificity based on fluorescence was a central element of the platform taking advantage of the growing list of reagent classes and the ability to multiplex. In addition, image analysis coupled to data management, data mining, and data visualization created a tool that focused on biological information and knowledge to begin exploring the functions of genes identified in the genomics revolution. This overview looks at the development of HCS, the evolution of the technologies, and the market up to the present day. In addition, the options for adopting uniform definitions is suggested along with a perspective on what advances are needed to continue building the value of HCS in biomedical research, drug discovery, and development and diagnostics.

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe-discovery and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of 'virtual' profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe-discovery and drug-discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections.

Machine vision-assisted analysis of structure-localization relationships in a combinatorial library of prospective bioimaging probes

With a combinatorial library of bioimaging probes, it is now possible to use machine vision to analyze the contribution of different building blocks of the molecules to their cell-associated visual signals. For this purpose, cell-permeant, fluorescent styryl molecules were synthesized by condensation of 168 aldehyde with 8 pyridinium/quinolinium building blocks. Images of cells incubated with fluorescent molecules were acquired with a high content screening instrument. Chemical and image feature analysis revealed how variation in one or the other building block of the styryl molecules led to variations in the molecules' visual signals. Across each pair of probes in the library, chemical similarity was significantly associated with spectral and total signal intensity similarity. However, chemical similarity was much less associated with similarity in subcellular probe fluorescence patterns. Quantitative analysis and visual inspection of pairs of images acquired from pairs of styryl isomers confirm that many closely-related probes exhibit different subcellular localization patterns. Therefore, idiosyncratic interactions between styryl molecules and specific cellular components greatly contribute to the subcellular distribution of the styryl probes' fluorescence signal. These results demonstrate how machine vision and cheminformatics can be combined to analyze the targeting properties of bioimaging probes, using large image data sets acquired with automated screening systems.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Comparison of variability and sensitivity between nuclear translocation and luciferase reporter gene assays

High-content screening (HCS), a technology based on subcellular imaging by automated microscopy and sophisticated image analysis, has emerged as an important platform in small-molecule screening for early drug discovery. To validate a subcellular imaging assay for primary screening campaigns, an HCS assay was compared with a non-image-based readout in terms of variability and sensitivity. A study was performed monitoring the accumulation of the forkhead transcription factor of the O subfamily (FOXO3a) coupled with green fluorescent protein in the nucleus of human osteosarcoma (U-2 OS) cells. In addition, the transcription of a luciferase gene coupled with a FOXO3a-responsive promoter was monitored. This report demonstrates that both assay formats show good reproducibility in primary and concentration response screening despite differences in statistical assay quality. In primary screening, the correlation of compound activity between the 2 assays was low, in contrast to the good correlation of the IC(50) values of confirmed compounds. Furthermore, the high-content imaging assay showed a mean shift of 2.63-fold in IC(50) values compared with the reporter gene assay. No chemical scaffold was specifically found with 1 of the technologies only, however these results validate the HCS technology against established assays for screening of new molecular entities.

Analytical methods to assess nanoparticle toxicity

During the past 20 years, improvements in nanoscale materials synthesis and characterization have given scientists great control over the fabrication of materials with features between 1 and 100 nm, unlocking many unique size-dependent properties and, thus, promising many new and/or improved technologies. Recent years have found the integration of such materials into commercial goods; a current estimate suggests there are over 800 nanoparticle-containing consumer products (The Project on Emerging Nanotechnologies Consumer Products Inventory, , accessed Oct. 2008), accounting for 147 billion USD in products in 2007 (Nanomaterials state of the market Q3 2008: stealth success, broad impact, Lux Research Inc., New York, NY, 2008). Despite this increase in the prevalence of engineered nanomaterials, there is little known about their potential impacts on environmental health and safety. The field of nanotoxicology has formed in response to this lack of information and resulted in a flurry of research studies. Nanotoxicology relies on many analytical methods for the characterization of nanomaterials as well as their impacts on in vitro and in vivo function. This review provides a critical overview of these techniques from the perspective of an analytical chemist, and is intended to be used as a reference for scientists interested in conducting nanotoxicological research as well as those interested in nanotoxicological assay development.

High-throughput screening for analysis of in vitro toxicity

The influence of combinatorial chemistry and high-throughput screening (HTS) technologies in the pharmaceutical industry during the last 10 years has been enormous. However, the attrition rate of drugs in the clinic due to toxicity during this period still remained 40-50%. The need for reduced toxicity failure led to the development of early toxicity screening assays. This chapter describes the state of the art for assays in the area of genotoxicity, cytotoxicity, carcinogenicity, induction of specific enzymes from phase I and II metabolism, competition assays for enzymes of phase I and II metabolism, embryotoxicity as well as endocrine disruption and reprotoxicity. With respect to genotoxicity, the full Ames, Ames II, Vitotox, GreenScreen GC, RadarScreen, and non-genotoxic carcinogenicity assays are discussed. For cytotoxicity, cellular proliferation, calcein uptake, oxygen consumption, mitochondrial activity, radical formation, glutathione depletion as well as apoptosis are described. For high-content screening (HCS), the possibilities for analysis of cytotoxicity, micronuclei, centrosome formation and phospholipidosis are examined. For embryotoxicity, endocrine disruption and reprotoxicity alternative assays are reviewed for fast track analysis by means of nuclear receptors and membrane receptors. Moreover, solutions for analyzing enzyme induction by activation of nuclear receptors, like AhR, CAR, PXR, PPAR, FXR, LXR, TR and RAR are given.

