Advances in high content screening for drug discovery

Droplet microarray platforms for high-throughput drug screening

High-throughput screening platforms are fundamental for the rapid and efficient processing of large amounts of experimental data. Parallelization and miniaturization of experiments are important for improving their cost-effectiveness. The development of miniaturized high-throughput screening platforms is essential in the fields of biotechnology, medicine, and pharmacology. Currently, most laboratories use 96- or 384-well microtiter plates for screening; however, they have disadvantages, such as high reagent and cell consumption, low throughput, and inability to avoid cross-contamination, which need to be further optimized. Droplet microarrays, as novel screening platforms, can effectively avoid these shortcomings. Here, the preparation method of the droplet microarray, method of adding compounds in parallel, and means to read the results are briefly described. Next, the latest research on droplet microarray platforms in biomedicine is presented, including their application in high-throughput culture, cell screening, high-throughput nucleic acid screening, drug development, and individualized medicine. Finally, the challenges and future trends in droplet microarray technology are summarized.

A high-throughput neutralizing assay for antibodies and sera evaluation against Epstein-Barr virus

BACKGROUND

Epstein-Barr virus (EBV) is a wide-spread human herpesvirus that is highly associated with infectious mononucleosis and several malignancies. Evaluation of EBV neutralizing antibody titers is important for serological studies, vaccine development and monoclonal antibody screening. The traditional method based on antibody inhibition of EBV transformation of B cells is very time-consuming. A more practical flow cytometry-based (FCM) approach to evaluate neutralizing titers is not amenable to achieving high-throughput evaluation of large-scale samples. A high-throughput approach is urgently needed.

RESULTS

Here, we present a rapid and high-throughput method based on high content imaging system (HCIS) analysis. EBV titers determined by the HCIS-based assay were similar to those obtained by the FCM-based assay. Neutralizing titers of sera and monoclonal antibodies measured by the HCIS-based assay strongly correlated with titers measured by the FCM-based assay. HCIS assays showed a strong correlation between B cell infection neutralizing titers and the anti-gp350 IgG titers in healthy EBV carriers and monkey sera. Finally, anti-gHgL IgG titers from sera of healthy EBV carriers significantly correlated with epithelial cell infection neutralizing titers.

CONCLUSIONS

This HCIS-based assay is a high-throughput assay to determine viral titers and evaluate neutralizing potentials of sera and monoclonal antibodies. This HCIS-based assay will aid the development of vaccines and therapeutic monoclonal antibody against EBV.

The impact of microfluidics in high-throughput drug-screening applications

Drug discovery is an expensive and lengthy process. Among the different phases, drug discovery and preclinical trials play an important role as only 5-10 of all drugs that begin preclinical tests proceed to clinical trials. Indeed, current high-throughput screening technologies are very expensive, as they are unable to dispense small liquid volumes in an accurate and quick way. Moreover, despite being simple and fast, drug screening assays are usually performed under static conditions, thus failing to recapitulate tissue-specific architecture and biomechanical cues present in vivo even in the case of 3D models. On the contrary, microfluidics might offer a more rapid and cost-effective alternative. Although considered incompatible with high-throughput systems for years, technological advancements have demonstrated how this gap is rapidly reducing. In this Review, we want to further outline the role of microfluidics in high-throughput drug screening applications by looking at the multiple strategies for cell seeding, compartmentalization, continuous flow, stimuli administration (e.g., drug gradients or shear stresses), and single-cell analyses.

Conjoint analysis of influence of LC-HCL and Mor-HCL on Vth and neurite length in hippocampal neuronal network

Lidocaine hydrochloride (LC-HCl) and morphine hydrochloride (Mor-HCl) are two kinds of most prevalently used anesthetics. However, their influences on electrical excitability of hippocampal neuronal networks and hippocampal brain slices were rarely studied. Previously, our group have assessed the influence of acetylcholine, alcohol and temperature change on the excitability of neural networks with the so-called Voltage Threshold Measurement Method (VTMM) based on microelectrode array (MEA). In this paper, we will study the influence of LC-HCl and Mor-HCl on the electrical excitability of neural networks and the morphological features of neurons, and discuss the relations between the changes of electrical excitability of neural networks and the morphological changes of neurons. The results of VTMM showed: The voltage threshold (V_Th) of hippocampal neuronal networks and hippocampal brain slices first increased and then decreased as the LC-HCl concentration increased. The V_Th of hippocampal neuronal networks and hippocampal brain slices increased as the Mor-HCl concentration increased. The results of HCS experiments showed: The neurite length change of cultured hippocampal neuronal networks increased first and then decreased with increased LC-HCl concentration, but decreased as the Mor-HCl concentration increased. The combined analysis of VTMM and HCS experiments showed that under effects of the two drugs, the V_Th and the hippocampal neurite length were strongly negatively correlated.