Chemotherapeutic drugs and human tumor cells cytokine network

The ability of human tumor cell lines to produce various cytokines, chemokines, angiogenic and growth factors was investigated using Luminex multiplex technology. Media conditioned by tumor cells protected tumor cells from drug-induced apoptosis and stimulated tumor cell proliferation. Antibodies neutralizing IL-6, CXCL8, CCL2 and CCL5 blocked this stimulation. Treatment of tumor cells with doxorubicin and cisplatin resulted in a substantial increase in the production of IL-6, CXCL8, CCL2, CCL5, BFGF, G-CSF and VEGF. This stimulation was associated with drug-induced activation of NF-kappaB, AP-1, AP-2, CREB, HIF-1, STAT-1, STAT-3, STAT-5 and ATF-2 transcription factors and upregulation of IL-6, CXCL8, FGF-2, CSF-3 and CCL5 gene expression. Treatment of tumor cells with doxorubicin and antibodies neutralizing G-CSF, CCL2 or CCL5 had higher inhibitory effects than each modality used alone. These results indicate that chemokines and growth factors produced by tumor by binding to the cognate receptors on tumor and stroma cells could provide proliferative and antiapoptotic signals helping tumor to escape drug-mediated destruction. Clinical studies showed that antibodies neutralizing VEGF (Avastin/Bevacizumab) or blocking HER2/neu signaling (Herceptin/Trastuzumab) could increase the efficacy of chemotherapy, although these beneficial effects have been limited. It is possible that drug-stimulated production of growth and proangiogenic factors could counterbalance the effects of antibody therapy. In addition, numerous growth factors and chemokines share angiogenic and growth-stimulating properties, and thus reduction of a single factor is insufficient to completely block tumor growth. Thus, a broad disruption of tumor cytokine network is needed to further increase the efficacy of cancer therapy.

Bioimage informatics: a new area of engineering biology

In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.

Contact:pengh@janelia.hhmi.org

Supplementary information:Supplementary data are available at Bioinformatics online.

A novel high-throughput assay for the quantitative assessment of receptor trafficking

1. Receptor transport between intracellular compartments has important consequences for receptor function and is an exciting area of current study. Existing methods for studying receptor trafficking often require labour-intensive techniques or are difficult to quantify reliably. We report a novel high-throughput method that uses automated imaging and analysis tools to accurately quantify cannabinoid CB1 receptor trafficking. 2. Haemagglutinin (HA)-tagged CB1 was stably expressed in HEK-293 cells and cell surface or total receptors were detected immunocytochemically. Images of receptor and nuclear staining were acquired with an automated fluorescent microscope (Discovery-1; Molecular Devices, Sunnyvale, CA, USA) and quantified at high throughput with MetaMorph (Molecular Devices) software. The 'Granularity' assay measured internalization by counting receptor clusters that appear during receptor endocytosis, a well-established approach. Our assay, referred to as 'Total Grey Value per Cell' (TGVC), measures the total fluorescence above background, normalized to cell count. 3. Incubation with the cannabinoid agonist HU-210 (100 nmol/L) resulted in rapid CB1 internalization, reaching a maximum within 20 min. Whether quantified by Granularity or TGVC, the time-course of endocytosis could be modelled with exponentially derived curves and with similar half-lives. We demonstrate the sensitivity of our TGVC method by measuring the concentration dependence of CB1 internalization and its versatility by measuring downregulation following chronic agonist exposure, whereby total CB1 was reduced to approximately 55% of basal after 3 h. 4. The TGVC quantification method described is efficient, accurate and versatile and is likely to provide a valuable tool in receptor trafficking studies.

High-content screening as a universal tool for fingerprinting of cytotoxicity of nanoparticles

Recent advances and progress in nanobiotechnology have demonstrated many nanoparticles (NPs) as potential and novel drug delivery vehicles, therapeutic agents, and contrast agents and luminescent biological labels for bioimaging. The emergence of new biomedical applications based on NPs signifies the need to understand, compare, and manage their cytotoxicity. In this study, we demonstrated the use of high-content screening assay (HCA) as a universal tool to probe the cytotoxicity of NPs and specifically cadmium telluride quantum dots (CdTe QDs) and gold NPs (Au NPs) in NG108-15 murine neuroblastoma cells and HepG2 human hepatocellular carcinoma cells. Neural cells represent special interest for NP-induced cytotoxicity because the optical and electrical functionalities of materials necessary for neural imaging and interfacing are matched well with the properties of many NPs. In addition, the cellular morphology of neurons is particularly suitable for automated high content screening. HepG2 cells represent a good model for high content screening studies since they are commonly used as a surrogate for human hepatocytes in pharmaceutical studies. We found the CdTe QDs to induce primarily apoptotic response in a time- and dosage-dependent manner and produce different toxicological profiles and responses in undifferentiated and differentiated neural cells. Au NPs were found to inhibit the proliferation and intracellular calcium release of HepG2 cells.