Investigating the pre-lethal cytotoxic effects of bis(2,4-di-tert-butylphenyl)phosphate on Chinese hamster ovary cells using high content analysis

Bis(2,4-di-tert-butylphenyl)Phosphate (bDtBPP) leaches out of polyethylene films used by the biopharmaceutical industry in single-use systems (SUS) for the culturing of drug producing cell lines. Previous studies found bDtBPP (0.025 - 0.110 mg/L) negatively affects Chinese hamster ovary (CHO) cell growth and productivity. Less information is known about the potential early stages of subtle pre-lethal cytotoxic effects of bDtBPP. This study aimed to investigate the pre-lethal cytotoxic effects in CHO-K1 cells of bDtBPP (0.005 - 0.25 μg/ml) at process relevant concentrations following 2, 24 and 48 h exposure, using high content analysis to investigate multiple pre-lethal cytotoxicity markers. After 48 h exposure, bDtBPP (0.005 - 0.25 μg/ml; P ≤ 0.001) increased nuclear intensity. A dose- and time-dependent reduction in mitochondrial mass was seen after exposure to bDtBPP. Reactive oxygen species increased after 2 h exposure to 0.25 μg/ml bDtBPP, 24 and 48 h exposure to 0.05 - 0.25 μg/ml bDtBPP (P ≤ 0.01 and P ≤ 0.001). BDtBPP induced subtle pre-lethal cytotoxic effects on CHO-K1 cellular health. This study highlights the cellular health benefits of the biopharmaceutical industry switching to alternative SUS plastics which do not leach bDtBPP, which may enhance CHO-K1 cell productivity.

Targeting phosphatidylinositol 3-kinase gamma (PI3Kγ): Discovery and development of its selective inhibitors

Phosphatidylinositol 3-kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of advanced solid tumors, leukemia, lymphoma, and inflammatory and autoimmune diseases. However, the high level of structural conservation among the members of the PI3K family and the diverse physiological roles of Class I PI3K isoforms (α, β, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. In this review, we provide an overview of the structural features of PI3Kγ that influence γ-isoform selectivity and discuss the structure-selectivity-activity relationship of existing clinical PI3Kγ inhibitors. Additionally, we summarize the experimental and computational techniques utilized to identify PI3Kγ inhibitors. The insights gained so far could be used to overcome the main challenges in development and accelerate the discovery of PI3Kγ-selective inhibitors.

High-Content Screening for Cryptosporidium Drug Discovery

High-content screening (HCS) is a cell-based type of phenotypic screening that combines multiple simultaneous readouts with a high level of throughput. A particular benefit of this form of screening for drug discovery is the ability to perform the interrogation in a biologically relevant system. This approach has greatly advanced the field of drug discovery for cryptosporidiosis, a diarrheal disease caused by protozoan parasites of Cryptosporidium spp. These parasites are obligate intracellular parasites and cannot be cultured in vitro without the support of a host cell, limiting the options for potential assay readout. Here we describe an established 384- or 1536-well format high-content imaging (HCI) assay of Cryptosporidium-infected HCT-8 human ileocecal adenocarcinoma cells. This HCS assay is a powerful tool to assess large numbers of compounds to power drug discovery, as well as to phenotypically characterize known Cryptosporidium-active compounds.

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

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

Chemical Screening of Nuclear Receptor Modulators

Nuclear receptors are ligand-inducible transcriptional factors that control multiple biological phenomena, including proliferation, differentiation, reproduction, metabolism, and the maintenance of homeostasis. Members of the nuclear receptor superfamily have marked structural and functional similarities, and their domain functionalities and regulatory mechanisms have been well studied. Various modulators of nuclear receptors, including agonists and antagonists, have been developed as tools for elucidating nuclear receptor functions and also as drug candidates or lead compounds. Many assay systems are currently available to evaluate the modulation of nuclear receptor functions, and are useful as screening tools in the discovery and development of new modulators. In this review, we cover the chemical screening methods for nuclear receptor modulators, focusing on assay methods and chemical libraries for screening. We include some recent examples of the discovery of nuclear receptor modulators.

Drug-pathway association prediction: from experimental results to computational models

Effective drugs are urgently needed to overcome human complex diseases. However, the research and development of novel drug would take long time and cost much money. Traditional drug discovery follows the rule of one drug-one target, while some studies have demonstrated that drugs generally perform their task by affecting related pathway rather than targeting single target. Thus, the new strategy of drug discovery, namely pathway-based drug discovery, have been proposed. Obviously, identifying associations between drugs and pathways plays a key role in the development of pathway-based drug discovery. Revealing the drug-pathway associations by experiment methods would take much time and cost. Therefore, some computational models were established to predict potential drug-pathway associations. In this review, we first introduced the background of drug and the concept of drug-pathway associations. Then, some publicly accessible databases and web servers about drug-pathway associations were listed. Next, we summarized some state-of-the-art computational methods in the past years for inferring drug-pathway associations and divided these methods into three classes, namely Bayesian spare factor-based, matrix decomposition-based and other machine learning methods. In addition, we introduced several evaluation strategies to estimate the predictive performance of various computational models. In the end, we discussed the advantages and limitations of existing computational methods and provided some suggestions about the future directions of the data collection and the calculation models development.

On-chip 3D neuromuscular model for drug screening and precision medicine in neuromuscular disease

This protocol describes the design, fabrication and use of a 3D physiological and pathophysiological motor unit model consisting of motor neurons coupled to skeletal muscles interacting via the neuromuscular junction (NMJ) within a microfluidic device. This model facilitates imaging and quantitative functional assessment. The 'NMJ chip' enables real-time, live imaging of axonal outgrowth, NMJ formation and muscle maturation, as well as synchronization of motor neuron activity and muscle contraction under optogenetic control for the study of normal physiological events. The proposed protocol takes ~2-3 months to be implemented. Pathological behaviors associated with various neuromuscular diseases, such as regression of motor neuron axons, motor neuron death, and muscle degradation and atrophy can also be recapitulated in this system. Disease models can be created by the use of patient-derived induced pluripotent stem cells to generate both the motor neurons and skeletal muscle cells used. This is demonstrated by the use of cells from a patient with sporadic amyotrophic lateral sclerosis but can be applied more generally to models of neuromuscular disease, such as spinal muscular atrophy, NMJ disorder and muscular dystrophy. Models such as this hold considerable potential for applications in precision medicine, drug screening and disease risk assessment.

Electrochemical Dithiothreitol Assay for Large-Scale Particulate Matter Studies

Particulate matter (PM) air pollution is associated with human morbidity and mortality. Measuring PM oxidative potential has been shown to provide a predictive measurement between PM exposure and adverse health impacts. The dithiothreitol (DTT) assay is commonly used to measure the oxidative potential of PM_2.5 (PM less than 2.5 μm aerodynamic diameter). In the common, kinetic form of this assay, the decay of DTT is quantified over time (indirectly) using 5,5'-dithiobis(2-nitrobenzoic acid) (DTNB, Ellman's reagent) via UV/vis absorbance spectroscopy. The loss of DTT can also be quantified directly using electrochemical detection. The objectives of this work were (1) to evaluate the electrochemical assay, using commercially available equipment, relative to the UV/vis absorbance assay, and (2) to apply the electrochemical method to a large (>100) number of PM_2.5 aerosol filter samples. Also presented here is the comparison an end-point assay to the kinetic assay, in an attempt to reduce the time, labor, and materials neccssary to quantify PM oxidative potential. The end-point, electrochemical assay gave comparable results to the UV/vis absorbance assay for PM filter sample analysis. Finally, high filter mass loadings (higher than about 0.5 μg PM per mm² filter) lead to sub-optimal DTT assay performance, which suggests future studies should limit particle mass loadings on filters.

A High-Content Screen Reveals New Small-Molecule Enhancers of Ras/Mapk Signaling as Probes for Zebrafish Heart Development

Zebrafish is the preferred vertebrate model for high throughput chemical screens to discover modulators of complex biological pathways. We adapted a transgenic zebrafish line, Tg(dusp6:EGFP), which reports on fibroblast growth factor (Fgf)/Ras/Mapk activity, into a quantitative, high-content chemical screen to identify novel Fgf hyperactivators as chemical probes for zebrafish heart development and regeneration. We screened 10,000 compounds from the TimTec ActiProbe library, and identified several structurally distinct classes of molecules that enhanced Fgf/Ras/Mapk signaling. We chose three agents—ST020101, ST011282, and ST006994—for confirmatory and functional studies based on potency, repeatability with repurchased material, favorable whole organism toxicity, and evidence of structure–activity relationships. Functional follow-up assays confirmed that all three compounds induced the expression of Fgf target genes during zebrafish embryonic development. Moreover, these compounds increased cardiac progenitor populations by effecting a fate change from endothelial to cardiac progenitors that translated into increased numbers of cardiomyocytes. Interestingly, ST006994 augmented Fgf/Ras/Mapk signaling without increasing Erk phosphorylation, suggesting a molecular mechanism of action downstream of Erk. We posit that the ST006994 pharmacophore could become a unique chemical probe to uncover novel mechanisms of Fgf signaling during heart development and regeneration downstream of the Mapk signaling node.

High-Throughput Screening Raman Spectroscopy Platform for Label-Free Cellomics

We present a high-throughput screening Raman spectroscopy (HTS-RS) platform for a rapid and label-free macromolecular fingerprinting of tens of thousands eukaryotic cells. The newly proposed label-free HTS-RS platform combines automated imaging microscopy with Raman spectroscopy to enable a rapid label-free screening of cells and can be applied to a large number of biomedical and clinical applications. The potential of the new approach is illustrated by two applications. (1) HTS-RS-based differential white blood cell count. A classification model was trained using Raman spectra of 52 218 lymphocytes, 48 220 neutrophils, and 7 294 monocytes from four volunteers. The model was applied to determine a WBC differential for two volunteers and three patients, producing comparable results between HTS-RS and machine counting. (2) HTS-RS-based identification of circulating tumor cells (CTCs) in 1:1, 1:9, and 1:99 mixtures of Panc1 cells and leukocytes yielded ratios of 55:45, 10:90, and 3:97, respectively. Because the newly developed HTS-RS platform can be transferred to many existing Raman devices in all laboratories, the proposed implementation will lead to a significant expansion of Raman spectroscopy as a standard tool in biomedical cell research and clinical diagnostics.