Integrating high-content screening and ligand-target prediction to identify mechanism of action

High-content screening is transforming drug discovery by enabling simultaneous measurement of multiple features of cellular phenotype that are relevant to therapeutic and toxic activities of compounds. High-content screening studies typically generate immense datasets of image-based phenotypic information, and how best to mine relevant phenotypic data is an unsolved challenge. Here, we introduce factor analysis as a data-driven tool for defining cell phenotypes and profiling compound activities. This method allows a large data reduction while retaining relevant information, and the data-derived factors used to quantify phenotype have discernable biological meaning. We used factor analysis of cells stained with fluorescent markers of cell cycle state to profile a compound library and cluster the hits into seven phenotypic categories. We then compared phenotypic profiles, chemical similarity and predicted protein binding activities of active compounds. By integrating these different descriptors of measured and potential biological activity, we can effectively draw mechanism-of-action inferences.

High-content imaging analysis of the knockdown effects of validated siRNAs and antisense oligonucleotides

High-content imaging (HCI) provides researchers with a powerful tool for understanding cellular processes. Although phenotypic analysis generated through HCI is a potent technique to determine the overall cellular effects of a given treatment, it frequently produces complex data sets requiring extensive interpretation. The authors developed statistical analyses to decrease the time spent to determine the outcome of each HCI assay and to better understand complex phenotypic changes. To test these tools, the authors performed a comparison experiment between 2 types of oligonucleotide-mediated gene silencing (OMGS), antisense oligonucleotides (ASOs), and short, double-stranded RNAs (siRNAs). Although similar in chemical structure, these 2 methods differ in cellular mechanism of action and off-target effects. Using a library of 50 validated ASOs and siRNAs to the same targets, the authors characterized the differential effects of these 2 technologies using a HeLa cell G2-M cell cycle assay. Although knockdown of a variety of targets by ASOs or siRNAs affected the cell cycle profile, few of those targets were affected by both ASOs and siRNAs. Distribution analysis of population changes induced through target knockdown led to the identification of targets that, when inhibited, could affect the G2-M transition in the cell cycle in a statistically significant manner. The distinctly different mechanisms of action of these 2 forms of gene silencing may help define the use of these treatments in both clinical and research environments.

High-Throughput Lead Finding and Optimisation for GPCR Targets

Driven by past successes and the detailed knowledge of signalling cascades and physiological processes, G-protein-coupled receptors are taking a prominent place in the portfolios of many pharmaceutical companies. To successfully address this target class, scientists need not only a good understanding of the specific receptor under investigation, but also the right tools from assay technology, reagent production to a hit-to-lead process that acknowledges the importance of parameters beyond potency and embraces the gain in knowledge of the last decade. This manuscripts attempts to summarise some of the changes and progress made across the pharmaceutical industry to design an efficient and effective strategy for finding and optimising small molecules modulating the activity of GPCRs.

High-throughput screening of cellular features using high-resolution light-microscopy; Application for profiling drug effects on cell adhesion

High-resolution light-microscopy and high-throughput screening are two essential methodologies for characterizing cellular phenotypes. Optimally combining these methodologies in cell-based screening to test detailed molecular and cellular responses to multiple perturbations constitutes a major challenge. Here we describe the development and application of a screening microscope platform that automatically acquires and interprets sub-micron resolution images at fast rates. The analysis pipeline is based on the quantification of multiple subcellular features and statistical comparisons of their distributions in treated vs. control cells. Using this platform, we screened 2200 natural extracts for their effects on the fine structure and organization of focal adhesions. This screen identified 15 effective extracts whose fractionation and characterization were further analyzed using the same microscope system. The significance of combining resolution, throughput and multi-parametric analyses for biomedical research and drug discovery is discussed.

Beta galactosidase complementation: a cell-based luminescent assay platform for drug discovery

Many cell-based assays interrogating cell pathway activation employ protocols that require microscopic imaging techniques. However, such assays are not in general widely adopted for primary screening. Protein complementation, particularly of enzymes, provides an alternative approach for cell pathway analysis, with a principal advantage that is amenable to high throughput screening using microtiter plate protocols. Notably, alpha complementation of the enzyme beta-galactosidase has been exploited as a technology in this regard, using substrates that generates luminescent signals. This review describes the various uses of this flexible technology to cell-based assay development.