General Staining and Segmentation Procedures for High Content Imaging and Analysis

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Neuronal Cell Morphology in Primary Cerebellar Granule Cells Using High-Content Analysis

Neurite outgrowth, one of the underlying cellular processes that defines the development and functionality of the mammalian nervous system, is also a sensitive indicator of neuronal cell health. From screening libraries of putative neurotherapeutic compounds to analyzing the millions of environmental pollutants for which we have inadequate neurotoxicity safety data, the large volume of chemical compounds that require evaluation is a major obstacle for manual imaging and analysis methods. In this context, high-content analysis (HCA) has emerged as a sensitive and accurate method for detecting changes in neuronal cell morphology within a format applicable to screening large chemical libraries. Advances in HCA technologies have enabled the automated imaging and quantitative analysis of neurite outgrowth morphology within a 96-well plate in less than 5 min. Traditionally, neurite outgrowth assessment has been conducted on immortalized cell lines such as pheochromocytoma (PC-12) cells that differentiate into neuron-like cells upon culture with nerve growth factor. Unfortunately, they do not retain all the in vivo characteristics of physiological neuronal tissue, including lack of synapse formation. As researchers refine neurite outgrowth quantitative analysis using HCA, an emerging question is how to quantify this biology in more complex models that more faithfully recapitulate in vivo environments. Primary neurons provide several benefits relative to neuronal cell lines, including the elaboration of axons from secondary dendrites and formation of both pre- and postsynaptic junctions. This chapter reviews techniques for evaluating neurite outgrowth using the ArrayScan HCA platform within a model system of primary cultures of rodent cerebellar granule cells.

Antihepatocellular Carcinoma Potential of Tetramethylpyrazine Induces Cell Cycle Modulation and Mitochondrial-Dependent Apoptosis: Regulation of p53 Signaling Pathway in HepG2 Cells In Vitro

Tetramethylpyrazine (TMP) was originally isolated from a traditional Chinese herbal medicine, Ligusticum chuanxiong In the present study, TMP exhibits potent antitumor activities in vitro. However, the molecular mechanisms remain to be defined. Hence, this study aims to investigate the antiproliferative and apoptotic effects of TMP on HepG2 and elucidate the underlying mechanisms. Analyses using Cell Counting Kit-8 and real-time cell analyzer indicated that TMP significantly inhibited HepG2 cell proliferation. We also observed that TMP induced cell cycle arrest at the G0/G1 checkpoint and apoptosis, using flow cytometry and high-content screening. Furthermore, our results predicted that TMP could directly decrease mitochondrial membrane potential (Δψm), increase the release of cytochrome c, and increase caspase activation, indicating that mitochondrial pathway apoptosis could be the mechanism for TMP within HepG2 cells. Moreover, TMP altered expression of p53 and the Bcl-2/Bax protein ratio, which revealed that TMP induced cell cycle arrest and caspase-dependent mitochondrial apoptosis in HepG2 cells in vitro. These studies provided mechanistic insights into the antitumor properties of TMP, which may be explored as a potential option for treatment of hepatocellular carcinoma.

Discovery of a novel ROCK2 inhibitor with anti-migration effects via docking and high-content drug screening

Rho-associated protein kinase (ROCK) mediated the reorganization of the actin cytoskeleton and has been implicated in the spread and metastatic process of cancer. In this study, structure-based high-throughput virtual screening was used to identify candidate compounds targeting ROCK2 from a chemical library. Moreover, high-content screening based on neurite outgrowth of SH-SY5Y cells (a human neuroblastoma cell line) was used for accelerating the identification of compounds with characteristics of ROCK2 inhibitors. The effects of bioactive ROCK2 inhibitor candidates were further validated using other bioassays including cell migration and wound healing in SH-SY5Y cells. Through the combined virtual and high-content drug screening, the compound 1,3-benzodioxol-5-yl[1-(5-isoquinolinylmethyl)-3-piperidinyl]-methanone (BIPM) was identified as a novel and potent ROCK2 inhibitor. Exposure of SH-SY5Y cells to BIPM led to significant changes in neurite length, cell migration and actin stress fibers. Further experiments demonstrated that BIPM was able to significantly inhibit phosphorylation of cofilin, a regulatory protein of actin cytoskeleton. These results suggest that BIPM could be considered as a promising scaffold for the further development of ROCK2 inhibitors for anti-cancer metastasis.

Target identification by image analysis

Covering: 1997 to the end of 2015Each biologically active compound induces phenotypic changes in target cells that are characteristic for its mode of action. These phenotypic alterations can be directly observed under the microscope or made visible by labelling structural elements or selected proteins of the cells with dyes. A comparison of the cellular phenotype induced by a compound of interest with the phenotypes of reference compounds with known cellular targets allows predicting its mode of action. While this approach has been successfully applied to the characterization of natural products based on a visual inspection of images, recent studies used automated microscopy and analysis software to increase speed and to reduce subjective interpretation. In this review, we give a general outline of the workflow for manual and automated image analysis, and we highlight natural products whose bacterial and eucaryotic targets could be identified through such approaches.

Morphological Evaluation of Nonlabeled Cells to Detect Stimulation of Nerve Growth Factor Expression by Lyconadin B

The success of drug development is greatly influenced by the efficiency of drug screening methods. Recently, phenotype-based screens have raised expectations, based on their proven record of identifying first-in-class drugs at a higher rate. Although fluorescence images are the data most commonly used in phenotype-based cell-based assays, nonstained cellular images have the potential to provide new descriptive information about cellular responses. In this study, we applied morphology-based evaluation of nonlabeled microscopic images to a phenotype-based assay. As a study case, we attempted to increase the efficiency of a cell-based assay for chemical compounds that induce production of nerve growth factor (NGF), using lyconadin B as a model compound. Because the total synthesis of lyconadin B was accomplished very recently, there is no well-established cell-based assay scheme for further drug screening. The conventional cell-based assay for evaluating NGF induction requires two types of cells and a total of 5 days of cell culture. The complexity and length of this assay increase both the risk of screening errors and the cost of screening. Our findings show that analysis of cellular morphology enables evaluation of NGF induction by lyconadin B within only 9 h.

Quantitative Cell-Based High-Content Screening for Vasopressin Receptor Agonists Using Transfluor®Technology

The authors demonstrate the use of a simple, universal G-protein-coupled receptor (GPCR) assay to screen for agonists for a specific GPCR. Cells stably expressing a green fluorescent protein (GFP)-labeled β-arrestin fusion protein and the vasopressin V2 receptor (V2R) were used in a high-content screening (HCS) assay to screen a small peptide library for V2R agonists. Cells were treated with the peptides at a final concentration of 500 nM for 30min. Agonist stimulation causes V2R internalization into endosomes. GFP-β-arrestin remains associated with the V2R in endosomes, resulting in a fluorescent pattern of intracellular spots. Assay plates were automatically imaged and quantitatively analyzed using an HCS imaging platformand a fast turnkey image analysis application optimized for detection of receptor activation and intracellular spots. Hits were further evaluated to determine their potency. The combination of unique biology, automated high-content analysis, and a powerful means of validating hits results in better leads.

High-Content Screening with siRNA Optimizes a Cell Biological Approach to Drug Discovery: Defining the Role of P53 Activation in the Cellular Response to Anticancer Drugs

Deciphering the effects of compounds on molecular events within living cells is becoming an increasingly important component of drug discovery. In a model application of the industrial drug discovery process, the authors profiled a panel of 22 compounds using hierarchical cluster analysis of multiparameter high-content screening measurements from nearly 500,000 cells per microplate. RNAi protein knockdown methodology was used with high-content screening to dissect the effects of 2 anticancer drugs on multiple target activities. Camptothecin activated p53 in A549 lung carcinoma cells pretreated with scrambled siRNA, exhibited concentration-dependent cell cycle blocks, and induced moderate microtubule stabilization. Knockdown of camptothecin-induced p53 protein expression with p53 siRNA inhibited the G1/S blocking activity of the drug and diminished its microtubule-stabilizing activity. Paclitaxel activated p53 protein at low concentrations but exhibited G2/M cell cycle blocking activity at higher concentrations where microtubules were stabilized. In cells treated with p53 siRNA, paclitaxel failed to activate p53 protein, but the knockdown did not have a significant effect on the ability of paclitaxel to stabilize microtubules or induce a G2/M cell cycle block. Thus, this model application of the use of RNAi technology within the context of high-content screening shows the potential to provide massive amounts of combinatorial cell biological information on the temporal and spatial responses that cells mount to treatment by promising therapeutic candidates.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point.

Benefits of Strategic Small-Scale Targeted Screening

High-throughput screening (HTS) is a key technology platform for the discovery of chemical probes and identification of potential drug leads. Once mainly found in industry, HTS is now an integral component of a significant number of academic basic and translational research enterprises. Although the allure of large-scale diversity set-based HTS is substantive, the inherent costs associated with this type of screening strategy are steep and often yield suboptimal return on investment. Perhaps more appealing, and potentially more rewarding, are smaller scale screening strategies using targeted libraries coupled with assays with high-physiological relevance. These "high-physiocontextual"-targeted library screening paradigms, in turn, may have significant impact on the quality of chemical probes and ensuing drug discovery efforts.

Efficient Drug-Pathway Association Analysis via Integrative Penalized Matrix Decomposition

Traditional drug discovery practice usually follows the "one drug - one target" approach, seeking to identify drug molecules that act on individual targets, which ignores the systemic nature of human diseases. Pathway-based drug discovery recently emerged as an appealing approach to overcome this limitation. An important first step of such pathway-based drug discovery is to identify associations between drug molecules and biological pathways. This task has been made feasible by the accumulating data from high-throughput transcription and drug sensitivity profiling. In this paper, we developed "iPaD", an integrative Penalized Matrix Decomposition method to identify drug-pathway associations through jointly modeling of such high-throughput transcription and drug sensitivity data. A scalable bi-convex optimization algorithm was implemented and gave iPaD tremendous advantage in computational efficiency over current state-of-the-art method, which allows it to handle the ever-growing large-scale data sets that current method cannot afford to. On two widely used real data sets, iPaD also significantly outperformed the current method in terms of the number of validated drug-pathway associations that were identified. The Matlab code of our algorithm publicly available at http://licong-jason.github.io/iPaD/.

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.

High content analysis assay for prediction of human hepatotoxicity in HepaRG and HepG2 cells

Drug-induced liver injury (DILI) results in the termination of drug development or withdrawal of a drug from the market. The establishment of a predictive, high-throughput preclinical test system to evaluate potential clinical DILI is therefore required. Here, we established a high content analysis (HCA) assay in human hepatocyte cell lines such as the HepaRG with normal expression levels of CYP enzymes and HepG2 with extremely low expression levels of CYP enzymes. Clinical DILI or non-DILI compounds were evaluated for reactive oxygen species (ROS) production, glutathione (GSH) consumption, and mitochondrial membrane potential (MMP) attenuation. A proportion of DILI compounds induced ROS generation, GSH depletion, and MMP dysfunction, which was consistent with reported mechanisms of DILI of these compounds. In particular, DILI compounds that deplete GSH via reactive metabolites exhibited a more marked decrease in intracellular GSH or increase in ROS production in HepaRG cells than in HepG2 cells. Comparison of the two cell lines with different levels of CYP expression might help clarify the contribution of metabolism to hepatocyte toxicity. These results suggest that the HCA assay in HepaRG and HepG2 cells might help improve the accuracy of evaluating clinical DILI potential during drug screening.

Alisol F 24 Acetate Enhances Chemosensitivity and Apoptosis of MCF-7/DOX Cells by Inhibiting P-Glycoprotein-Mediated Drug Efflux

Multidrug resistance (MDR) is a prime reason for numerous failed oncotherapy approaches. In the present study, we investigated whether Alisol F 24 acetate (ALI) could reverse the MDR of MCF-7/DOX cells, a multidrug-resistant human breast cancer cell line. We found that ALI was a potent P-glycoprotein (P-gp) inhibitor, in the Caco-2-monolayer cell model. ALI showed a significant and concentration-dependent cytotoxic effect on MCF-7/DOX cells in combination with doxorubicin by increasing intracellular accumulation and inducing nuclear migration of doxorubicin. However, ALI had no such effect on MCF-7 cells. In addition, ALI also promoted doxorubicin-induced early apoptosis of MCF-7/DOX cells in a time-dependent manner. These results suggest that ALI can enhance chemosensitivity of doxorubicin and reinforce its anti-cancer effect by increasing its uptake, especially inducing its nuclear accumulation in MCF-7/DOX cells. Therefore, ALI could be developed as a potential MDR-reversing agent in cancer chemotherapy in further study.

High-content screening identifies inhibitors of the nuclear translocation of ATF6

Activating transcription factor 6 (ATF6) is a transmembrane protein that consists of a cytoplasmic domain and an endoplasmic reticulum (ER) luminal domain. As unfolded protein levels arise in the ER, the ER cytoplasmic domain of ATF6 moves to the nucleus, where it activates the transcription of a range of genes, including those involved in apoptosis. As ATF6 only becomes functional once it has moved to the nucleus, compounds that inhibit its re-localization are of therapeutic interest. The aim of the present study was to rapidly and accurately identify such compounds using a novel image‑based, high‑content screening (HCS) technique. The results from the HCS analysis were then confirmed by luciferase reporter assays, western blot analysis and the measurement of cell viability. We found that HCS identified compounds which inhibited ATF6 nuclear translocation with high specificity, as confirmed by the luciferase reporter assay and western blot analysis. Moreover, we demonstrated that 3 of the 80 identified compounds impaired ATF6-mediated induced cell death. The data from this study support the theory that HCS is a novel, high throughput method which can be used for accurate and rapid compound screening.

A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens

Heterogeneity is well recognized as a common property of cellular systems that impacts biomedical research and the development of therapeutics and diagnostics. Several studies have shown that analysis of heterogeneity: gives insight into mechanisms of action of perturbagens; can be used to predict optimal combination therapies; and can be applied to tumors where heterogeneity is believed to be associated with adaptation and resistance. Cytometry methods including high content screening (HCS), high throughput microscopy, flow cytometry, mass spec imaging and digital pathology capture cell level data for populations of cells. However it is often assumed that the population response is normally distributed and therefore that the average adequately describes the results. A deeper understanding of the results of the measurements and more effective comparison of perturbagen effects requires analysis that takes into account the distribution of the measurements, i.e. the heterogeneity. However, the reproducibility of heterogeneous data collected on different days, and in different plates/slides has not previously been evaluated. Here we show that conventional assay quality metrics alone are not adequate for quality control of the heterogeneity in the data. To address this need, we demonstrate the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in an SAR screen, describe a workflow for quality control in heterogeneity analysis. One major challenge in high throughput biology is the evaluation and interpretation of heterogeneity in thousands of samples, such as compounds in a cell-based screen. In this study we also demonstrate that three heterogeneity indices previously reported, capture the shapes of the distributions and provide a means to filter and browse big data sets of cellular distributions in order to compare and identify distributions of interest. These metrics and methods are presented as a workflow for analysis of heterogeneity in large scale biology projects.

Correlating intracellular nonviral polyplex localization with transfection efficiency using high-content screening

High-content screening (HCS) has gained interest in cellular imaging because of its ability to provide statistically significant data from multiple parameters simultaneously in cell-based assays. Although HCS has been mainly used in drug discovery, it has other potentially useful applications, such as elucidating the processes involved in nonviral gene vector-mediated gene delivery, as was explored in this study. HCS was used to measure transfection efficiency and cytotoxicities of polyplexes made from fluorescently labeled polyethylenimine (PEI) and pDNA encoding EGFP (pEGFP-N1). The results generated using HCS were confirmed using more conventional and labor-intensive methods. For the first time, a relationship between transfected cells and the number of polyplexes in the cytoplasm was shown. Four to five polyplex signals were found in the cytoplasm of successfully transfected cells, whilst nontransfected cells harbored less than one polyplex signal within the cytoplasm. HCS has the potential to be used as a tool in the field of gene delivery. HCS can not only simultaneously measure transfection efficiency and cytotoxicity of various nonviral gene vectors; it can also be used to track such vectors through various subcellular compartments.

Drug-target interaction prediction: databases, web servers and computational models

Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.

A novel PI3K inhibitor PIK-C98 displays potent preclinical activity against multiple myeloma

Recent clinical trials have demonstrated targeting PI3K pathway is a promising strategy for the treatment of blood cancers. To identify novel PI3K inhibitors, we performed a high throughput virtual screen and identified several novel small molecule compounds, including PIK-C98 (C98). The cell-free enzymatic studies showed that C98 inhibited all class I PI3Ks at nano- or low micromolar concentrations but had no effects on AKT or mTOR activity. Molecular docking analysis revealed that C98 interfered with the ATP-binding pockets of PI3Ks by forming H-bonds and arene-H interactions with specific amino acid residues. The cellular assays demonstrated that C98 specifically inhibited PI3K/AKT/mTOR signaling pathway, but had no effects on other kinases and proteins including IGF-1R, ERK, p38, c-Src, PTEN, and STAT3. Inhibition of PI3K by C98 led to myeloma cell apoptosis. Furthermore, oral administration of C98 delayed tumor growth in two independent human myeloma xenograft models in nude mice but did not show overt toxicity. Pharmacokinetic analyses showed that C98 was well penetrated into myeloma tumors. Therefore, through a high throughput virtual screen we identified a novel PI3K inhibitor that is orally active against multiple myeloma with great potential for further development.

Development of an image-based screening system for inhibitors of the plastidial MEP pathway and of protein geranylgeranylation

In a preceding study we have recently established an in vivo visualization system for the geranylgeranylation of proteins in a stably transformed tobacco BY-2 cell line, which involves expressing a dexamethasone-inducible GFP fused to the prenylable, carboxy-terminal basic domain of the rice calmodulin CaM61, which naturally bears a CaaL geranylgeranylation motif (GFP-BD-CVIL). By using pathway-specific inhibitors it was there demonstrated that inhibition of the methylerythritol phosphate (MEP) pathway with oxoclomazone and fosmidomycin, as well as inhibition of protein geranylgeranyl transferase type 1 (PGGT-1), shifted the localization of the GFP-BD-CVIL protein from the membrane to the nucleus. In contrast, the inhibition of the mevalonate (MVA) pathway with mevinolin did not affect this localization. Furthermore, in this initial study complementation assays with pathway-specific intermediates confirmed that the precursors for the cytosolic isoprenylation of this fusion protein are predominantly provided by the MEP pathway. In order to optimize this visualization system from a more qualitative assay to a statistically trustable medium or a high-throughput screening system, we established now new conditions that permit culture and analysis in 96-well microtiter plates, followed by fluorescence microscopy. For further refinement, the existing GFP-BD-CVIL cell line was transformed with an estradiol-inducible vector driving the expression of a RFP protein, C-terminally fused to a nuclear localization signal (NLS-RFP). We are thus able to quantify the total number of viable cells versus the number of inhibited cells after various treatments. This approach also includes a semi-automatic counting system, based on the freely available image processing software. As a result, the time of image analysis as well as the risk of user-generated bias is reduced to a minimum. Moreover, there is no cross-induction of gene expression by dexamethasone and estradiol, which is an important prerequisite for this test system.

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.

Screening technologies for small molecule discovery: the state of the art

Screening, high-throughput screening, and ultra-high-throughput screening are all really just points on a spectrum that represent differing applications of the same process: the creation of biologically relevant assays that are relevant, reproducible, reliable, and robust. Whether the discovery program is developing a pharmaceutical, an academic probe, cosmetics, pesticides, or a toxicity monitoring assay, the development of a screen focuses on generating a method that will reliably deliver reproducible results over a period of weeks, months, or years and that will generate consistent results for every test along the way. This review provides both historical perspective on how this unique scientific discipline evolved and commentary on the current state of the art technologies and techniques.

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.

Development of an image-based screening system for inhibitors of the plastidial MEP pathway and of protein geranylgeranylation

We have recently established an in vivo visualization system for the geranylgeranylation of proteins in a stably transformed tobacco BY-2 cell line, which involves expressing a dexamethasone-inducible GFP fused to the prenylable, carboxy-terminal basic domain of the rice calmodulin CaM61, which naturally bears a CaaL geranylgeranylation motif (GFP-BD-CVIL). By using pathway-specific inhibitors it was demonstrated that inhibition of the methylerythritol phosphate (MEP) pathway with oxoclomazone and fosmidomycin, as well as inhibition of protein geranylgeranyl transferase type 1 (PGGT-1), shifted the localization of the GFP-BD-CVIL protein from the membrane to the nucleus. In contrast, the inhibition of the mevalonate (MVA) pathway with mevinolin did not affect this localization. Furthermore, complementation assays with pathway-specific intermediates confirmed that the precursors for the cytosolic isoprenylation of this fusion protein are predominantly provided by the MEP pathway. In order to optimize this visualization system from a more qualitative assay to a statistically trustable medium or a high-throughput screening system, we established new conditions that permit culture and analysis in 96-well microtiter plates, followed by fluorescence microscopy. For further refinement, the existing GFP-BD-CVIL cell line was transformed with an estradiol-inducible vector driving the expression of a RFP protein, C-terminally fused to a nuclear localization signal (NLS-RFP). We are thus able to quantify the total number of viable cells versus the number of inhibited cells after various treatments. This approach also includes a semi-automatic counting system, based on the freely available image processing software. As a result, the time of image analysis as well as the risk of user-generated bias is reduced to a minimum. Moreover, there is no cross-induction of gene expression by dexamethasone and estradiol, which is an important prerequisite for this test system.

Feature-expression heat maps--a new visual method to explore complex associations between two variable sets

INTRODUCTION

Existing methods such as correlation plots and cluster heat maps are insufficient in the visual exploration of multiple associations between genetics and phenotype, which is of importance to achieve a better understanding of the pathophysiology of psychiatric and other illnesses. The implementation of a combined presentation of effect size and statistical significance in a graphical method, added to the ordering of the variables based on the effect-ordered data display principle was deemed useful by the authors to facilitate in the process of recognizing meaningful patterns in these associations.

MATERIALS AND METHODS

The requirements, analyses and graphical presentation of the feature-expression heat map are described. The graphs display associations of two sets of ordered variables where a one-way direction is assumed. The associations are depicted as circles representing a combination of effect size (color) and statistical significance (radius).

RESULTS

An example dataset is presented and relation to other methods, limitations, areas of application and possible future enhancements are discussed.

CONCLUSION

The feature-expression heat map is a useful graphical instrument to explore associations in complex biological systems where one-way direction is assumed, such as genotype-phenotype pathophysiological models.

Clift MJ, Blank F, Petri-Fink A, Rothen-Rutishauser B. Quantification of nanoparticles at the single-cell level: an overview about state-of-the-art techniques and their limitations

With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

Multiplexed high content screening assays create a systems cell biology approach to drug discovery

High content screening (HCS) has emerged as an important platform technology for early drug discovery from target identification through in vitro ADME/Tox. The focus is now on implementing multiplexed assays, developing and using advanced reagents and developing and harnessing more sophisticated informatics tools. Multiplexed HCS assays have the potential to dramatically improve the early drug discovery process by creating systems cell biology profiles on the activities of compounds. It is predicted that multiplexed HCS assays will accelerate the overall workflow and produce deeper functional knowledge, thereby permitting better decisions on what compounds to pursue.:

Phospho-specific flow cytometry in drug discovery

Here we present phospho-specific flow cytometry as a new tool for drug discovery with applications throughout the drug development pipeline, from target identification to library screening, disease model assessment and clinical screening and diagnostics. The single cell, multiparameter nature of flow cytometry generates high-content datasets, and current improvements in the technology are rapidly increasing its high-throughput capacity, making it a valuable platform in modern drug discovery.: